Integrated Assessment of Battery Degradation and Advanced Characterizations in Renewable–Hydrogen Hybrid Architectures

Abstract

Lithium-ion batteries are widely used in electric mobility, renewable energy integration, portable electronics, and renewable–hydrogen hybrid energy systems. Despite significant advances in battery materials and design, long-term degradation remains a major challenge that affects system reliability, efficiency, and economic viability. In renewable–hydrogen hybrid architectures, battery degradation influences not only energy storage performance but also hydrogen production stability, electrolyzer operation, fuel cell utilization, and overall system efficiency. Major degradation mechanisms include solid electrolyte interphase (SEI) growth, electrolyte decomposition, lithium inventory loss, transition-metal dissolution, particle cracking, and structural phase transformations. This review provides a comprehensive assessment of degradation mechanisms affecting lithium-ion battery components and their implications for renewable–hydrogen hybrid systems. Advanced characterization techniques, including in situ and operando X-ray diffraction, electron microscopy, spectroscopy, electrochemical impedance spectroscopy, cyclic voltammetry, and differential capacity analysis, are examined for their ability to reveal chemical, structural, and morphological changes during battery operation. Particular emphasis is placed on the effects of dynamic load variations, partial state-of-charge cycling, temperature fluctuations, and intermittent renewable energy inputs that accelerate degradation in hybrid systems. The review further discusses mitigation strategies such as surface engineering, electrolyte optimization, material doping, thermal management, intelligent energy management systems, predictive maintenance, and machine learning-based prognostics. Key challenges associated with battery–hydrogen integration, including efficiency trade-offs, component ageing, hydrogen production stability, and lifecycle costs, are critically analysed. The adaptability of hybrid systems under varying operating conditions is also explored, highlighting the importance of degradation-aware control strategies, digital twins, and real-time diagnostics. Finally, future research directions are identified, including multiscale characterization, physics-informed machine learning, techno-economic optimization, and life-synergy modelling. These approaches are essential for developing reliable, adaptive, and cost-effective renewable–hydrogen hybrid energy systems capable of supporting long-term decarbonization objectives.

1. Introduction

One of the major causes of environmental pollution has been ascribed to the usage of fossil fuels, and efforts are being made to identify alternative energy sources [1,2]. Several processes have been developed to reduce emissions resulting from using fossil fuels for power generation [3]. Alternative energy sources, besides fuel cells, can save the environment and provide substantial energy [4]. Battery integration into renewable–hydrogen hybrid systems has been extensively investigated to improve system flexibility, efficiency, and reliability and to store the generated power. Recent work has shown that the addition of lithium-ion batteries to wind–hydrogen systems greatly mitigates power fluctuations and stabilizes the electrolyzer, making hydrogen production more consistent under variable renewable inputs [5]. Research on solar–battery–hydrogen microgrids also shows that batteries help to reduce renewable curtailment and achieve optimization of round-trip energy efficiency by taking over short-term balancing while hydrogen fulfils the long-term storage requirement [6]. Other studies have found that battery-supported hybrid systems have the potential to suppress operational stress on electrolyzers by keeping relatively constant electrical loads, thereby prolonging equipment life [7]. Complementary multiple hydro and wind hybrid applications have also shown that combining batteries with hydrogen in such systems enhances system economics and lowers the levelized cost of energy for remote or islanded applications [8]. Generally, batteries are critical elements in renewable–hydrogen configurations, enabling fast response, load levelling, and operational scheduling to enhance hydrogen production and renewable energy incorporation. Lithium-ion batteries with reasonable energy density have become the preferred energy storage solution for several consumer electronic devices, according to reports by numerous researchers [9]. Li et al. [10] revealed that one way to improve the energy density of lithium-ion batteries is to make the cathode material more active and reduce the system temperature. However, some high-voltage cathode materials, e.g., LiCoPO₄, have been shown to be susceptible to marked deterioration after running for several cycles [11,12]. A research study [13] using atomic resolution techniques showed that the main factor behind the gradual degradation of the LiCoPO₄ cathode material is the formation of antisite defects, and the mechanisms need to be clearly understood. With increasing potential, conventional electrolytes undergo oxidation, resulting in the breakdown of the electrode–electrolyte interface [11]. On the other hand, at the anode’s operation potential, the electrolyte is reduced to form a solid electrolyte interphase (SEI). The SEI protects the anode by preventing further degradation from the electrolyte. However, cathode electrolyte interphase (CEI) film formation is often unstable and can impede the electrode’s passivation process. Structural deterioration in cathode particles can also arise from the generation of antisite defects and the formation of unstable delithiated phases, both of which are readily attacked by the electrolyte [14]. The partial degradation of the battery and diminished performance indicate that lithium-ion batteries still face competitive challenges in the market. To invest in storage batteries, achieve the objective of understanding lithium-ion battery degradation, and find applications for their use, a longer battery life must be guaranteed. Additionally, variations in potential, stress and temperature make it difficult to understand the mechanism of degradation, which requires sophisticated characterization methods. The principal methods currently used to characterize the degradation of lithium-ion batteries are generally not adequate and cannot provide insights into their microstructural degradation. Novel methods for lithium-ion battery decomposition have come into being in recent years using machine learning techniques to understand the mechanical behaviour of lithium batteries during breakdown, as reported by Zhang et al. [15]. But characterizing CEI layers, as well as the lithiation mechanisms in the layers, faces significant challenges, mainly on the nanoscale, such that detecting lithium becomes a necessary point of reference [16]. Researchers [17] carried out experiments on samples from a complete stack representative of an industrial battery application. The results show that irreversible changes occur at all size levels for both electrodes [17]. During the negative phase, other researchers observed the breakdown and deterioration of the active material [18]. The cracking of active cathode particles, with separation of the electrode sheet, was also observed [18]. However, understanding how various microscopy techniques work in combination can help identify links between the microstructure and chemistry of the degraded material, offering insights into the local environment of a lithium-ion battery, which is one of the objectives of this review. As a result, it is essential to find a way to relate the degradation of commercial lithium-ion batteries to the findings of the different characterization techniques. This article reviews the degradation of lithium-ion battery components using different characterization techniques. One additional novel aspect of this study is a review that uses developed techniques to identify the causes of the substantial degradation observed in the lithium-ion battery material. The bottom-line goal is to understand the prevailing degradation mechanism of the system components and improve their potential application in lithium-ion battery materials. Moreover, as one of the objectives of this review, improving our understanding of different mitigation techniques will provide feasible protection to lithium-ion batteries used in different applications.

2. Hydrogen Production in Hybrid Renewable Energy Systems

The production of hydrogen has garnered significant interest in contemporary hybrid renewable energy systems since it provides renewable energy for use in different applications. In a renewable-intensive energy system, hydrogen is produced using water electrolysis, where electricity from wind or photovoltaic power-producing facilities is selectively supplied to an electrolyzer, which decomposes water into hydrogen and oxygen. This technology generates clean fuel for backup power generation, transportation, and industrial heating [19]. Guo et al. [20] reported that the efficiency of hydrogen production is significantly influenced by the stability of power demand and the feedback capability of the electrolyzer, as well as the operational strategy for the timing of hydrogen synthesis in relation to electricity demands [20].

2.1. Role of Batteries in Hybrid Energy Configurations

In hybrid power systems, the battery functions as the storage mechanism and provides short-term support for managing rapid fluctuations in renewable energy. Lithium-ion batteries are frequently selected for this purpose because of their elevated round-trip efficiency, rapid response time, and scalability across distribution and off-grid networks [9]. An electrical battery, when integrated with a hydrogen subsystem, is typically engineered to absorb rapid transients, with the majority of the power levels and durations supported by the hydrogen production unit, yielding synergistic operational benefits that enhance system resilience and economic feasibility.

Table 1. Improvements in the present study compared to previous studies.

Research Area	Key References	Limitation of Previous Studies	Improvement in Present Review
Battery ageing mechanisms	Vetter et al. [21]	Focus on electrochemical ageing	Integrates hybrid renewable–hydrogen operation
Graphite cracking and mechanical degradation	Takahashi et al. [22]; Pistorio et al. [23]	Material-level focus	Links material degradation to system performance
AI-based prognostics	Zhang et al. [15]; Richardson et al. [24]	Prediction-oriented	Combines AI with physical degradation mechanisms
EIS-based diagnostics	Tröltzsch et al. [25]; Galeotti et al. [26]	Single-technique focus	Multi-technique characterization framework
Degradation modelling	O’Kane et al. [27]; Li et al. [28]	Limited system integration	Includes battery–hydrogen interactions

shows the improvements in the present study compared to previous studies.

2.2. Hydrogen Production and Battery Functionality

An integrated renewable–hydrogen energy system, which incorporates both electrochemical storage and the hydrogen path, may be used to mitigate variations and improve flexibility in the power system. In such systems, electricity is produced by intermittent renewable sources (solar photovoltaics, wind energy) and electrolysis to produce hydrogen, while decarbonization occurs in various sectors through electrolytic hydrogen production [29]. The long-term ability to store energy may facilitate decarbonization across a wide range of applications, such as electricity reconversion (sector coupling), industrial processes and coalition into the transport sector [29]. A variety of electrolyzers are used for hydrogen production, for example, proton exchange membrane (PEM) and solid oxide systems, which possess different dynamic behaviours that may affect their usage in renewable-powered systems. Curcio et al. [30] show that PEM-based electrolyzers offer better response in load following, which can achieve higher current density for renewable energy integration [30]. However, lithium-ion battery and material conversion efficiencies are still vulnerable to transient electrical input, which puts strong demand on intermediate buffering storage. In such hybrid systems, the lithium-ion battery can act as a fast response system to reduce fluctuations in voltage and power before energy is supplied to the hydrogen generation subsystem [31]. An intercalation-based anode and a transition-metal oxide cathode, together with the electrolyte, separator, and current collectors, are used in the internal design of the battery to enable high round-trip efficiency [32]. Improved control is needed to synchronize the power flow balance when utilizing battery and hydrogen systems to improve economic performance. The trade-offs between hydrogen production subsystems and battery degradation highlight the need for systems that can consider electrochemical stability, operational robustness, and life-time cost. Andersen [33] asserts that a battery’s storage system moderates power variations encountered in hybrid energy systems, hence enhancing hydrogen production and diminishing the frequency of start–stop cycles, which subsequently alleviates mechanical or electrochemical stress on hydrogen production equipment. Recently, advanced control has been suggested to optimize economic advantages by synchronizing the power dispatch of battery and hydrogen systems, especially in scenarios with significant renewable integration [34].

2.3. Battery Degradation in Hybrid Energy Systems

Lithium-ion batteries utilized in hybrid hydrogen–renewable systems experience increased degradation due to operating at a partial state of charge or rapid temperature fluctuations resulting from charge–discharge cycling [35]. Deterioration results from electrochemical, mechanical, and thermal processes that occur within the cell. These factors encompass the persistent expansion of the solid electrolyte interphase (SEI), depletion of active lithium inventory, microcracking in the cathode due to recurrent lattice expansion and contraction, and deterioration of the pore structure in the separator [36]. During the transition from a battery-dominant to a hydrogen-dominant regime, the battery encounters fluctuating currents that exacerbate side reactions, increase impedance, and diminish the total accessible capacity of the storage element, resulting in a decreased usable lifespan of the energy storage component. Studies [36] have shown that the effects of battery degradation are experienced from the cell level to the system level in hybrid renewable–hydrogen systems. Because a degraded battery provides diminished protection, the electrolyzer and fuel cells are subjected to greater power fluctuations, resulting in accelerated deterioration rates of these components and reduced consistency in hydrogen production.

2.3.1. Impacts of Battery Degradation on the Lifespan and Efficiency of Electrolyzers in Hybrid Systems

Battery degradation presents a significant challenge in renewable–hydrogen hybrid systems because batteries serve as the primary buffering component between intermittent renewable energy sources and hydrogen production units. Unlike standalone battery applications, degradation in hybrid systems has far-reaching implications that extend beyond individual cell performance and directly affect overall system reliability, hydrogen production stability, and economic viability. As battery capacity decreases and internal resistance increases over time, the system may require larger battery installations or more frequent battery replacements to maintain operational reliability, thereby increasing lifecycle and operational costs [37].

The consequences of battery degradation are particularly critical in systems where stable power delivery is required for electrolyzer operation. Fluctuations in battery performance can introduce power variability, reducing the robustness of hydrogen production and adversely affecting power quality and energy management strategies. Consequently, battery health becomes a key determinant of long-term system sustainability, highlighting the importance of real-time degradation monitoring and predictive maintenance frameworks for renewable–hydrogen energy infrastructures.

The degradation behaviour of lithium-ion batteries in hybrid systems is considerably more complex than in conventional stationary storage applications. Studies have shown that variable renewable generation, partial state-of-charge operation, frequent charge–discharge cycling, and temperature fluctuations accelerate ageing processes and contribute to non-uniform degradation patterns [37]. At the electrochemical level, these degradation mechanisms are associated with the continuous growth of the solid electrolyte interphase (SEI), loss of active lithium inventory, cathode particle microcracking during repeated phase transitions, electrolyte decomposition, and transition-metal dissolution. Collectively, these processes increase cell impedance, reduce energy storage capability, and impair power delivery performance.

