This bimonthly review paper highlights a comprehensive overview of the latest research on lithium batteries. A total of 7666 online papers from June 1, 2025, to July 31, 2025, were examined through the Web of Science database. Firstly, the BERTopic topic model was used to analyze the abstract text and the research topic map of lithium battery papers was drawn. 100 papers were selected for highlighting in this review. The selected studies cover various aspects of lithium batteries.Cathode materials including Ni-rich layered oxides and other novel materials are improved by doping, surface coating, and microstructural modifications. The cycling performances of Si-based anode are enhanced by structural design. Great efforts have been devoted to the interfacial and bulk structure design of lithium metal anode. Studies on solid-state electrolytes focus on the structure design and performances of polymer, oxide, sulfide, and halide electrolytes, as well as their composite forms. In contrast, liquid electrolytes are improved through optimal solvent and lithium salt design for different battery applications and incorporating novel functional additives. For solid-state batteries, the surface coating and synthesis methods of cathodes and the optimization of composite cathodes, interface construction of lithium metal anode, as well as the synthesis of other anode types are widely investigated. In addition, lithium-sulfur and lithium-oxygen batteries have also garnered significant attention. There are also many papers on the ion transport and degradation mechanisms in electrodes, lithium deposition morphology and lithium diffusion pathways in electrolytes, the analysis of thermal runaway of full batteries, the theoretical simulation of void formation and dendrite growth mechanisms at solid electrolyte/lithium interfaces, as well as the application of high-throughput computations and big-data modeling in lithium batteries.

In lithium-ion batteries, electrolyte additives such as fluorinated ethylene carbonate (FEC) and vinylene carbonate (VC) have been widely employed to enhance the stability of the electrode/electrolyte interface; however, their effects on graphite electrodes remain unclear. In this study, the interfacial behavior of FEC and VC on graphite anodes in lithium-ion batteries is systematically investigated. The distinct mechanisms by which FEC and VC influence graphite surfaces are elucidated through various characterization techniques, including cyclic voltammetry, electrochemical impedance spectroscopy, scanning electron microscopy, transmission electron microscopy, and X-ray photoelectron spectroscopy. Electrochemical impedance results indicate that, in Li|Gr cells, the total impedance before and after solid electrolyte interphase (SEI) formation with FEC is lower than that with VC, whereas in Li|Ref|Gr cells, the total impedance with FEC is higher than that with VC. The interfacial impedances are further deconvoluted using the electrochemical impedance spectroscopy-distribution of relaxation time (EIS-DRT) method to determine the SEI impedance, the charge-exchange impedance at the SEI-graphite interface, and the SEI–electrolyte interface charge-exchange impedance in Li|Gr cells. The characteristic relaxation times of FEC and VC are essentially consistent for each component, with values of 5×10^-5 s for SEI impedance, 3×10^-4 s for SEI-graphite interface charge exchange, and 5×10^-3 s for SEI-electrolyte interface charge exchange. The results show that VC reduction at 0.77 V forms an organic-rich SEI, significantly reducing impedance at the graphite interface but exhibiting poor compatibility with lithium metal, thereby increasing the total cell impedance. In contrast, FEC reduction at 1 V forms a LiF-rich SEI on the graphite surface, which increases graphite interface impedance yet greatly improves the stability of the lithium metal electrode. The adverse effect of FEC on the graphite interface is outweighed by its stabilizing effect on lithium metal, ultimately reducing the total cell impedance. This study provides important experimental insights and theoretical guidance for the optimized design of electrolytes in lithium-ion batteries.

Natural graphite possesses advantages such as high capacity, stable voltage platform, and low cost; however, it suffers from defects and poor electrolyte compatibility, limiting its widespread application. In the digital field, the anode material of lithium-ion batteries primarily comprises artificial graphite prepared from needle coke or petroleum coke. This study investigates the effect of a composite anode consisting of natural graphite and artificial graphite on the performance of digital lithium-ion batteries, using pouch cells as the research object. The anode materials and assembled batteries were analyzed using scanning electron microscopy (SEM), laser particle size analysis, specific surface area analysis, and electrochemical impedance spectroscopy, among other methods. The electrochemical performance of batteries utilizing composite graphite (C-Gr; 70% artificial graphite + 30% natural graphite) and pure artificial graphite (A-Gr) anodes was evaluated. The results show that the direct current internal resistance, solid electrolyte interphase (SEI) film impedance, and charge transfer impedance of composite graphite anodes are relatively high, leading to greater internal temperature rise, significant polarization, and reduced performance during high-rate, constant power, and low-temperature discharge conditions. The large specific surface area of the composite graphite anode increases the side reactions with the electrolyte, resulting in decreased residual capacity and recovery capacity after full-charge storage at high temperatures. After 500 cycles at room temperature, the capacity retention of the composite graphite anode was 76%, which was 11.6% lower than that of the artificial graphite anode. Furthermore, the thickness swelling rate and internal resistance growth rate were 1.8% and 26.3% higher than those of the artificial graphite anode, respectively. SEM analysis reveals significant thickening and increased cracking of the SEI film on the composite graphite anode after cycling, leading to reversible capacity fading. In addition, the degradation of the anode material indirectly affects the structural stability of the cathode material. After cycling with the composite graphite anode, more Ni, Co, and Mn elements dissolved from the cathode material, with Mn content approximately double that of the artificial graphite anode. Severe particle cracking and skeleton structure destruction were also observed in the ternary cathode material.

Rechargeable aluminum-ion batteries (AIBs) are regarded as promising next-generation electrochemical energy storage systems due to their high capacity, low cost, and enhanced safety. However, the development of high-performance cathode materials remains a critical challenge for the commercialization of AIBs. In this study, nitrogen-doped carbon nanofibers (N-CNFs) were synthesized via electrospinning and subsequent annealing, serving as substrates for a hydrothermal process to uniformly load bimetallic sulfide, resulting in a flexible, free-standing NiCo₂S₄@N-CNF composite. The composition, structure, and morphology were characterized by scanning electron microscopy, transmission electron microscopy, energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy. The NiCo₂S₄@N-CNF composite was directly employed as a cathode for AIBs, and its specific capacity, cycling stability, and rate performance were evaluated through constant current charge-discharge tests and cyclic voltammetry. The results demonstrate that the cauliflower-like NiCo₂S₄ is uniformly wrapped on the N-CNFs, forming a flexible, free-standing structure suitable for direct use as a cathode in AIBs. At a current density of 100 mA/g, the specific capacity reached 266.3 mA h/g, and after 200 cycles, it maintained a discharge capacity of 151.6 mAh/g, indicating excellent specific capacity and cycling stability. Moreover, in rate performance tests, the specific capacity recovered well after high current shocks, demonstrating good rate capability. Analysis of XRD patterns and valence state changes of Ni and Co during charge and discharge confirmed that the aluminum storage mechanism in NiCo₂S₄ involves the reversible intercalation and de-intercalation of Al³⁺ ions facilitated by the bimetallic synergistic effect. This study provides theoretical guidance and a design reference for the development of high-performance cathode materials for AIBs.

