Search Results (169)

To address the limitations of conventional LC resonant battery equalization circuits, including slow balancing speed under small voltage differences, limited scalability in multi-cell configurations, and the risk of over-equalization, this paper proposes a dual-layer LC resonant equalization topology integrated with a Boost-assisted mechanism and a state-of-charge (SOC)-based dual closed-loop current control strategy. In the proposed topology, a Boost converter is introduced to actively enhance the effective voltage difference between cells, thereby improving the equalization current amplitude and accelerating the balancing process. A switched-inductor structure is further adopted to enable scalable inter-group energy transfer in multi-cell battery systems. To improve control accuracy, SOC is selected as the balancing variable, and a dual closed-loop control framework is designed, where the outer loop regulates SOC deviation, and the inner loop controls the equalization current via proportional–integral (PI) controllers. A MATLAB/Simulink model is established to evaluate the proposed method under multiple operating conditions, including idle, charging, and discharging states. The results show that the proposed topology significantly reduces the equalization time compared with conventional LC resonant circuits and improves balancing speed by approximately 49% under the dual closed-loop control strategy. In addition, the system maintains stable performance across different operating conditions. It should be noted that this study focuses on topology design and control strategy validation through simulation. Due to the focus on topology validation and control mechanism analysis, this study is limited to simulation-based verification. Experimental implementation will be conducted in future work. Full article

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO₄)₂ and Zn(OTf)₂, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The presence of carboxyl groups in CSAM and the existence of O-H bonding facilitated ion movement, resulting in enhanced ionic conductivity and preventing dendrite formation. Incorporating these hydrogels with high-performance zinc salts, such as zinc triflate (Zn(OTf)₂), resulted in stable symmetric cell cycling over 4000 h with a uniform voltage profile under 1 mA/cm² and a low overpotential of around 53 mV cycling with CSAM. Rate-dependent full-cell testing showed that the PBI solid electrolyte delivers higher capacity retention at different current densities, whereas CSAM exhibits markedly better long-term stability, even at low voltages, owing to its effective dendrite suppression, which helps preserve cathode performance over extended cycling. Full article

Accurately determining actual energy consumption is essential for guiding technological developments in the transport sector, assessing vehicle development outcomes, and designing effective energy and climate policies. Although laboratory driving cycles such as the WLTP provide standardized benchmarks, they do not reflect the complex interactions between human behavior, environmental conditions, and vehicle dynamics under real-world operating conditions. This article presents an integrated framework for assessing long-term, actual energy carrier consumption in four main vehicle categories: internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), hydrogen fuel cell electric vehicles (H2EVs), and battery electric vehicles (BEVs). The entire discussion here is based on the results of data analysis from natural operation using the so-called vehicle energy footprint. This framework provides a method for determining the average energy carrier consumption for each group of vehicles with the specified drivetrains. This information formed the basis for assessing the total energy demand for the operation of the analyzed vehicle types in normal operation. The simulations show that among mid-range passenger vehicles, ICEVs are the most energy-intensive in normal operation, followed by H2EVs and HEVs, and BEVs are the least. This study highlights the methodological challenges and implications of accurately quantifying energy consumption. The presented method for assessing energy demand in vehicle operation can be useful for manufacturers, consumers, fleet operators, and policymakers, particularly in terms of energy efficiency, emission reduction, and public health protection. Full article

