Aqueous Zn-iodine batteries(ZIBs)face the formidable challenges towards practical implementation,including metal corrosion and rampant dendrite growth on the Zn anode side,and shuttle effect of polyiodide species from...Aqueous Zn-iodine batteries(ZIBs)face the formidable challenges towards practical implementation,including metal corrosion and rampant dendrite growth on the Zn anode side,and shuttle effect of polyiodide species from the cathode side.These challenges lead to poor cycle stability and severe self-discharge.From the fabrication and cost point of view,it is technologically more viable to deploy electrolyte engineering than electrode protection strategies.More importantly,a synchronous method for modulation of both cathode and anode is pivotal,which has been often neglected in prior studies.In this work,cationic poly(allylamine hydrochloride)(Pah^(+))is adopted as a low-cost dual-function electrolyte additive for ZIBs.We elaborate the synchronous effect by Pah^(+)in stabilizing Zn anode and immobilizing polyiodide anions.The fabricated Zn-iodine coin cell with Pah^(+)(ZnI_(2) loading:25 mg cm^(−2))stably cycles 1000 times at 1 C,and a single-layered 3.4 cm^(2) pouch cell(N/P ratio~1.5)with the same mass loading cycles over 300 times with insignificant capacity decay.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
Single-atom catalysts(SACs)have garnered significant attention in lithium-sulfur(Li-S)batteries for their potential to mitigate the severe polysulfide shuttle effect and sluggish redox kinetics.However,the development...Single-atom catalysts(SACs)have garnered significant attention in lithium-sulfur(Li-S)batteries for their potential to mitigate the severe polysulfide shuttle effect and sluggish redox kinetics.However,the development of highly efficient SACs and a comprehensive understanding of their structure-activity relationships remain enormously challenging.Herein,a novel kind of Fe-based SAC featuring an asymmetric FeN_(5)-TeN_(4) coordination structure was precisely designed by introducing Te atom adjacent to the Fe active center to enhance the catalytic activity.Theoretical calculations reveal that the neighboring Te atom modulates the local coordination environment of the central Fe site,elevating the d-band center closer to the Fermi level and strengthening the d-p orbital hybridization between the catalyst and sulfur species,thereby immobilizing polysulfides and improving the bidirectional catalysis of Li-S redox.Consequently,the Fe-Te atom pair catalyst endows Li-S batteries with exceptional rate performance,achieving a high specific capacity of 735 mAh g^(−1) at 5 C,and remarkable cycling stability with a low decay rate of 0.038%per cycle over 1000 cycles at 1 C.This work provides fundamental insights into the electronic structure modulation of SACs and establishes a clear correlation between precisely engineered atomic configurations and their enhanced catalytic performance in Li-S electrochemistry.展开更多
Rechargeable Zn/Sn-air batteries have received considerable attention as promising energy storage devices.However,the electrochemical performance of these batteries is significantly constrained by the sluggish electro...Rechargeable Zn/Sn-air batteries have received considerable attention as promising energy storage devices.However,the electrochemical performance of these batteries is significantly constrained by the sluggish electrocatalytic reaction kinetics at the cathode.The integration of light energy into Zn/Sn-air batteries is a promising strategy for enhancing their performance.However,the photothermal and photoelectric effects generate heat in the battery under prolonged solar irradiation,leading to air cathode instability.This paper presents the first design and synthesis of Ni_(2)-1,5-diamino-4,8-dihydroxyanthraquinone(Ni_(2)DDA),an electronically conductiveπ-d conjugated metal-organic framework(MOF).Ni_(2)DDA exhibits both photoelectric and photothermal effects,with an optical band gap of~1.14 eV.Under illumination,Ni_(2)DDA achieves excellent oxygen evolution reaction performance(with an overpotential of 245 mV vs.reversible hydrogen electrode at 10 mA cm^(−2))and photothermal stability.These properties result from the synergy between the photoelectric and photothermal effects of Ni_(2)DDA.Upon integration into Zn/Sn-air batteries,Ni_(2)DDA ensures excellent cycling stability under light and exhibits remarkable performance in high-temperature environments up to 80℃.This study experimentally confirms the stable operation of photo-assisted Zn/Sn-air batteries under high-temperature conditions for the first time and provides novel insights into the application of electronically conductive MOFs in photoelectrocatalysis and photothermal catalysis.展开更多