Lithium cobalt oxide (LCO) offers advantages such as long cycle life, high energy density, and no memory effect, making it widely used in wearable digital products. Increasing the charging cut-off voltage can effectively enhance the battery's energy density; however, it also induces adverse effects, including electrolyte oxidation and decomposition and cobalt ion dissolution, resulting in performance degradation. In this study, a bifunctional additive, cyanomethyl p-toluenesulfonate (CMPTS), was introduced to improve battery performance. CMPTS participates in the formation of the solid electrolyte interphase (SEI) on the anode and the cathode electrolyte interphase (CEI) on the cathode, suppressing further redox reactions of carbonate solvents and lithium hexafluorophosphate (LiPF₆), and preventing cobalt ion dissolution from LCO. This promotes the insertion and extraction of lithium ions (Li⁺) through the solid passivation film. Using CMPTS as an electrolyte additive in AG/LCO full cells, charge-discharge tests were conducted at 0.5 C within 3.0—4.55 V. The cell containing 1% CMPTS exhibited a capacity retention of 90.4% after 500 cycles at room temperature, compared to 80.8% for the baseline cell. At 45 ℃, after 350 cycles, the capacity retention rates of the CMPTS-containing and baseline cells were 83.2% and 78.1%, respectively. These results demonstrate that CMPTS significantly enhances the electrochemical performance of lithium-ion batteries.

To harness the excellent fluidity and self-healing characteristics of liquid metal, two novel electrodes, liquid metal nanoparticles (LMNP) and liquid metal film (LMF), were fabricated via probe ultrasonication and doctor-blading methods, respectively. The microstructural features, mechanical properties, and electrochemical performances of these electrodes were comprehensively investigated using focused ion beam milling, scanning electron microscopy, nanoindentation, and electrochemical measurements. The LMNP electrode exhibited a uniform dispersion of nanoparticles within the matrix, forming strong interparticle connections, whereas the LMF electrode formed a continuous film on the substrate, which developed cracks at the interface with the current collector. The LMNP electrode demonstrated superior rate capability and cycling stability compared to the LMF electrode. After 300 cycles at a current density of 2.0 A/g, the LMNP electrode maintained a reversible specific capacity of 399.3 mAh/g with a capacity retention of 86.9%. During cycling, both electrodes underwent particle size reduction and self-healing-induced welding, providing additional conductive pathways that facilitated charge transfer. Moreover, both electrodes exhibited a gradual transition from a soft to a rigid structure during cycling; however, the LMNP electrode achieved this transition more rapidly, resulting in earlier structural stabilization and enhanced electrochemical performance. These findings provide critical insights into the application of liquid metal-based electrodes and offer valuable guidance for designing high-performance anode materials for lithium-ion batteries.

Phase change material (PCM)-based latent heat storage cooling technology has broad applications in aerospace thermal management because of its high energy storage density and passive temperature regulation capability. Copper foam, which is commonly employed to enhance the thermal conductivity of PCMs, suppresses natural convection while improving heat transfer. Complex force fields, including hypergravity, microgravity, and variable acceleration induced by vehicle maneuvers, interact with this convection suppression and introduce uncertainties in the overall heat transfer enhancement effect. Herein, experiments were conducted to analyze the effects of copper foam on the heat transfer and temperature control performance of PCM under different force field conditions. The results indicated that under positive force fields, incorporating copper foam reduces the PCM melting time by up to 62.5% and extends the effective temperature control time by up to 153.4%. Under negative force fields, the melting enhancement effect of copper foam decreases as the force field intensity increases, and the temperature uniformity and late-stage effective temperature control time of composite phase change materials (CPCMs) slightly decrease compared with that of pure PCM. Notably, the addition of copper foam considerably improves the heat transfer stability of the phase change thermal control unit under complex force fields; the fluctuation amplitudes of the melting time and temperature control duration of CPCMs are reduced by 86.8% and 52.6%, respectively, compared with that of pure PCM. These findings provide valuable theoretical insights for the optimal design of phase change materials in aerospace thermal management systems under complex force field conditions.

Large-scale, long-duration energy storage technologies are vital for achieving the dual-carbon goals. Among them, Liquid Air Energy Storage (LAES) has received significant attention due to its high energy density, geographical flexibility, long service life, and environmental friendliness. As the core cold storage unit in LAES, the thermal performance of the packed bed directly impacts the cycle efficiency and economic viability of the system. Traditional cold storage packed beds use an axial-flow design, where the heat transfer fluid enters from the bottom and exits from the top after exchanging heat with the storage material. This design suffers from high pressure drop, large pump power consumption, and severe velocity fluctuations, limiting its overall performance. To overcome these limitations, a novel design of radial-flow cold packed bed is proposed, in which the cooling fluid enters via a central inlet at the bottom, flows radially through the storage material, and exits centrally after heat exchange. Numerical simulations were conducted to analyze the flow velocity, interstitial convective heat transfer coefficient, pressure drop, and exergy efficiency of the radial-flow packed bed under different working fluid pressures, and to compare these results with those of the axial-flow configuration. Results indicate that under a storage capacity of 150 MWh and a fluid pressure of 0.1 MPa, the radial-flow packed bed experiences a pressure drop of only 2 kPa during charge/discharge, markedly lower than the 82.8 kPa observed in the axial-flow bed. The exergy efficiency of the radial-flow system reaches 87.7%, significantly outperforming the 59.8% efficiency of the axial-flow configuration. When the working pressure increases to 0.8 MPa, the pressure drop during the charge/discharge process decreases significantly in both radial- and axial-flow beds. The influence of pumping power on exergy efficiency becomes negligible, and the axial-flow bed achieves a higher exergy efficiency of 93.1%. Therefore, the radial-flow cold storage packed bed is more suitable for low-pressure charge/discharge operating conditions. This study offers theoretical insights and design references for structural optimization of cold packed beds, highlighting the strong potential of radial-flow designs in practical energy storage applications.

