Thermal safety boundary of lithium-ion battery at different state of charge

Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charges(SOCs)has significant implications for reinforcing the thermal safety design of the lithium-ion battery module.This study first investigates the thermal safety boundary(TSB)correspondence at the cells and modules level under the guidance of a newly proposed concept,safe electric quantity boundary(SEQB).A reasonable thermal runaway propagation(TRP)judgment indicator,peak heat transfer power(PHTP),is proposed to predict whether TRP occurs.Moreover,a validated 3D model is used to quantitatively clarify the TSB at different SOCs from the perspective of PHTP,TR trigger temperature,SOC,and the full cycle life.Besides,three different TRP transfer modes are discovered.The interconversion relationship of three different TRP modes is investigated from the perspective of PHTP.This paper explores the TSB of LIBs under different SOCs at both cell and module levels for the first time,which has great significance in guiding the thermal safety design of battery systems.

Adaptive battery thermal management systems in unsteady thermal application contexts

With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial perspectives.Temperature,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is crucial.Since the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management system.Conventional battery thermal management systems have basic temperature control capabilities for most conventional application scenarios.However,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating conditions.In this context,this paper presents the latest advances and representative research related to battery thermal management system.Firstly,starting from battery thermal profile,the mechanism of battery heat generation is discussed in detail.Secondly,the static characteristics of the traditional battery thermal management system are summarized.Then,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research cases.Finally,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.

Explainable Neural Network for Sensitivity Analysis of Lithium-ion Battery Smart Production

Battery production is crucial for determining the quality of electrode,which in turn affects the manufactured battery performance.As battery production is complicated with strongly coupled intermediate and control parameters,an efficient solution that can perform a reliable sensitivity analysis of the production terms of interest and forecast key battery properties in the early production phase is urgently required.This paper performs detailed sensitivity analysis of key production terms on determining the properties of manufactured battery electrode via advanced data-driven modelling.To be specific,an explainable neural network named generalized additive model with structured interaction(GAM-SI)is designed to predict two key battery properties,including electrode mass loading and porosity,while the effects of four early production terms on manufactured batteries are explained and analysed.The experimental results reveal that the proposed method is able to accurately predict battery electrode properties in the mixing and coating stages.In addition,the importance ratio ranking,global interpretation and local interpretation of both the main effects and pairwise interactions can be effectively visualized by the designed neural network.Due to the merits of interpretability,the proposed GAM-SI can help engineers gain important insights for understanding complicated production behavior,further benefitting smart battery production.

Small but mighty:Empowering sodium/potassium-ion battery performance with S-doped SnO_(2) quantum dots embedded in N,S codoped carbon fiber network

SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.

High-performance magnesium/sodium hybrid ion battery based on sodium vanadate oxide for reversible storage of Na^(+)and Mg^(2+)

Magnesium ion batteries(MIBs)are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation.Magnesium-sodium hybrid ion batteries(MSHBs)are an effective way to address these problems.Here,we report a new type of MSHBs that use layered sodium vanadate((Na,Mn)V_(8)O_(20)·5H_(2)O,Mn-NVO)cathodes coupled with an organic 3,4,9,10-perylenetetracarboxylic diimide(PTCDI)anode in Mg^(2+)/Na^(+)hybrid electrolytes.During electrochemical cycling,Mg^(2+)and Na^(+)co-participate in the cathode reactions,and the introduction of Na^(+)promotes the structural stability of the Mn-NVO cathode,as cleared by several ex-situ characterizations.Consequently,the Mn-NVO cathode presents great specific capacity(249.9 mA h g^(−1)at 300 mA g^(−1))and cycling(1500 cycles at 1500 mA g^(−1))in the Mg^(2+)/Na^(+)hybrid electrolytes.Besides,full battery displays long lifespan with 10,000 cycles at 1000 mA g^(−1).The rate performance and cycling stability of MSHBs have been improved by an economical and scalable method,and the mechanism for these improvements is discussed.

