Perspective of Materials Characterisation and Performance Evaluation of Advanced Nanomaterials for Bioenergy Systems: A Systematic Review ^†

Abstract

Advanced nanomaterials are becoming increasingly critical for improving the efficiency, durability, and sustainability of bioenergy systems, with applications spanning biomass conversion, catalysis, and bioelectrochemical energy generation. This systematic bibliometric and thematic review analyses Scopus-indexed literature from 2020 to 2025 to elucidate global research trends in nanomaterial characterisation and performance evaluation for bioenergy applications. Bibliometric mapping using VOSviewer version 1.6.18 reveals a rapidly growing research landscape structured around three dominant themes: nanocatalysts for biodiesel and bioethanol production, nanostructured enhancements in bioelectrochemical and anaerobic digestion systems, and surface-engineered materials for energy conversion and storage. The review highlights the pivotal role of structural and morphological characterisation techniques including SEM, TEM, AFM, and XRD in establishing structure–property–performance relationships that underpin catalytic activity, electron transfer efficiency, and system stability. Beyond short-term catalytic and electrochemical metrics, increasing attention is given to mechanical stability, durability, and long-term operational reliability, which are shown to be critical determinants of scalability. Emerging strategies such as additive manufacturing and hybrid material systems enable the integration of nanomaterials into architected, mechanically robust structures, mitigating degradation and enhancing sustained performance. A concise conceptual framework is presented to link nanomaterial classes, characterisation challenges, targeted bioenergy applications, and scalability constraints. Despite significant progress, gaps remain in standardised characterisation protocols, durability-focused testing, and life-cycle assessment. Addressing these challenges is essential for translating laboratory-scale advances into scalable, sustainable bioenergy technologies.

1. Introduction

The pressing need to shift from fossil fuel energy systems to low-carbon, renewable alternatives has heightened worldwide research initiatives in sustainable energy technology. Bioenergy systems, which extract energy from biomass through various biochemical and thermochemical processes, have become fundamental to this shift due to their renewable characteristics, potential for carbon neutrality, and capacity to utilise a variety of organic feedstocks [1,2]. The efficiency, scalability, and environmental sustainability of bioenergy systems are fundamentally reliant on progress in materials science, especially in the design and use of advanced nanomaterials [3]. The rapid worldwide transition to sustainable energy systems has established bioenergy as a crucial component of the clean energy revolution. Bioenergy systems, derived from sustainable biological resources such as biomass, have the potential to mitigate greenhouse gas emissions, reduce reliance on fossil fuels, and support circular economy initiatives [4]. Technologies such as biofuel cells, microbial fuel cells, and biomass-to-energy conversion systems are being more widely investigated for their potential to offer environmental and economic benefits. The efficacy of these systems is often limited by the efficiency of their energy conversion and storage mechanisms [5,6].

Nanomaterials, fabricated at dimensions of 1–100 nm, exhibit remarkable physicochemical characteristics, such as elevated surface area-to-volume ratios, adjustable porosity, improved catalytic efficacy, and customised electronic configurations. These qualities have facilitated advancements across the bioenergy value chain, including biomass conversion, catalytic upgrading, energy storage, and electrochemical conversion. In catalytic biofuel production, nanostructured metal oxides, carbon nanomaterials, and hybrid composites have enhanced the reaction kinetics and selectivity of processes such as biodiesel transesterification and bioethanol fermentation [7,8]. In bioenergy storage devices, such as biofuel cells and hybrid supercapacitors, nanostructured electrodes enhance electron transfer efficiency, biocompatibility, and long-term stability. In recent years, sophisticated nanomaterials—spanning carbon-based nanostructures, metal–organic frameworks (MOFs), transition metal oxides, and doped polymers—have emerged as significant performance enhancers in bioenergy systems. Their distinctive physicochemical characteristics, including elevated surface area, adjustable porosity, and catalytic efficacy, have facilitated substantial improvements in electron transfer rates, biocatalyst stability, and overall device performance. These developments have significantly influenced electrode design, catalyst support development, and bio-interface engineering, thereby connecting laboratory-scale demonstrations with scalable applications [3,9,10].

Materials characterisation is a crucial facilitator of these advancements, establishing the connection between nanomaterial structure and functional performance. Methods such as X-ray diffraction (XRD), transmission electron microscopy (TEM), Raman spectroscopy, and electrochemical impedance spectroscopy (EIS) enable researchers to investigate morphology, crystallinity, surface chemistry, and charge-transfer kinetics with exceptional precision. This structural–functional relationship not only informs rational material design but also expedites the conversion of ideas into practical technologies [11,12,13]. Characterisation elucidates the structure–property–performance connections, facilitating rational design and the optimisation of nanomaterials for targeted bioenergy applications [14,15]. Despite the rapid expansion of this multidisciplinary study subject, the literature remains fragmented, with studies dispersed across various domains, including materials science, electrochemistry, biotechnology, chemical engineering, renewable energy, and environmental sciences. This dispersion complicates the acquisition of a unified understanding of worldwide research trends, key contributors, and emerging theme orientations. Bibliometric analysis, a quantitative and data-driven method for mapping scientific literature, provides a strategic answer to this gap. Utilising bibliometric tools like VOSviewer to examine Scopus-indexed publications enables the identification of prominent authors, institutions, and nations, the tracing of citation flows, and the mapping of theme networks that delineate the intellectual framework of the area. This systematic review aims to

• Identify prominent journals/publications contributing to this domain.
• Delineate the worldwide research output concerning the junction of nanomaterials characterisation and performance improvement in bioenergy systems.
• Emphasise novel materials, characterisation methodologies, and performance indicators influencing the advancement of bioenergy technology.

2. Methodology

This section lists the step-by-step approach used to perform this systematic literature review. It contains a report describing the data acquisition, processing, and analysis.