To investigate the energy storage and release characteristics of a closed thermochemical reactor utilizing SrBr₂·6H₂O, a three-dimensional transient coupled model integrating fluid flow, heat transfer, and thermochemical reactions was established. The model was employed to analyze variations in temperature, conversion rate, and heat transfer fluid (HTF) outlet temperature during the energy storage and release processes. The effects of different fin configurations on thermal performance were compared, and the influences of HTF temperature, HTF flow velocity, and water vapor pressure on reactor performance were systematically examined. The results indicate that radial heat transfer within the reactor is constrained by the low thermal conductivity of the thermochemical energy storage material (TCM). Fins accelerate reaction rates and improve the thermal grade of the heated fluid during discharge. Under equivalent surface area conditions, longitudinal fins exhibit superior heat transfer enhancement and energy storage/release performance compared to radial fins. Specifically, the storage and discharge times of the longitudinal fin reactor are reduced by 36.96% and 35.97%, respectively, while those of the radial fin reactor are reduced by 20.74% and 20.07%, respectively, relative to the nonfin reactor. HTF temperature and water vapor pressure exert significant impacts. An increase in HTF temperature promotes the charging process, reducing the charging time by 59.94% and increasing the charging power. However, it inhibits the discharging process, increasing the discharging time by 65.26% and decreasing the discharging power. Conversely, higher water vapor pressure hinders the energy storage process and facilitates energy release, increasing the energy storage time by 40.83% and reducing the energy release time by 84.39%. Although increasing HTF flow velocity enhances heat transfer between TCM and HTF and accelerates the charging and discharging processes, its influence is less pronounced, reducing the charging and discharging times by only 14.14% and 5.91%, respectively. These findings provide valuable guidance for the practical application of closed hydrated salt thermochemical reactors.

Thermal energy storage technology is crucial for the development and utilization of renewable energy. Compared with traditional energy storage methods, thermochemical energy storage offers advantages such as stability and cross-seasonal storage, effectively addressing the mismatch between energy supply and demand in both time and space for solar energy utilization. Among various thermal energy storage technologies, adsorption-type thermochemical energy storage shows significant potential for development. In the field of medium- and low-temperature thermochemical energy storage, zeolite 13X is an economical and safe material. The conventional packed-bed reactor is a simple and reliable structure. In this study, a numerical model was established using Fluent to simulate the output performance of a zeolite-filled thermochemical reactor. The effects of inlet wet air temperature, inlet wet air flow rate, inlet wet air humidity, and initial zeolite adsorption capacity on reactor performance were investigated. The mass transfer process inside the reactor, variations in zeolite adsorption, and changes in reactor output power were analyzed. The sensitivity of reactor output performance to different parameters was identified, providing theoretical guidance for reactor design. The results indicate that the reactor output thermal power is most sensitive to changes in the initial adsorption capacity of zeolite. When the initial adsorption capacity decreases from 0.19 kg/kg to 0.15 kg/kg, the reactor output power increases by 49%. Conversely, it is least sensitive to variations in the inlet wet air flow rate; increasing the flow rate from 80 kg/h to 160 kg/h results in only a 20% increase in thermal power. Increasing the inlet wet air flow rate reduces the reactor outlet temperature, while increasing the inlet wet air temperature and reducing the initial zeolite adsorption capacity can significantly enhance the outlet temperature, which can reach up to 90 ℃.

In recent years, electrochemical energy storage technology has attracted considerable attention for applications in smart grids and new-energy electric vehicles due to its high energy density and excellent sustainability advantages. Among various components, electrode materials play a critical role in determining electrochemical performance. Molybdenum (Mo)-based materials have emerged as a promising class of electrode materials owing to the variable valence states of Mo, tunable crystal structures, and high reversible capacity. Mo-based materials primarily include oxides (e.g., MoO₂ and MoO₃), chalcogenides (e.g., MoS₂, MoSe₂, and MoTe₂), carbides, nitrides, phosphides, transition metal molybdates, and Mo-based composites. However, their sluggish carrier diffusion kinetics and substantial volume expansion during electrochemical reactions often lead to poor cycling stability, which restricts their commercialization as electrode materials. To overcome these challenges, researchers have developed strategies such as micro/nanoscale structural regulation, carbon matrix hybridization, heteroatom doping, and composite integration design to optimize the electrochemical performance of Mo-based materials. Based on current research progress, this review systematically summarizes the synthesis methods, structural characterization, modification strategies, carrier storage mechanisms, and structure-property relationships of various Mo-based electrode materials. Furthermore, perspectives on crystal structure design and future application potential of Mo-based materials are presented, aiming to provide guidance for developing novel, high-performance Mo-based electrode materials and to advance their use in next-generation electrochemical energy storage technologies.

Silicon has attracted considerable attention as one of the most promising anode materials for lithium-ion batteries due to its high theoretical specific capacity, elemental abundance, and environmental friendliness. However, its large-scale application is limited by low conductivity, significant volume expansion, and electrode pulverization. To address these challenges, silicon particles can be reduced to the nanoscale to leverage the size effect; when the particle size is below 150 nm, electrode pulverization during cycling is significantly mitigated, and volume expansion is alleviated. Additionally, volume changes can be constrained and conductivity enhanced by incorporating high-strength materials. The silicon-carbon composite prepared by chemical vapor deposition (CVD) integrates the advantages of both silicon and carbon, enabling in situ confined growth of silicon particles within the porous carbon matrix. Benefiting from the excellent conductivity and mechanical strength of the carbon framework, CVD-derived silicon-carbon composites exhibit outstanding specific capacity and cycling stability as anodes. This unique structural design and performance make them promising candidates for next-generation anode materials in advanced preparation technologies. However, systematic research on CVD silicon-carbon anodes remains insufficient, and a comprehensive framework has yet to be established. In particular, the structure-activity relationships involving deposition kinetics (such as the influence of carbon substrate structure on deposition behavior and the microstructural evolution of silicon) and engineering applications are not fully understood. Based on this context, this paper systematically reviews the research progress on CVD silicon-carbon anode technology and establishes a multi-dimensional analytical framework: ① the co-regulation mechanism of carbon substrate structure and silicon source characteristics on deposition kinetics; ② interface engineering strategies and structural optimization methods for high-energy-density electrodes; and ③ key technical bottlenecks in large-scale preparation. By integrating existing research findings, this review constructs a knowledge system bridging basic research and engineering applications, elucidates core challenges hindering industrialization, and proposes process optimization pathways, providing scientific guidance for the rational design and controlled fabrication of next-generation CVD silicon-carbon anodes.