Bilevel Optimal Infrastructure Planning Method for the Inland Battery Swapping Stations and Battery-Powered Ships

Green shipping and electrification have been the main topics in the shipping industry.In this process,the pure battery-powered ship is developed,which is zero-emission and well-suited for inland shipping.Currently,battery swapping stations and ships are being explored since battery charging ships may not be feasible for inland long-distance trips.However,improper infrastructure planning for battery swapping stations and ships will increase costs and decrease operation efficiency.Therefore,a bilevel optimal infrastructure planning method is proposed in this paper for battery swapping stations and ships.First,the energy consumption model for the battery swapping ship is established considering the influence of the sailing environment.Second,a bilevel optimization model is proposed to minimize the total cost.Specifically,the battery swapping station(BSS)location problem is investigated at the upper level.The optimization of battery size in each battery swapping station and ship and battery swapping scheme are studied at the lower level based on speed and energy optimization.Finally,the bilevel self-adaptive differential evolution algorithm(BlSaDE)is proposed to solve this problem.The simulation results show that total cost could be reduced by 5.9%compared to the original results,and the effectiveness of the proposed method is confirmed.

An aqueous BiI_(3)-Zn battery with dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox

The development of aqueous battery with dual mechanisms is now arousing more and more interest.The dual mechanisms of Zn^(2+)(de)intercalation and I^(-)/I_(2)redox bring unexpected effects.Herein,differing from previous studies using Zn I_(2)additive,this work designs an aqueous Bi I_(3)-Zn battery with selfsupplied I^(-).Ex situ tests reveal the conversion of Bi I_(3)into Bi(discharge)and Bi OI(charge)at the 1st cycle and the dissolved I^(-)in electrolyte.The active I^(-)species enhances the specific capacity and discharge medium voltage of electrode as well as improves the generation of Zn dendrite and by-product.Furthermore,the porous hard carbon is introduced to enhance the electronic/ionic conductivity and adsorb iodine species,proven by experimental and theoretical studies.Accordingly,the well-designed Bi I_(3)-Zn battery delivers a high reversible capacity of 182 m A h g^(-1)at 0.2 A g^(-1),an excellent rate capability with 88 m A h g^(-1)at 10 A g^(-1),and an impressive cyclability with 63%capacity retention over 20 K cycles at 10 A g^(-1).An excellent electrochemical performance is obtained even at a high mass loading of 6 mg cm^(-2).Moreover,a flexible quasi-solid-state Bi I_(3)-Zn battery exhibits satisfactory battery performances.This work provides a new idea for designing high-performance aqueous battery with dual mechanisms.

Enhancing I^(0)/I^(-)Conversion Efficiency by Starch Confinement in Zinc-lodine Battery

The redox couple of I^(0)/I^(-)in aqueous rechargeable iodine–zinc(I^(2)-Zn)batteries is a promising energy storage resource since it is safe and cost-effective,and provides steady output voltage.However,the cycle life and efficiency of these batteries remain unsatisfactory due to the uncontrolled shuttling of polyiodide(I_(3)^(-)and I_(5)^(-))and side reactions on the Zn anode.Starch is a very low-cost and widely sourced food used daily around the world.“Starch turns blue when it encounters iodine”is a classic chemical reaction,which results from the unique structure of the helix starch molecule–iodine complex.Inspired by this,we employ starch to confine the shuttling of polyiodide,and thus,the I^(0)/I^(-)conversion efficiency of an I^(2)-Zn battery is clearly enhanced.According to the detailed characterizations and theoretical DFT calculation results,the enhancement of I^(0)/I^(-)conversion efficiency is mainly originated from the strong bonding between the charged products of I_(3)^(-)and I_(5)^(-)and the rich hydroxyl groups in starch.This work provides inspiration for the rational design of high-performance and low-cost I^(2)-Zn in AZIBs.

