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 charg...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.展开更多
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 previo...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.展开更多
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 ...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.展开更多
Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical ener...Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.展开更多
Al is considered as a promising lithium-ion battery(LIBs)anode materials owing to its high theoretical capacity and appropri-ate lithation/de-lithation potential.Unfortunately,its inevitable volume expansion causes th...Al is considered as a promising lithium-ion battery(LIBs)anode materials owing to its high theoretical capacity and appropri-ate lithation/de-lithation potential.Unfortunately,its inevitable volume expansion causes the electrode structure instability,leading to poor cyclic stability.What’s worse,the natural Al2O3 layer on commercial Al pellets is always existed as a robust insulating barrier for elec-trons,which brings the voltage dip and results in low reversible capacity.Herein,this work synthesized core-shell Al@C-Sn pellets for LIBs by a plus-minus strategy.In this proposal,the natural Al2O3 passivation layer is eliminated when annealing the pre-introduced SnCl2,meanwhile,polydopamine-derived carbon is introduced as dual functional shell to liberate the fresh Al core from re-oxidization and alle-viate the volume swellings.Benefiting from the addition of C-Sn shell and the elimination of the Al2O3 passivation layer,the as-prepared Al@C-Sn pellet electrode exhibits little voltage dip and delivers a reversible capacity of 1018.7 mAh·g^(-1) at 0.1 A·g^(-1) and 295.0 mAh·g^(-1) at 2.0 A·g^(-1)(after 1000 cycles),respectively.Moreover,its diffusion-controlled capacity is muchly improved compared to those of its counterparts,confirming the well-designed nanostructure contributes to the rapid Li-ion diffusion and further enhances the lithium storage activity.展开更多
Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy de...Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy density,low cost,and recyclability.However,the study on Mg-air battery(MAB)is still at the laboratory level currently,mainly owing to the low anodic efficiency caused by the poor corrosion resistance.In order to reduce corrosion losses and achieve optimal utilization efficiency of Mg anode,the design strategies are reviewed from microstructure perspectives.Firstly,the corrosion behaviors have been discussed,especially the negative difference effect derived by hydrogen evolution.Special attention is given to the effect of anode micro-structures on the MAB,which includes grain size,grain orientation,second phases,crystal structure,twins,and dislocations.For further improvement,the discharge performance,long period stacking ordered phase and its enhancing effect are considered.Meanwhile,given the current debates over Mg dendrites,the potential risk,the impact on discharge,and the elimination strategies are discussed.Microstructure control and single crystal would be promising ways for MAB anode.展开更多
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 mod...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.展开更多
For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing m...For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical scenarios.To address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this paper.First,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency degrees.Then,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery health.Furthermore,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model adaptability.Finally,field data of 10 EVs exhibiting different SOHs are used to verify the proposed methods.By using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.展开更多
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 compar...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.展开更多
The scarcity of wettability,insufficient active sites,and low surface area of graphite felt(GF)have long been suppressing the performance of vanadium redox flow batteries(VRFBs).Herein,an ultra-homogeneous multipledim...The scarcity of wettability,insufficient active sites,and low surface area of graphite felt(GF)have long been suppressing the performance of vanadium redox flow batteries(VRFBs).Herein,an ultra-homogeneous multipledimensioned defect,including nano-scale etching and atomic-scale N,O codoping,was used to modify GF by the molten salt system.NH4Cl and KClO3 were added simultaneously to the system to obtain porous N/O co-doped electrode(GF/ON),where KClO3 was used to ultra-homogeneously etch,and O-functionalize electrode,and NH4Cl was used as N dopant,respectively.GF/ON presents better electrochemical catalysis for VO_(2)+/VO_(2)+and V3+/V2+reactions than only O-functionalized electrodes(GF/O)and GF.The enhanced electrochemical properties are attributed to an increase in active sites,surface area,and wettability,as well as the synergistic effect of N and O,which is also supported by the density functional theory calculations.Further,the cell using GF/ON shows higher discharge capacity,energy efficiency,and stability for cycling performance than the pristine cell at 140 mA cm−2 for 200 cycles.Moreover,the energy efficiency of the modified cell is increased by 9.7%from 55.2%for the pristine cell at 260 mA cm−2.Such an ultra-homogeneous etching with N and O co-doping through“boiling”molten salt medium provides an effective and practical application potential way to prepare superior electrodes for VRFB.展开更多
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 chan...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.展开更多
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...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.展开更多
Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.Ho...Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the‘‘mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.展开更多
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 capac...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.展开更多
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 b...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.展开更多
The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above...The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.展开更多
Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cann...Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications.This paper proposes an innovative active protection and cooling integrated battery module using smart materials,magneto-sensitive shear thickening fluid(MSTF),which is specifically designed to address safety threats posed by lithium-ion batteries(LIBs)exposed to harsh mechanical and environmental conditions.The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics(SPH)methodology that incorporates the intricate interplay of non-Newtonian fluid behavior,capturing the fluid-structure coupling inherent to the MSTF.This approach is further advanced by adopting an enhanced Herschel-Bulkley(H-B)model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect(MRE)and shear thickening(ST)behavior.Numerical simulation results show that in the case of cooling,the MSTF is an effective cooling medium for rapidly reducing the temperature.In terms of mechanical abuse,the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module,resulting in 66%and 61.7%reductions in the maximum stress within the battery jellyroll,and 31.1%and 23%reductions in the reaction force,respectively.This mechanism effectively lowers the risk of short-circuit failure.The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design.展开更多
In the scope of developing new electrochemical concepts to build batteries with high energy density,chloride ion batteries(CIBs)have emerged as a candidate for the next generation of novel electrochemical energy stora...In the scope of developing new electrochemical concepts to build batteries with high energy density,chloride ion batteries(CIBs)have emerged as a candidate for the next generation of novel electrochemical energy storage technologies,which show the potential in matching or even surpassing the current lithium metal batteries in terms of energy density,dendrite-free safety,and elimination of the dependence on the strained lithium and cobalt resources.However,the development of CIBs is still at the initial stage with unsatisfactory performance and several challenges have hindered them from reaching commercialization.In this review,we examine the current advances of CIBs by considering the electrode material design to the electrolyte,thus outlining the new opportunities of aqueous CIBs especially combined with desalination,chloride redox battery,etc.With respect to the developing road of lithium ion and fluoride ion batteries,the possibility of using solid-state chloride ion conductors to replace liquid electrolytes is tentatively discussed.Going beyond,perspectives and clear suggestions are concluded by highlighting the major obstacles and by prescribing specific research topics to inspire more efforts for CIBs in large-scale energy storage applications.展开更多
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 ...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.展开更多
Due to the energy crisis caused by limited fossil fuel reserves,extensive use of the renewable energy sources such as wind or solar energy is deemed to replace the use of traditional fossil fuels in the future^([1−3])...Due to the energy crisis caused by limited fossil fuel reserves,extensive use of the renewable energy sources such as wind or solar energy is deemed to replace the use of traditional fossil fuels in the future^([1−3]).However,most renewable energy sources face the same problem,which is the intermittency of energy.For example,solar energy cannot be utilized at night.That means the continuous energy demand required for large-scale power grids can’t be satisfied by a single solar panel model.展开更多
基金supported by the National Natural Science Foundation of China(No.U20A20310 and No.52176199)sponsored by the Program of Shanghai Academic/Technology Research Leader(No.22XD1423800)。
文摘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.
基金funding from National Natural Science Foundation of China(52103053,52102312)Huxiang Young Talents of Hunan Province(2022RC1004)+1 种基金Macao Young Scholars Program(AM2021011)Foundation of State Key Laboratory of Utilization of Woody Oil Resource(GZKF202126)。
文摘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.
基金financially supported by the National Natural Science Foundation of China(No.61904073)the Spring City Plan-Special Program for Young Talents(No.K202005007)+2 种基金the Yunnan Talents Support Plan for Young Talents(No.XDYC-QNRC-2022-0482)the Yunnan Local Colleges Applied Basic Research Projects(Nos.202101BA070001-138,2018FH001-016)the Key Laboratory of Artificial Microstructures in Yunnan Higher Education,the Frontier Research Team of Kunming University 2023。
文摘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.
基金supported by the National Natural Science Foundation of China(52203364,52188101,52020105010)the National Key R&D Program of China(2021YFB3800300,2022YFB3803400)+2 种基金the Strategic Priority Research Program of Chinese Academy of Science(XDA22010602)the China Postdoctoral Science Foundation(2022M713214)the China National Postdoctoral Program for Innovative Talents(BX2021321)。
文摘Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.
基金supported by the National Natural Science Foundation of China(No.62105277)the Natural Science Foundation of Henan Province(No.232300420139)the Internationalization Training of High-Level Talents of Henan Province,and Nanhu Scholars Program for Young Scholars of XYNU.