With the advantages of abundant resources and cost-effectiveness, sodium-ion batteries (SIBs) have emerged as promising energy storage technologies. The development of high-performance anode materials is critical to their commercialization. Among various options, carbon-based materials are regarded as the most promising anodes owing to their stable structures, cost-effectiveness, and high safety. Coal is considered a high-quality carbon source due to its affordability, high carbon yield, and tunable molecular structure. However, the inherent high aromaticity of coal and the complexity of its components result in a highly ordered and uncontrollable evolution of the derived carbon microcrystalline structure. This significantly hinders the design of high-performance coal-based carbon anodes. In this paper, we introduce the structure and properties of coal and its pyrolysis mechanism, aiming to address the critical challenges associated with coal-based anodes for SIBs. We summarize recent technological advancements in preparing anode materials using coal as a carbon source, focusing on microstructural modulation of amorphous carbon. Finally, we discuss future challenges and research directions for coal-based anodes to provide guidance for developing and applying high-performance coal-derived carbon materials.

Developing novel solid-state electrolytes with excellent comprehensive performance is crucial for achieving high safety and high energy density in all-solid-state batteries. Among various electrolyte material systems, halide electrolytes have garnered widespread attention from academia and industry due to their high ionic conductivity, high oxidation potential, good ductility, and strong compatibility with cathode materials. While lithium-ion halide electrolytes have been extensively studied, sodium-ion halide electrolytes are still in their early developmental stages and face several challenges. Sodium halides exhibit differences in crystal structure, ion transport mechanisms, and electrochemical performance. A systematic understanding of their structure-property relationships is essential for guiding the development of high-performance electrolytes. This review summarizes recent advancements in sodium halide solid-state electrolytes, with particular emphasis on the influence of different crystal structures on sodium-ion transport mechanisms and the roles of defects, structural disorder, and polyanionic frameworks in enhancing ionic conductivity. The effects of various synthesis methods on the microstructure of these materials are also discussed. Furthermore, the interfacial stability, electrochemical stability window, and cycling performance of sodium halide electrolytes in all-solid-state batteries are systematically evaluated. Finally, this review outlines future development directions, aiming to advance sodium-ion halide electrolytes and promote next-generation energy storage technologies.

Thermal runaway propagation (TRP) within a battery module, triggered by the thermal runaway of individual cells, is a significant cause of severe accidents in battery systems. To investigate the TRP behavior of real battery modules and their associated transportation risks in containers, this study focuses on 1P31S battery modules and conducts full-scale experiments simulating packaging transportation scenarios. The effect of the state of charge (SOC) on the TRP process is emphasized. The results indicate that simultaneously triggering two cells through heating does not initiate TRP in modules with 30% SOC but can cause thermal runaway in 9—10 cells in modules with 100% SOC (where four triggered cells are fully charged, and the remaining cells are at 30% SOC). The TRP speed ranges from 0.0315 to 0.0606 mm/s and leads to the melting of the packaging expanded polyethylene (EPE) foam and the plastic top cover of the module. As SOC increases, the maximum temperatures of the cells and packaging box, TRP speed, and heat transfer all increase. The maximum temperatures measured in the triggered cells and adjacent cells in the 100% SOC module were 495.2 ℃ and 649.5 ℃, respectively, significantly higher than 237.2 ℃ and 131.9 ℃ in the 30% SOC module. Furthermore, the substantial heat generated by TRP in the 100% SOC module caused the maximum temperature at the top center of the packaging box to reach 57.1 ℃, nearly double that of the 30% SOC module. Cells at 30% SOC did not fail when the heat received from the previous cell through thermal conduction was no more than 117.1 kJ but experienced thermal runaway when the received heat exceeded 140.8 kJ. In contrast, only 61.2 kJ of heat was required to trigger TRP among cells at 100% SOC. This study provides a reference for battery module design and the safety of battery module transportation in containers.

With the accelerated transformation of the global energy structure towards renewable energy, the efficient and stable operation of photovoltaic energy storage systems, as a key carrier of clean energy, is of vital importance. This article focuses on the intelligent operation and maintenance of photovoltaic energy storage systems, and delves deeply into its significance, technical support, and optimization strategies. This research achievement provides theoretical basis and practical guidance for promoting the large-scale application and sustainable development of photovoltaic energy storage systems, and helps the energy industry achieve the goal of green and low-carbon transformation.

To address the safety and stability issues caused by power fluctuations in renewable energy generation and load in regional distribution networks, while considering the coupling of high- and low-frequency fluctuations on both the generation and load sides, this study proposes a two-stage hybrid energy storage configuration method based on empirical mode decomposition and multi-objective optimization. The framework aims to establish a coordinated optimization mechanism that integrates high-/low-frequency fluctuation mitigation with economic operation and system stability. In the first-stage model, a moving average filter is used to extract the power fluctuations that need to be mitigated by the hybrid energy storage system. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is then applied to separate the high- and low-frequency components of the minute-level grid-connected power fluctuations. By considering the comprehensive cost of supercapacitors (SCs) and minute-level fluctuations, the optimal noise standard deviation and the mode boundary number between high- and low-frequency components are determined to achieve an optimal SC configuration for mitigating high-frequency minute-level fluctuations in photovoltaic generation. In the second-stage model, a multi-objective optimization based on an improved multi-objective particle swarm optimization algorithm is conducted to optimize the capacity configuration of the hybrid energy storage system, with the objectives of minimizing the comprehensive system cost, power loss, and voltage fluctuations. This approach provides a configuration scheme that simultaneously addresses minute-level and hourly-level fluctuations. The proposed method is validated using the IEEE 33-node system. The results demonstrate that, compared to traditional methods, this approach effectively considers the coupling of high- and low-frequency fluctuations at individual nodes and across the system. Specifically, it reduces minute-level high-frequency grid-connected fluctuations by 91.1%, the average voltage deviation by 10.1%, the maximum voltage deviation by 55.4%, system power loss by 55.9%, and system purchased electricity by 10.88%.

Nowadays, the environmental pollution and energy shortage are becoming increasingly serious. New energy wind power generation can effectively solve related problems. However, due to the wind speed fluctuations, the power generation system faces the challenges of power fluctuations and frequency instability. Flywheel energy storage control technology can achieve the conversion of kinetic energy and electric energy using high-speed rotating bodies, and has the advantages of high-frequency charge/discharge capability, millisecond-level response and extended service life. Flywheel energy storage control technology can be used to suppress power fluctuations in new energy wind power generation systems and maintain the stability of the power grid. It can also improve the frequency response characteristics of the system, enhance the voltage quality at the grid connection point, and suppress voltage flicker and harmonics, thus providing key technological support for the secure and stable operation of high-proportion new energy power systems.