The field of electrochemical devices, encompassing energy storage, fuel cells, electrolysis, and sensing, is fundamentally reliant on the electrode materials that govern their performance, efficiency, and sustainability. Traditional materials, while foundational, often face limitations such as restricted reaction kinetics, structural deterioration, and dependence on costly or scarce elements, driving the need for continuous innovation. Emerging electrode materials are designed to overcome these challenges by delivering enhanced reaction activity, superior mechanical robustness, accelerated ion diffusion kinetics, and improved economic feasibility. In energy storage, for example, the shift from conventional graphite in lithium-ion batteries has led to the exploration of silicon-based anodes, offering a theoretical capacity more than tenfold higher despite the challenge of massive volume expansion, which is being mitigated through nanostructuring and carbon composites. Simultaneously, the rise of sodium-ion batteries, appealing due to sodium’s abundance, necessitates materials like hard carbon for the anode, as sodium’s larger ionic radius prevents efficient intercalation into graphite. In electrocatalysis, the high cost of platinum in fuel cells is being addressed by developing Platinum-Group-Metal-free (PGM-free) catalysts like metal–nitrogen–carbon (M-N-C) materials for the oxygen reduction reaction (ORR). Similarly, for the oxygen evolution reaction (OER) in water electrolysis, cost-effective alternatives such as nickel–iron hydroxides are replacing iridium and ruthenium oxides in alkaline environments. Furthermore, advancements in materials architecture, such as MXenes—two-dimensional transition metal carbides with metallic conductivity and high volumetric capacitance—and Single-Atom Catalysts (SACs)—which maximize metal utilization—are paving the way for significantly improved supercapacitor and catalytic performance. While significant progress has been made, challenges related to fundamental understanding, long-term stability, and the scalability of lab-based synthesis methods remain paramount for widespread commercial deployment. The future trajectory involves rational design leveraging advanced characterization, computational modeling, and machine learning to achieve holistic, system-level optimization for sustainable, next-generation electrochemical devices. Full article

Vanadium redox flow batteries (VRFBs) experience performance losses driven by electrode ageing, yet the underlying mechanisms remain poorly resolved under operational conditions. This work presents a novel application of dynamic electrochemical impedance spectroscopy (DEIS) in both full-cell and three-electrode configurations to monitor kinetic and transport processes throughout complete charge–discharge cycles. Carbon felt electrodes subjected to thermal activation, chemical degradation, and electrochemical ageing were systematically examined to capture a broad range of ageing-induced modifications. Complementary electrochemical impedance spectroscopy (EIS) measurements at selected states of charge were performed to highlight the substantial differences between spectra recorded under load and at open-circuit conditions. The results reveal that the impedance response of the full cell is dominated by processes occurring at the negative electrode, and that ageing leads to increased charge-transfer resistance and enhanced state of charge-dependent variation. X-ray photoelectron spectroscopy (XPS) analysis confirms significant modifications in surface chemistry, including variations in the sp²/sp³ carbon distribution and the enrichment of oxygen-containing functional groups, which correlate with the observed electrochemical behavior. Overall, this study demonstrates—for the first time under realistic VRFB cycling conditions—that DEIS provides unique diagnostic capabilities, enabling mechanistic insights into electrode ageing that are inaccessible to conventional impedance approaches. Full article

Polyampholytes combine cationic and anionic groups in one macromolecular platform and are emerging as versatile components for energy storage and conversion. This review synthesizes how their charge balance, hydration, and architecture can be engineered to address ionic transport, interfacial stability, and safety across batteries, supercapacitors, solar cells, and fuel cells. We classify annealed, quenched, and zwitterionic systems, outline molecular design strategies that tune charge ratio, distribution, and crosslinking, and compare device roles as gel or solid electrolytes, eutectogels, ionogels, binders, separator coatings, and interlayers. Comparative tables summarize ionic conductivity, cation transference number, electrochemical window, mechanical robustness, and temperature tolerance. Across Li and Zn batteries, polyampholytes promote ion dissociation, homogenize interfacial fields, suppress dendrites, and stabilize interphases. In supercapacitors, antifreeze hydrogels and poly(ionic liquid) networks maintain conductivity and elasticity under strain and at subzero temperature. In solar cells, zwitterionic interlayers improve work function alignment and charge extraction, while ordered networks in fuel cell membranes enable selective ion transport with reduced crossover. Design rules emerge that couple charge neutrality with controlled hydration and dynamic crosslinking to balance conductivity and mechanics. Key gaps include brittleness, ion pairing with multivalent salts, and scale-up. Opportunities include soft segment copolymerization, ionic liquid and DES plasticization, side-chain engineering, and operando studies to guide translation. Full article

