Search Results (5,844)

Accurate State of Charge (SOC) estimation for retired power batteries remains a critical challenge due to their degraded electrochemical properties and heterogeneous aging mechanisms. Traditional methods relying solely on electrical parameters (e.g., voltage and current) exhibit significant errors, as aged batteries experience altered internal resistance, capacity fade, and uneven heat generation, which distort the relationship between electrical signals and actual SOC. To address these limitations, this study proposes a surface temperature-assisted SOC estimation method, leveraging the distinct thermal characteristics of retired batteries. By employing infrared thermal imaging, key temperature feature regions—the positive/negative tabs and central area—are identified, which exhibit strong correlations with SOC dynamics under varying operational conditions. A Gated Recurrent Unit (GRU) neural network is developed to integrate multi-region temperature data with electrical parameters, capturing spatial–temporal thermal–electrical interactions unique to retired batteries. The model is trained and validated using experimental data collected under constant current discharge conditions, demonstrating superior accuracy compared to conventional methods. Specifically, our method achieves 64.3–68.1% lower RMSE than traditional electrical-parameter-only approaches (V-I inputs) across 0.5 C–2 C discharge rates. Results show that the proposed method reduces SOC estimation errors compared to traditional voltage-based models, achieving RMSE values below 1.04 across all tested rates. This improvement stems from the model’s ability to decode localized heating patterns and their hysteresis effects, which are particularly pronounced in aged batteries. The method’s robustness under high-rate operations highlights its potential for enhancing the reliability of retired battery management systems in secondary applications such as energy storage. Full article

Depression represents one of the most prevalent mental health disorders globally, significantly impacting quality of life and posing substantial healthcare challenges. Traditional diagnostic methods rely on subjective assessments and clinical interviews, often leading to misdiagnosis, delayed treatment, and suboptimal outcomes. Recent advances in biosensing technologies offer promising avenues for objective depression assessment through detection of relevant biomarkers and physiological parameters. This review examines multi-modal biosensing approaches for depression by analyzing electrochemical biosensors for neurotransmitter monitoring alongside wearable sensors tracking autonomic, neural, and behavioral parameters. We explore sensor fusion methodologies, temporal dynamics analysis, and context-aware frameworks that enhance monitoring accuracy through complementary data streams. The review discusses clinical validation across diagnostic, screening, and treatment applications, identifying performance metrics, implementation challenges, and ethical considerations. We outline technical barriers, user acceptance factors, and data privacy concerns while presenting a development roadmap for personalized, continuous monitoring solutions. This integrative approach holds significant potential to revolutionize depression care by enabling earlier detection, precise diagnosis, tailored treatment, and sensitive monitoring guided by objective biosignatures. Successful implementation requires interdisciplinary collaboration among engineers, clinicians, data scientists, and end-users to balance technical sophistication with practical usability across diverse healthcare contexts. Full article

UNS S41003 is a low-cost, low-carbon ferritic stainless steel that exhibits moderate corrosion resistance but limited mechanical performance. This study evaluates the electrochemical behavior of untreated and thermomechanically treated UNS S41003 samples. Corrosion tests were conducted in acidic electrolytes with varying pH to simulate aggressive environments relevant to industrial and structural applications where exposure to acidic media and corrosive pollutants occurs. Potentiodynamic polarization curves for all samples displayed passive regions typically associated with protective oxide film formation; however, localized pitting corrosion was detected post-test. Electrochemical impedance spectroscopy indicated a marked decrease in corrosion resistance as pH decreased. The corrosion resistance of the treated alloy remained comparable to that of the untreated condition, indicating that thermomechanical processing did not detrimentally affect passivity or corrosion performance under the tested conditions. The literature suggests that the applied treatment enhances mechanical properties, supporting the potential use of this alloy in structural components subjected to acidic environments requiring a balance of mechanical strength and corrosion resistance. Full article

Mechanical friction offers a frequent approach for sustainable energy harvesting, as it can be captured and transformed into electricity by means of the triboelectric phenomenon. Theoretically, this electricity may subsequently be employed to drive electrochemical water purification processes. Herein, the experimental results confirm that the SiC particles effectively trigger the tribocatalytic decomposition of Rhodamine B (RhB). During the tribocatalytic decomposition of dye, mechanical friction is generated at the contact surface between the tribocatalyst and a custom-fabricated polytetrafluoroethylene (PTFE) rotating disk, under varying conditions of stirring speed, temperature, and pH value. Hydroxyl radicals and superoxide radicals are confirmed as the dominant reactive species participating in tribocatalytic dye decomposition, as demonstrated by reactive species inhibition experiments. Furthermore, the SiC particles demonstrate remarkable reusability, even after being subjected to five consecutive recycling processes. The exceptional tribocatalytic performance of SiC particles makes them potentially applicable in water purification by harnessing environmental friction energy. Full article