2.1. Data Sources

The data acquisition process for this study was performed in three progressive steps. During the first step, a careful selection of the keywords was performed. The author tried different keywords ranging from “Materials Characterization AND Performance Evaluation AND Advanced Nanomaterials AND Bioenergy Systems OR Renewable energy systems” which was changed due to a need to expand the keywords to accommodate some other publications. Thus, the following keywords were considered: “Advanced AND nanomaterials OR Materials AND characterization AND Performance AND evaluation AND Renewable AND energy AND systems OR bioenergy OR bioenergy AND systems AND storage”. The second step involved searching for keywords in the Scopus database, which initially yielded 46,144 documents. The final step involved exporting the documents in CSV format, which included complete bibliographic information (title, abstract, year of publication, author affiliations, source journals, and other relevant bibliometric parameters). The search was conducted on 11 August 2025, and the inclusion and exclusion criteria were strictly adhered to. A chart summarising the search procedure is shown in Figure 1.

2.2. Data Analysis

The first stage of analysis was the screening of the obtained data, which initially yielded 46,144 documents; this was later reduced to 10,790 documents after reducing the publication years from 2019 to 2025; limiting the subject area to engineering, energy, material science, chemistry, chemical engineering, environmental science, agricultural and biological sciences, computer science, and earth and planetary sciences; reducing the document type to reviews, articles and conference papers; reducing the publication stage to final papers only and not articles in press; restricting the language to English only; and amending the open access search to all open access, gold and green documents only. The exported document was screened for consistency with the research focus in its title, and many of the articles exported failed this test. The total number of documents that met the threshold was eventually 810; these were further screened for repetition avoidance and abstract consistency, resulting in a total of 140 papers. The review ultimately utilised 132 documents that were accessible for download (see

Table 1. Journal selection steps and counts.

S/N	Step	Action/Criteria	Resulting Records (n)	Bias-Mitigation Notes
1.	Identification	Scopus initial retrieval (broad keywords: nanomaterials, characterisation, bioenergy)	46,144	Maximise recall
2.	Database filtering	Years 2019–2025; Subject areas; Doc types; English; Final; Access (All/Gold/Green)	10,790	Objective, metadata-based
3.	Title screening	Advanced nanomaterials + characterisation + bioenergy performance context	810	Predefined inclusion terms
4.	Deduplication	Duplicates and repeated proceedings versions removed	140	Automated manual check
5.	Abstract check	Explicit characterisation–performance linkage required	132	No journal/citation filtering

). Following data screening and refinement, the final dataset was analysed using the bibliometric mapping techniques implemented in VOSviewer. Keyword co-occurrence analysis was employed to identify dominant thematic structures within the literature. Both author keywords and indexed keywords extracted from the Scopus database were considered. To ensure relevance and reduce noise from infrequently used terms, a minimum occurrence threshold was applied, such that only keywords that appeared multiple times across the dataset were included in the analysis.

Co-occurrence relationships were calculated using full counting, where each keyword occurrence was weighted equally. Network normalisation was performed using the association strength method, which balances link weights based on total keyword occurrences and allows for meaningful comparison of thematic relationships. The resulting keyword network was clustered using VOSviewer’s built-in clustering algorithm with default resolution settings, enabling natural grouping of related research themes. The identified clusters were interpreted based on the most prominent and strongly connected keywords, leading to the classification of three dominant thematic areas within the field. To support the robustness and reproducibility of the thematic clustering, the stability of the keyword co-occurrence network was examined under small variations in the minimum keyword occurrence threshold and clustering resolution parameters. The resulting cluster composition and dominant keywords remained consistent, with no material changes observed in the three major thematic clusters identified. This confirms that the reported thematic structure is not sensitive to minor parameter adjustments. Dataset refinement prioritised relevance over citation metrics by applying predefined metadata and content-based screening criteria. Broad initial keywords maximised recall, while title and abstract screening ensured inclusion of studies explicitly linking nanomaterial characterisation to bioenergy performance. Citation-based exclusion was not applied, and seminal contributions remain indirectly represented through citation linkages.

2.3. Methodological Limitations

The bibliometric analysis was intentionally limited to Scopus-indexed publications from 2020 to 2025 to capture the most recent and application-driven phase of research on advanced nanomaterials for bioenergy systems. This period reflects accelerated developments in nanomaterial synthesis, advanced and operando characterisation techniques, performance optimisation, and sustainability-oriented design, which are central to the objectives of this review. While seminal studies published prior to 2020 established the foundational principles of nanomaterials and bioenergy technologies, restricting the temporal scope enables a focused assessment of contemporary research trends, thematic convergence, and current performance benchmarks. Consequently, this study emphasises recent research dynamics rather than the full historical evolution of the field; however, the influence of earlier foundational works is indirectly captured through citation linkages within the analysed literature. In addition, the exclusive reliance on Scopus as the data source, while ensuring consistency and high bibliographic quality, may introduce database-related bias. Relevant studies published in non-Scopus-indexed journals, regional or emerging outlets, conference proceedings, and grey literature are not fully represented. The focus on English-language publications may further under-represent region-specific research contributions, particularly from developing bioenergy economies. As a result, the identified publication trends, collaboration networks, and thematic structures should be interpreted as a focused snapshot of current research priorities within the Scopus database rather than a fully exhaustive representation of global research activity in this field.

3. Results

The section is divided into two parts: the first part presents the quantitative outcomes of the work, while the second part focuses on the thematic expression of the study’s objectives.

3.1. Annual Publication Trends in Nanomaterials for Bioenergy

The year of publication depicted in

Table 2. Year of publication per year from 2021 to 2024.

Years	Frequency
2021	1
2022	6
2023	13
2024	112
Grand Total	132

illustrates the trend of research publications per year from 2021 to 2024. The table indicates that there were more publications on the subject matter in 2024 than in previous years. The trend is clearly shown in Figure 2.

The figure illustrates an upward trend in the publication rate between 2021 and 2024. The trend reached its peak in 2024, and there is strong hope that publications in 2025 will exceed those in 2024, given the upward trend observed.

3.2. Distribution of Journals and Publication Sources

Table 3. Journals/publication sources.

Publication Source	Frequency
Energies	7
Results in Engineering	6
Nanomaterials	5
Polymers	4
Journal of Power Sources	2
Nano Materials Science	2
Materials	2
Applied Sciences (Switzerland)	2
Case Studies in Chemical and Environmental Engineering	2
Energy Reports	2
Processes	2
Environmental Advances	2
Journal of Materials Research and Technology	2
Green Chemistry	2

presents the common publication sources, specifically those with multiple publications among the works published over the specified years. This is further explained in Figure 3.