Ionomers are promising materials because ionic interactions and their reversible clustering provide sensitivity to stimuli and facilitate energy dissipation, polymer miscibility, and ion transport. The existence of a wide variety of interacting ionic groups and their associated macromolecular structures provides the basis for considering the supramolecular organization of ionic polymeric materials as a factor determining the emergence of specific properties. The main structural elements of ionomers are ionic clusters, and the properties of ionomers are determined by their sizes and size distribution. Ionomers are attractive for use in composites, actuators, coatings, dyed textiles, adhesives, shape-memory and self-healing materials, water purification membranes, and ion-exchange membranes for fuel cells and batteries. This paper presents a review of the macromolecular structure and supramolecular organization of ionomers and their properties, depending on the basis of their ionic functionalization. The ionic functions of ionomers are determined primarily by the type of ion (cations or anions) that serves as the basis for their functionalization. Ionomers containing both anionic and cationic pendant ions are considered, with attention given to the influence of the nature of the counterions used on the properties of ionomers. Full article

Inherent conductivity and high redox activity endow polyaniline (PANI) with great potential to serve as a cathode material for aqueous zinc-ion batteries. However, compared with traditional strongly acidic electrolytes (pH < 1), its electrochemical performances are moderated in weakly acidic zinc salt electrolytes (pH > 3) because of spontaneous deprotonation. Herein, a carboxyl-modified PANI was designed and synthesized by introducing carboxyl groups at the para-position of the terminal benzene rings within the polymer chains. In this conjugated system, the electron density in the polymer chains was redistributed with a higher one around the substituent due to the electron-withdrawing effect of carboxyl groups and meanwhile carboxyl groups characterized by a proton donor render PANI achieve a proton-involved electrochemical reaction. Consequently, the carboxyl-modified PANI cathode, in a Zn//PANI cell, delivers an impressive specific capacity of 226 mAh g⁻¹ along with excellent rata capability and cycling stability. This work presented some new insights into the molecule structure design of PANI-based polymers applied in advanced aqueous batteries. Full article

The growing use of lithium-ion batteries (LIBs) in electric vehicles has accelerated the need for efficient strategies to extend their lifespan through second-life applications, where retired batteries are repurposed for stationary storage and other less demanding roles. This paper reviews the most pertinent degradation mechanisms underlying battery aging and the most frequently occurring faults during battery operation. After establishing the correlation between degradation and fault occurrence, reliable state-of-health (SOH) and remaining useful life (RUL) predictions are identified as central to ensuring safety, reliability, and cost-effectiveness in repurposed systems. Next, we present a systematic review of the recently published studies on battery prognosis, with methods categorized into three groups: (i) physics-informed and hybrid models; (ii) purely data-driven approaches; and (iii) transfer learning and features extraction methods. A comparative analysis highlights the strengths and limitations of each group and identifies the most promising approaches for battery repurposing. Modeling heterogeneous second-life packs remains particularly challenging, as cells often enter repurposing with different usage histories and only partial BMS records. In this context, transfer learning and domain adaptation emerge as the most promising directions. In parallel, Generative Adversarial Networks (GANs) can help in addressing the challenge of data scarcity, particularly when integrated into hybrid frameworks for second-life applications. At the same time, systematic exploration of health indicators—including the possibility of stage-specific ones—remains essential. Finally, reinforcement learning offers a complementary yet still underexplored path, enabling real-time adaptation in dynamic scenarios, as batteries enter nonlinear regimes beyond the knee point. Full article