To meet the practical demand for safe and stable operation of new power systems, it is important to study the control strategy and stability mechanism of grid-forming (GFM) energy storage converters. This study establishes a small-signal impedance model of a GFM energy storage system connected to an AC power grid based on droop control. The impedance model expression in complex vector form is used to simplify the modeling process, and the dynamic characteristics of the active power loop are analyzed. The impedance model is verified through frequency sweep and time-domain simulations. Subsequently, the small-signal stability of the GFM energy storage system connected to the grid is analyzed using the generalized Nyquist criterion, with theoretical results consistent with time-domain simulation analysis. The results indicate that as the active power droop coefficient and short-circuit ratio increase, system stability deteriorates. This finding is further validated on a physical experimental platform.

The rapid development of large-scale data centers and network cloud technology has led to continuous technological upgrades in data center related industries, while also bringing about increasing energy demand. Traditional data centers are equipped with high-power energy transmission devices to meet their own power needs. With the continuous optimization and upgrading of energy storage systems, new control methods have been provided for energy management in large-scale data centers. In this regard, this study reviews the operational characteristics and categories of current data center energy storage system architectures, including central structures and distributed energy storage architectures, and summarizes in detail the advantages and limitations of different architectures. In addition, the study explored the application of energy storage systems in load shedding safety control and new energy integration safety control, as well as the strategies adopted to ensure network security. Through the dynamic application of energy storage systems, data centers can more effectively manage energy, reduce peak electricity consumption, integrate new energy, and thereby reduce costs and environmental impact.

Integrated energy systems (IESs) offer high energy efficiency and low emissions. To address challenges such as mismatches between the heating and user sides and excessive waste heat under traditional operation strategies, this paper proposes an IES incorporating an electric-thermal hybrid energy storage system and introduces a time-sequential flexible operation strategy. By considering equipment operating characteristics and using the energy quality coefficient method, a three-objective optimization is performed. The sustainability of the IES is further evaluated through emergy analysis. The results show that compared with the conventional strategy, the time-sequential flexible operation strategy improves the comprehensive energy utilization rate by 5% and reduces operating costs by 626,544 yuan. It also achieves the highest sustainability development index (4.18) in the emergy analysis. The gas boiler maintains a relatively large capacity across different strategies, serving as the primary heating unit. Additionally, natural gas prices impact sustainability by approximately 36%, while electricity prices have a more substantial effect, reaching up to 72.33%.

The widespread application of lithium-ion batteries in electric vehicles is limited by performance constraints. To address the shortcomings of single-material systems, this study proposes a dual-system battery pack design integrating ternary lithium (NCM) and lithium iron phosphate (LFP) batteries, which has been successfully applied in practical vehicle systems. To ensure thermal safety, we investigate the thermal characteristics of a dual-system battery pack composed of 18650 NCM and LFP cells. A three-dimensional electrochemical–thermal coupling model is developed for the dual-system battery pack. Three air-cooling configurations (Z-type, U-type, and T-type) are designed, and experiments are conducted to analyze heat generation differences between the two cell types and to validate the model. Thermal dissipation performance under natural and forced air cooling is compared at different cell positions, leading to an optimized cell arrangement. The results show that the optimized layout effectively reduces the maximum temperature difference in the battery pack, improving temperature uniformity. At an inlet wind speed of 8 m/s, the U-type configuration reduces maximum temperature, average temperature, and maximum temperature difference by 7.68%, 6.86%, and 21.2%, respectively, compared to the Z-type configuration. Despite exhibiting a higher inlet-outlet pressure differential (78.21 Pa vs. 50.59 Pa for the Z-type), the U-type configuration achieves enhanced thermal uniformity through improved airflow distribution, effectively balancing cooling efficiency and pressure drop. Orthogonal experiments further examine the impact of intra-group spacing in the U-type configuration. Kruskal-Wallis test results indicate that within the range of 1.5—4.5 mm, intra-group spacing has minimal influence on temperature, while the cooling configuration and inlet air velocity predominantly determine thermal management performance. This research provides critical insights into optimizing thermal safety in hybrid battery systems.

To reduce the charging and discharging costs of gravity energy storage systems, this paper proposes a dynamic adjustment method and an initial sequence recombination method based on a linear machine gravity energy storage system (LMGESS). First, the structure and operational mechanism of the LMGESS are described. Then, considering the relationship between energy storage demand and photovoltaic power generation capacity, as well as the relationship between rated charging power and photovoltaic output power, the photovoltaic output is categorized into three cases. Subsequently, a comparative analysis of the charging cost per unit capacity is conducted between the dynamic adjustment method and the traditional rated power charging method in these cases. Finally, taking into account the state transition characteristics of the LMGESS, the initial sequence recombination method was introduced to optimize its participation in automatic generation control (AGC) auxiliary services. The results show that the dynamic adjustment method achieves a lower charging cost per unit capacity compared to the rated power method during LMGESS charging. Even when the charging costs per unit capacity of both methods are the same, the energy storage capacity realized by the dynamic adjustment method is significantly higher. Moreover, the initial sequence recombination method substantially reduces the discharging cost of the LMGESS. After optimization, the discharging cost of the LMGESS participating in AGC is reduced by 31.3%, and the minimum discharging cost under different initial heavy object sequences is 57.5% lower than the maximum discharging cost.

The heat and power cogeneration system based on micro compressed air energy storage (micro CAES) offers a simple structure and operational flexibility. Owing to the constantly changing energy demands of small-scale electricity and heat users, such systems frequently operate under variable loads. However, the dynamic characteristics of these systems under continuous variable loads have not been sufficiently investigated. This paper establishes a comprehensive dynamic and control model for the micro CAES cogeneration system, considering variable operating conditions and the effects of volume inertia. Based on this model, the continuous variable load regulation characteristics during energy storage and release processes, as well as the charge-discharge cycle performance under different load rates, are analyzed. The results show that under continuous variable loads, the actual power output of the compressor and expander units closely follows the set values, with maximum power deviation remaining below 9%. During energy storage, the system's exergy efficiency improvement attributed to the heat storage and heat exchanger increases as the load rate decreases. Conversely, during energy release, lower load rates lead to reduced isentropic efficiency at each stage and exacerbate the negative effects of the throttling valve on the exergy efficiency of the energy release process. The system achieves a maximum round-trip efficiency of 0.61 and an energy efficiency of 0.82. While decreasing the load rate reduces the round-trip and energy efficiencies of the charge-discharge cycle, it results in a higher heat-to-power ratio of the supplied energy. This study provides a theoretical reference for the application of micro CAES systems in distributed energy systems.