Aqueous redox flow batteries (ARFBs) have attracted significant attention in the field of electrochemical energy storage due to their high intrinsic safety, low cost, and flexible system configuration. However, the advancement of this technology is still hindered by several critical challenges, including capacity decay, structural optimization, and the design and application of key materials as well as their performance within battery systems. Addressing these issues requires systematic theoretical foundations and scientific guidance. Numerical modeling has emerged as a powerful tool for investigating the complex physical and electrochemical processes within flow batteries across multiple spatial and temporal scales. It also enables predictive performance analysis and cost-effective optimization at both the component and system levels, thus accelerating research and development. This review provides a comprehensive overview of recent progress in the modeling of ARFBs. Taking the all-vanadium redox flow battery as a representative example, we summarize the key multiphysics phenomena involved and introduce corresponding multi-scale modeling strategies. Furthermore, specific modeling considerations are discussed for phase-change ARFBs, such as zinc-based ones involving solid–liquid phase transition, and hydrogen–bromine systems characterized by gas–liquid two-phase flow, highlighting their distinctive features compared to vanadium systems. Finally, this paper explores the major challenges and potential opportunities in the modeling of representative ARFB systems, aiming to provide theoretical guidance and technical support for the continued development and practical application of ARFB technology. Full article

In this study, a Z-scheme Ho₂InSbO₇/Ag₃PO₄ (HAO) heterojunction photocatalyst was successfully fabricated for the first time by ultrasound-assisted solvothermal method. The structural features, compositional components and morphological characteristics of the synthesized materials were thoroughly characterized by a series of techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectrum, X-ray photoelectron spectroscopy, transmission electron microscopy, scanning electron microscopy and energy-dispersive X-ray spectroscopy. A comprehensive array of analytical techniques, including ultraviolet-visible diffuse reflectance absorption spectra, photoluminescence spectroscopy, time-resolved photoluminescence spectroscopy, photocurrent testing, electrochemical impedance spectroscopy, electron paramagnetic resonance, and ultraviolet photoelectron spectroscopy, was employed to systematically investigate the optical, chemical, and photoelectronic properties of the materials. Using oxytetracycline (OTC), a representative tetracycline antibiotic, as the target substrate, the photocatalytic activity of the HAO composite was assessed under visible light irradiation. Comparative analyses demonstrated that the photocatalytic degradation capability of the HAO composite surpassed those of its individual components. Notably, during the degradation process, the application of the HAO composite resulted in an impressive removal efficiency of 99.89% for OTC within a span of 95 min, along with a total organic carbon mineralization rate of 98.35%. This outstanding photocatalytic performance could be ascribed to the efficient Z-scheme electron-hole separation system occurring between Ho₂InSbO₇ and Ag₃PO₄. Moreover, the adaptability and stability of the HAO heterojunction were thoroughly validated. Through experiments involving the capture of reactive species and electron paramagnetic resonance analysis, the active species generated by HAO were identified as hydroxyl radicals (•OH), superoxide anions (•O₂⁻), and holes (h⁺). This identification provides valuable insights into the mechanisms and pathways associated with the photodegradation of OTC. In conclusion, this research not only elucidates the potential of HAO as an efficient Z-scheme heterojunction photocatalyst but also marks a significant contribution to the advancement of sustainable remediation strategies for OTC contamination. Full article

This study synthesized FeNiCuAlX high-entropy alloys (HEAs) (where X = Cr, Co, Mn) using arc melting and investigated their high-temperature oxidation behavior in air at 900 °C. The oxidation kinetics of all alloys followed a parabolic rate, with the oxidation rate constants (kp) of FeNiCuAlCr, FeNiCuAlCo, and FeNiCuAlMn being approximately two to three orders of magnitude lower than that of the FeNiCu alloy. Specifically, FeNiCuAlCr exhibited the lowest kp value of 1.72 × 10⁻⁶ mg²·cm⁴/s, which is significantly lower than those of FeNiCuAlCo (3.29 × 10⁻⁶ mg²·cm⁴/s) and FeNiCuAlMn (1.71 × 10⁻⁵ mg²·cm⁴/s). This suggests that the addition of chromium promotes the formation of a dense Al₂O₃/Cr₂O₃ oxide layer, significantly enhancing the oxidation resistance. Furthermore, corrosion resistance was assessed through potentiodynamic polarization and electrochemical impedance spectroscopy in a 3.5% NaCl solution. FeNiCuAlCr demonstrated exceptional resistance to localized corrosion, as indicated by its low corrosion current density (45.7 μA/cm²) and high pitting potential (−0.21 V), highlighting its superior corrosion performance. Full article