Trifunctional robust electrocatalysts based on 3D Fe/N-doped carbon nanocubes encapsulating Co4N nanoparticles for efficient battery-powered water electrolyzers

Herein,we have designed a highly active and robust trifunctional electrocatalyst derived from Prussian blue analogs,where Co_(4)N nanoparticles are encapsulated by Fe embedded in N-doped carbon nanocubes to synthesize hierarchically structured Co_(4)N@Fe/N-C for rechargeable zinc-air batteries and overall water-splitting electrolyzers.As confirmed by theoretical and experimental results,the high intrinsic oxygen reduction reaction,oxygen evolution reaction,and hydrogen evolution reaction activities of Co_(4)N@Fe/N-C were attributed to the formation of the heterointerface and the modulated local electronic structure.Moreover,Co_(4)N@Fe/N-C induced improvement in these trifunctional electrocatalytic activities owing to the hierarchical hollow nanocube structure,uniform distribution of Co_(4)N,and conductive encapsulation by Fe/N-C.Thus,the rechargeable zinc-air battery with Co_(4)N@Fe/N-C delivers a high specific capacity of 789.9 mAh g^(-1) and stable voltage profiles over 500 cycles.Furthermore,the overall water electrolyzer with Co_(4)N@Fe/N-C achieved better durability and rate performance than that with the Pt/C and IrO2 catalysts,delivering a high Faradaic efficiency of 96.4%.Along with the great potential of the integrated water electrolyzer powered by a zinc-air battery for practical applications,therefore,the mechanistic understanding and active site identification provide valuable insights into the rational design of advanced multifunctional electrocatalysts for energy storage and conversion.

Lithium-Ion Battery Pack Based on Fuzzy Logic Control Research on Multi-Layer Equilibrium Circuits

In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs,a new multilayer equilibrium topology is designed in this paper.The structure adopts a hierarchical structure design,which includes intra-group equilibrium,primary inter-group equilibrium and secondary inter-group equilibrium.This structure greatly increases the number of equilibrium paths for lithium-ion batteries,thus shortening the time required for equilibrium,and improving the overall efficiency.In terms of control strategy,fuzzy logic control(FLC)is chosen to control the size of the equilibrium current during the equilibrium process.We performed rigorous modeling and simulation of the proposed system by MATLAB and Simulink software.Experiments show that the multilayer equilibrium circuit structure greatly exceeds the traditional single-layer equilibrium circuit in terms of efficacy,specifically,the Li-ion battery equilibrium speed is improved by 12.71%in static equilibrium,14.48%in charge equilibrium,and 11.19%in discharge equilibrium.In addition,compared with the maximum value algorithm,the use of the FLC algorithm reduces the equalization time by about 3.27%and improves the energy transfer efficiency by about 66.49%under the stationary condition,which verifies the feasibility of the equalization scheme.

Electro-spraying/spinning: A novel battery manufacturing technology

Lithium-ion battery(LIB) industry seems to have met its bottle neck in cutting down producing costs even though much efforts have been put into building a complete industrial chain. Actually, manufacturing methods can greatly affect the cost of battery production. Up to now, lithium ion battery producers still adopt manufacturing methods with cumbersome sub-components preparing processes and costly assembling procedures, which will undoubtedly elevate the producing cost. Herein, we propose a novel approach to directly assemble battery components(cathode, anode and separator) in an integrated way using electro-spraying and electro-spinning technologies. More importantly, this novel battery manufacturing method can produce LIBs in large scale, and the products show excellent mechanical strength, flexibility, thermal stability and electrolyte wettability. Additionally, the performance of the as-prepaed Li Fe PO_(4)||graphite full cell produced by this new method is comparable or even better than that produced by conventional manufacturing approach. In brief, this work provides a new promising technology to prepare LIBs with low cost and better performance.