Furthermore, the dynamic operating conditions characteristic of renewable–hydrogen systems can intensify degradation pathways. Uneven current distributions and rapid power fluctuations may promote lithium plating, particularly during high-rate charging or low-temperature operation, thereby accelerating irreversible capacity loss and increasing safety concerns [38]. Compared with conventional grid-scale storage applications, batteries in hybrid systems often experience higher cycling frequencies and more demanding load profiles, which further accelerate capacity fading and resistance growth. As a result, the battery’s ability to perform its buffering function progressively diminishes, exposing electrolyzers and fuel cells to greater electrical stress and operational instability.

The implications of battery degradation therefore extend beyond the cell level and influence the performance of the entire hybrid energy architecture. Reduced battery efficiency and storage capacity can decrease hydrogen production consistency, compromise system flexibility, and increase operational expenditure due to maintenance and replacement requirements [39]. These challenges have motivated the development of advanced battery management approaches that integrate electrochemical diagnostics, degradation modelling, and machine learning-based prognostics. Such methods enable early detection of deterioration trends, estimation of remaining useful life, and implementation of mitigation strategies before substantial performance losses occur [40,41]. Consequently, the integration of predictive health monitoring systems is increasingly viewed as a prerequisite for achieving economically viable and reliable renewable–hydrogen hybrid energy systems.

2.3.2. Impact of Partial State-of-Charge Cycling in Hybrid Systems

Hybrid systems often use partial state-of-charge cycling, where batteries are charged and discharged within a narrow range of states of charge. This alleviates severe stress but also yields distinct modes of degradation. Limited cycling reduces mechanical stress and strain from volume expansion of active materials. But it can accelerate chemical degradation reactions, such as the formation of the interfacial layer and lithium imbalance. This can result in efficiency loss and increased resistance. While shallow cycling provides a longer cycle life, it might not necessarily increase the energy delivered to the user. Furthermore, non-uniform ageing can occur, affecting the battery’s reliability. These processes are impacted by temperature and operating conditions. Elevated temperatures can lead to faster degradation, and low temperatures can result in lithium plating. So, temperature control is essential. New models, including deep learning, have been created to gain insights into these processes. These can capture intricate relationships in battery data that are impossible to capture with more conventional approaches. But they need extensive data and are hard to understand.

2.3.3. Impact of Deep Cycling and Shallow Cycling on Capacity Degradation

Depth of discharge (DoD) strongly influences capacity degradation in the lithium-ion batteries used in renewable–hydrogen hybrid systems. Deep cycling, usually involving large charge–discharge swings such as 80–100% DoD, accelerates capacity fade because electrode materials experience greater mechanical, electrochemical, and thermal stress during each cycle. In contrast, shallow cycling, typically within narrower operating windows such as 10–50% DoD, reduces structural strain and extends cycle life, although it limits the usable energy available per cycle [42].

Deep cycling increases capacity degradation through several coupled mechanisms. Large lithium insertion and extraction ranges cause repeated expansion and contraction of active materials, promoting particle cracking, loss of electrical contact, and exposure of fresh electrode surfaces to the electrolyte. This accelerates solid electrolyte interphase (SEI) growth, consumes cyclable lithium, and increases cell impedance. NREL reports that lithium-ion cycle life depends strongly on DoD, C-rate, and temperature, with deeper discharge generally reducing battery lifetime. In hybrid hydrogen systems, deep cycling may occur when batteries are required to compensate for prolonged renewable energy deficits before hydrogen or fuel cell backup becomes available. Under such conditions, batteries experience higher energy throughput per cycle, which increases capacity loss and shortens replacement intervals. Shallow cycling reduces the severity of mechanical and electrochemical degradation because the battery operates within a narrower state-of-charge window. This limits lattice expansion, reduces electrode stress, and slows impedance growth. Cui et al. developed a cycle-life prediction model specifically for lithium-ion batteries under shallow-depth discharge conditions and identified DoD, temperature, discharge rate, and taper voltage as stress factors that are important for controlling capacity loss [42]. Similarly, techno-economic modelling of second-life batteries showed that restricting the operating window to approximately 15–65% state of charge can reduce cycle ageing and extend project life. This indicates that shallow cycling can be an effective strategy for extending battery service life in hybrid renewable–hydrogen systems.

Quantitatively, deep cycling can reduce the number of achievable cycles by several times compared with shallow cycling. For example, commercial LiFePO₄ systems are often reported to deliver around 3000 cycles at 100% DoD, about 5000 cycles at 80% DoD, around 8000 cycles at 50% DoD, and more than 12,000 cycles at 30% DoD, although exact values depend on chemistry, temperature, C-rate, and manufacturer design. This trend shows that reducing DoD from full cycling to moderate or shallow cycling can more than double practical cycle life. Therefore, in hybrid hydrogen architectures, a battery operated at shallow DoD may provide longer service life and lower replacement cost, while a deeply cycled battery may provide higher short-term usable capacity at the expense of accelerated degradation. However, shallow cycling is not always universally beneficial. While it reduces mechanical stress, prolonged operation within narrow partial state-of-charge windows can produce non-uniform ageing, lithium inventory imbalance, and complex degradation patterns [42]. Therefore, the optimal cycling strategy should not only minimize DoD but also consider temperature control, C-rate limitation, hydrogen production demand, renewable variability, and economic replacement cost. In renewable–hydrogen hybrid systems, the most effective approach is degradation-aware dispatch, where the battery handles short-duration fluctuations while hydrogen storage manages long-duration energy deficits. This reduces deep discharge events, stabilizes electrolyzer operation, and improves both battery lifetime and hydrogen system reliability.

2.3.4. Specific Capacity Degradation Mechanisms in Renewable–Hydrogen Hybrid Energy Systems

Specific capacity degradation is one of the most critical indicators of performance deterioration in lithium-ion batteries operating within renewable–hydrogen hybrid energy systems [21]. Unlike conventional battery storage applications, batteries in hybrid systems are subjected to highly dynamic operating conditions characterized by intermittent renewable generation, fluctuating load demands, electrolyzer load-following operation, and frequent transitions between charging and discharging states. These conditions accelerate electrochemical ageing processes and contribute to a progressive reduction in the amount of charge that can be stored and delivered by the battery over time.

The primary mechanism responsible for capacity degradation is the continuous loss of cyclable lithium resulting from the growth of the solid electrolyte interphase (SEI) layer at the anode surface. In hybrid renewable–hydrogen systems, batteries frequently operate under partial state-of-charge conditions and experience irregular current profiles due to renewable intermittency. Such operating conditions promote repeated SEI formation and repair processes, consuming active lithium and gradually reducing the available charge capacity. As a consequence, the battery’s energy storage capability decreases even when the electrode structure remains relatively intact.

Another significant contributor to capacity fade is the degradation of cathode materials. Repeated cycling associated with renewable energy fluctuations causes structural changes within cathode particles, including phase transitions, microcrack formation, particle fragmentation, and transition-metal dissolution. These degradation processes reduce the availability of active material for lithium intercalation and de-intercalation reactions, thereby decreasing the reversible capacity of the cell. The problem becomes particularly severe in hybrid systems where batteries are frequently required to absorb rapid power fluctuations and maintain stable power delivery to electrolyzers.

Lithium plating represents another important degradation pathway under hybrid operating conditions. During periods of high renewable generation, batteries may experience rapid charging rates while operating at low temperatures or elevated states of charge. Under these conditions, lithium ions cannot intercalate efficiently into the graphite structure and instead deposit as metallic lithium on the anode surface. This process results in irreversible lithium loss, reduced capacity, increased impedance, and potential safety hazards. Furthermore, plated lithium can react with the electrolyte, accelerating SEI growth and promoting additional degradation.

Temperature fluctuations also play a crucial role in capacity degradation. Renewable–hydrogen systems are often deployed in environments where operating temperatures vary significantly throughout the day and across seasons. Elevated temperatures accelerate electrolyte decomposition, SEI growth, and transition-metal dissolution, while low temperatures increase internal resistance and promote lithium plating. The combined effects of thermal stress and cycling-induced degradation create complex ageing behaviour that is often more severe than that observed in conventional stationary battery applications.

The interaction between batteries and hydrogen production subsystems further influences capacity degradation. Batteries are commonly used to smooth short-term renewable fluctuations before power is supplied to electrolyzers. While this buffering function improves hydrogen production stability, it subjects the battery to high-frequency cycling and continuous charge redistribution. Such operational demands increase electrode stress, accelerate active material degradation, and shorten battery lifespan. As battery capacity decreases, its ability to stabilize electrolyzer operation diminishes, creating a feedback mechanism that can negatively affect both battery performance and hydrogen production efficiency. Recent studies [27] suggest that degradation-aware energy management strategies can significantly reduce capacity loss by limiting excessive cycling, controlling charging rates, maintaining optimal state-of-charge windows, and coordinating battery operation with hydrogen storage systems. Advanced diagnostic tools, including electrochemical impedance spectroscopy, differential capacity analysis, machine learning prognostics, and digital twin technologies, have also demonstrated potential for predicting capacity degradation and enabling proactive maintenance [27]. These approaches provide valuable opportunities for extending battery lifetime and improving the overall reliability of renewable–hydrogen hybrid energy systems. Specific capacity degradation in renewable–hydrogen hybrid systems arises from the combined effects of electrochemical ageing, mechanical deterioration, thermal stress, and operational variability. Understanding these interacting degradation mechanisms is essential for developing robust battery management strategies, improving system efficiency, and ensuring the long-term economic viability of hybrid renewable–hydrogen energy infrastructures [15].

2.3.5. Comparative Studies of Battery Degradation in Hybrid vs. Standalone Systems

Degradation is a major challenge in energy storage applications, including renewable energy integration, electric vehicles, and microgrids. While lithium-ion batteries are widely used for their efficiency and energy density, their capacity and performance degrade over time due to electrochemical and mechanical ageing. The effects of this degradation are highly dependent on the application. In this respect, two typical battery systems (standalone systems and hybrid systems) have different ageing characteristics due to their different operating conditions, load profiles and control strategies. Battery degradation can be classified into calendar ageing and cycling ageing [43]. Calendar ageing is the degradation of a battery at rest and is mainly dependent on temperature and state of charge, while cycling ageing is caused by charging and discharging. At the level of the materials used, degradation processes include the growth of the interface layer, loss of active materials, lithium plating and breakdown of the electrolyte. Due to the sensitivity to operating conditions, system design is a key factor in life expectancy. In standalone systems, such as those in off-grid renewable energy systems, the battery is the main source of energy. This can result in poor and high-depth cycling due to variable energy supply and demand. For example, solar systems normally undergo charging when the sun is up and deep discharge when the sun is down. This increases stress on the electrode materials, leading to structural damage (cracking) and loss of electrical contact. Additionally, extended periods of partial charge can cause lithium distribution issues and side reactions, which also contribute to degradation. Environmental factors are also crucial in off-grid systems. Batteries are typically placed in environments with inadequate temperature control, exposing them to temperature variations. Elevated temperatures can lead to chemical degradation, while low temperatures result in higher resistance and lead to lithium plating. These factors shorten the life of a battery if not managed. Hybrid systems, however, operate batteries alongside other energy sources like solar or wind power or utilities. In these systems, the battery is not the only energy source and can be managed more carefully. Batteries are usually operated at modest states of charge to avoid high states of charge and deep discharge. These systems also tend to reduce the magnitude and frequency of the cycles, relieving battery stress. However, hybrid systems pose new challenges. In some cases, batteries undergo fast but shallow charge and discharge cycles, as is the case in hybrid electric vehicles. While these cycles minimize mechanical strain, they can still contribute to capacity loss. Also, prolonged operation within a narrow state-of-charge range can encourage certain degradation processes not observed in deep cycling. Comparative research suggests depth of discharge plays an important role. Extended cycle life is typically achieved with shallow cycling, but this may not translate into better energy throughput over the battery lifetime. This comparison is further complicated by the effects of temperature and control strategies, as hybrid systems can be better managed. The other key difference is the control strategies. Hybrid systems use energy and battery management systems to manage operations in real time. This can reduce stress and increase battery life through predictive and adaptive algorithms. On the other hand, independent systems may use basic control strategies, which may not reduce degradation over time. Advances in machine learning have improved battery health prediction for both systems. Machine learning approaches can learn complex patterns between operating conditions and degradation, allowing more precise predictions of the remaining useful life. But these methods are more suited to hybrid systems, since large amounts of data can be collected. Economically, while standalone systems have higher degradation rates, leading to more frequent replacements, hybrid systems, despite their complexity, could provide better value over time due to increased efficiency and longevity. In the end, the choice of these configurations should take into account technical and economic aspects [44].