Metal anodes promise improvements in energy density and cost; however, their performance is determined within the first several nanometers at the interface. This review reports on how polymer-based artificial solid electrolyte interphases (SEIs) are engineered to stabilize Li and aqueous-Zn anodes, and how these designs are now evaluated against operando readouts rather than post-mortem snapshots. We group the related molecular strategies into three classes: (i) side-chain/ionomer chemistry (salt-philic, fluorinated, zwitterionic) to increase cation selectivity and manage local solvation; (ii) dynamic or covalently cross-linked networks to absorb microcracks and maintain coverage during plating/stripping; and (iii) polymer–ceramic hybrids that balance modulus, wetting, and ionic transport characteristics. We then benchmark these choices against metal-specific constraints—high reductive potential and inactive Li accumulation for Li, and pH, water activity, corrosion, and hydrogen evolution reaction (HER) for Zn—showing why a universal preparation method is unlikely. A central element is a system of design parameters and operando metrics that links material parameters to readouts collected under bias, including the nucleation overpotential (η_nuc), interfacial impedance (charge transfer resistance (R_ct)/SEI resistance (R_SEI)), morphology/roughness statistics from liquid-cell or cryogenic electron microscopy (Cryo-EM), stack swelling, and (for Li) inactive-Li inventory. By contrast, planar plating/stripping and HER suppression are primary success metrics for Zn. Finally, we outline parameters affecting these systems, including the use of lean electrolytes, the N/P ratio, high areal capacity/current density, and pouch-cell pressure uniformity, and discuss closed-loop workflows that couple molecular design with multimodal operando diagnostics. In this view, polymer artificial SEIs evolve from curated “recipes” into predictive, transferable interfaces, paving a path from coin-cell to prototype-level Li- and Zn-metal batteries. Full article

In this research article, a silicon carbide (SiC) nanocluster has been designed and characterized as an anode electrode for lithium (Li), sodium (Na), potassium (K), beryllium (Be), magnesium (Mg), boron (B), aluminum (Al) and gallium (Ga)-ion batteries through the formation of SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters. A vast study on energy-saving by SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC complexes was probed using computational approaches accompanying density state analysis of charge density differences (CDDs), total density of states (TDOS) and molecular electrostatic potential (ESP) for hybrid clusters of SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC. The functionalization of Li, Na, K, Be, Mg, B, Al and Ga metal/metalloid elements can raise the negative charge distribution of carbon elements as electron acceptors in SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters. Higher Si/C content can increase battery capacity through SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters for energy storage processes and to improve the rate performance by enhancing electrical conductivity. Full article

Accurate estimation of lithium-ion battery (LIB) state of health (SOH) underpins safe operation, predictive maintenance, and lifetime-aware energy management. Despite recent advances in machine learning (ML), systematic benchmarking across heterogeneous real-world cells remains limited, often confounded by data leakage and inconsistent validation. Here, we establish a leakage-averse, cross-battery evaluation framework encompassing 32 commercial LIBs (B5–B56) spanning diverse cycling histories and temperatures (≈4 °C, 24 °C, 43 °C). Models ranging from classical regressors to ensemble trees and deep sequence architectures were assessed under blocked 5-fold GroupKFold splits using RMSE, MAE, R² with confidence intervals, and inference latency. The results reveal distinct stratification among model families. Sequence-based architectures—CNN–LSTM, GRU, and LSTM—consistently achieved the highest accuracy (mean RMSE ≈ 0.006; per-cell R² up to 0.996), demonstrating strong generalization across regimes. Gradient-boosted ensembles such as LightGBM and CatBoost delivered competitive mid-tier accuracy (RMSE ≈ 0.012–0.015) yet unrivaled computational efficiency (≈0.001–0.003 ms), confirming their suitability for embedded applications. Transformer-based hybrids underperformed, while approximately one-third of cells exhibited elevated errors linked to noise or regime shifts, underscoring the necessity of rigorous evaluation design. Collectively, these findings establish clear deployment guidelines: CNN–LSTM and GRU are recommended where robustness and accuracy are paramount (cloud and edge analytics), while LightGBM and CatBoost offer optimal latency–efficiency trade-offs for embedded controllers. Beyond model choice, the study highlights data curation and leakage-averse validation as critical enablers for transferable and reliable SOH estimation. This benchmarking framework provides a robust foundation for future integration of ML models into real-world battery management systems. Full article