Aiming at the problem of variable operating condition adjustment of the air turbine in the compressed air energy storage system, this paper analyzes the variable operating condition of the air turbine using the "throttling + air supplement" distribution mode, and compares the two strategies of the split range control and the air supplement pressure control of the turbine load regulation. Firstly, a dynamic simulation model of a 10MW/110MWh compressed air energy storage system under all working conditions was established. Through multidisciplinary simulation modeling technology, a unified platform was realized to solve the dynamic characteristics of the thermal system and the control system in real time, and the dynamic characteristics of the turbine under varying working conditions were obtained, and the adjustment effects of different turbine load control strategies were further verified. The simulation results show that: considering the factors of turbine load stability output and system gas consumption rate in the full sliding pressure range, the split range control strategy has higher performance. When the throttle control valve is not fully open, the throttle valve opening should be further increased to the maximum. Under the rated intake parameters, the split range control strategy can reduce the gas consumption rate by 0.35%.

Energy is a fundamental element of human production and life, serving as the foundation for survival and social development. In future power systems, thermal power plants will primarily serve as auxiliary peak regulation sources, providing greater flexibility to accommodate renewable energy integration. This requires combined heating and power units (CHP) to enhance their operational flexibility and avoid frequent start-stop cycles during peak regulation. In this study, a CHP unit is coupled with a compressed carbon dioxide energy storage system (CCES) and a steam ejector (SE), and three improvement schemes are proposed. The technical potential of the CHP-SE-CCES coupling system (CSC) is investigated through a thermodynamic model, and its operational feasibility is analyzed. The advantages of the different schemes relative to the basic system are evaluated, and the influence of key parameters on the performance of the CCES and the CSC is discussed. The results indicate that the addition of an SE significantly improves the operational flexibility of the coupled system. Underrated thermal load conditions, schemes 2 and 3 can reduce the electric load by 68.56 MW and 50.56 MW, respectively, thus expanding the feasible operating range and enhancing thermoelectric decoupling capability. Increasing the hot water tank temperature improves the system power efficiency from 48.84% to 66.84%, the energy storage density from 1.07 kWh/m³ to 1.47 kWh/m³, and the power change ratio from 55.85% to 57.82%. Considering overall energy consumption, scheme 2 emerges as the optimal approach. The proposed method promotes flexible transformation of CHP units and provides a technical reference for integrating thermoelectric units with CCES technology.

Lithium-ion batteries (LIBs) are widely used while sensitive to temperature. There is a risk of thermal runaway (TR) during practical work. Especially for large-capacity batteries under high-rate charge/discharge conditions, the risk of TR can be increased. A TR model is established to study the battery TR process caused by pole overheating. The heat propagation and TR characteristics of the LIBs were analyzed. The results show that the pole overheating caused by loose connecting plates can lead to serious heat accumulation problems under the battery tab. With the increased heating power, the TR trigger time is greatly advanced, and the peak temperature is increased. Compared to the bottom and front heating conditions, the temperature rise during the TR caused by pole heating is reduced by 17.2% and 10.9%, respectively, and the battery will reach a higher peak temperature in less time. In addition, it was found that the heat propagation characteristics of the battery under pole heating are similar to the overheating of the tab region caused by the high-rate charge/discharge of the LIBs. According to it, a liquid cooling plate with oblique channels was designed, and the heat dissipation effect of this cooling plate was analyzed. The results demonstrated that the oblique channel cooling plate can effectively suppress the TR of the LIBs and improve the temperature uniformity of the battery. Compared with straight channel cooling plate, the standard deviation of the battery temperature under oblique channel cooling plate can be further reduced by 18.9%. This work provides a reference for the LIBs risk assessment and the structural design of liquid cooling plates.

With the continuous acceleration of the global energy transition, power storage has increasingly become a core sector of the energy industry. Lithium-ion batteries, as crucial components of electrochemical energy storage systems, have attracted significant attention from both the market and researchers. In practical applications, battery cycle life and long-term safety are key technical indicators for evaluating energy storage batteries and are closely interrelated. This study focuses on high-capacity lithium iron phosphate batteries and summarizes the testing protocols for high-temperature accelerated aging and the safety characteristics of batteries after cycling. The results show that within the first 200 cycles, the high-temperature accelerated aging effect cannot be strictly described as a fixed multiple of room-temperature cycling aging. However, as the number of cycles increases, the ratio of capacity degradation rates under 45 ℃ and 25 ℃ cycling approaches 2 and gradually stabilizes. These findings provide an important basis for predicting the service life of lithium-ion batteries. Furthermore, it was observed that the thermal runaway triggering temperature decreases as the state of health (SOH) declines. Based on the current results, the ratio of thermal runaway temperature to SOH can be maintained between 130 and 145, offering a theoretical foundation and data support for life prediction, real-time monitoring, and safety warnings in practical applications.

This paper proposes a collaborative monitoring and evaluation framework for the operation status of lithium-ion battery energy storage power plants, which integrates machine learning and deep learning, to address the difficulties in multi-source data fusion and the inability of traditional methods to effectively capture nonlinear degradation features. A multi-level feature extraction and fusion mechanism has been systematically designed to solve the problems of temporal and spatial misalignment of multimodal data such as voltage current temperature, and insufficient extraction of implicit degradation features, providing a new solution for the monitoring and evaluation of the operation status of lithium-ion energy storage power plants.

Based on a production line big data platform, rapid sorting of outgoing batteries using capacity data can improve the consistency of battery packs and extend their service life; however, this method alone does not ensure dynamic consistency. In this study, a novel approach is proposed to predict the internal resistance of batteries during the capacity grading stage using production line big data, followed by rapid sorting that combines predicted internal resistance with capacity data. Specifically, production line data are collected, and relevant features are screened using the Pearson correlation coefficient (PCC). A neural network model based on a multilayer perceptron (MLP) is constructed to predict battery internal resistance. The predicted internal resistance values are then integrated with capacity data, and the Fuzzy C-Means (FCM) clustering algorithm is employed to classify the batteries into four grades. The effectiveness of the proposed sorting method is evaluated using charge-discharge voltage curve characteristics as assessment criteria and compared with the traditional capacity-based sorting method. The results demonstrate that the mean absolute percentage error (MAPE) of internal resistance prediction is 1.2%, and the overall optimization rate of the sorting process reaches 14.9%, representing a significant improvement over traditional capacity sorting. This study offers a new method for the rapid sorting of production line batteries, supporting the enhancement of battery pack consistency and performance.