Previous work has explored the effects of variable loads on electrolyzer–battery systems. Electrolyzer–battery systems are increasingly being incorporated in hydrogen generation using renewable energy. But the variable output of solar and wind power plants creates dynamic loads that impact the efficiency and lifetime of an electrolyzer. Thus, handling these variable loads is critical. The power generated from renewable sources fluctuates based on weather conditions, resulting in variable power input to the electrolyzer. This can result in frequent start-ups and shut-downs and partial load operations, both of which affect efficiency and increase wear. Electrolyzers are usually designed to operate under constant conditions, and variations in these conditions can affect their efficiency. The use of batteries can mitigate this problem. They accumulate energy during periods of over-supply and discharge during periods of under-supply, resulting in a more consistent power supply to the electrolyzer. This helps to stabilize the electrolyzer and increase efficiency. But this buffering effect also introduces cycling stresses on the battery, affecting its degradation. Load conditions in these systems can be constant, ramping, cycling or random. These load profiles introduce various stresses. For instance, sharp load variations can lead to thermal and mechanical stress, while cycling can lead to battery deterioration. Control strategies are important in managing these effects. Techniques like predictive control can enable the system to anticipate and respond to changes in power output. These strategies can enhance efficiency and mitigate degradation but rely on precise predictions and models. Dynamic operation also impacts electrolyzer performance, with energy loss and increased resistance due to changes in operating conditions. Batteries smooth load variations but must be carefully managed to prevent degradation from frequent cycling. Financially, load smoothing enhances efficiency and lowers maintenance costs, but the cost of batteries needs to be offset. System design is a balance of these considerations. New technologies like artificial intelligence and digital twins can help to enhance system performance. They help to predict changes in load and optimize control to enhance resilience.

2.3.6. Economicity, Efficiency Coupling, and Life-Synergy Models in Renewable–Hydrogen Hybrid Systems

The increasing deployment of renewable–hydrogen hybrid systems has shifted research attention beyond energy balancing and hydrogen production toward integrated assessments of economic performance, operational efficiency, and component lifetime [45,46,47,48]. While batteries, electrolyzers, hydrogen storage systems, and fuel cells are often analysed independently, recent studies suggest that the overall sustainability of hybrid energy systems depends on the coupling of economicity, energy conversion efficiency, and degradation behaviour of the constituent components. From an economic perspective, the viability of renewable–hydrogen hybrid systems is commonly evaluated using indicators such as Net Present Cost (NPC), levelized cost of energy (LCOE), Levelized Cost of Hydrogen (LCOH), and component replacement costs. Vetter et al. [21] demonstrated that battery degradation significantly contributes to lifecycle cost because capacity fade and resistance growth increase replacement frequency and reduce energy throughput. Similarly, O’Kane et al. [27] reported that degradation-aware operational strategies can substantially reduce lifecycle expenditure by minimizing stress-induced ageing mechanisms. Consequently, modern techno-economic analyses increasingly incorporate degradation costs rather than assuming constant battery performance throughout the project lifetime.

The efficiency coupling between battery storage and hydrogen subsystems represents another critical factor affecting system performance. Lithium-ion batteries typically achieve round-trip efficiencies exceeding 90%, whereas hydrogen pathways involving electrolysis, storage, and fuel cell reconversion generally exhibit lower round-trip efficiencies ranging between 25% and 45% [49]. Despite these efficiency differences, the complementary characteristics of both technologies create significant operational advantages. Batteries provide rapid response and short-duration storage, while hydrogen systems offer long-duration and seasonal energy storage capabilities. Studies have shown that effective coordination between these storage technologies can reduce renewable energy curtailment, stabilize electrolyzer operation, and improve overall system utilization. However, excessive reliance on battery buffering may accelerate cycling-induced degradation, whereas excessive hydrogen utilization may increase conversion losses and operational costs. Therefore, efficiency optimization should consider both energy conversion pathways and degradation-related penalties. The concept of life-synergy has recently emerged as a promising framework for evaluating the mutual interactions between battery ageing, electrolyzer degradation, fuel cell deterioration, and system-level operational strategies. Unlike conventional lifetime models that treat each component independently, life-synergy approaches recognize that degradation of one subsystem directly influences the operating conditions and ageing behaviour of other subsystems. For example, a healthy battery can effectively absorb transient renewable fluctuations, thereby reducing start–stop cycles in electrolyzers and fuel cells and extending their operational lifetime. Conversely, battery degradation reduces buffering capability, exposing hydrogen production equipment to larger power fluctuations and accelerating degradation processes. Such interactions demonstrate that component lifetimes within hybrid systems are strongly coupled rather than independent. Recent advances in artificial intelligence and digital twin technologies have enabled the development of predictive life-synergy models capable of simultaneously monitoring battery state-of-health, hydrogen system performance, and economic indicators. Richardson et al. [24] demonstrated that data-driven prognostic models can accurately estimate battery state-of-health and remaining useful life under varying operational conditions. Similarly, Zhang et al. [15] employed machine learning approaches to identify degradation patterns from electrochemical impedance spectra, enabling early detection of performance deterioration. The integration of such predictive tools into energy management systems offers opportunities to dynamically balance economic objectives, efficiency optimization, and component longevity. Furthermore, degradation-aware dispatch strategies have been proposed to optimize power allocation between battery and hydrogen subsystems. Such strategies seek to minimize degradation costs while maintaining hydrogen production targets and renewable energy utilization. O’Kane et al. [27] argued that future hybrid energy systems should employ coupled electrochemical–economic models capable of simultaneously evaluating efficiency, degradation, and replacement costs. This integrated approach is expected to improve long-term system sustainability while reducing lifecycle expenditures.

2.4. Basics of Lithium-Ion Batteries

Batteries comprise interconnected electrochemical cells that store chemical energy and turn it into electrical energy. All electrochemical cells rely on redox (reduction–oxidation) reactions, which entail electron transfer between various species and the participation of reactants and products in redox reactions [50]. Energy storage in electrochemical cells is accomplished through the spatial segregation of oxidation and reduction processes occurring at separate electrodes, known as the cathode and anode, respectively. Ionic transport in a battery transpires via a liquid electrolyte. In lithium-ion batteries, lithium ions (Li⁺) serve as the charge carriers, as illustrated in Figure 1.

The anode of a lithium-ion battery typically consists of a copper current collector with carbon-based active components affixed to it. Graphite serves as an effective host material for a standard lithium-ion battery, demonstrating a favourable performance by lithiating at a comparatively low potential of 0.2 V vs. Li/Li⁺ and exhibiting a commendable gravimetric energy density of 372 mAh g⁻¹ [51]. More studies [51] have focused on the development of silicon (oxide)/graphite composites due to the significantly increased energy density attainable through the utilization of advanced active anode materials. However, the use of these composites incurs a cost, prompting ongoing efforts for their enhancement. Basically, a battery comprises four primary components, each contributing to its overall performance and efficiency, as illustrated in

Table 2. Components and functions of lithium-ion batteries.

S/No	Lithium-Ion Battery Component	Function	Reference
1	Anode	Anode materials play the role of energy density for the silicon or silicon oxide materials and carbon materials that provide good electrical conductivity, allow reversible lithium-ion intercalation, and exhibit excellent cycle stability.	[52]
2	Cathode	The cathode is made up of conductive aluminium foil as the current collector. Its surface is then covered with metallic oxide particles containing lithium and having the following general formula: (I) and a solvent, binder, conductive agent, and small amount of additional conductive material. The cycle life of a lithium-ion battery is controlled by positive electrode material.	[53]
3	Separator	A microporous film serves as a separator made of plastics such as polypropylene (PP), polyethylene (PE) and other plastic materials. It is strategically placed between the positive and negative plates of the battery to stop self-discharge and reduce short-circuiting risk between both poles. The separator features a high number of micropores, which allow for lithium-ion conductance. This will allow the battery to complete its circuit and charge or discharge.	[52,54]
4	Electrolyte	An electrolyte acts as a carrier to transport lithium ions between the cathode and the anode. The components in lithium-ion battery electrolytes are critical to the general performance and effectiveness of LIBs. By optimizing the composition of the electrolyte and adding electrolyte additives, we can expect enhancement in cycle life, safety and Li+ transmission performance of batteries. The adoption of a suitable electrolyte for a lithium-ion battery is expected to maximize the concerted performance.	[55,56,57]

.

Working Principle and Operating Range of Lithium-Ion Batteries

In a lithium-ion battery, the porous separator acts as an insulator between the electrodes and allows ionic transport through the cell. Lithium ions move from one electrode to the opposite face of the electrode in the battery during the charging or discharging process [58]. Conductive salts are added to lithium-ion battery electrolytes, and they are also used to improve the properties of added auxiliary agents. In the discharging process, most of the lithium is intercalated into the cathode active material [59]. When charging, lithium is oxidized at the cathode by an external current, and, in the process, Li diffuses through the electrolyte/separator and intercalates into graphite at the anode, which is then depleted during discharging [59]. A polymer separator is interposed between the two electrodes, which keeps the anode from contacting the cathode while allowing ionic conduction. According to Liu et al. [60], the usable range of a graphite anode exceeds the decomposition window of an electrolyte at low potentials and needs to be carefully monitored. Chandrasekaran et al. [61] investigated various circumstances and found that under lithiation, the potential drops to around 100 mV versus metallic lithium. Chae et al. [62] indicated that electrolyte reduction occurred on the surface of the anode, producing a solid film covering the anode [62]. The existence of an SEI can act as a protective film on graphite and can be used as anode active materials for lithium-ion batteries [48]. Lee et al. [63] proposed that, unlike other batteries, a lithium-ion battery should have its cell voltage and temperature continuously monitored. Vu et al. [64] mentioned that, compared to other technologies, lithium-ion cells suffer problems of low voltages at deep discharges. While there are many shortcomings of lithium-ion cell design, the cost ratio of lithium-ion batteries is low in some existing technologies [65]. In addition, the development of electric vehicles (EVs) further requires higher energy density in lithium-ion batteries.

3. Degradation Mechanism of Lithium-Ion Battery Components

The reactions in lithium-ion batteries cause deterioration of battery components due to various interrelated physical and chemical mechanisms that diminish performance. These mechanisms can be categorized into three main types, namely, electrochemical, mechanical, and thermally driven behaviours, each of which affects capacity retention and power supply in distinct manners. Gilbert et al. [66] reported that the stability of electrolytes can be deteriorated by electrochemical reactions within a cell through the creation of protective ionically conductive surface layers and the dissolution of active components [66]. Qian et al. [67] developed an advanced pseudo-two-dimensional (P2D) model that accounts for both solid electrolyte interphase (SEI) formation and lithium plating reactions, enabling a detailed representation of ageing mechanisms in lithium-ion batteries. A capacity-fade-based method for predicting charge–discharge behaviour was also proposed and validated using experimental results. The findings provide valuable insights and a comprehensive reference framework for coupled anode degradation modelling in Li-ion battery systems. Wu et al. [68] disclosed that certain mechanisms disrupt the internal equilibrium of ions and electrons, leading to a depletion of lithium inventory (LLI), increased internal resistance, and reduced rate capability. Mechanical and thermal degradation arise from the mechanical forces applied to battery materials during cycling and fluctuations in temperature [69]. Li et al. [18] revealed that repeated volume expansion and contraction can subject particles to microcracks, electrical contact failures, and active material pulverization while also exposing them to ageing at elevated or non-uniform temperatures, which exacerbates side reactions and leads to separator damage [18]. These degradation categories influence energy loss, diminish power output, and shorten the lifespan of batteries.

3.1. Categorization of Ageing Effects in Lithium-Ion Battery Degradation

Calendar Ageing vs. Cycle Ageing and Mechanisms

For lithium-ion batteries, degradation can generally be divided into ageing due to pure time and the classical number of charge–discharge cycles [70]. This ageing is due to slow chemical processes such as: electrolyte degradation, passive film growth, and lithium consumption [70]. In contrast, cycle ageing is due to cycling-induced variations in electrode potential, lattice expansion and ionic conductivity, which progressively change internal components. Chahbaz et al. [71] postulated that by differentiating these two processes, it is possible to design tests that partition time-dependent kinetics from cyclic stress effects. Both calendar ageing and cycle ageing contribute to the degradation of lithium-ion batteries, which results in poor battery life, efficacy, and performance. Fly et al. [70] revealed that it is quite possible that molecules decompose not only during charge–discharge cycles but also during reactions on an electrode surface to form a thicker solid electrolyte interphase [70]. The trapped active lithium ion in this layer limits the available storage quantity for exchange. Guo et al. [72] found that ageing is mainly correlated with storage temperature and selected state of charge (SOC), highlighting the importance of adequate storage solutions [72]. Meanwhile, the cycle ageing mechanism is due to mechanical and electrochemical effects throughout the lithium-ion insertion/desertion process. During charging and discharging, particles located under electrodes may pulverize and become smaller due to expansion/contraction at electrodes, which might result in changes in contacts between the current collector and active materials [72]. This breakage of pieces creates more surfaces for additional nucleation of the SEI and leads to more lithium consumption. In addition, cycle-driven breakdown of electrolytes and changes in pore size can influence pore structures and retard ion diffusion. Gauthier et al. [73] demonstrated that such progressive changes are often more pronounced at higher depths of discharge and higher corrosion rates.