文摘Al is considered as a promising lithium-ion battery(LIBs)anode materials owing to its high theoretical capacity and appropri-ate lithation/de-lithation potential.Unfortunately,its inevitable volume expansion causes the electrode structure instability,leading to poor cyclic stability.What’s worse,the natural Al2O3 layer on commercial Al pellets is always existed as a robust insulating barrier for elec-trons,which brings the voltage dip and results in low reversible capacity.Herein,this work synthesized core-shell Al@C-Sn pellets for LIBs by a plus-minus strategy.In this proposal,the natural Al2O3 passivation layer is eliminated when annealing the pre-introduced SnCl2,meanwhile,polydopamine-derived carbon is introduced as dual functional shell to liberate the fresh Al core from re-oxidization and alle-viate the volume swellings.Benefiting from the addition of C-Sn shell and the elimination of the Al2O3 passivation layer,the as-prepared Al@C-Sn pellet electrode exhibits little voltage dip and delivers a reversible capacity of 1018.7 mAh·g^(-1) at 0.1 A·g^(-1) and 295.0 mAh·g^(-1) at 2.0 A·g^(-1)(after 1000 cycles),respectively.Moreover,its diffusion-controlled capacity is muchly improved compared to those of its counterparts,confirming the well-designed nanostructure contributes to the rapid Li-ion diffusion and further enhances the lithium storage activity.
基金supported by National Natural Science Foundation of China(52371095)Innovation Research Group of Universities in Chongqing(CXQT21030)+2 种基金Chongqing Talents:Exceptional Young Talents Project(CQYC201905100)Chongqing Youth Expert Studio,Chongqing Overseas Chinese Entrepreneurship and Innovation Support Program(cx2023117)Chongqing Natural Science Foundation Innovation and Development Joint Fund(CSTB 2022NS CQLZX0054)。
文摘Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy density,low cost,and recyclability.However,the study on Mg-air battery(MAB)is still at the laboratory level currently,mainly owing to the low anodic efficiency caused by the poor corrosion resistance.In order to reduce corrosion losses and achieve optimal utilization efficiency of Mg anode,the design strategies are reviewed from microstructure perspectives.Firstly,the corrosion behaviors have been discussed,especially the negative difference effect derived by hydrogen evolution.Special attention is given to the effect of anode micro-structures on the MAB,which includes grain size,grain orientation,second phases,crystal structure,twins,and dislocations.For further improvement,the discharge performance,long period stacking ordered phase and its enhancing effect are considered.Meanwhile,given the current debates over Mg dendrites,the potential risk,the impact on discharge,and the elimination strategies are discussed.Microstructure control and single crystal would be promising ways for MAB anode.
基金supported by the Open Project of Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle(No.ZDSYS202304)the National Natural Science Foundation of China(No.62303007)the Anhui Provincial Natural Science Foundation(No.2308085ME142)。
文摘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.
基金supported in part by the National Natural Science Foundation of China,China(Grant No.52102420)the National Key Research and Development Program of China,China(Grant No.2022YFE0102700)the China Postdoctoral Science Foundation,China(Grant No.2023T160085)。
文摘For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical scenarios.To address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this paper.First,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency degrees.Then,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery health.Furthermore,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model adaptability.Finally,field data of 10 EVs exhibiting different SOHs are used to verify the proposed methods.By using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.
基金supported by the National Natural Science Foundation of China (52075420)the National Key Research and Development Program of China (2020YFB1708400)。
文摘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.
基金supported by the National Natural Science Foundation of China(No.51872090)Natural Science Foundation of Hebei Province(No.E2019209433,E2022209158)Colleges and Universities in Hebei Province Science and Technology Research Project(No.JZX2024026).
文摘The scarcity of wettability,insufficient active sites,and low surface area of graphite felt(GF)have long been suppressing the performance of vanadium redox flow batteries(VRFBs).Herein,an ultra-homogeneous multipledimensioned defect,including nano-scale etching and atomic-scale N,O codoping,was used to modify GF by the molten salt system.NH4Cl and KClO3 were added simultaneously to the system to obtain porous N/O co-doped electrode(GF/ON),where KClO3 was used to ultra-homogeneously etch,and O-functionalize electrode,and NH4Cl was used as N dopant,respectively.GF/ON presents better electrochemical catalysis for VO_(2)+/VO_(2)+and V3+/V2+reactions than only O-functionalized electrodes(GF/O)and GF.The enhanced electrochemical properties are attributed to an increase in active sites,surface area,and wettability,as well as the synergistic effect of N and O,which is also supported by the density functional theory calculations.Further,the cell using GF/ON shows higher discharge capacity,energy efficiency,and stability for cycling performance than the pristine cell at 140 mA cm−2 for 200 cycles.Moreover,the energy efficiency of the modified cell is increased by 9.7%from 55.2%for the pristine cell at 260 mA cm−2.Such an ultra-homogeneous etching with N and O co-doping through“boiling”molten salt medium provides an effective and practical application potential way to prepare superior electrodes for VRFB.