The chart in Figure 3 shows that the three most prominent journals whose works are relevant in characterisations and performance evaluation of nanomaterials in bioenergy systems are Energies, Results in Engineering, Nanomaterials, and Polymers. Energies had the highest number of publications and Results in Engineering had the second highest number of publications. Energy and Results in Engineering and Nanomaterials and Polymers are publications by the prominent publishers Elsevier and MDPI, respectively. This sets both Elsevier and MDPI at the forefront of prominence in energy-related publications.

3.3. Thematic Outcome of the Study

3.3.1. Material Characterisation Techniques for Advanced Nanomaterials in Bioenergy Systems

The characterisation of materials can be viewed based on four categories: structural/morphological characterisation techniques, surface area and porosity, surface chemistry and bonding, and thermal stability characterisation [16,17,18,19,20], as shown in Figure 4. The structural or morphological techniques focus on studying the structure, shape, and physical features of materials at micro- and nanoscales [21,22,23]. Surface area and porosity characterisation techniques measure how much surface area a material has and the size/volume of pores, which is crucial for catalysis, adsorption, and energy storage [24]. The surface chemistry and bonding characterisation techniques reveal the chemical interactions, surface energies and bonding nature of [24,25], while the thermal stability characterisation techniques measure how materials respond to heat, which is vital for stability and performance in high-temperature applications [26,27]. For this study, which focuses on the material characterisation techniques of advanced nanomaterials in bioenergy systems, we shall focus our attention on the structural/morphological characterisation techniques because of their ability to consider materials up to the nano-level.

• Scanning electron microscopy (SEM): High-resolution scanning electron microscopy (SEM) is very effective for characterising the size and form of nanoparticles. Scanning electron microscopy (SEM) offers real-time imaging with nanometre resolution and an extensive scanning area, facilitating the development and integration of robotic nanomanipulation systems within large vacuum chambers to achieve concurrent imaging and direct interactions with objects at submicrometer and nanometre scales [28,29,30,31]. Furthermore, SEM can be combined with advanced technologies such as electron beam lithography (EBL) and focused ion beam (FIB) for in situ nanomaterial engineering and production [32,33].
• Preparation of samples
  The accuracy of SEM nanoparticle size and shape measurements heavily depends on sample preparation [34,35,36]. There is no single optimal preparation method suitable for all nanoparticles; instead, various techniques are considered effective depending on the specific properties of the nanoparticles and the measurand, which refers to the quantity or attribute being measured. It is crucial to ensure that test or analytical samples are representative and relevant to the measurand. Instruments used for preparing and handling nanoparticles must be kept clean and stored in a dry, sanitised environment, preferably within an area fitted with high-efficiency particulate air (HEPA) filtration throughout sample processing [37,38].
• Mechanical Characterisation using Scanning Electron Microscopy
  Comprehending the mechanical characteristics of nanomaterials is crucial for miniaturised electronic, optical, thermal, and electromechanical systems [39]. Nevertheless, owing to scaling effects and geometric disparities, as the surface-to-volume ratio escalates with the reduction in structural dimensions, nanostructures such as nanowires (NWs), carbon nanotubes (CNTs), and ultrathin films demonstrate markedly distinct mechanical properties in comparison to their bulk equivalents, indicating that one cannot readily extrapolate nanomaterial mechanical properties from bulk characteristics [40,41,42].
• Electrical Characterisation in Scanning Electron Microscopy
  A deeper comprehension of the electrical characteristics of nanomaterials will facilitate the development of next-generation nanoelectronics and nanosensors, which achieve exceptional performance [6,43,44].
• Mechanism of Operation Nanomaterial Configuration
  According to [45], a solitary nanomaterial, such as a nanowire, nanotube, or thin film, is fabricated and positioned inside an electron microscopy chamber.
  • Probe Placement: Two delicate electrical probes are strategically placed to contact the nanostructure. In a nanowire, one probe may interface with the apex of the nanowire, while the other connects to the growth substrate.
  • Administering Stimuli: External circumstances are imposed while the probes assess the current and voltage.
  • Mechanical Stress: The probes are capable of measuring variations in electrical conductivity during tensile, compressive, or bending tests on the nanostructure.
  • Environmental Changes: Probes may be used to assess electrical resistance or current flow when the material encounters varying temperatures or gases, yielding information about temporal characteristics and chemical reactivity.
  • Data Acquisition: Through the analysis of recorded electrical signals, such as current–voltage (I-V) curves, researchers can determine the electrical conductivity and resistance of nanomaterials, as well as the impact of environmental factors on these characteristics.

2.

Transmission Electron Microscopy (TEM): Transmission electron microscopy (TEM) (Figure 5) is a commonly used method for characterising nanomaterials, offering both structural and chemical information about samples [46,47]. It enables researchers to directly visualise and capture images of nanomaterials, similar to the SEM method, with atomic-scale resolution of less than 1 nm. Nonetheless, TEM utilises higher-intensity electron beams, yielding pictures with superior resolution relative to the SEM approach [47,48]. Consequently, TEM may provide enhanced information about nanomaterials, including their granularity and crystallinity. Transmission electron microscopy (TEM) mostly depends on the following factors:

• The ratio of the distance across the picture plane to the objective lens.
• The fraction of the distance between the specimen and the objective lens.

3.

Atomic Force Microscopy (AFM): Atomic force microscopy (AFM) is a form of scanning probe microscopy that creates highly detailed three-dimensional topographical images with subnanometre resolution [49,50]. AFM offers high-resolution images of biomass materials. Additionally, the nanoscale contact force between the probe and the sample enables detection without damaging the sample, while simultaneously showcasing the real-time mechanical and surface features of the material [51]. The ability of AFM probes to interact with biomass materials under gentle conditions (such as room temperature, normal pressure, or biomimetic liquids) is essential for examining the microscopic properties of biomass [52]. AFM analyses the surface structure and properties of materials by sensing subtle interatomic forces between the sample surface and the probe tip.

4.

X-ray Diffraction (XRD): Nanomaterials possess distinctive features that make them appropriate for many applications, including electronics, energy storage, medicine, and catalysis. Characterising the structure and composition of nanomaterials is crucial for understanding and optimising their characteristics. X-ray diffraction (XRD) is an effective method for analysing and characterising nanomaterials [45,53,54]. X-ray diffraction (XRD) is a non-invasive method that is used to ascertain the crystalline structure and composition of materials using X-rays.