3.2. Categorization of Anode Degradation in Lithium-Ion Batteries

3.2.1. Development of Graphite in Passivation Films on the Anode

The solid electrolyte interphase (SEI), as it is termed, begins with the development of a passivation film on the surface of the graphite active material and forms on the anode side of the electrode. This form of deterioration is considered the most enduring and ongoing phenomenon at an anode [74]. The SEI is generated through the irreversible electrochemical breakdown of the electrolyte at the electrode interface [74]. The occurrence of a lithium-consuming irreversible electrochemical reaction is attributed to the thermodynamic instability of the electrolyte at operational potentials [75]. The research has additionally shown that lithium’s electrochemical intercalation directly competes with this process [75]. Wang et al. [74] identified a layer of reaction by-products acting as an electrical insulator that blocks the entry of electrolyte molecules and allows lithium ions to pass, creating a passivating coating [74]. Thickening of the SEI has been associated with a linear relationship with the duration of the process, which impedes further reduction of the electrolyte and lithium consumption [74]. However, during the progress of SEI formation, its continued growth consumes lithium and contributes to loss of energy capacity as well as reduced battery life [74]. Li et al. [76] revealed that decomposition of electrolytes causes a decrease in ionic activity and an increase in internal resistance. The authors argued that due to continuing volume variations and mechanical strain, which always expose active materials to electrolytes, SEI formation cannot be avoided [76]. The authors [76] reported that excessive discharge electrical potentials at an electrode can induce oxidation–reduction processes at a copper foil current collector [76]. Moreover, the authors [76] advised that inadequate adherence of an active material to a current collector might result in substantial capacity degradation [76]. Moreover, dissolved copper species in an electrolyte can be gradually deposited on electrode surfaces, obstructing intercalation sites and diminishing both the capacity and lifespan of the anode in a battery.

3.2.2. Silicon Oxide Volume Fluctuation

The utilization of silicon (Si) and silicon oxides as anode materials in lithium-ion batteries seems promising, and these materials are generally employed as a composite with graphite. However, similar to graphite, thorough studies have demonstrated that the lithiation and delithiation of silicon result in significant volume variations [77]. A change in volume can lead to rapid expansion of the SEI, resulting in lithium loss and fragmenting silicon particles into a fine powder, potentially pulverizing the entire electrode, as illustrated in Figure 2.

As shown in Figure 2, there are cracks parallel to the surface of silicon on both sides of each delithation and lithiation process that enlarge and shrink when going through the SEI layer. The SEI layer also decomposes and reforms during a longer cycle life, as reported by Jia et al. [78]. Comparing SiOx and graphite, it was observed that volume variations were less extreme in both cases than for silicon [79]. However, the origin of the phenomenon is different [79]. As for the case of elemental silicon, silicon oxides have a lower initial coulombic efficiency, such that irreversible lithium silicates are formed during the initial lithiation process [80]. During the subsequent delithiation, the lithium silicates remain completely inert, and the residual silicon is able to alloy reversibly with lithium [81]. A sufficiently high upper limit of lithium Si oxide in the lithium–Si ratio effectively provides volume changes in silicon oxides, while Si oxides naturally have low electrical conductivity, resulting in incapable autogenic cells with active substances.

3.2.3. Degradation of the Anode Material Caused by Mechanical Processes

Numerous researchers have demonstrated that the intercalation of lithium into the interstitial spaces of graphite planes results in the growth of graphite layers [82]. The cyclical action, including expanding and contracting, as previously explained, may induce microcracks at the grain boundaries in polycrystalline graphite. Pistorio et al. [23] reported that the size of an active material experiencing cracking is proportional to the current flowing through it [23]. According to previous findings, the co-intercalation of solvent, gas evolution, and electrolyte reduction at graphite can intensify particle cracking and accelerate electrode degradation [83]. Other researchers [18] have demonstrated that significant cracking can induce a continuous expansion within graphite particles throughout each cycle, ultimately resulting in an increase in the overall volume of the entire active material due to recurrent stress [18]. The heightened volume further intensifies the internal pressures within the electrode stack geometries of lithium batteries, particularly in cylindrical cells constrained by rigidity. Lin et al. [84] indicated that the formation of numerous particle fractures, when a neighbouring particle separates from its associates and becomes electrically isolated, substantially diminishes an anode’s power storage capacity. Takahashi et al. [22] showed that the expansion and contraction of an active material due to these processes, along with the resultant cracking, may also result in the shattering of the SEI structure, thereby exposing the anode graphite surfaces directly to the electrolyte.

3.2.4. Modelling the SEI and AI-Based Degradation Prediction

The solid electrolyte interphase is a major determinant of battery degradation. It develops on the anode and prevents ongoing electrolyte decomposition, but it grows over time, resulting in the loss of lithium and an increase in resistance. Existing SEI growth models are based on physical and chemical considerations, including diffusion. These models offer insights into the processes but can be complicated and may not be accurately parameterized. Data-driven methods using artificial intelligence can learn degradation patterns. Neural networks, such as long short-term memory (LSTM) networks, can forecast battery health from usage data without requiring explicit models of all physical processes. A hybrid approach leverages physics-based and data-driven approaches. These models can be physically consistent and capture complex and hard-to-model behaviour. However, there are still issues with data, interpretability, and generalizability to other battery systems. Overcoming these challenges will be crucial for the successful adoption of AI-based strategies in battery management systems. The degradation pathways of various cathode chemistries (NMC, LFP, NCA) have been extensively studied. The choice of cathode material is a key factor in the performance, lifespan, and safety of lithium-ion batteries. NMC (nickel–manganese–cobalt), NCA (nickel–cobalt–aluminium) and LFP (lithium iron phosphate) are some of the widely used materials with unique structures and electrochemical properties, which result in different degradation pathways. This knowledge is crucial for selecting the right battery chemistry for applications like electric vehicles and energy storage. The degradation of batteries involves a combination of lithium loss, structural changes and interfacial reactions. Some processes, such as the formation of an interphase on the anode, are common to all batteries, but degradation is largely determined by the cathode chemistry. NMC materials are layered and offer high energy density. But they are vulnerable to high voltage and temperature. One problem is that transition metals dissolve and relocate to the anode, where they promote undesirable side reactions. Moreover, the surface can undergo phase changes to less conducting phases, which inhibit lithium transport. Nickel-rich NMC is particularly unstable due to the reactivity of highly oxidized nickel species with the electrolyte. Cycling also causes stress through volume expansion and contraction, causing cracks in particles. NCA is similar to NMC but contains aluminium instead of manganese. This increases specific energy and decreases stability. Like high-nickel-content NMC, NCA is prone to structural changes and surface phase transformations that can block lithium-ion diffusion. Its high nickel content makes it highly susceptible to thermal runaway and degradation under extreme conditions, such as deep discharge and fast charging. By contrast, LFP has an olivine structure that is inherently stable and safe. It is nickel- and cobalt-free, avoiding problems with metal dissolution. Consequently, LFP batteries tend to degrade more gradually and have a longer lifespan. The degradation is related to a loss of electrical contact within the electrode rather than an instability of the active material itself. But LFP has a lower energy density and conductivity than layered oxides. Comparing these materials, NMC and NCA will deliver higher energy but will be more vulnerable to stress (such as temperature, high state of charge and fast charging). LFP is more stable and safer but offers lower energy density. Moreover, the cross-talk between electrodes varies: in NMC and NCA cells, dissolved metal ions attack the anode, while this does not occur in LFP cells. In summary, there are trade-offs. NMC or NCA are suitable for high energy density whilst LFP is more suitable for long life and safe applications. Future research should be aimed at material modification and control techniques to minimize degradation in all chemistries.

3.3. Categorization of Cathode Degradation in Lithium-Ion Batteries

3.3.1. Dissolution of Transition Metals Used as Cathodes

The cathode active materials in lithium-ion batteries progressively deteriorate over time due to fluctuating environmental and operational conditions. Studies [85] have demonstrated that the degradation of active materials undermines the advantages of enhanced reversible capacity provided by nickel-rich layered materials utilized in the cathode components of a battery system. The dissolution of constituent metals in layered transition-metal oxides can lead to a decline in the performance of lithium-ion batteries under specific conditions. Both increased cathode potential and increased temperatures expedite dissolution, potentially resulting in structural instability of the host material. Zhan et al. [85] indicated that the occupation of lithium-ion transport sites by dissolved metal species further diminishes the pathways available for diffusion through or along a specific cathode.

3.3.2. Phase Transitions, Oxide Formation, and Degradation of Major Cathode Materials

Cathode degradation is one of the primary causes of performance loss in lithium-ion batteries and is strongly associated with structural phase transitions that occur during repeated lithium insertion and extraction. Under prolonged cycling, elevated temperatures, high states of charge, or overcharging conditions, cathode materials may undergo irreversible phase transformations that destabilize the crystal lattice and promote oxygen release. The released oxygen can react with the electrolyte to form surface oxide species and decomposition products, resulting in the formation of resistive surface layers, increased impedance, and accelerated capacity fade [21]. These phase transitions are often accompanied by transition-metal dissolution, microcrack formation, particle fracture, and loss of active lithium inventory, all of which contribute to long-term battery degradation. Among commercial cathode materials, lithium nickel manganese cobalt oxide (NMC) exhibits degradation primarily through phase transitions from the layered structure to spinel- and rock-salt-like phases during cycling, particularly at high voltages. These transformations are associated with oxygen loss, transition-metal migration, and surface reconstruction, leading to increased impedance and reduced lithium-ion diffusivity [86]. High-nickel NMC materials are especially susceptible to microcrack formation due to anisotropic lattice expansion and contraction during cycling. The resulting cracks expose fresh surfaces to the electrolyte, accelerating side reactions and transition-metal dissolution. Lithium nickel cobalt aluminium oxide (NCA) cathodes offer high energy density but suffer from structural instability at elevated states of charge. Nickel-rich regions are prone to oxygen evolution and surface degradation, resulting in the formation of inactive oxide layers and rock-salt surface phases [87]. In addition, NCA materials experience particle cracking and thermal instability, particularly under aggressive cycling conditions. The degradation of NCA is often characterized by capacity loss, impedance growth, and reduced thermal safety margins due to oxygen release from the cathode lattice. Lithium cobalt oxide (LCO), widely used in portable electronics, exhibits degradation mechanisms associated with phase transitions and cobalt dissolution at high operating voltages. Excessive delithiation destabilizes the layered structure and promotes oxygen release, leading to the formation of Co₃O₄ and other surface oxide species [5]. These reactions increase interfacial resistance and reduce reversible lithium storage capacity. Furthermore, repeated cycling can induce lattice distortion and mechanical stress, resulting in particle cracking and progressive performance deterioration. Although the degradation pathways differ among NMC, NCA, and LCO cathodes, a common feature is the occurrence of phase transitions that trigger oxygen release, surface oxide formation, transition-metal dissolution, and structural instability. These interconnected degradation mechanisms ultimately lead to capacity fade, impedance growth, reduced power capability, and shortened battery lifetime. Advanced characterization techniques such as in operando X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and X-ray absorption spectroscopy (XAS) have been widely employed to monitor these phase transformations and provide insights into cathode degradation mechanisms.

3.4. Electrolyte and Separator Deterioration in Lithium-Ion Batteries

The properties and components of the electrolyte significantly influence the behaviour of both the electrolyte and the overall battery. Among emerging clean energy technologies, protonic solid oxide fuel cells (P-SOFCs) have gained widespread interest due to their ability to provide efficient, reliable, and environmentally sustainable power generation [88]. Furthermore, the chemicals employed in battery production and their reactivity with positive and negative electrodes influence the overall electrolyte properties [89]. Recent research by Tawonezvi et al. [89] demonstrated that the formation of di-fluorophosphate (DFP) and phosphorus fluoride oxide (POF₃) in electrode materials indicates the presence of conductive salts within lithium hexafluorophosphate (LiPF₆) that decomposed in the presence of impurity water, resulting in a reduction in the electrolyte’s ionic conductivity and an increase in the cell’s ohmic resistance. Tang et al. [88] provided a comprehensive review of machine learning-assisted advances and perspectives for electrolytes in protonic solid oxide fuel cells. During the formation of the SEI at the anode surface, the polymerization process’s behaviour, in relation to different electrolyte additives, is crucial for the subsequent phases of a lithium-ion battery’s lifespan [90].

3.4.1. Gas Evolution and Its Impact on Cell Swelling, Pressure Build-Up, and Separator Integrity

Gas evolution is a critical degradation phenomenon in lithium-ion batteries and becomes increasingly significant under the demanding operating conditions of renewable–hydrogen hybrid energy systems [91]. During battery ageing, electrolyte decomposition, solid electrolyte interphase (SEI) instability, lithium plating, cathode decomposition, and overcharge reactions generate gaseous by-products such as carbon monoxide (CO), carbon dioxide (CO₂), hydrogen (H₂), oxygen (O₂), and light hydrocarbons [92]. The rate of gas generation is strongly influenced by temperature, state of charge, cycling intensity, and cell chemistry. The accumulation of these gases within sealed cells increases internal pressure, resulting in cell swelling and mechanical deformation. In pouch cells, gas evolution commonly manifests as thickness expansion, whereas cylindrical and prismatic cells experience elevated internal pressure that may compromise structural integrity and safety [93]. Excessive pressure build-up can promote electrode delamination, loss of interfacial contact, and increased transport resistance, ultimately accelerating capacity fade and power degradation. Gas generation also has significant implications for separator integrity. Mechanical stress induced by cell swelling can deform separator structures, alter pore morphology, and reduce electrolyte wettability. Furthermore, pressure accumulation and reactive gaseous species may promote separator shrinkage, pore blockage, or mechanical failure, thereby increasing the risk of internal short circuits and thermal runaway [94]. Oxygen evolution from highly delithiated cathodes is particularly detrimental because it can react with electrolyte components, generating additional heat and accelerating degradation reactions [87]. In renewable–hydrogen hybrid systems, batteries are frequently subjected to fluctuating charging rates, partial state-of-charge operation, and intermittent renewable energy inputs that can intensify gas-generating side reactions. Consequently, monitoring gas evolution provides valuable insights into battery health and degradation progression. Advanced characterization techniques such as differential electrochemical mass spectrometry (DEMS), gas chromatography–mass spectrometry (GC-MS), operando pressure measurements, and in situ spectroscopy have emerged as powerful tools for identifying gaseous products and quantifying their evolution during cycling. Understanding the mechanisms of gas generation and their effects on cell swelling, pressure build-up, and separator degradation is therefore essential for improving battery safety, reliability, and lifetime in renewable–hydrogen hybrid energy systems.