Physics-based battery SOC estimation methods:Recent advances and future perspectives

The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures.However,few reviews involving SOC estimation focused on electrochemical mechanism,which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS.For this reason,this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS.First,the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated.Second,future perspectives of the current researches on physics-based battery SOC estimation are presented.The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Challenges in Li-ion battery high-voltage technology and recent advances in high-voltage electrolytes

The electrolyte directly contacts the essential parts of a lithium-ion battery,and as a result,the electrochemical properties of the electrolyte have a significant impact on the voltage platform,charge discharge capacity,energy density,service life,and rate discharge performance.By raising the voltage at the charge/discharge plateau,the energy density of the battery is increased.However,this causes transition metal dissolution,irreversible phase changes of the cathode active material,and parasitic electrolyte oxidation reactions.This article presents an overview of these concerns to provide a clear explanation of the issues involved in the development of electrolytes for high-voltage lithium-ion batteries.Additionally,solidstate electrolytes enable various applications and will likely have an impact on the development of batteries with high energy densities.It is necessary to improve the high-voltage performance of electrolytes by creating solvents with high thermal stabilities and high voltage resistance and additives with superior film forming performance,multifunctional capabilities,and stable lithium salts.To offer suggestions for the future development of high-energy lithium-ion batteries,we conclude by offering our own opinions and insights on the current development of lithium-ion batteries.

Heat transfer enhanced inorganic phase change material compositing carbon nanotubes for battery thermal management and thermal runaway propagation mitigation

Developing technologies that can be applied simultaneously in battery thermal management(BTM)and thermal runaway(TR)mitigation is significant to improving the safety of lithium-ion battery systems.Inorganic phase change material(PCM)with nonflammability has the potential to achieve this dual function.This study proposed an encapsulated inorganic phase change material(EPCM)with a heat transfer enhancement for battery systems,where Na_(2)HPO_(4)·12H_(2)O was used as the core PCM encapsulated by silica and the additive of carbon nanotube(CNT)was applied to enhance the thermal conductivity.The microstructure and thermal properties of the EPCM/CNT were analyzed by a series of characterization tests.Two different incorporating methods of CNT were compared and the proper CNT adding amount was also studied.After preparation,the battery thermal management performance and TR propagation mitigation effects of EPCM/CNT were further investigated on the battery modules.The experimental results of thermal management tests showed that EPCM/CNT not only slowed down the temperature rising of the module but also improved the temperature uniformity during normal operation.The peak battery temperature decreased from 76℃to 61.2℃at 2 C discharge rate and the temperature difference was controlled below 3℃.Moreover,the results of TR propagation tests demonstrated that nonflammable EPCM/CNT with good heat absorption could work as a TR barrier,which exhibited effective mitigation on TR and TR propagation.The trigger time of three cells was successfully delayed by 129,474 and 551 s,respectively and the propagation intervals were greatly extended as well.

Exploring battery material failure mechanisms through synchrotron X-ray characterization techniques

Rechargeable battery cycling performance and related safety have been persistent concerns.It is crucial to decipher the capacity fading induced by electrode material failure via a range of techniques.Among these,synchrotron-based X-ray techniques with high flux and brightness play a key role in understanding degradation mechanisms.In this comprehensive review,we summarize recent advancements in degra-dation modes and mechanisms that were revealed by synchrotron X-ray methodologies.Subsequently,an overview of X-ray absorption spectroscopy and X-ray scattering techniques is introduced for charac-terizing failure phenomena at local coordination atomic environment and long-range order crystal struc-ture scale,respectively.At last,we envision the future of exploring material failure mechanism.

Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data

Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation models.In addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging data.We incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV curves.Correlation analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional flexibility.The validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 mAh.Achieving this level of precision for OCV estimation requires only around 50 s collection of partial charging data.Further validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed method.Additional cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV estimation.Our method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.