The mechanism of X-ray diffraction (XRD) relies on the diffraction of X-rays by atoms inside a crystal [55,56]. When X-rays strike a crystal, they are dispersed by the atoms, producing a diffraction pattern that is indicative of the crystal structure.

5.

Characterisation of Nanomaterials by XRD

X-ray diffraction (XRD) is employed to ascertain the crystal structure, lattice parameters, and composition of nanoparticles and nanowires [57]. The diffraction pattern generated by these materials facilitates the determination of their size and morphology [58,59]. For instance, the XRD pattern of nanoparticles can be utilised to calculate their average size through the Scherrer equation, as shown in Equation (1):

$$D={\displaystyle \frac{k\lambda }{\beta cos\theta }}$$

(1)

where D represents the average size of the nanoparticles, K denotes a constant, λ signifies the wavelength of the X-rays, β indicates the full width at half maximum (FWHM) of the diffraction peak, and θ refers to the angle of incidence.

X-ray diffraction (XRD) is a widely used method for characterising nanoparticles (NPs). XRD generally provides information on the crystalline structure, phase composition, lattice parameters, and crystalline grain size. The latter parameter is determined using the Scherrer equation, utilising the widening of the most intense peak from an XRD measurement for a given [60,61]. The XRD methods, which are often used to dry powder samples derived from colloidal solutions, provide statistically representative, volume-averaged data.

Table 4. Comparative table showing the structural/morphological characterisation techniques.

Technique	Properties	Applicable Nanomaterials	Strengths	Limitation	References
SEM	Surface morphology, particle size	Nanoparticles, nanocomposites, and catalysts	High-resolution imaging of surface morphology	Limited to surface structure, no chemical bonding information.	[62,63]
TEM	Crystallinity, internal structure	Nanocatalysts, energy storage materials	Atomic resolution, internal structure analysis,	Requires a thin sample and complex sample preparation	[64,65,66]
AFM	Surface topography, roughness, nanoscale defects	Catalysts, electrode, biomolecular interactions	High-resolution, topography, 3D imaging	Slower scanning time, limited to small areas of the sample	[50,67]
XRD	Crystallinity, phase structure	Nanocatalysts, electrodes, biofuels	Identify crystallinity, phase analysis	Limited to crystalline materials, no surface chemistry information	[68,69]

provides a comparative overview of four commonly used characterisation techniques, highlighting their analytical capabilities, suitable applications, strengths, and inherent limitations in the context of nanomaterials for bioenergy systems. Collectively, the techniques show that no single method can achieve complete nanomaterial characterisation. Instead, a combined approach using both imaging and structural analysis is essential to gain a comprehensive understanding of material properties, performance, and suitability for bioenergy applications. The discussion of material characterisation in this review focuses primarily on structural and morphological techniques, including SEM, TEM, AFM, and XRD, due to their central role in elucidating nanoscale features that govern the functional behaviour of advanced nanomaterials in bioenergy systems. Electrochemical techniques such as cyclic voltammetry, electrochemical impedance spectroscopy, and degradation or stability analysis are highly relevant. However, they are more appropriately considered performance evaluation methods, as they assess operational efficiency, charge-transfer behaviour, and durability at the device or system level. Consequently, these electrochemical techniques are discussed within the context of bioenergy conversion performance and application-specific evaluation rather than within the core materials characterisation subsection.

Table 5 consolidates the links among structure, properties, and performance in nanomaterial-enabled bioenergy systems by directly correlating characterisation outputs such as crystallinity, particle size, surface roughness, and pore distribution with functional performance measures. The table illustrates that nanoscale structural characteristics determined via SEM, TEM, AFM, and XRD directly influence catalytic activity, mass transfer dynamics, electron transport efficacy, and operational stability in biodiesel, bioethanol, and bioelectrochemical systems. This synthesis connects materials characterisation with performance assessment, offering a mechanistic foundation for understanding the reported efficiency improvements and facilitating the rational design of nanomaterials for high-performance and sustainable bioenergy applications.

SEM, TEM, AFM, and XRD provide complementary and multiscale insights that, together, enable robust structure–property–performance relationships to be established for bioenergy nanomaterials. SEM offers statistically representative information on surface morphology, particle size, and agglomeration, which directly influence accessible surface area, mass-transfer behaviour, and catalyst dispersion in bioenergy conversion processes [29,30,31,32,33,62,63]. TEM extends this analysis to the nanoscale and atomic level, revealing internal structure, crystallinity, lattice defects, and phase boundaries that govern intrinsic catalytic activity, electron transport, and stability [46,47,48,64,65,66]. AFM provides three-dimensional surface topography and nanoscale roughness data, allowing correlations between surface texture, adhesion sites, and interfacial phenomena such as enzyme immobilisation, biofilm formation, and extracellular electron transfer in bioelectrochemical systems [49,50,51,52,67]. XRD complements these imaging techniques by supplying bulk-averaged information on crystal structure, phase composition, and crystallite size, which are critical for interpreting thermal stability, reaction selectivity, and long-term durability [53,54,55,56,57,58,59,60,61,68,69]. When applied in combination, these techniques link nanoscale structure and surface features to functional properties, enabling a comprehensive understanding of how material design choices translate into performance and scalability in bioenergy applications [14,15,65,70].

Table 5. Structure–property–performance relationships in nanomaterials for bioenergy systems.

Characterisation Output	Technique(s)	Property Revealed	Impact on Bioenergy Performance	References
Crystallinity, phase composition	XRD	Crystal structure, crystallite size	Higher catalytic activity, thermal stability, improved biodiesel yield	[57,58,59,60,61,65,71,72,73]
Particle size, morphology	SEM, TEM	Surface area, active site density	Faster reaction kinetics, higher conversion efficiency	[29,30,31,32,33,64,65,66,70,74]
Surface roughness, topology	AFM	Nanoscale roughness, adhesion sites	Enhanced electron transfer, improved BES power output	[49,50,51,52,75,76,77]
Porosity, pore distribution	SEM/TEM, structural analysis	Mass-transfer pathways	Improved reactant diffusion, selectivity, and stability	[24,68,78,79,80,81,82]

Table 5. Structure–property–performance relationships in nanomaterials for bioenergy systems.