3.4.2. Separator Ageing, Ceramic-Coated Separator Degradation, and Dendrite Formation

Separators play a critical role in lithium-ion batteries by physically isolating the anode and cathode while allowing lithium-ion transport through their porous structure. Although separators are generally considered electrochemically inactive components, their degradation can significantly affect battery safety, performance, and lifetime, particularly under the demanding operating conditions encountered in renewable–hydrogen hybrid energy systems. Separator ageing is primarily associated with pore closure, mechanical creep, thermal shrinkage, oxidation, and structural deterioration resulting from prolonged cycling and elevated temperatures [95,96]. One of the most common ageing mechanisms is pore closure, which occurs when separator pores become partially or completely blocked by decomposition products, SEI fragments, electrolyte degradation products, or deposited lithium species. Pore closure reduces ionic conductivity, increases internal resistance, and limits lithium-ion transport between electrodes. As cycling progresses, the resulting concentration polarization can accelerate battery degradation and reduce energy efficiency [96]. Mechanical creep represents another important ageing mechanism, whereby continuous compressive stresses generated during electrode expansion and contraction gradually deform the separator structure. Such deformation can alter pore geometry, reduce porosity, and compromise the separator’s ability to maintain electrode separation [95]. Separator oxidation becomes increasingly significant under high-voltage operation. Oxidative degradation of polyolefin separators, particularly polyethylene (PE) and polypropylene (PP), can result in polymer chain scission, loss of mechanical strength, and deterioration of thermal stability. Furthermore, oxidation products may contaminate the electrolyte and contribute to additional side reactions, accelerating overall cell degradation [96,97]. To improve thermal stability and mechanical robustness, modern lithium-ion batteries frequently employ ceramic-coated separators consisting of inorganic ceramic particles such as Al₂O₃, SiO₂, TiO₂, or boehmite deposited on conventional polyolefin substrates [3]. These hard ceramic layers improve heat resistance, suppress separator shrinkage, enhance electrolyte wettability, and provide improved resistance against dendrite penetration. Ceramic coatings also promote more uniform lithium-ion flux distribution, reducing localized current density hotspots that can trigger lithium plating [97]. Despite their advantages, ceramic-coated separators are not immune to degradation. Repeated cycling and electrode volume changes can generate mechanical stresses at the ceramic–polymer interface, leading to coating delamination, particle detachment, microcrack formation, and loss of coating uniformity. High-temperature operation may further weaken interfacial adhesion between the ceramic layer and polymer substrate. As degradation progresses, exposed regions of the underlying polymer separator become vulnerable to thermal shrinkage and mechanical damage, reducing the protective function of the ceramic coating [97]. Separator degradation is closely linked to lithium dendrite formation, one of the most critical safety concerns in lithium-ion batteries. Dendrites typically originate from non-uniform lithium deposition caused by high charging rates, low temperatures, electrolyte depletion, or local current density variations. Initially, lithium deposits form as small protrusions on the anode surface; however, continued lithium plating promotes the growth of needle-like or mossy structures that progressively extend toward the separator. While ceramic coatings can delay dendrite penetration by increasing mechanical resistance, persistent dendrite growth may eventually fracture the coating, penetrate separator pores, and create internal short circuits between the anode and cathode [98]. The interaction between separator ageing and dendrite formation often creates a self-accelerating degradation cycle. Pore blockage and separator deformation promote non-uniform current distribution, which enhances lithium plating and dendrite nucleation. In turn, dendrite growth damages separator structures, increases local stress concentrations, and further accelerates separator degradation. Consequently, advanced characterization techniques such as scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray computed tomography (XCT), Raman spectroscopy, and operando optical microscopy are increasingly used to monitor separator degradation and dendrite evolution in real time [98]. In renewable–hydrogen hybrid energy systems, batteries frequently operate under fluctuating power demands, partial state-of-charge conditions, and variable environmental temperatures, all of which can exacerbate separator ageing and dendrite formation. Therefore, the development of advanced separator materials, robust ceramic coatings, dendrite-resistant architectures, and degradation-aware battery management strategies remains essential for enhancing the safety, durability, and long-term reliability of hybrid energy storage systems.

3.5. Hierarchical and Causal Framework of Battery Degradation in Renewable–Hydrogen Hybrid Systems

Battery degradation in renewable–hydrogen hybrid systems is not governed by isolated failure mechanisms but rather by a hierarchy of interconnected electrochemical, mechanical, thermal, and operational processes. Understanding the causal relationships among these degradation phenomena is essential for developing accurate diagnostic tools, predictive models, and mitigation strategies. At the first level, system operating conditions act as the primary degradation drivers. These include fluctuating renewable energy inputs, partial state-of-charge operation, deep and shallow cycling, high charging rates, temperature variations, and frequent load transitions associated with electrolyzer and fuel cell operation. Such conditions create electrochemical and mechanical stresses that initiate degradation at the electrode–electrolyte interface.

The second level involves interfacial degradation processes, with solid electrolyte interphase (SEI) growth serving as the dominant ageing mechanism. Repeated SEI formation and repair consume cyclable lithium and increase interfacial resistance. Simultaneously, electrolyte decomposition generates gaseous and solid by-products that further thicken the SEI layer and reduce ionic conductivity. Under high charging currents or low-temperature conditions, non-uniform lithium-ion transport may lead to lithium plating on the anode surface. The third level consists of material degradation mechanisms triggered by interfacial instability. Lithium plating promotes dendrite formation and irreversible lithium loss, while transition-metal dissolution from cathode materials contaminates the electrolyte and accelerates SEI degradation. Repeated lithiation and delithiation induce mechanical stresses that generate particle cracking, electrode pulverization, and loss of electrical contact within active materials. These structural changes expose fresh surfaces to the electrolyte, accelerating secondary reactions and creating a feedback loop that intensifies degradation.

At the fourth level, structural degradation progresses to phase instability and loss of active materials. Cathode phase transitions, lattice distortion, and crystal structure collapse reduce lithium storage capability and impair electrochemical reversibility. Simultaneously, particle fracture and electrode delamination increase charge transfer resistance and reduce the effective utilization of active materials.

The final level corresponds to system-level performance degradation. The cumulative effects of lithium inventory loss, active material degradation, impedance growth, and structural deterioration manifest as capacity fade, power loss, reduced energy efficiency, and shortened battery lifetime. In renewable–hydrogen hybrid systems, these effects extend beyond battery performance and influence hydrogen production stability, electrolyzer efficiency, fuel cell operation, and overall system economics. This hierarchical framework demonstrates that degradation mechanisms are strongly coupled rather than independent. Consequently, advanced characterization techniques, degradation-aware control strategies, machine learning prognostics, and digital twin models should be designed to capture these causal relationships rather than focusing on individual degradation phenomena in isolation. Such an integrated perspective is particularly important for renewable–hydrogen hybrid architectures, where battery degradation directly affects system reliability, hydrogen production efficiency, and long-term economic sustainability.

4. Advanced Degradation Characterizations in Renewable–Hydrogen Hybrid Architectures

Advanced degradation characterization techniques have become increasingly important for understanding the complex ageing behaviour of lithium-ion batteries operating in renewable–hydrogen hybrid architectures. Unlike conventional battery systems, hybrid configurations expose batteries to intermittent renewable generation, partial state-of-charge operation, dynamic load fluctuations, and frequent charge–discharge transitions, which accelerate degradation through multiple interacting mechanisms. Consequently, advanced characterization approaches such as electrochemical impedance spectroscopy (EIS), differential capacity analysis (dQ/dV), X-ray diffraction (XRD), scanning and transmission electron microscopy (SEM/TEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and operando characterization techniques are increasingly employed to monitor structural, chemical, and electrochemical changes during operation. These methods enable the identification of degradation pathways including solid electrolyte interphase growth, lithium inventory loss, transition-metal dissolution, particle cracking, electrolyte decomposition, and phase transformations that contribute to capacity fade and performance deterioration. More recently, machine learning-assisted diagnostics, digital twins, and data-driven prognostic frameworks have emerged as powerful tools for integrating multiscale characterization data, enabling real-time state-of-health estimation, remaining useful life prediction, and degradation-aware energy management. The combination of advanced characterization, artificial intelligence, and predictive analytics is expected to significantly enhance the reliability, efficiency, and economic viability of future renewable–hydrogen hybrid energy systems by supporting early fault detection, adaptive control, and proactive maintenance strategies.

4.1. Characterization Techniques for Degradation Analysis

The progression of internal components of lithium-ion batteries can be assessed using different characterization techniques. These techniques can provide a clear understanding of lithium-ion degradation processes and are discussed in the subsequent sections.

4.1.1. Electrochemical Characterization

Electrochemical characterization is a necessary approach to discover the degradation process in lithium-ion batteries since this technique probes the dynamic responses of charge transfer, ion transport, and oxidation–reduction (redox) activities at electrode materials. With the degradation of battery cells, their electrochemical behaviour is changed, which indicates a combined effect of structural and kinetic/transport-related degradation [18,84]. Methods such as cyclic voltammetry, impedance spectroscopy, differential capacity analysis, and intermittent titration have been established for the quantitative assessment of solid electrolyte interphase (SEI) growth, lithium plating, active material depletion, and the escalation of internal resistance [99]. These are the methods for establishing a quantitative relationship between quantifiable performance decline and subsurface physicochemical processes. Research by Ha et al. [100] underscored the significance of cyclic voltammetry, electrochemical impedance spectroscopy, differential capacity analysis, and intermittent titration methods in correlating physical degradation with quantifiable electrochemical signals, as illustrated in Figure 3.

Figure 3a shows the evolution of voltage–capacity profiles during cycling, where increasing polarization and reduced capacity are observed with ageing. Figure 3b presents the corresponding dQ/dV curves, revealing peak shifts and intensity reductions associated with degradation of active materials. Figure 3c illustrates the gradual capacity fade over 600 cycles, indicating the cumulative impact of electrochemical and structural degradation processes.

4.1.2. Cyclic Voltammetry Indicators of Lithium-Ion Battery Degradation

Cyclic voltammetry (CV) is typically employed to assess redox activity, reaction reversibility, and kinetic characteristics associated with electrode ageing. Cyclic voltammetry involves applying a voltage to a cell that oscillates within a predetermined potential range at a specified scan rate, resulting in discernible oxidation–reduction peaks associated with the current [101]. The degradation of batteries alters both the positions and morphologies of these peaks, as well as their magnitudes observed in cyclic voltammetry tests [102]. The process results in a decrease in peak current amplitude caused by active material depletion, resulting in increased overpotential [102]. Electrochemical CV plots also demonstrate the formation of catalytic pathways, and these continue to grow in number with deterioration [103]. An increase in peak potential values, enhanced peak separation, and reduced peak current with age suggest that polarization has increased [104]. Kim et al. [105] further suggested that the distortion of a CV peak is correlated with SEI film thickness and a rise in impedance. Likewise, Lin et al. [106] employed CV to observe irreversible phase transitions occurring in Ni-rich cathodes during repetitive cycling. As lithium-ion batteries aged, a widening of the peaks in the cyclic voltammetry curves occurred due to slowing charge transfer kinetics. Further shifted or broadened peaks (at high angles) were also visible, implying the formation of extra phases or parasitic side reactions [106]. Decreases in peak intensities indicate that the capacity decrease over failure may be a gradual decline and/or no specific phenomena are caused by crystalline lithium percolation site failures. For this reason, besides its use as a qualitative visualization tool, CV can also be considered quantitative for the determination of the reversibility of reactions taking place at an electrode interface, its electroactivity stability, and changes in redox processes due to degradation. Han et al. [107] noted that the disappearance of distinctive plateaus in graphite anodes is associated with structural collapse and particle fracturing. Furthermore, additional parasitic peaks may arise from electrolyte oxidation or the formation of unstable surface coatings. Consequently, CV serves as a proficient instrument for the online examination of reversible deterioration (e.g., Li⁺ ion entrapment) and irreversible degradation (e.g., electrode disintegration or SEI breakdown).