This mini-review emphasizes the potential of biomass-derived materials as sustainable components for next-generation electrochemical energy storage systems. Biomass obtained from abundant and renewable natural resources can be transformed into carbonaceous materials. These materials typically possess hierarchical porosities, adjustable surface functionalities, and inherent heteroatom doping. These physical and chemical characteristics provide the structural and chemical flexibility needed for various electrochemical applications. Additionally, biomass-derived materials offer a cost-effective and eco-friendly alternative to traditional components, promoting green chemistry and circular resource utilization. This review provides a systematic overview of synthesis methods, structural design strategies, and material engineering approaches for their use in lithium-ion batteries (LIBs), lithium–sulfur batteries (LSBs), and supercapacitors (SCs). It also highlights key challenges in these systems, such as the severe volume expansion of anode materials in LIBs and the shuttle effect in LSBs and discusses how biomass-derived carbon can help address these issues. Full article

This paper presents a comparative study of data-driven modeling approaches for vanadium redox flow batteries (VRFBs), utilizing Multiple Linear Regression (MLR) and Random Forest (RF) algorithms. Experimental voltage–capacity datasets from a 1 kW/1 kWh VRFB system were digitized, processed, and used for model training, validation, and testing. The MLR model, built using eight optimized features, achieved a mean error (ME) of 0.0204 V, a residual sum of squares (RSS) of 8.87, and a root mean squared error (RMSE) of 0.1796 V on the test data, demonstrating high predictive performance in stationary operating regions. However, it exhibited limited accuracy during dynamic transitions. Optimized through out-of-bag (OOB) error minimization, the Random Forest model achieved a training RMSE of 0.093 V and a test RMSE of 0.110 V, significantly outperforming MLR in capturing dynamic behavior while maintaining comparable performance in steady-state regions. The accuracy remained high even at lower current densities. Feature importance analysis and partial dependence plots (PDPs) confirmed the dominance of current-related features and SOC dynamics in influencing VRFB terminal voltage. Overall, the Random Forest model offers superior accuracy and robustness, making it highly suitable for real-time VRFB system monitoring, control, and digital twin integration. This study highlights the potential of combining machine learning algorithms with electrochemical domain knowledge to enhance battery system modeling for future energy storage applications. Full article

The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and labor-intensive, hindering their large-scale production. Recent advances in 3D printing technology offer innovative pathways to address these challenges. By combining design flexibility with material optimization, 3D printing holds the potential to enhance battery performance and enable customized structures. This review systematically examines the application of 3D printing technology in fabricating key AZIB components, including electrodes, electrolytes, and integrated battery designs. We critically compare the advantages and disadvantages of different 3D printing techniques for these components, discuss the potential and mechanisms by which 3D-printed structures enhance ion transport and electrochemical stability, highlight critical existing scientific questions and research gaps, and explore potential strategies for optimizing the manufacturing process. Full article

This study examines the effect of temperature during pyrolysis on the capacity of cedar wood-derived biochar to be employed as a sustainable electrode material for supercapacitors. Cedar wood-derived biochars were produced at different temperatures of 800 °C, 900 °C, 1000 °C and 1100 °C and fully characterized in terms of their structural, physicochemical and electrochemical properties, including specific surface area, hydrophobicity, electrical conductivity, and surface functional groups. The results indicated that the cedar wood biochar obtained through pyrolysis at 900 °C (BC900) provided optimal electrical conductivity, hydrophobicity, and porosity characteristics relative to the other cedar wood biochars produced by pyrolysis at 800 °C to 1100 °C. Specifically, when compared to commercial activated carbon (AC), BC900 provided half the specific capacitance at a current density of 1 A g⁻¹ and indicated that there is more potential for improvement with further activation and doping. The influence of the binder (either polyvinylidene fluoride (PVDF) or chitosan) in combination with conductive carbon black (CB) was also examined. Electrodes fabricated with PVDF binder showed higher specific capacitance, while biochar electrodes made from CB and chitosan (BC900/CB/chitosan) showed better electrical conductivity, wettability, and good electrochemical stability with >95% capacity retention even after 10,000 cycles. Full article