Characterisation Output	Technique(s)	Property Revealed	Impact on Bioenergy Performance	References
Crystallinity, phase composition	XRD	Crystal structure, crystallite size	Higher catalytic activity, thermal stability, improved biodiesel yield	[57,58,59,60,61,65,71,72,73]
Particle size, morphology	SEM, TEM	Surface area, active site density	Faster reaction kinetics, higher conversion efficiency	[29,30,31,32,33,64,65,66,70,74]
Surface roughness, topology	AFM	Nanoscale roughness, adhesion sites	Enhanced electron transfer, improved BES power output	[49,50,51,52,75,76,77]
Porosity, pore distribution	SEM/TEM, structural analysis	Mass-transfer pathways	Improved reactant diffusion, selectivity, and stability	[24,68,78,79,80,81,82]

3.3.2. Evaluation of the Performance of Nanomaterials in Bioenergy Conversion Processes

Nanocatalysts for Making Biodiesel

Various forms of biofuels, such as bioethanol, biogas, and biodiesel, are created depending on the feedstock materials used. Biofuels, such as biodiesel, are promoted as a more environmentally friendly alternative to fossil fuels, aiming to reduce greenhouse gas emissions and dependence on limited resources. Conventional biodiesel manufacturing methods face challenges such as high costs, inefficiency, and ecological impacts, which nanocatalysts are well-positioned to address. Nanocatalysts offer benefits due to their small size, high reactivity, and durability, leading to enhanced biodiesel production [83,84]. They possess superior features compared to traditional catalysts, including a higher surface area-to-volume ratio, improved mass transfer, adjustable surface chemistry, and enhanced thermal stability. These qualities lead to increased biodiesel yields, shorter reaction times, and greater catalyst reusability [70,74].

Figure 6 shows various techniques for producing biofuels from nanomaterials. The cost of synthesising nanocatalysts can be significantly reduced by utilising agricultural or industrial waste materials, potentially decreasing production costs to around 1.05 USD per kilogram [85,86]. Synthesis techniques such as sol–gel processing, co-precipitation, and hydrothermal synthesis are used for nanocatalysts, with agricultural residues offering a cost-effective and environmentally friendly approach [87].

Table 6. Different forms of nanocatalysts and their use in biofuel production.

Nanocatalysts	Description	Examples and (Mode of Synthesis)	Feedstock Source	Reference
Metal oxide-based	They are conventionally used for the production of biodiesel.	Nano-MgO, MgO/MgFe2O4, KOH/Fe2O3/Al2O3, Na2SiO3	Goat fat, sunflower oil, palm oil, corn oil, canola oil, soybean oil, animal fat, cooking oil	[71,72,73]
Carbon-based	The physical and chemical properties of nanocatalysts made from carbon materials, including graphene, carbon nanotubes, and reduced graphene oxides, have been characterised and correspond to various morphologies and sizes of the resulting non-composite materials. It has been discovered that nanocatalysts with acidic properties, high porosity, and large surface areas have better catalytic activity.	KOH-loaded MWCNTs (impregnation method), silicon carbide/sodium hydroxide–graphene oxide (in situ impregnation method), sulfonated biochar and activated carbon (pyrolysis method)	Canola oil, rapeseed oil, oleic acid, used cooking oil, oleic acid, vegetable oil.	[93,94]
Zeolite-based	Zeolite materials are now being used more frequently than before. The existence of active acidic and basic sites, high catalytic activity, easily modifiable structures using various functions, and metal exchange are only a few of the distinctive qualities they notably possess.	Zeolite/chitosan/KOH Lanthanum–natural zeolite (La/NZA) (impregnation method), ZSM-5 (nanosheets) (Hydrothermal method), Li/NaY zeolite (Hydrothermal and microemulsion)	Waste cooking oil, crude palm oil, linoleic acid, shea butter, castor oil	[95,96]

presents various forms of nanocatalysts, their descriptions, and the feedstocks from which they are derived. The catalysts used in biodiesel production could be categorised into homogeneous and heterogeneous [89,90,91,92].

In

Table 7. Quantitative performance comparison of nanocatalyst classes for biodiesel and bioethanol production.

Nanocatalyst Class	Yield/Conversion (%)	Reaction Time	Recyclability (Cycles)	Supporting References
Metal oxide-based nanocatalysts (e.g., CaO, MgO, ZnO, mixed oxides)	85–98% biodiesel yield	1–3 h	3–6	[65,70,71,72,73,74,97]
Carbon-based nanocatalysts (CNTs, graphene, sulfonated biochar)	80–95% biodiesel yield	2–4 h	4–7	[76,92,93,94,98,99]
Zeolite-based nanocatalysts (ZSM)	75–92% biodiesel yield	2–5 h	5–8	[95,96,100,101]
Magnetic nanocatalysts (Fe3O4-based composites)	85–97% biodiesel yield	1–3 h	6–10	[90,102,103,104,105]
Enzyme-immobilised nanocatalysts (bioethanol fermentation)	60–85% sugar-to-ethanol conversion	24–72 h

, among catalyst categories, metal oxide-based and magnetic nanocatalysts typically provide superior biodiesel yields, frequently surpassing 90%, alongside diminished reaction durations of under three hours, underscoring their appropriateness for expedited conversion operations. Carbon-based and zeolite-based nanocatalysts exhibit marginally extended reaction durations while providing superior structural stability and surface tunability, hence enhancing selectivity and recyclability. Magnetic nanocatalysts routinely surpass non-magnetic systems in recovery efficiency and reusability, demonstrating stability over six to ten cycles with no activity loss. In bioethanol synthesis, enzyme-immobilised nanocatalysts generally improve sugar conversion efficiency and enzyme lifetime, rather than decreasing reaction time, highlighting some distinctions between catalytic and biochemical conversion routes. The quantitative comparison highlights that catalyst selection entails trade-offs among activity, durability, recovery, and economic factors rather than a singular ideal criterion. In Table 5, reported values represent representative ranges under optimised laboratory conditions. Variations arise from differences in feedstock type, alcohol-to-oil ratio, catalyst loading, temperature, and reactor configuration.