Thin polymer electrolyte with MXene functional layer for uniform Li^(+) deposition in all-solid-state lithium battery

Solid polymer electrolyte(SPE) shows great potential for all-solid-state batteries because of the inherent safety and flexibility;however, the unfavourable Li+deposition and large thickness hamper its development and application. Herein, a laminar MXene functional layer-thin SPE layer-cathode integration(MXene-PEO-LFP) is designed and fabricated. The MXene functional layer formed by stacking rigid MXene nanosheets imparts higher compressive strength relative to PEO electrolyte layer. And the abundant negatively-charged groups on MXene functional layer effectively repel anions and attract cations to adjust the charge distribution behavior at electrolyte–anode interface. Furthermore,the functional layer with rich lithiophilic groups and outstanding electronic conductivity results in low Li nucleation overpotential and nucleation energy barrier. In consequence, the cell assembled with MXene-PEO-LFP, where the PEO electrolyte layer is only 12 μm, much thinner than most solid electrolytes, exhibits uniform, dendrite-free Li+deposition and excellent cycling stability. High capacity(142.8 mAh g-1), stable operation of 140 cycles(capacity decay per cycle, 0.065%), and low polarization potential(0.5 C) are obtained in this Li|MXene-PEO-LFP cell,which is superior to most PEO-based electrolytes under identical condition. This integrated design may provide a strategy for the large-scale application of thin polymer electrolytes in all-solid-state battery.

Co/CoO heterojunction rich in oxygen vacancies introduced by O_(2) plasma embedded in mesoporous walls of carbon nanoboxes covered with carbon nanotubes for rechargeable zinc-air battery

Herein,Co/CoO heterojunction nanoparticles(NPs)rich in oxygen vacancies embedded in mesoporous walls of nitrogen-doped hollow carbon nanoboxes coupled with nitrogen-doped carbon nanotubes(P-Co/CoOV@NHCNB@NCNT)are well designed through zeolite-imidazole framework(ZIF-67)carbonization,chemical vapor deposition,and O_(2) plasma treatment.As a result,the threedimensional NHCNBs coupled with NCNTs and unique heterojunction with rich oxygen vacancies reduce the charge transport resistance and accelerate the catalytic reaction rate of the P-Co/CoOV@NHCNB@NCNT,and they display exceedingly good electrocatalytic performance for oxygen reduction reaction(ORR,halfwave potential[EORR,1/2=0.855 V vs.reversible hydrogen electrode])and oxygen evolution reaction(OER,overpotential(η_(OER,10)=377mV@10mA cm^(−2)),which exceeds that of the commercial Pt/C+RuO_(2) and most of the formerly reported electrocatalysts.Impressively,both the aqueous and flexible foldable all-solid-state rechargeable zinc-air batteries(ZABs)assembled with the P-Co/CoOV@NHCNB@NCNT catalyst reveal a large maximum power density and outstanding long-term cycling stability.First-principles density functional theory calculations show that the formation of heterojunctions and oxygen vacancies enhances conductivity,reduces reaction energy barriers,and accelerates reaction kinetics rates.This work opens up a new avenue for the facile construction of highly active,structurally stable,and cost-effective bifunctional catalysts for ZABs.

Light-assisted rechargeable zinc-air battery:Mechanism,progress,and prospects

Exploring effective energy storage systems is critical to alleviate energy scarcity.Rechargeable zinc-air batteries are promising energy storage devices.However,conventional rechargeable zinc-air battery systems face many challenges associated with electrolytes and electrodes,causing inferior electrochemistry performance.The light-assisted strategy represents a novel and innovative approach to conventional zinc-air battery technology that uses only electrical energy.This strategy effectively combines both light and electrical energy conversion/storage mechanisms.In addition,light-assisted rechargeable zinc-air batteries can achieve photocharging with or without applied electrical bias by partially using solar energy and the acceleration of oxygen reduction/evolution reaction kinetics.In this paper,the working mechanism and structural design of the light-assisted rechargeable zinc-air batteries are introduced based on the theory of photoelectrochemistry and its characteristics.Then,the latest advances in electrolyte and photocathode design strategies are discussed in detail.The performance enhancement of aqueous light-assisted rechargeable zinc-air batteries using photoelectric materials is explained.Finally,a summary and outlook on the further modification of properties of light-assisted rechargeable zinc-air batteries,especially the photovoltaic electrode catalyst design strategies,are illustrated.This review provides insights and guidance for the design of high-performance light-assisted rechargeable Zn-air batteries for next-generation energy storage devices.