基金financially supported by the National Key Research and Development Program(Grant No.2022YFE0207400)the National Natural Science Foundation of China(Grant No.U22A20168 and 52174225)。
文摘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.
基金This work was financially supported by the National Nat-ural Science Foundation of China No.U20A20247 and 51922038.
文摘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.
基金supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China[Grant No.52222708]the Natural Science Foundation of Beijing Municipality[Grant No.3212033]。
文摘Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the‘‘mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.
基金supported by the Shandong Provincial Natural Science Foundation,China(No.ZR2019MEM014)。
文摘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.
基金This work was supported by the National Key R&D Program of China(2021YFB2402002)the Beijing Natural Science Foundation(L223013)the Chongqing Automobile Collaborative Innovation Centre(No.2022CDJDX-004).
文摘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.
基金sponsored by the Science and Technology Program of State Grid Corporation of China(4000-202355090A-1-1ZN)。
文摘The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.
基金Project supported by the National Natural Science Foundation of China(Nos.12072183 and11872236)the Key Research Project of Zhejiang Laboratory(No.2021PE0AC02)。
文摘Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications.This paper proposes an innovative active protection and cooling integrated battery module using smart materials,magneto-sensitive shear thickening fluid(MSTF),which is specifically designed to address safety threats posed by lithium-ion batteries(LIBs)exposed to harsh mechanical and environmental conditions.The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics(SPH)methodology that incorporates the intricate interplay of non-Newtonian fluid behavior,capturing the fluid-structure coupling inherent to the MSTF.This approach is further advanced by adopting an enhanced Herschel-Bulkley(H-B)model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect(MRE)and shear thickening(ST)behavior.Numerical simulation results show that in the case of cooling,the MSTF is an effective cooling medium for rapidly reducing the temperature.In terms of mechanical abuse,the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module,resulting in 66%and 61.7%reductions in the maximum stress within the battery jellyroll,and 31.1%and 23%reductions in the reaction force,respectively.This mechanism effectively lowers the risk of short-circuit failure.The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design.
基金the support of the National Energy-Saving and Low-Carbon Materials Production and Application Demonstration Platform Program (TC220H06N)the National Natural Science Foundation of China (51832004,51972259,52127816)the Natural Science Foundation of Hubei Province (2022CFA087)。
文摘In the scope of developing new electrochemical concepts to build batteries with high energy density,chloride ion batteries(CIBs)have emerged as a candidate for the next generation of novel electrochemical energy storage technologies,which show the potential in matching or even surpassing the current lithium metal batteries in terms of energy density,dendrite-free safety,and elimination of the dependence on the strained lithium and cobalt resources.However,the development of CIBs is still at the initial stage with unsatisfactory performance and several challenges have hindered them from reaching commercialization.In this review,we examine the current advances of CIBs by considering the electrode material design to the electrolyte,thus outlining the new opportunities of aqueous CIBs especially combined with desalination,chloride redox battery,etc.With respect to the developing road of lithium ion and fluoride ion batteries,the possibility of using solid-state chloride ion conductors to replace liquid electrolytes is tentatively discussed.Going beyond,perspectives and clear suggestions are concluded by highlighting the major obstacles and by prescribing specific research topics to inspire more efforts for CIBs in large-scale energy storage applications.
基金This work is supported by National Natural Science Founda-tion of China(U2004199)National Key Research and Devel-opment Program of China(2018YFD0200606)+1 种基金China Postdoctoral Science Foundation(2021T140615),Natural Sci-enceFoundationofHenanProvince(212300410285)Young Talent Support Project of Henan Province(2021HYTP028).
文摘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.
基金support from the National Natural Science Foundation of China(22076116)the Sino-German Center for Research Promotion(GZ1579)the China Scholarship Council(202007030003)for the financial support.
文摘Due to the energy crisis caused by limited fossil fuel reserves,extensive use of the renewable energy sources such as wind or solar energy is deemed to replace the use of traditional fossil fuels in the future^([1−3]).However,most renewable energy sources face the same problem,which is the intermittency of energy.For example,solar energy cannot be utilized at night.That means the continuous energy demand required for large-scale power grids can’t be satisfied by a single solar panel model.