Nanocatalysts, made up of particles smaller than 100 nm, bridge the gap between homogeneous and heterogeneous catalysis, offering enhanced features such as increased surface area, more catalytic sites, improved activity, selectivity, efficiency, and reusability [92]. They also reduce mass transfer resistance and deactivation. Nanocatalysts are classified into two types, magnetic and non-magnetic, as follows [102,103]:

• Magnetic nanocatalysts: Magnetic nanocatalysts have recently garnered significant attention from researchers due to their notable magnetic properties. Numerous efforts have been made in this field, resulting in the development and application of various magnetic nanocomposites for the transesterification of different feedstocks in biodiesel production [90] NC KF/CaO-Fe₃O₄ is a new magnetic nanocatalyst used in biodiesel synthesis, derived from Stillingia oil. This nanocarrier has a diameter of 50 nm and exhibits high efficiency, allowing for multiple reuses with minimal decline in activity. About ninety percent of the catalyst can be recovered when used at 65 °C, with a methanol/oil molar ratio of 12:1 and a catalyst concentration of 4% after three hours of reaction. Using magnetic nanocomposites, a fast, simple, and cost-effective nanotechnological method was developed for biodiesel production from soybean oil by [104]. Co-precipitation was used to synthesise a composite of magnetic iron/cadmium and iron/tin oxide nanoparticles, which were then tested for their effectiveness in hydrolysis, transesterification, and esterification of soybean oil and its fatty acids. At 200 °C and a reaction time of one hour, esterification facilitated by iron/tin oxide nanoparticles achieved an efficiency of around 84%. Furthermore, these NCs could be magnetically recovered and reused up to four additional times without significant loss of activity; however, a decline in activity was observed in the iron/cadmium oxide catalyst [105].
• Non-magnetic nanocatalysts: Non-magnetic nanocatalysts include metal oxides (e.g., ZnO, TiO₂-ZnO, Co/ZnO, Ni-doped ZnO, CaO), supported catalysts (e.g., KF/CaO, Cs/Al/Fe₃O₄), zeolites, metal–organic frameworks (MOFs), and hydrotalcites [106,107]. These have demonstrated increased biodiesel yields under various optimal conditions, although issues such as catalyst leakage and deactivation over multiple cycles are sometimes encountered and they include:
  • Metal Oxides: This category of nanocatalysts (NC) is regarded as very promising and is therefore extensively used in biodiesel generation from diverse feedstocks. SiO₂/ZrO₂ catalysts synthesised using the sol–gel technique has a large surface area and demonstrate commendable efficiency, allowing for reuse beyond six cycles of transesterification [65,97].
• Zeolites: A different kind of catalyst used in the industrial production of biodiesel is zeolites (Zes). Zeolites are esteemed for their potent acidic properties, extensive dimension, shape affinity, and unique molecular sieving capacity, which contribute to their exceptional catalytic performance and widespread use in many catalytic applications over the years [100,101].
• Hydrotalcite: Hydrotalcite, a naturally occurring chemical, has significant potential for use, hence garnering heightened interest. Due to the numerous applications of hydrotalcite, current studies have focused on the production of nano-hydrotalcites, also known as anionic clays or aluminium–magnesium-layered double hydroxides. Hydrotalcite compounds are classified as positively charged, two-dimensional, nanostructured anionic clays that include two distinct forms of metallic cations, which are interspersed among densely packed hydroxyl groups [108].

Bioethanol Fermentation Enhancers

Nanoparticles are especially important for improving the effectiveness of biological processes. The use of these compounds in preparing and utilising second- and third-generation biomass, as well as in manufacturing various liquids (biodiesel and bioethanol/biobutanol) and gaseous biofuels, is an emerging field with the potential to lower processing and production costs while increasing the quality and quantity of the final product.

Pretreatment and hydrolysis: Nanobiocatalysts, such as cellulase attached to silica nanoparticles or magnetic supports, enhance enzymatic hydrolysis and increase its longevity. When immobilised cellulase was used on silica, it yielded 1.6 times more sugar and produced two to three times more bioethanol through SSF than when the enzyme was free [109,110]. Pretreatment of biomass is an essential but expensive process and enhancing the preprocessing of biomass is the first step for the affordable generation of bioethanol and biobutanol. The use of nanoparticles for this objective, among many alternative methods for pretreating raw biomass, enhances the robustness of the process.

Production and separation: Nanocomposites facilitate fermentation and downstream separation, potentially leading to higher yields and a more sustainable process [111]. In the generation of liquid fuels through fermentation, nanoparticles impact the biochemical synthesis process by altering either enzyme activity or the gas–liquid mass transfer rate. Numerous metal nanoparticles, including those of iron, cobalt, copper, and manganese, have demonstrated efficacy as catalytic materials in renewable energy generation. Ref. [112] documented a 166.1% increase in bioethanol production using methyl-functionalized silica nanoparticles in syngas fermentation, with the only limitation being the ineffective reuse of the nanoparticles.

Catalysts for Biomass Pyrolysis and Thermochemical Conversion

Bio-oil obtained from biomass pyrolysis has several unfavourable characteristics—namely elevated oxygen content, acidity, and instability that restrict its direct use within current fuel infrastructures. Thermochemical upgrading methods, such as catalytic cracking, hydrodeoxygenation (HDO), and steam reforming, are crucial for enhancing the quality of bio-oil [78]. Nevertheless, conventional catalysts used in these processes often experience coking, sintering, and a decline in activity over time. Nanocatalysts offer a viable solution to these challenges due to their structural integrity and enhanced efficacy [79,80]. Research indicates that nanocatalysts used in hydrodeoxygenation (HDO) can produce up to 61.2% upgraded bio-oil compared to 43.8% achieved with traditional bulk catalysts. In catalytic cracking, nanocatalysts enhance hydrocarbon yields at temperatures between 380 °C and 420 °C, with reaction durations of 15 to 30 min and catalyst loadings of 4.5 to 6.5 wt% [81,82].