In energy storage power stations, vertically arranged battery modules are commonly used. When thermal runaway gas produced by lower-layer batteries ignites, it can induce fire propagation to the upper-layer batteries. To investigate the fire propagation characteristics and energy transfer mechanisms during this triggering process, this study employed 100 Ah lithium iron phosphate (LiFePO₄) batteries as the research object. Three sets of fire propagation experiments were designed using double-layer battery modules with one, two, and three batteries per layer. The bottom batteries were heated to induce venting, and the thermal runaway gas was actively ignited. Experimental phenomena and temperature variations were recorded, and the temperature rise rates and stages were analyzed. Additionally, the cumulative energy transferred from each bottom battery to the top battery during fire propagation was quantitatively examined, and heat transfer via different paths was decoupled. Results indicate that three bottom batteries can simultaneously trigger thermal runaway in the top batteries. The maximum temperature rise of the top batteries was 115.9℃ (22.1%) higher than that of the bottom batteries, and the maximum temperature rise rate was 6.5 ℃/s (86.7%) higher. Prior to thermal runaway, the top batteries exhibited three temperature rise stages, with the average temperature rise rate during the flame jet stage approximately double that of the flame baking stage. During fire propagation, the cumulative energy transferred from the three bottom batteries to the top battery was 249.1 kJ, 334.3 kJ, and 379.7 kJ, respectively. Heat transfer through the bottom surface accounted for 47.5%, while transfer through the side surface accounted for 52.5%. This study provides important guidance and scientific support for the safety design of energy storage battery systems and fire propagation suppression.

The joint evaluation of state of charge (SOC) and state of health (SOH) of lithium batteries is a prerequisite for ensuring stable and efficient operation of batteries. This study provides a review of current related joint evaluation methods. Firstly, the difficulties faced in evaluating the SOC and SOH of lithium batteries were analyzed in sequence, including initial value dependence, linear characteristics, and physical field coupling issues; Then, a detailed analysis was conducted on the emerging joint evaluation methods for SOC and SOH of lithium batteries, which are supported by big data and deep learning technologies. The focus was on exploring the evaluation emphasis and operational logic under different data-driven models. Finally, the development process of related technologies in recent years was summarized, hoping to provide some reference for the development of energy storage industry and research on lithium battery evaluation technology.

Mining lithium-ion batteries face severe safety and reliability challenges under extreme working conditions in coal mines. Although high-precision physical modeling is a potential solution, traditional experimental methods are limited by high cost and risk, while mechanism-based models struggle to adapt to actual complex working conditions. To address this, a collaborative estimation framework based on digital twins is proposed. Taking a 228 Ah mining lithium-ion battery as the object, a battery characteristic characterization system considering multi-factor coupling of temperature, multiplicity, state of charge (SOC), and aging is established by improving the first-order RC equivalent circuit model. Based on the Simulink/Simscape multiphysics field co-simulation platform, a digital twin system integrating electrochemical, thermodynamic, and state estimation algorithms is constructed. The convective heat transfer, unscented Kalman filter (UKF), and extended Kalman filter (EKF) modules are integrated to perform comparative analyses of SOC and temperature joint estimation. The experimental results of UKF show that the maximum permissible errors (MPE) of SOC estimation under BBDST conditions are 0.3937%, 0.4347%, and 0.5067% at 25 ℃, 45 ℃, and 60 ℃, respectively, while the MPE of temperature estimation are 0.74 ℃, 1 ℃, and 0.9613 ℃. Under DST conditions, the MPE of SOC estimation are 0.1829%, 0.0034%, and 0.0035% at 25 ℃, 45 ℃, and 60 ℃, respectively, and the MPE of temperature estimation are 0.6 ℃, 0.9992 ℃, and 0.9740 ℃. The results confirm that the model possesses excellent temperature adaptability and generalization capability, serving as a reliable digital twin verification platform for next-generation intelligent battery management system (BMS) development. This provides significant theoretical value and broad engineering application prospects.

During the aging process of power batteries, characteristic changes such as capacity degradation, increased internal resistance, and decreased consistency occur. Although these changes present significant challenges to the safety of retired battery (RB) cascade utilization, they also form an important basis for battery state assessment and screening. This paper first analyzes the role of domestic and international policies and regulations in promoting and regulating the development of cascade utilization and examines safety hazards using engineering examples. The requirements for the extraction and processing methods of characteristic indicators (CI) in terms of efficiency and accuracy are proposed. Focusing on the "model-testing-algorithm" framework, the extraction and processing of CI are innovatively divided into two major categories: "emphasizing efficiency" and "emphasizing accuracy." The paper discusses how testing methods and intelligent algorithms can improve efficiency in CI extraction and processing, and it introduces how models and algorithms can enhance accuracy in multi-dimensional CI extraction and phased application. Finally, in combination with policy document requirements, various methods are summarized and compared to provide a theoretical basis for the forthcoming "retired battery wave" expected around 2030.

With the widespread application of solar energy storage equipment, real-time monitoring of its operating status and problem detection have become crucial. This paper presents a method for detecting issues in solar energy storage equipment, which combines the relevant technologies and theoretical foundations of deep learning and image recognition. By collecting image data from the solar energy storage equipment, deep learning algorithms are utilized to process and analyze the images, achieving accurate identification and localization of potential problems. This method has a high detection accuracy and efficiency, providing strong support for the maintenance and management of solar energy storage equipment.

Owing to their high energy density and long life cycle, lithium batteries have been widely used in electric vehicles, energy storage systems, and portable devices. However, capacity regeneration is an inevitable phenomenon during battery use, which influences the accuracy of battery health assessment. To reduce the influence of capacity regeneration on assessment accuracy, a new method combining variational mode decomposition and a generative adversarial network is proposed. First, variational mode decomposition is applied to decompose the iso-pressure-drop discharge-time characteristic, which reflects the capacity regeneration phenomenon during lithium battery discharge. The main degradation-trend component and local fluctuation component are then separated using Pearson correlation coefficient analysis, enabling a better characterization of battery health. The main degradation-trend component represents the overall degradation of the battery, while the local fluctuation component captures the variations caused by capacity regeneration. Second, to further enhance the features related to local wave components and the capacity regeneration phenomenon, a Fourier transform is used to extract the mid- and low-frequency components that reflect capacity regeneration. For components in these frequency bands, a generative adversarial network is employed to generate additional data. These generated data are then combined with the multifeature set obtained from variational mode decomposition to form a new, enriched multifeature set. Next, a support vector machine algorithm is used to train this new multifeature set to achieve accurate estimation of the battery's state of health. Finally, validation experiments are conducted using NASA and CALCE datasets. The experimental results show that, compared with traditional methods, the proposed method keeps the root-mean-square error within 4.5%, effectively reducing the influence of capacity regeneration on battery health assessment accuracy.