Morphine is an opioid extracted from the poppy plant and highly effective for moderate to severe pain management. Development of techniques to measure the concentration of this highly addictive drug in various matrices is very important. This work was aimed at the development of a sensitive electrochemical method for detection of morphine in wastewater. Molecularly imprinted (MIP) electrodes were made by the electro-polymerization process using pyrrole as a monomer. Electro-polymerization was performed on glassy carbon electrodes in the presence of morphine before the extraction of the entrapped morphine molecules. Various techniques were employed to monitor the polymerization and response of the fabricated electrodes toward morphine. These techniques included Fourier transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), square wave voltammetry (SWV), and electrochemical impedance spectroscopy (EIS). The morphine concentration was determined using SWV and CV by measuring the change in the redox peak current of [Fe(CN)₆]^−3/−4. These MIP electrode sensors were used to analyze morphine concentrations between 0 and 80.0 nM solution. The SWV showed a wider linear response region than CV. The detection limit using SWV was found to be 1.9 nM, while using CV, the detection limit was 2.75 nM. This MIP electrode sensor exhibited specificity when other closely related molecules were included and hence has potential as a cheap alternative technique for analysis of morphine. Full article

This paper introduces PyBEP, a Python-based tool for the automated and optimized selection of open-circuit potential (OCP) curves and calculation of stoichiometric cycling ranges for lithium-ion battery electrodes based on open-circuit voltage (OCV) measurements. Thereby, it overcomes key challenges in traditional approaches, which are often time-intensive and susceptible to errors due to manual curve digitization, data inconsistency, and coding complexities. The originality of PyBEP arises from the systematic integration of automated electrode chemistry identification, quality-controlled database usage, refinement of the results using incremental capacity methodology, and simultaneous optimization of multiple electrode parameters. The PyBEP database leverages high-quality, curated OCP data and employs differential evolution optimization for precise OCP determination. Validation against literature data and experimental results confirms the robustness and accuracy of PyBEP, consistently achieving precision of 10 mV or better. PyBEP also offers features like electrode chemical composition identification and quality enhancement of measurement data, further extending the battery modeling functionalities without the need for battery disassembly. PyBEP is open-source and accessible on GitHub, providing a streamlined, accurate resource for the battery research community, making PyBEP a unique and directly applicable toolkit for electrochemical researchers and engineers. Full article

The present study investigates dye-sensitized solar cells (DSSCs) incorporating natural extracts from the microalgae Spirulina and Chlorella as photosensitizers. TiO₂-based electrodes were prepared and immersed in methanolic algae extracts for 24 and 48 h. UV–Vis spectroscopy revealed absorption peaks near 400 nm and 650 nm, characteristic of chlorophyll. Electrochemical analyses, including photochronoamperometry and open-circuit potential, confirmed the photosensitivity and charge transfer capabilities of all systems. The cell sensitized with Chlorella after 48 h of immersion exhibited the highest energy conversion efficiency (0.0184% ± 0.0015), while Spirulina achieved 0.0105% ± 0.0349 after 24 h. Chlorella’s superior performance is attributed to its higher chlorophyll content and enhanced light absorption, facilitating more efficient electron injection and interaction with the TiO₂ surface. Although the efficiency remains lower than that of conventional silicon-based solar cells, the results highlight the potential of natural colorants as sustainable and low-cost alternatives for photovoltaic applications. Nonetheless, further, improvements are required, particularly in dye stability and anchorage, to improve device performance. This research reinforces the viability of natural photosensitizers in DSSC technology and supports continued efforts to optimize their application. Full article

Metal–Organic Frameworks (MOFs) have emerged as advanced porous crystalline materials due to their highly ordered structures, ultra-high surface areas, fine-tunable pore sizes, and massive chemical diversity. These features, arising from the coordination between an almost unlimited number of metal ions/clusters and organic linkers, have resulted in significant interest in MOFs for applications in gas storage, catalysis, sensing, energy, and biomedicine. Beyond their stand-alone properties and applications, recent research has increasingly explored the integration of MOFs with other substrates, particularly electrodes, polymeric thin films, and glass surfaces, to create synergistic effects that enhance material performance and broaden application potential. Coating MOFs onto these substrates can yield significant benefits, including, but not limited to, improved sensitivity and selectivity in electrochemical sensors, enhanced mechanical and separation properties in membranes, and multifunctional coatings for optical and environmental applications. This review provides a comprehensive and up-to-date summary of recent advances (primarily from the past 3–5 years) in MOF coating techniques, including layer-by-layer assembly, in situ growth, and electrochemical deposition. This is followed by a discussion of the representative applications arising from MOF-substrate coating and an outline of key challenges and future directions in this rapidly evolving field. This article aims to serve as a focused reference point for researchers interested in both fundamental strategies and applied developments in MOF surface coatings. Full article