Electrodes for Bioelectrochemical Systems (BESs)

Recent developments in nanomaterial-based electrodes for BESs, including microbial fuel cells (MFCs), aim to enhance extracellular electron transfer (EET) and increase power output. Bioelectrochemical systems (BESs) harness microorganisms for energy generation, suggesting that bacteria that are often considered hazardous may be rendered non-hazardous through their ability to produce alternative energy sources, thus offering dual benefits: waste reduction and simultaneous energy production [75]. The effectiveness of these systems relies on the electrode material, which influences the mechanisms of extracellular electron transport and electron collection. Various materials have been tested as electrode substances to optimise energy efficiency. Recently, carbon-based nanomaterials such as graphene sheets, carbon nanotubes, and quantum dots have been successfully utilised as cathode and anode electrodes [76,77]. These nanoparticles are environmentally friendly, non-toxic, and display remarkable physical and chemical stability.

Operational Durability, Mechanical Stability, and Scalability

Beyond environmental considerations, mechanical stability and long-term durability directly influence scalability by determining material lifetimes and replacement rates. Although catalytic and electrochemical metrics prevail in laboratory investigations, mechanical stability, durability, and long-term reliability ultimately dictate scalability [99].

Nanomaterials often deteriorate under sustained thermal, mechanical, and chemical stress due to agglomeration, leaching, and structural failure, constraining operating lifespans in biodiesel reactors and bioelectrochemical systems [65,70,74,90]. Additive manufacturing and hybrid material solutions address these difficulties by incorporating nanoparticles into mechanically resilient, architected supports or composite matrices, thereby enhancing structural integrity, material retention, and resistance to degradation [75,76,77,90,102,103,104,105]. Durability-focused designs are crucial for maintaining performance throughout prolonged operation and for extensive bioenergy implementation [113,114]. The interrelationships between nanomaterial classes, characterisation challenges, targeted bioenergy applications, and scalability constraints are summarised in

Table 8. Conceptual framework linking nanomaterials, characterisation challenges, and targeted bioenergy applications.

Nanomaterial Class	Targeted Bioenergy Application	Key Performance Role	Critical Characterisation Focus	Key Scalability Challenge	Supporting References
Metal-oxide nanocatalysts (CaO, MgO, mixed oxides)	Biodiesel transesterification	High catalytic activity, fast reaction kinetics	Crystallinity, phase composition, particle size (XRD, SEM/TEM)	Catalyst leaching, sintering, limited reuse	[57,58,59,60,61,65,70,71,72,73,74]
Magnetic nanocomposites (Fe3O4-based)	Biodiesel production and upgrading	Easy recovery, recyclability	Core–shell integrity, dispersion, morphology (TEM, SEM)	Mechanical durability over multiple cycles	[90,102,103,104,105]
Carbon-based nanomaterials (CNTs, graphene, biochar)	Bioelectrochemical systems (MFCs, BES)	Enhanced electron transfer, conductivity	Surface roughness, topology, defect density (SEM, AFM)	Electrode delamination, long-term stability	[49,50,51,52,75,76,77,98]
Enzyme-immobilised nanomaterials	Bioethanol fermentation	Improved enzymatic efficiency and reuse	Surface chemistry, binding stability (AFM, spectroscopy)	Enzyme deactivation, operational lifetime	[109,110]
Hybrid/additively manufactured nanocomposites	Structured catalysts, electrodes, reactors	Structural integrity, controlled mass transport	Multiscale architecture, interface stability (SEM, operando methods)	Scalability, printability, life-cycle impacts	[75,76,77,90,102,103,104,105,113,114]

.

The literature reveals marked differences in the scalability, cost-effectiveness, and industrial readiness of advanced nanomaterials for bioenergy applications [3,9,10,88]. Metal oxide nanocatalysts (e.g., CaO, MgO, mixed oxides) are consistently identified as the most industrially viable due to their low material cost, simple synthesis routes, and compatibility with existing biofuel production infrastructure, despite ongoing challenges related to leaching and long-term stability [65,70,71,72,73,74,97]. Carbon-based nanomaterials and magnetic nanocomposites demonstrate superior catalytic and electrochemical performance and enhanced recyclability, particularly in bioelectrochemical systems and biodiesel catalysis, but face scale-up complexity and cost constraints that currently limit their deployment to pilot-scale applications [75,76,77,90,93,94,102,103,104,105]. In contrast, enzyme-immobilised systems, metal–organic frameworks, and hybrid nanostructures offer significant efficiency and selectivity enhancements but remain at low technology-readiness levels owing to complex synthesis, durability concerns, and limited techno-economic validation [95,96,109,110,113,114]. Overall, the literature indicates that industrial readiness correlates more strongly with synthesis simplicity, durability, and compatibility with existing process infrastructure than with peak laboratory-scale performance metrics [70,90,113]. In nanocatalyst-assisted biodiesel and bioethanol production, catalyst deactivation, recyclability, and long-term stability play a decisive role in determining overall system efficiency and sustainability, often outweighing peak laboratory conversion efficiencies [70,90,92]. Catalyst deactivation arising from active-site leaching, sintering, surface fouling, coke formation, or enzyme denaturation leads to declining reaction rates, reduced yields, and increased energy and material inputs to maintain target production levels [65,70,74,97]. Recyclability directly influences catalyst lifetime and environmental performance, with recoverable systems particularly heterogeneous and magnetic nanocatalysts—reducing catalyst consumption, separation energy demand, and solid waste generation across multiple cycles [90,102,103,104,105]. Long-term stability under realistic operating conditions is essential for scale-up, as stable nanocatalysts ensure consistent conversion efficiency, predictable reactor operation, and lower life-cycle impacts in both biodiesel transesterification and bioethanol fermentation processes [70,90,113]. Overall, the literature indicates that cumulative energy yield, economic viability, and environmental sustainability are governed more strongly by durability and reusability than by short-term catalytic activity [70,90,114].