Today, hydrogen is already widely regarded as up-and-coming source of energy. It is essential to meet energy needs while reducing environmental pollution, since it has a high energy capacity and does not emit carbon oxide when burned. However, for the widespread application of hydrogen energy, it is necessary to search new technical solutions for both its production and storage. A promising effective and cost-efficient method of hydrogen generation and storage can be the use of solid materials, including nanomaterials in which chemical or physical adsorption of hydrogen occurs. Focusing on the recommendations of the DOE, the search is underway for materials with high gravimetric capacity more than 6.5% wt% and in which sorption and release of hydrogen occurs at temperatures from −20 to +100 °C and normal pressure. This review aims to summarize research on hydrogen generation and storage using silicon nanostructures and silicon composites. Hydrogen generation has been observed in Si nanoparticles, porous Si, and Si nanowires. Regardless of their size and surface chemistry, the silicon nanocrystals interact with water/alcohol solutions, resulting in their complete oxidation, the hydrolysis of water, and the generation of hydrogen. In addition, porous Si nanostructures exhibit a large internal specific surface area covered by SiH_x bonds. A key advantage of porous Si nanostructures is their ability to release molecular hydrogen through the thermal decomposition of SiHx groups or in interaction with water/alkali. The review also covers simulations and theoretical modeling of H₂ generation and storage in silicon nanostructures. Using hydrogen with fuel cells could replace Li-ion batteries in drones and mobile gadgets as more efficient. Finally, some recent applications, including the potential use of Si-based agents as hydrogen sources to address issues associated with new approaches for antioxidative therapy. Hydrogen acts as a powerful antioxidant, specifically targeting harmful ROS such as hydroxyl radicals. Antioxidant therapy using hydrogen (often termed hydrogen medicine) has shown promise in alleviating the pathology of various diseases, including brain ischemia–reperfusion injury, Parkinson’s disease, and hepatitis. Full article

In this work, a novel solid polymer electrolyte with a disordered structure has been designed, combining polyethylene glycol (PEG) as the flexible segments and hexamethylene diisocyanate (HDI) as the rigid segments. The synthesis was realized by alternating flexible PEG with rigid HDI through a peptide bond (–CO–NH–), which disrupts the ordered structures of PEG, generating electron-deficient Lewis acid groups. The pathbreaking introduction of HDI blocks not only bridges links between the PEG molecules but also generates electron-deficient Lewis acid groups. Therefore, the original ordered structures of PEG are disrupted by both the alternating chains between PEG and HDI and the Lewis acid groups. As a result, the PEG_H/L4000 electrolytes (PEG molecular weight of 4000) exhibit a strong anion-capture ability that decreases the crystallinity of polymers, which further achieves a high ionic conductivity close to 10⁻³ S·cm⁻¹ with the lithium-ion transference numbers up to 0.88. The symmetric Li|PEG_H/L4000|Li cells maintain a low and stable voltage polarization for more than 800 h at 0.1 mA·cm⁻². Furthermore, the LiFePO₄|PEG_H/L4000|Li all-solid-state cells perform well both in cycling and rate performances. The design of polymer disordered structures for polymer electrolytes provides a new thought for manufacturing all-solid-state lithium-ion batteries with high safety as well as long life. Full article

Electrochemical impedance spectroscopy (EIS) is widely used at the laboratory level for monitoring/diagnostics of battery cells, but the design and validation of in situ, online measurement systems based on EIS face challenges due to complex hardware–software interactions and non-idealities. This study aims to develop an integrated co-simulation framework to support the design, debugging, and validation of EIS measurement systems devoted to the online monitoring of battery cells, helping to predict experimental results and identify/correct the non-ideality effects and sources of uncertainty. The proposed framework models both the hardware and software components of an EIS-based system to simulate and analyze the impedance measurement process as a whole. It takes into consideration the effects of physical non-idealities on the hardware–software interactions and how those affect the final impedance estimate, offering a tool to refine designs and interpret test results. For validation purposes, the proposed general framework is applied to a specific EIS-based laboratory prototype, previously designed by the research group. The framework is first used to debug the prototype by uncovering hidden non-idealities, thus refining the measurement system, and then employed as a digital model of the latter for fast development of software algorithms. Finally, the results of the co-simulation framework are compared against a theoretical model, the real prototype, and a benchtop instrument to assess the global accuracy of the framework. Full article