4.1.3. Electrochemical Impedance Spectroscopy (EIS) as a Degradation Indicator of Lithium-Ion Batteries

Electrochemical impedance spectroscopy offers the benefit of a comprehensive frequency-domain study of non-functional battery resistances and interfacial activities. Electrochemical impedance spectroscopy (EIS) can analyse changes in the impedance spectrum by applying a minor sinusoidal perturbation over a wide frequency range to determine the contributions of the solid electrolyte interphase (SEI) layer, charge transfer, mass transport, electrolyte conductivity, and diffusion [108]. Fitting equivalent circuit models that represent diverse physical phenomena to Nyquist or Bode graphs yields a qualitative representation of those phenomena. Ageing significantly affects both interfacial and transport resistance. Suarez-Hernandez et al. [109] point out that EIS could be one of the few useful techniques to follow long-term degradation processes. The Nyquist and Bode plots obtained from EIS present contributions related to ohmic resistance, SEI resistance, charge transfer kinetics, and mass transfer [110]. Kiani et al. [110] showed that an enlargement of EIS semicircles is related to an increase in SEI thickness and a decrease in electrolyte access. Moreover, Cavaliere et al. [111] demonstrated that the growth of a Warburg tail reflects weak Li-ion diffusion in aged electrodes. As the ageing process is generally accompanied by an increase in impedance over time, EIS remains one of the most reliable and well-established techniques for ageing assessment. With the cycling of Li-ion cells, the impedance spectrum possesses some typical changes such as increased SEI resistance, charge transfer semicircles, and elongated Warburg tails due to hindered lithium-ion diffusion. Cavaliere et al. [111] also revealed that an increase in high-frequency semicircles with time is attributed to thickening of the solid electrolyte interphase (SEI), which is unstable, while an increase in mid-frequency impedance indicates damaged electrode/active sites of storage at the anode–electrode/electrolyte interface. At low-frequency levels, enhanced diffusion impedance could originate from the blockage of electrode pores, particle crushing or inhibited ion transportation. Therefore, EIS allows a rich deconvolution of degradation sources at different length scales. The representative equivalent circuit fitting facilitates the physical interpretation of impedance variations. Kim et al. [112] demonstrate that elevated high-frequency resistances result from electrolyte decomposition, whereas mid-frequency semicircles arise from charge transfer resistance linked to surface reconstruction. Low-frequency impedance (Warburg diffusion) diminishes when the porosity of cathodes decreases or when electrodes experience microstructural collapse. These relationships allow EIS to quantitatively track deterioration processes such as SEI instability, loss of electrical contact, and electrode densification.

4.1.4. Analysis of Differential Capacity (dQ/dV) Profiles of Lithium-Ion Battery Degradation

dQ/dV analysis, derived from the derivative of capacitance with respect to voltage, exhibits significant sensitivity to minor alterations in reaction mechanisms and phase transitions. Sharp features in the dQ/dV curve are associated with well-defined potential plateaus corresponding to successive states of Li intercalation [113]. The decay breaks, dislodges or distorts them, and dQ/dV is a sensitive means to identify structural deformations, depletion of the lithium budget and kinetic limitations. The technique is capable of monitoring the growth of lithium plating and damage to intercalation pathways. dQ/dV derived from capacity and voltage differential signals increases sensitivity to small changes in voltage profiles, thus aiding in a high-resolution visualization of reaction stages. Fly et al. [113] showed that broadening of peaks in dQ/dV results from significant degradation of the electrode active material with an increase in polarization. Mijailovic et al. [114] first observed lithium plating using dQ/dV, which showed distinct new peaks that formed at low potential. The changes in the dQ/dV peaks reflect a kinetic slowdown and modification to lithiation pathways as batteries age. With continued cycling, the features of the dQ/dV curves become lower and displaced to higher potential due to loss of active materials, increased resistance, and changes in staging. The disappearance of certain peaks represents irreversible structural damage, while the appearance of new ones might indicate degradation reactions or formation of new inactive phases. However, one of the advantages of using dQ/dV instead of charging/discharging capacity is that it can be used to amplify small voltage fluctuations; hence, it is better suited for an early detection scheme before they appear in capacity measurements. Kim et al. [115] suggested that the lack of clear dQ/dV responses in a graphite electrode reflects disordering at stage transitions. The splitting of dQ/dV peaks in a layered oxide cathode is attributed to cation mixing or irreversible phase transition. Sensitive to voltage kinetics, this strategy has already been used in mechanistic studies to diagnose electrode degradation before capacity loss occurs and stands as a valuable tool for extending ageing studies.

4.2. Structural and Morphological Techniques to Characterize Degradation

Deciphering structural dynamics of lithium-ion battery electrodes is crucial for a fundamental understanding of the sources of physicochemical degradation. Structural alterations often precede the electrochemically defined end-of-life of lithium-ion batteries by a wide margin, and even in the absence of discernible capacity loss, more advanced diagnostics are needed [116]. The combination of X-ray diffraction (XRD), electron microscopy (SEM/TEM), atomic force microscopy (AFM) and X-ray tomography offers several points of view at different length scales that give an overall picture of the degradation evolution, as illustrated in Figure 4.

While electrochemical methods measure functional decay, they do not identify dynamic microstructural and morphological changes responsible for the decay. The quantitative techniques used to study phase transformation, crystallographic distortion, surface layer formation, and mass transport in bulk materials include XRD, electron microscopy, atomic force microscopy, and X-ray tomography [117,118]. It is very important to be able to make direct observations of degradation phenomena correlated with material instability and long-term capacity loss. Although electrochemical methods evaluate functional degradation, they cannot provide an understanding of the dynamic changes in microstructure and morphology leading to degradation. The quantitative tools used to characterize phase transformation, crystallographic distortion, surface layer growth, and mass transport in bulk materials include XRD, electron microscopy, atomic force microscopy, and X-ray tomography. However, to enhance the performance of lithium-ion batteries, it is very important to understand degradation processes with respect to material instability and long-term capacity loss.

4.2.1. X-Ray Diffraction (XRD)

X-ray diffraction (XRD) remains one of the most informative techniques to detect changes in the crystallographic structure upon cycling. Insertion/extraction of lithium causes changes in lattice parameters that result in peak shifts, decreases or broadening of reflections in XRD patterns. Liang et al. [119] revealed that layered oxide cathode degradation is commonly characterized by the progressive movement of (003) and (104) reflections, accompanied by a decrease in their intensity ratio, which implies the beginning of cation mixing and weak structural disorder [119]. Extended cycling under operation or repeated high-voltage pulsing could lead to irreversible phase transitions into spinel phases, which appear as extra reflections unrelated to the pristine structure [120]. Such a phase transition directly demonstrates the bulk instability under electrochemical loading. Besides phase identification, XRD is a powerful tool for determining micro-strain and reduction in crystallite size. An incremental, stress-compensated lithiation process leads to unit cell distortion, manifested as increasing peak broadening upon cycling. A certain amount of micro-strain is linked with failure of particle breakage and reduced electrical contact in high-capacity cathodes [121]. By using this technique to measure micro-strain and crystalline disorder, XRD can detect mechanical failure precursors that are invisible during early-stage degradation. Lachal et al. [122] explored and described the de/lithiation mechanisms of LiFePO₄ by X-ray diffraction (XRD). The extraction of lithium ions from the particle generated a core made up of LiFePO 4, as shown in Figure 5.

4.2.2. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM)

Additionally, SEM provides a comprehensive understanding of surface morphology and mesoscale alterations during electrode ageing. Surface roughness, intergranular cracking, detachment between binders and active materials, and slurring at copper current collectors, which leads to an augmented solid electrolyte interphase on the anode, are all identified as potential causes of pore obstruction. Using SEM, Tong et al. [123] observed that the surface thickening and exfoliation on the anode and faceted fracture pattern on the cathode side of an electrode during operation were due to degradation of the electrodes. The authors [123] ascribed the morphological changes to capacity deterioration as a result of prolonged cycling.

Nanometric scaling characterization of material degradation can be performed using the TEM technique. This characterization method has been used to observe lattice fringes, surface deformation, grain boundaries, and nanoscale cracking of materials [124]. TEM also allows observation of inhomogeneous solid electrolyte interphase (SEI) growth, identification of smooth, thick SEI films and their evolution into unstable multilayers. Sun et al. [124] employed TEM to investigate atomic-scale deterioration, including dislocation formation, amorphization, and the development of ultrathin reconstructed layers on the surface of Ni-rich cathodes. The ability to make these measurements at the nanoscale provides invaluable information about degradation mechanisms that can be difficult to detect using XRD and SEM, especially during initial states when changes happen locally first and then spread throughout a sample. Ramdon et al. [125] also employed the TEM method to perform in situ characterization of LIBs (Figure 6).

The results indicated that the first lithiation leads to the simultaneous expansion of pure Al nanowires in both the radial and longitudinal directions (Figure 6c,d). The onset of void formation during the preliminary delithiation phase is seen in Figure 6e. In the second lithiation phase, these spaces are partially repaired and diminished in size, as illustrated in Figure 6f. Following the second delithiation, there is an augmentation in both the quantity and dimensions of the voids. The study’s findings provide a comprehensive analysis of the current understanding of lithiation and delithiation mechanisms in lithium-ion batteries; however, the preparation of transmission electron microscopy samples, which must be less than 1 µm thick to permit electron passage, may limit the accurate localization of analysed particles within the electrode.

4.2.3. Atomic Force Microscopy (AFM)

In addition to the morphological characterization techniques discussed above, atomic force microscopy (AFM) provides a complementary approach for investigating battery degradation by offering high-resolution surface topography and nanoscale material property measurements. Unlike conventional imaging techniques, AFM enables the simultaneous evaluation of surface morphology, roughness, adhesion, stiffness, and mechanical properties, making it particularly valuable for studying the evolution of the solid electrolyte interphase (SEI) during battery operation.

AFM is especially effective for examining changes in SEI structure and mechanical integrity as batteries age. Through force–distance measurements, researchers have shown that aged SEI layers often exhibit reduced elastic modulus and increased brittleness as a result of repeated formation and breakdown during cycling [126]. Furthermore, AFM height profiling reveals progressive increases in surface roughness on anode materials, indicating unstable SEI growth and degradation processes that contribute to higher interfacial resistance and diminished electrochemical performance. Yoon et al. [127] demonstrated that AFM can establish a direct micro-mechanistic relationship between changes in interfacial properties and battery performance deterioration, providing valuable insights into degradation pathways that are difficult to observe using other characterization methods.

When combined with electron microscopy, X-ray diffraction, spectroscopic techniques, and electrochemical diagnostics, AFM contributes to a comprehensive multiscale characterization framework for lithium-ion battery degradation. This integrated approach enables a deeper understanding of the structural, chemical, mechanical, and electrochemical changes occurring within battery electrodes and interfaces, thereby supporting more accurate diagnosis of degradation mechanisms and the development of effective mitigation strategies, as summarized in

Table 3. Lithium-ion battery structural and morphological degradation characterization techniques and findings.

S/N	Method Used	Findings	Reference
1	SEM	The results indicate that a higher current density increases lithium nucleation and below 300 μA cm−2, Cu film defects cause isolated lithium growth, leading to film cracking and lithium rod formation.	[128]
2	TEM	High electric fields at nanowire tips initiate lithium fibre nucleation and directional growth along the nanowire axis.	[129]
3	AFM	The technique provides useful information on the phenomena that take place at battery interfaces under operational conditions.	[130]
4	SEM	Localized lithium deposition initiates at pre-plated sites on a Cu film, eventually forming predominantly needle-like lithium structures with micrometre-scale heights.	[131]
5	X-Ray Tomography	Applied 3D imaging methods visualized the internal battery cell structure at different states (pre- and post-operation).	[132]
6	X-Ray diffraction	The results suggested that lithium plating on graphite anodes is heterogeneous and strongly correlated with local lithiation levels.	[133]
7	XPS	In situ XPS revealed the reaction pathway and key intermediates of oxalate formation during lithium–CO2 interactions.	[134]

.

Despite extensive research on the degradation mechanisms of lithium-ion battery components, it is well acknowledged that the surface coating of battery materials, particularly the solid electrolyte interphase (S/CEI) layer, is vulnerable to atmospheric fluctuations that can occur when the battery is removed from the cell, especially upon exposure to air. Consequently, an in situ or in operando characterization of the S/CEI layer might be beneficial for elucidating the degradation mechanism [35]. Nonetheless, many specific obstacles arise with each technique concerning data collection, the implementation of in situ or in operando cell analysis, and the capacity to correlate the acquired results [35]. A system capable of monitoring alterations in both the materials and the electrolytes at elevated voltages would be beneficial, as high-voltage battery materials such as LiCoPO₄ undergo considerable deterioration.

4.2.4. Spectroscopic Material Degradation Characterization Techniques

Spectroscopic techniques are essential for comprehending the chemical processes involved in the ageing of lithium-ion batteries. Electrochemical measures assess functional alterations, structural imaging evaluates physical changes, and spectroscopic techniques provide direct analysis of chemical bonding, surface composition, interphase development, and ion transport. Figure 7 illustrates the various ways that material degradation is characterized through spectroscopy. These observations are essential, as most degradation routes (SEI decomposition, electrolyte oxidation, transition-metal dissolution, and interfacial reconstruction mechanisms) stem from alterations in chemical states that cannot be detected using diffraction or microscopy alone. Lu et al. [135] described different characterization techniques capable of identifying the comprehensive behaviour of deterioration mechanisms at both the bulk and surface levels of materials.