3.3.3. Influence of Deactivation, Recyclability, and Long-Term Stability on Efficiency and Sustainability

In nanocatalyst-assisted biodiesel and bioethanol production, catalyst deactivation, recyclability, and long-term stability are decisive factors governing overall system efficiency and sustainability, often outweighing peak laboratory conversion efficiencies [70,90,92]. Catalyst deactivation caused by active-site leaching, surface fouling, sintering, coke formation, or enzyme denaturation leads to declining reaction rates, reduced yields, and increased energy and material inputs required to maintain target production levels, thereby lowering process efficiency and increasing operational costs [65,70,74,97]. Recyclability strongly influences sustainability by determining catalyst lifetime and replacement frequency; nanocatalysts that can be readily recovered and reused, particularly heterogeneous and magnetic systems, reduce material consumption, downstream separation requirements, and solid-waste generation, improving both process economics and environmental performance [90,102,103,104,105]. Long-term stability under realistic operating conditions is critical for scaling laboratory results to industrial systems, as stable nanocatalysts maintain consistent activity and selectivity over multiple cycles, enabling predictable reactor performance, reduced downtime, and lower energy penalties associated with catalyst regeneration or replacement in both biodiesel transesterification and bioethanol fermentation processes [70,90,113]. Overall, the literature indicates that nanocatalyst sustainability is governed less by maximum short-term conversion efficiency and more by durability, reusability, and resistance to deactivation, with catalysts that balance moderate activity and high stability delivering superior cumulative energy yields and life-cycle performance [70,90,114].

3.3.4. Structured Sustainability Assessment Framework

A structured analysis of sustainability can be achieved by evaluating the environmental and societal impacts of nanomaterials in bioenergy systems through a life-cycle assessment framework aligned with circular bioeconomy concepts. This structure consists of four interrelated stages. The initial phase, material synthesis, evaluates energy intensity, precursor toxicity, and the utilisation of crucial or non-renewable resources, which are recognised as significant factors influencing the environmental impact of advanced nanomaterials [16,19,115]. The second stage, operational use, emphasises catalytic efficiency, material stability, and the possible release of nanoparticles during bioenergy conversion processes, along with related environmental and health hazards [75,115,116]. The third step, recovery and reuse, assesses recyclability, catalyst regeneration efficacy, and performance retention across several operational cycles. Strategies like magnetic recovery and the synthesis of waste-derived nanomaterials are especially pertinent at this juncture, as they minimise material losses and facilitate closed-loop operations [90,102,103,104,105]. The third phase, end-of-life management, pertains to degradation behaviour, environmental persistence, bioaccumulation potential, and secure disposal or recycling methods, which are inadequately investigated for numerous hybrid and composite nanomaterials [115,116].

Circular bioeconomy indicators, such as the utilisation of biomass or waste-derived feedstocks, material durability (see Table 7), regeneration capacity, and incorporation into resource-efficient energy systems, offer supplementary metrics for evaluating sustainability in conjunction with performance [9,85,86,114]. Utilising this structured approach facilitates a comprehensive assessment of the trade-offs between efficiency improvements and environmental accountability, ensuring that advancements in nanomaterial-enabled bioenergy systems are consistent with long-term sustainability and circular economy goals.

3.4. Challenges in Sustainability

Advanced nanomaterials hold significant promise for bioenergy systems; however, they also raise substantial concerns regarding their sustainability. Although several studies have demonstrated efficiency improvements in the laboratory, they have not comprehensively assessed the product from inception to completion. This absence results in environmental impact issues [115]. Nanomaterials, particularly in the context of complex hybrid composites, have restricted recovery and reutilization possibilities. This limitation complicates their integration into energy-recycling systems.

The potential bioaccumulation and cytotoxicity of nanomaterials in ecosystems and humans remain inadequately studied, raising concerns over their toxicity and safety. Stricter eco-design criteria and toxicity assessments are necessary [116]. To address these disparities and ensure that performance improvements do not negatively impact on the environment or society, researchers should incorporate sustainability criteria from the outset. Operando spectroscopy and in situ transmission electron microscopy (TEM) are more frequently being used to study catalytic and structural changes under real operational conditions. Das & Sharma [113] argued that this method offers a more comprehensive understanding of the underlying processes additionally, computational modelling and machine learning support high-throughput evaluation of nanomaterials. Ref. [114] assert that they aid performance prediction and offer recommendations for trial design, thereby shortening the innovation cycle. Integrating nanomaterial applications into a circular bioeconomy promotes sustainable feedstock use, material recovery, and waste minimisation.

4. Future Perspectives for Additive Manufacturing and Hybrid Nanomaterial Systems

Additive manufacturing (AM) is set to profoundly impact the future design of nanomaterial-enabled bioenergy systems by facilitating precise control over three-dimensional architecture, porosity, and material distribution. This control enables nanomaterials to be integrated into structurally optimised catalytic supports and electrodes, enhancing mass transfer, electron transport, and operational stability relative to traditional randomly packed systems. The integration of additive manufacturing with hybrid material systems that include nanocatalysts, carbon nanostructures, polymers, ceramics, or biomass-derived matrices provides synergistic performance improvements, such as increased durability, recyclability, and mechanical strength.

Future investigations should emphasise the links among structure, properties, and performance in additively built bioenergy components, facilitated by operando and multiscale characterisation methods. Significant hurdles persist in the formulation of printable nanomaterials, scalability, long-term stability, and life cycle assessment. Bridging these gaps is crucial for transitioning AM-enabled hybrid nanomaterial systems from laboratory demonstrations to sustainable industrial bioenergy applications.

5. Conclusions

This systematic review reveals that substantial improvements in biomass conversion, catalysis, and energy storage, facilitated by enhanced nanomaterials, are crucial for the future development of bioenergy. The results showed that research outputs are growing rapidly, with theme clusters emerging around specific topics, such as surface-engineered designs for electrochemical applications, nanostructured improvements in anaerobic digestion, and nanocatalysts for biodiesel and bioethanol production. To systematically construct high-performance nanomaterials for bioenergy systems, characterisation methods such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and X-ray powder diffraction (XRD) are used.

Nanomaterials, particularly nanocatalysts derived from feedstock, offer significant advantages in bioenergy conversion processes, including enhanced yield, stability, recyclability, and efficiency. Nanoparticles have shown the potential to overcome the long-standing restrictions of inefficiency, cost, and scalability in bioelectrical systems, pyrolysis, and fermentation. Nonetheless, continuing obstacles exist, including expensive synthesis costs, a lack of recognised characterisation methodologies, and limited use of sustainability evaluations such as life-cycle analysis. Concerns regarding toxicity, recovery, and recyclability highlight the need for a more comprehensive eco-centric strategy.