In recent years, sodium-ion batteries (SIBs) have emerged as promising alternatives to lithium-ion batteries, owing to their low material cost, absence of resource constraints, and broad operational temperature range. However, research on the fire safety and thermal characteristics of SIBs lags behind their commercialization. In this study, a 180 Ah square aluminum-shell SIB was selected as the research subject. Using an adiabatic accelerating calorimeter and a closed pressure vessel, thermal runaway experiments under adiabatic, overheating, and 0.5C overcharge conditions were conducted to investigate temperature, voltage, and gas generation behaviors under electro-thermal abuse. The results show that (1) under adiabatic conditions, the self-heating onset temperature (T_onset) was 115.9 ℃, the thermal runaway trigger temperature (T_tr) was 201.3 ℃, and the maximum temperature (T_max) reached 444.8 ℃. The maximum temperature rise rate during thermal runaway was 2353 ℃/min, and the mass loss was 22.8%. (2) under overheating conditions, thermal runaway started at approximately 171.8 ℃, with a T_max of 484.5 ℃. The total volume of mixed gas released after thermal runaway was 123.3 L, mainly consisting of hydrogen (35.4%), carbon dioxide (31.0%), carbon monoxide (19.2%), and ethylene (4.3%), with a mass loss of 25.0%. (3) under 0.5C overcharge conditions, thermal runaway occurred when the state of charge reached approximately 190.8%. The T_max was 573.6 ℃, and the total gas released was 200.3 L, primarily containing carbon dioxide (29.1%), hydrogen (28.1%), carbon monoxide (20.8%), and ethylene (14.4%), with a mass loss of 48.0%. These findings provide a reference for the safety design and risk assessment of high-capacity SIBs.

Smart grid is an important upgrade of modern energy industry technology, which can achieve intelligent control of the power system by integrating modern electronic information technology, communication technology, and automation control technology. With the development of renewable energy and the application of distributed energy storage systems, the combination of smart grids and distributed energy storage systems has become the key to improving the utilization of modern power grid resources. This research discusses the coordinated control strategy between the real-time information monitoring technology in the smart grid and the distributed energy storage system in detail. First, it describes the information architecture and power consumption information monitoring process of the modern smart grid, and then proposes the coordinated control strategy scheme between the distributed energy storage system and the smart grid, including adaptive control scheme, machine learning prediction model, advanced measurement system and blockchain edge computing technology. Finally, it summarizes the advantages and future development trends of the coordinated control between the smart grid and the distributed energy storage system.

Liquid immersion cooling battery energy storage systems (BESS) have garnered significant attention owing to their superior heat transfer performance and high battery consistency. However, comprehensive studies on their economic feasibility remain scarce. This paper presents a technical and economic analysis of immersion-cooled BESS. The study begins with a technical comparison, detailing key features, system configurations, and components of pack immersion, cluster immersion, BESS cabinets, and BESS containers. Subsequently, based on the overall system structures, main component costs, heat generation calculation models, and economic evaluation frameworks, the economic performance of four immersion energy storage configurations is assessed. Furthermore, the impact of battery lifespan extension under immersion thermal management on overall system economics is examined, alongside an analysis of the influence of immersion fluid costs and structural parameters. The results indicate that, under certain conditions, economic metrics such as payback time (PBT), net present value (NPV), and internal rate of return (IRR) for immersion-cooled systems fall within a favorable range. For example, the pack-immersed battery container system exhibits a static PBT of 4.65 years, a dynamic PBT of 5.81 years, an NPV of CNY 4.3409 million, and an IRR of 18.14%, underscoring the economic advantages of immersion-cooled BESS.

With the ongoing transformation of the global energy structure and the advancement of "dual-carbon" goals, compressed air energy storage (CAES), as a clean, efficient, and large-scale energy storage technology, has become a crucial support for facilitating grid integration of renewable energy and establishing new power systems, attracting widespread attention. This paper reviews the development background, demand, historical evolution, and construction status of CAES technology by analyzing recent related studies. The working principle, technical classifications, and gas storage methods of CAES are thoroughly analyzed. Furthermore, its multi-scenario applications on the power generation side, grid side, and user side are summarized. The challenges and bottlenecks faced by CAES technology are also discussed. The analysis indicates that CAES plays a vital role in all three aspects—power generation, grid operation, and end-user applications—yet it faces challenges related to efficiency, cost, environmental impact, and market-based revenue models. Through technological innovations, such as the development of high-efficiency core equipment and the implementation of intelligent scheduling systems, CAES performance can be significantly improved. Model optimization, including the integration of virtual power plants and the promotion of shared energy storage models, can further expand its applications. Additionally, ecological collaboration and international cooperation, involving the establishment of industry standards and the promotion of technology exchanges, can enhance the global influence of CAES. These measures will enable CAES technology to play a greater role in future energy transitions. Future development should focus on the localization of high-temperature thermal storage materials, multi-technology integration, enhancement of policy support, and internationalization of technical standards. These advancements will support the large-scale development of CAES and the decarbonization of the energy industry, contributing to energy security and the realization of the "dual-carbon" goal.

New quality productivity's driving force lies in comprehensive improvement of workers' quality, in turn raising requirements for workers' knowledge reserves and skill levels. The new energy materials and devices specialty, established in response to China's "Carbon Peak and Carbon Neutrality" strategy and the needs of emerging engineering disciplines such as new energy, new materials, high-end equipment, and sustainable development, crucially supports the national industrial structure's adjustment. Despite new quality productivity's rapidly reshaping the energy industry ecosystem, however, this specialty's talent cultivation faces challenges such as lagging knowledge iteration, insufficient innovation capabilities, and weak industrial adaptability. The New Energy Materials and Devices major at Suzhou University of Science and Technology combines characteristics of materials-related disciplines with the fundamental tasks of cultivating students' moral character and optimizing the first classroom through curriculum reform focused on cultivating students' abilities in academic innovation, engineering practice, and human-machine collaboration to reconstruct the second classroom. Additionally, a talent cultivation system of "one center, two classrooms, and four integrations" has been established by integrating science and education to stimulate innovative driving forces, that is, integrating: industry and education to create a collaborative education platform; specialized innovation and entrepreneurship to enhance innovation and entrepreneurship capabilities; and varied disciplines to broaden academic horizons. This system provides both a theoretical framework and a practical paradigm for cultivating innovative talents in the new energy materials and devices specialty, offering significant reference value to promote deep integration of chains in education, talent, and industry.