4.2.5. X-Ray Photoelectron Spectroscopy (XPS) and Raman Spectroscopy of Local Bonding and Carbon-Based Structure Changes

XPS is one of the characterization techniques used to understand depth and interface chemistry in terms of both elemental composition and oxidation state. Studies [136] have shown interactions between electrolytes and electrode materials during the active life of a lithium-ion battery, resulting in a series of complex interphase films formed at electrodes. The deconvolution of these films with XPS is possible due to the sensitivity with which the technique can detect species such as LiF, Li₂CO₃, R–OCO₂Li and inorganic oxides that build up on electrode surfaces [137]. With ageing, SEI films can become thicker and composite with both organic and inorganic moieties. Ageing under high voltage leads to an increase in LiF derived from hydrogen fluoride and oxidized carbonate compounds, while storage ageing generates organic solvent reduction products [138]. XPS analysis on the surface of a cathode, for example, usually shows not only transition-metal fluorides but also an oxygen-deficient layer, which can reduce electrical conductivity. While the D and G bands of carbonaceous materials are attributed to the chaos and order of graphitic structures, respectively, ageing results in a modification of the D/G intensity ratio, indicating increased disorder caused by SEI deposition or structural degradation [139]. Raman spectra of cathodic materials indicate a shift in the metal–oxygen bond environment, suggesting structural deformation, cation re-organization, or surface reconstruction.

4.2.6. FTIR Spectroscopy for Functional Group and Electrolyte Decomposition Sensing

FTIR spectroscopy, although less popular than the more commonly used Raman spectroscopy, provides additional details pertaining to the functional groups and organics produced during the decomposition of an electrolyte. During battery cycling, solvent reduction, salt decomposition, and polymeric compounds are formed, which build up at the electrolyte–electrode interface. When characterized by FTIR, LiPF₆ and its derivatives, especially its partially reduced form, show absorption peaks indicative of C=O stretching, C–O–C linkages and P–F or P–O bonds, the presence of which reflects the degradation of LiPF₆ [140]. FTIR is effective and widely used to determine the breakdown of binders, oxidation of the electrode surface, and changes in polymeric separators. FTIR distinguishes between different degradation pathways in LIB interphases that result from complex interphase chemistry by identifying the presence of certain intact bonds. FTIR has been demonstrated to be useful for binder degradation, electrode surface oxidation, and polymer-type separator changes [140]. FTIR can assign specific chemical bonds to differentiate competing degradation mechanisms that develop in the complex chemistry of LIB interfaces.

4.2.7. NMR Spectroscopy on Lithium-Ion Mobility and Local Chemical Environments

NMR spectroscopy serves as a distinctive instrument for acquiring insights into lithium-ion mobility, diffusion characteristics, lithiation–delithiation mechanisms, and the local chemical environment in both electrodes and electrolytes. Solid-state NMR offers a direct local assessment of Li⁺ dynamics through relaxation times and chemical shifts related to lithium in different coordination states. Variation in these characteristics may be attributed to sluggish diffusion, trapped lithium, or alterations in site occupation, known as common phenomena associated with ageing electrodes. The NMR approach has demonstrated that Ni-rich cathodes exhibit reduced lithium mobility following surface reconstruction and pore blockage [141]. Due to its sensitivity to bulk properties rather than solely surface characteristics, NMR complements XPS and Raman spectroscopy by revealing interior degradation mechanisms that these instruments alone cannot detect in lithium-ion batteries.

4.2.8. In Situ and Operando Methods for Degradation Studies

Operando and in situ characterization techniques are considered important methods for understanding degradation processes in LIBs due to their ability to capture structural, chemical, and electrochemical changes during operation, as shown in Figure S1. Please see the Supplementary File for further details. In contrast to ex situ research, operando approaches enable the correlation of dynamic changes with electrochemical states. This feature is crucial, as numerous degradation mechanisms (e.g., phase transition, interphase creation, mechanical fracture, and oxygen release) are transient and typically vary throughout cycling. Recent advanced diagnostic research has shown that operando techniques enable the revelation of mechanisms that would otherwise remain obscure or disrupted due to specimen manipulation [142].

4.2.9. In Situ X-Ray Diffraction for Tracking of Phase Transitions and In Situ Electron Microscopy of Evolution at the Nanoscale

Operando X-ray diffraction (XRD) facilitates in situ monitoring of crystallographic changes during charge–discharge cycling. By continuously documenting diffraction patterns throughout cell operation, researchers may monitor reversible lithiation-induced structural alterations and irreversible deterioration, which may encompass phase decomposition or cation migration. An operando XRD examination of a layered oxide cathode revealed transient intermediate phases that occur solely during high-voltage cycling but disappear under equilibrium conditions [143]. The capacity to monitor such events in real time provides significant insights into how metastable states contribute to long-term structural instability. In situ TEM provides nanoscale insights into electrode shape and atomic arrangement during lithiation. Contemporary experimental TEM stages can conduct electrochemical cycling within a microscope, enabling direct visualization of crack initiation and propagation, grain boundary movement, and solid-state amorphization. Silicon anodes have been shown to significantly expand and fracture during in situ TEM tests, corroborating established ideas regarding mechanical degradation [144]. A less established instance of the intervention to electrochemically observe operando effects is presented in recent research on nickel-rich cathodes, where real-time evidence of surface reconstruction indicates the formation of disordered rock-salt layers during cycling [145].

4.2.10. In Situ Raman Spectroscopy on Bonding and Lattice Vibrations and XAS for Theoretical Dynamics of Electronic Structures

In situ Raman spectroscopy provides molecular-level insights into vibrational modes whose locations are altered when electrodes interact with Li ions. Raman mapping during cycling reveals the reduction and amplification of graphite staging transitions, metal–oxygen vibrational modes in multilayer cathodes, and solid electrolyte interphase-related species on anode surfaces. Given that Raman spectroscopy is sensitive to the local symmetry/bond length of cations, operando studies have been performed to follow the evolution of such early-stage structural disorders, which can be quite challenging to obtain from diffraction measurements [146]. These features render Raman techniques a powerful way to monitor the evolution of chemical bonding associated with an electrochemical signal. In operando XAS allows the exploration of changes in the oxidation state, local geometry, and electrical transition of electrode materials. Researchers can take advantage of a particular absorption edge by fixing the energy of the incident beam to track changes in the oxidation state and local states during the cycle [147]. In a study, Yang et al. [148] showed that the ratio of Ni²⁺ and Ni⁴⁺ in a cathode material changed with the application of high voltage, indicating the onset of oxygen incorporation as a charge-compensatory mechanism. This research helps to explain the chemical nature of oxygen release and surface restructuring, leading to the degradation of a battery at high voltage. Through in operando testing, scientists can distinguish the reversible entrapment of lithium from the irreversible loss of charge contributing to battery capacity degradation [149].

4.3. Modelling and Simulation of Degradation in Lithium-Ion Batteries

Lithium-ion battery (LIB) degradation simulation and modelling have proven useful in the prediction of cell processes, especially those that are hard to directly observe. Researchers [150] have revealed that the degradation of LIB cells results from a combination of electrochemical reactions, heat generation, mechanical forces, and material degradation. The multi-physics phenomena are presented in Figure S2. Please see the Supplementary File for further details. By coupling such physical realms, it is possible to simulate crucial processes of degradation, such as lithium plating, particle breakage, and active material shedding [151]. By understanding the degradation process and conducting laboratory-scale testing, predictive models of maintenance and life extension techniques for batteries can be enhanced.

4.3.1. Multi-Physics: Electrochemical–Thermal–Mechanical (ETM) and Advanced Models

Electrochemical–thermal–mechanical (ETM) coupled models are capable of simultaneously explaining the coupling among lithiation kinetics, generated heat, and mechanical strain. Researchers [152] reported that volumetric expansion of a material during the intercalation process results in mechanical stresses, which in turn affect reaction kinetics and transport properties. Feng et al. [153] employed the ETM characterization technique to assess the effect of local temperature on the SEI layer, the ionic conductivity governed by strain, and the evolution of the accumulated heat in the region of thermal escape during the fast charging process. The objective was to understand the degradation mechanism of a lithium-ion battery. The results showed that significant degradation occurred in the energy density, cycle life, and safety of the battery with increasing battery usage.

4.3.2. Lithium Plating and SEI Evolution Predictions with ETM Models and Finite Element Modelling (FEM) of Stress and Crack Propagation

Advanced ETM models involve complex interphase formation dynamics capable of simulating distributions of SEI thickness and lithium plating thresholds. A study performed by Zhuang et al. [154] showed that local overpotential, temperature gradients, and diffusion-induced stresses have a considerable effect on plating. At high C-rates and lower temperatures, models predict considerable concentration gradients of lithium with a dramatically increased risk of plating, especially in the vicinity of the anode. Other researchers [155] demonstrated that ETM models are excellent for simulating charging protocols capable of augmenting thermal overload and mechanical degradation processes. FEM offers excellent spatial resolution for studying the effects of stress development and cracking within electrode particles and composite electrodes. Studies [156] have shown that macroscopic stress concentrations significantly arise at particle surfaces and grain boundaries due to anisotropic expansion forces induced by the insertion and extraction of lithium from particles, and these forces can result in particle cracking. With cyclic loading, oscillations in the stress state increase within large contacting areas until the threshold of catastrophic failure is attained [157]. By applying the finite element method (FEM) approach at the mono-particular or electrode scale, important structural parameters affecting the mechanics of stability of particles and electrodes can be established.

4.3.3. Machine Learning in Degradation Forecasting

Machine learning (ML) has demonstrated potential in predicting capacity fading and internal resistance increase in lithium-ion batteries (LIBs). In contrast to mechanistic models, machine learning utilizes previous cycling data, impedance spectroscopy, voltage capacity curves, and temperature signals to discern intricate degradation patterns [15]. Techniques including random forests, Gaussian processes, and neural networks have demonstrated the capability to accurately predict the long-term ageing process [158,159]. Machine learning approaches are ideally suited for real-time health diagnostics in rapid assessments, such as battery management systems (BMSs), as demonstrated by Severson et al. [159] and Attia et al. [160], where practically efficient algorithms can be employed to monitor system health effectively. Recent studies [161] have focused on hybrid modelling methods that integrate physics-based models with machine learning to leverage the advantages of each. These methodologies incorporate physical principles, such as mass conservation, thermodynamic consistency, or degradation kinetics, into machine learning architectures to facilitate physically interpretable predictions. The integration of ETM multi-physics simulation, FEM mechanical modelling, and machine learning-driven prediction constitutes a comprehensive model ecosystem for the study of lithium-ion battery deterioration. Together, these offer insights into LIB deterioration across multiple scales and domains for advancements in materials engineering, thermal management, electrode architecture design, and sophisticated battery diagnostics. In the next generation of lithium-ion batteries, innovative solutions such as physics-informed neural networks, uncertainty simulation, and digital twin solutions will continue to improve forecasting and deterioration management.

4.3.4. Characterization Techniques: Resolution, Advantages, and Limitations

To understand battery degradation, methods that can probe materials at various scales are needed. Battery degradation involves atomic to macroscopic scales, so multiple methods are used to complement each other. Electron microscopy techniques like SEM and TEM are commonly used for structural studies. SEM offers high-resolution images (nanometre resolution) of surfaces and can be used to study morphology and fractures. It is easy to operate but is only applicable to surfaces. TEM provides a resolution down to the atomic scale, which can be used to investigate crystal structures and interfaces. But it involves complicated sample preparation, a limited area of observation and the risk of damaging sensitive materials. X-ray diffraction is widely employed to determine crystal structures and track phase transformations. It is non-destructive and can be used for bulk measurements, such as in situ studies during battery operation. However, it cannot be used to identify amorphous phases or obtain spatial information. Surface-sensitive methods like XPS provide information on composition and oxidation states, which are useful for characterizing surface layers. But they are only surface-sensitive and need vacuum conditions. Raman spectroscopy reveals bonding, structure and composition, particularly of carbon-based materials, but interpretation of signals is complex. Electrochemical techniques (impedance spectroscopy, cyclic voltammetry) assess battery performance and processes. These methods are simple to use and yield valuable system-level information, but they do not directly measure structural changes. More sophisticated techniques like synchrotron spectroscopy and X-ray tomography provide more detailed information on local atomic environments and 3D structures. However, they require expert users and facilities. Every technique has its own advantages and drawbacks. Local techniques give specific details but may not be representative of the whole, while bulk techniques give average information but lose local detail. Thus, it is crucial to use a combination of techniques. New operando methods, where batteries are measured during operation, have also enhanced our understanding of degradation in action. Electrode–electrolyte coupling effects have been extensively studied. Electrode–electrolyte interactions are critical for battery operation and degradation. This interaction takes place at the interface where lithium ions undergo phase transfer, where chemical reactions and transport are strongly coupled. A key consequence of this interaction is the development of layers on both electrodes. These layers act as a protective shield; they also add resistance and are dynamic. These layers grow and use up lithium, and they degrade capacity. This interaction varies with the type of electrode. For instance, graphite electrodes form relatively stable layers, but silicon electrodes experience significant volume changes, which cyclically disrupt the interface and continually degrade. For cathodes, high-energy materials like layered oxides undergo surface transformations at high voltages, which enhance interactions with the electrolyte. Electrolyte additives can also affect these reactions. Additives can be added to help stabilize layers and decrease reactions. But stability is hard to achieve, particularly in extreme conditions. Transport effects also come into play. At high currents, concentration gradients arise, causing lithium distribution non-uniformity and raising the risk of lithium plating. Temperature is also critical: high temperatures speed up degradation processes, and low temperatures slow ion transport and increase plating. Mechanical stress contributes as well. The swelling and shrinking of electrode materials during cycling open up cracks, exposing new surfaces and promoting reactions. This leads to a coupled degradation process. Coupling is highly sensitive to the charging state of a battery, cycling depth and rate. Higher charge levels and higher rates generally lead to greater degradation, showing the need for system control. Recent experimental approaches have led to a better understanding of such interfacial processes. In situ and operando techniques provide real-time monitoring of changes, and models include coupled electrochemical and transport processes. Machine learning is also being applied to predict degradation from data. However, there are still challenges in capturing the complexity and multiscale nature of these effects. It is challenging to model interface behaviour in realistic conditions. In conclusion, the coupling between electrodes and electrolytes is crucial for battery durability and performance. It encompasses coupled chemical, mechanical and transport interactions over time. A multidisciplinary approach involving cutting-edge experiments and modelling is crucial for enhancing battery life and designing next-generation energy storage technologies.

5. Strategies to Reduce the Degradation of Lithium-Ion Batteries

Lithium-ion battery mitigation against degradation is associated with materials engineering, electrolytes, thermal or mechanical stabilization, and advanced control strategies. Battery degradation occurs through various processes such as surface reconstruction, gas reactions, unstable SEI, lithium plating, mechanical breakdown, and electrolyte instability [162]. Contemporary mitigation strategies mostly apply systemic treatment methodologies in conjunction with modifications at the molecular or electrolytic level in order to improve cycle life or safety or optimize performance at elevated scales [163]. This aims to mitigate the processes of deterioration occurring at various scales within the cellular design of lithium-ion batteries.

5.1. Surface Treatments for Stabilizing Cathodes and Anodes and Doping Schemes for Bulk Stability Boosters

Surface coating is the most efficient technique tested to date for mitigating the chemical and structural degradation of electrode components. Materials such as Al₂O₃, ZrO₂, LiNbO₃, and Li₃PO₄ have been used as coatings that work to reduce electrolyte degradation, promote the dissolution of transition metals, and stabilize oxygen networks in high-voltage cathodes [164]. The use of oxide nanometric coating layers in high-performance cathode components has been investigated by several researchers [165,166]. The results showed that nanometric coating layers can provide effective protection of electrodes. Doping of electrode materials significantly changes the lattice constant, electrical, and diffusion path properties, thereby improving inherent stability. Additives such as Mg, Al, Ti, and W in layer-structured oxides are known to have stabilized interactions between metals and oxygen and hinder unwanted cation diffusion, which otherwise aid in phase transitions and degradation at high voltages [167]. The introduction of other metals or ceramics in silicon anodes has been proven to stabilize the structure, thereby reducing volume expansion and cracking during lithiation. Doping techniques seem to advance coating strategies by improving methods of stabilizing the crystal lattice, thereby inhibiting further micro-strains, in addition to improving tolerance to temperature and mechanical stresses induced during cyclic testing [168].

5.2. Electrolyte Additives for Interface Stabilization and Transition to Solid-State Electrolytes for Improved Safety

Electrolyte additives are commonly used to adjust interphase electrochemistry and prevent degradation of anode and cathode interfaces [169]. Additives such as fluoroethylene carbonate (FEC), vinylene carbonate (VC), and lithium bis(oxalato)borate (LiBOB) have been shown to enhance the formation of solid electrolyte interphase (SEI) and cathode electrolyte interphase (CEI) layers on the interfaces of electrodes, which thus prevent the continuous degradation of the electrolyte [170]. Various additives prevent the destructive effects of species such as hydrofluoric acid (HF), which help degrade transition metals and the SEI [171]. Solid-state electrolytes (SSEs) are an effective method for mitigation that can ensure non-flammable liquid electrolytes as well as suppress lithium dendrites. While sulphide, oxide, and polymeric solid-state electrolytes ensure an improved electrochemical window and thermal stability over traditional carbonate electrolytes, mechanical robustness can act as a barrier to dendritic infiltration, whereas chemical stability reduces parasitic reactions at interfaces between electrodes and electrolytes [172,173].

5.3. Separator Design for Thermal and Mechanical Protection and Management to Avoid Early Failure

Improvements in separation additives can suppress degradation by the heat closure effect, enhance ionic selectivity, and prevent mechanical failure [174]. For instance, a ceramic-coated separator with high porosity can support structures at high temperatures while suppressing shrinkage rates; thus, internal short circuiting can be avoided [175]. Zhang et al. [176] demonstrated that new trends in separators involving nanoporous designs or coatings can effectively control the distribution of Li-ion currents while suppressing the growth of lithium dendrites in high-rate charge processes. Improvements in separators are highly necessary to stabilize cellular processes at high stresses. Effective thermal management is an essential factor in degradation control for lithium-ion batteries because higher temperatures enhance all degradation reactions, such as SEI layer decomposition, electrolyte oxidation, gas evolution, and mechanical damage [177]. Advanced thermal management solutions, such as liquid-cooled plates, phase change materials (PCMs), micro-channel heat exchangers, and thermoelectric coolers, maintain a homogeneous temperature within batteries, therefore ensuring reduced temperature gradients and associated degradation effects [178]. In this research work, the use of thermally conductive agents added to electrodes and/or separators is considered a method of providing effective heat dissipation in batteries.

6. Research Directions and Final Remarks

Failure mechanisms in lithium-ion batteries are not driven by one factor alone but by the confluence of multiple factors that are electrochemical, structural, thermal, and mechanical in nature. According to Kaliaperumal et al. [179], mechanisms appear in the form of loss in capacity, power, elevated impedance, and reduced margins of safety, even though they arise from atomic, cell, and pack processes. A number of diagnostic tools have also been designed to study and interpret these mechanisms of degradation. Electrochemical techniques such as cyclic voltammetry, electrochemical impedance spectroscopy, differential capacity analysis, charge transfer resistance, diffusion coefficients, and protection of the interphase layer have been used to study battery degradation [135,180]. Structural analysis techniques, such as X-ray diffraction, electron microscopy, atomic force microscopy, and X-ray computed tomography, have also been used to study the mechanisms of phase transition, particle breakage, and loss of porosity in three-dimensional cracks produced during the functioning of battery cells [118]. On the contrary, a number of other techniques, such as X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, have also been used to interpret the mechanisms of interfacial reactions, electrolyte decomposition, and component lithium diffusion [181]. Although there are many analysis tools to choose from, no existing technique can comprehensively represent degradation. Conventional cycling and impedance tests tend to mix and match several processes that occur simultaneously, such as SEI growth, active material separation, and electrolyte degradation. While it is true that in situ and operando experiments have helped solve some of these problems, as they attempt to investigate structural and chemical variations when a cell is actually working, such experiments are generally only possible for a limited number of cell designs and facilities [182]. As such, there is a discrepancy between laboratory-scale and real-world observations. In the simulation arena, apart from electrochemical–thermal–mechanical process simulations and FEM model simulations of fracture mechanics, the use of machine learning algorithms for the interpretation of degradation curves from large-scale cycle tests is increasingly seen as important. Combined physics-respecting models using artificial intelligence and the digital twin concept provide the opportunity for real-time prognosis with cell-specific prediction accuracy when grounded in thorough experimental research. The combination of highly accurate models, complete in situ testing data, and artificial intelligence analytics is about to revolutionize the development and use of lithium-ion batteries throughout the entire product lifecycle. Future directions for the next generation of lithium-ion battery materials include the passivation of both the bulk and interfaces of electrode materials to improve durability against degradation. This requires a focus beyond nickel-rich layered cathode materials to compositions and structures that alleviate oxygen evolution and cation migration. The coupling of composite silicon–graphite architecture, tailored SEI-forming additives, and selectively optimized binders is an efficient approach for accommodating volumetric changes and reducing particle breakage in anodes. Future research work must include optimization of materials and processes for durability, safety, and recyclability, using lifecycle assessments and techno-economic analyses.

Sodium-Ion and Potassium-Ion Batteries as Emerging Alternatives to Lithium-Ion Batteries

Although lithium-ion batteries (LIBs) dominate the current energy storage market, concerns regarding lithium resource availability, geopolitical supply chain constraints, rising material costs, and sustainability have stimulated intensive research into alternative battery chemistries. Among the most promising candidates are sodium-ion batteries (SIBs) and potassium-ion batteries (PIBs), which offer the potential for lower cost, greater resource abundance, and improved sustainability while maintaining electrochemical characteristics similar to those of LIBs [183,184]. Sodium-ion batteries operate through reversible sodium-ion intercalation and de-intercalation between the cathode and anode, analogous to lithium-ion batteries. Sodium is significantly more abundant and widely distributed than lithium, making SIBs attractive for large-scale stationary energy storage and renewable energy integration applications. Furthermore, sodium-ion batteries can utilize aluminium current collectors on both electrodes, reducing manufacturing costs. However, the larger ionic radius of Na⁺ (1.02 Å) compared with Li⁺ (0.76 Å) results in slower diffusion kinetics, lower energy density, and greater volumetric changes during cycling [185]. Consequently, research efforts have focused on developing advanced cathode materials, hard-carbon anodes, and optimized electrolytes to improve cycle stability and energy density. Potassium-ion batteries have emerged as another promising alternative due to the exceptional abundance and low cost of potassium resources. Interestingly, despite the larger ionic radius of K⁺ (1.38 Å), potassium exhibits lower Lewis acidity and higher ionic conductivity in certain electrolytes than lithium and sodium ions [186]. Potassium-ion batteries also possess a relatively low redox potential (−2.93 V vs. SHE), enabling cell voltages comparable to those of LIBs. In addition, graphite can reversibly host potassium ions, allowing the use of conventional graphite anodes without the need for specialized hard-carbon materials. Nevertheless, the large size of potassium ions generates significant volume expansion, structural stress, and accelerated electrode degradation during cycling, which remain major challenges for long-term stability. From a degradation perspective, sodium-ion and potassium-ion batteries share several ageing mechanisms with lithium-ion batteries, including solid electrolyte interphase (SEI) growth, electrolyte decomposition, transition-metal dissolution, active material loss, and particle cracking. However, the larger ionic radii of Na⁺ and K⁺ introduce additional mechanical stresses that can intensify structural degradation and accelerate capacity fading [187]. Furthermore, electrolyte stability and interfacial compatibility remain critical challenges, particularly for potassium-ion systems operating at high voltages. Recent advances in material engineering, nanostructured electrodes, electrolyte additives, and artificial intelligence-assisted battery design have significantly improved the performance of both sodium-ion and potassium-ion technologies. Several sodium-ion battery systems have already reached commercialization for stationary energy storage applications, while potassium-ion batteries remain at an earlier stage of development. For renewable–hydrogen hybrid energy systems, sodium-ion batteries are particularly attractive because their lower cost and abundant raw materials may facilitate large-scale deployment where energy density is less critical than cost, safety, and sustainability. Notwithstanding their promise, neither sodium-ion nor potassium-ion batteries currently match the energy density and maturity of lithium-ion technology. Nevertheless, continued advances in materials science, degradation mitigation, and cell engineering are expected to enhance their competitiveness. As a result, sodium-ion and potassium-ion batteries are increasingly regarded as viable complementary technologies capable of supporting future renewable energy integration, grid-scale storage, and sustainable hybrid energy architectures.

7. Conclusions

Lithium-ion batteries are a crucial element of hybrid energy systems commonly utilized in hydrogen production. The persistent operational conditions of the batteries lead to the growth and reconditioning of the solid electrolyte interphase (SEI), depletion of active lithium inventory, dissolution of transition metals, gas evolution, and cumulative structural damage, including microcracking and phase transformations in cathodes with high nickel or high voltage content. The research has summarized facets of lithium-ion battery materials and prevailing deterioration mechanisms. Many constituent materials in lithium-ion batteries experience significant capacity degradation over charging and recharging cycles, limiting their applicability for large-scale commercial use. The deterioration of electrodes in lithium-ion batteries may stem from unwanted chemical reactions between the electrolyte and electrode at solid–liquid interfaces, as well as from internal structural disintegration inside the electrode particles. The formation of unstable phases close to the electrode–electrolyte interface may exacerbate the electrolyte’s role in unfavourable side effects and increased deterioration. A comprehensive understanding of degradation pathways is essential to enhance the electrochemical performance of electrodes and to devise mitigation strategies. This work presents a systematic assessment of electrode deterioration and characterization methodologies utilized to investigate various degradation routes. This paper offers a comprehensive overview of novel approaches in electron and ion microscopy designed to investigate degradation processes occurring on the electrode surface and within individual primary particles.