Graphdiyne(GDY)is a two-dimensional carbon allotrope with exceptional physical and chemical properties that is gaining increasing attention.However,its efficient and scalable synthesis remains a significant challenge....Graphdiyne(GDY)is a two-dimensional carbon allotrope with exceptional physical and chemical properties that is gaining increasing attention.However,its efficient and scalable synthesis remains a significant challenge.We present a microwave-assisted approach for its continuous,large-scale production which enables synthesis at a rate of 0.6 g/h,with a yield of up to 90%.The synthesized GDY nanosheets have an average diameter of 246 nm and a thickness of 4 nm.We used GDY as a stable coating for potassium(K)metal anodes(K@GDY),taking advantage of its unique molecular structure to provide favorable paths for K-ion transport.This modification significantly inhibited dendrite formation and improved the cycling stability of K metal batteries.Full-cells with perylene-3,4,9,10-tetracarboxylic dianhydride(PTCDA)cathodes showed the clear superiority of the K@GDY anodes over bare K anodes in terms of performance,stability,and cycle life.The K@GDY maintained a stable voltage plateau and gave an excellent capacity retention after 600 cycles with nearly 100%Coulombic efficiency.This work not only provides a scalable and efficient way for GDY synthesis but also opens new possibilities for its use in energy storage and other advanced technologies.展开更多
Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy densit...Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.展开更多
La-Mg-Ni-based hydrogen storage alloys with superlattice structures are the new generation anode material for nickel metal hydride(Ni-MH)batteries owing to the advantages of high capacity and exceptional activation pr...La-Mg-Ni-based hydrogen storage alloys with superlattice structures are the new generation anode material for nickel metal hydride(Ni-MH)batteries owing to the advantages of high capacity and exceptional activation properties.However,the cycling stability is not currently satisfactory enough which plagues its application.Herein,a strategy of partially substituting La with the Y element is proposed to boost the capacity durability of La-Mg-Ni-based alloys.Furthermore,phase structure regulation is implemented simultaneously to obtain the A5 B19-type alloy with good crystal stability specifically.It is found that Y promotes the phase formation of the Pr5 Co19-type phase after annealing at 985℃.The alloy containing Y contributes to the superior rate capability resulting from the promoted hydrogen diffusion rate.Notably,Y substitution enables strengthening the anti-pulverization ability of the alloy in terms of increasing the volume match between[A_(2)B_(4)]and[AB5]subunits,and effectively enhances the anti-corrosion ability of the alloy due to high electronegativity,realizing improved long-term cycling stability of the alloy from 74.2%to 78.5%after cycling 300 times.The work is expected to shed light on the composition and structure design of the La-Mg-Ni-based hydrogen storage alloy for Ni-MH batteries.展开更多
This study shows that sulfide solid-state electrolytes,β-Li_(3)PS_(4)and Li_(6)PS_(5)Cl,are flammable solids.Both solid-state electrolytes release sulfur vapor in a dry,oxidizing environment at elevated temperature&l...This study shows that sulfide solid-state electrolytes,β-Li_(3)PS_(4)and Li_(6)PS_(5)Cl,are flammable solids.Both solid-state electrolytes release sulfur vapor in a dry,oxidizing environment at elevated temperature<300℃.Sulfur vapor is a highly flammable gas,which then auto-ignites to produce a flame.This behavior suggests that an O_(2)-S gas-gas reaction mechanism may contribute to all-solid-state battery thermal runaway.To improve all-solid-state battery safety,current work focuses on eliminating the O_(2)source by changing the cathode active material.The conclusion of this study suggests that all-solidstate battery safety can also be realized by the development of solid-state electrolytes with less susceptibility to sulfur volatilization.展开更多
The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational per...The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.展开更多
Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlo...Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.展开更多
Sulfide-based all-solid-state lithium batteries(ASSLBs) with nickel-rich oxide cathodes are emerging as primary contenders for the next generation rechargeable batteries,owing to their superior safety and energy densi...Sulfide-based all-solid-state lithium batteries(ASSLBs) with nickel-rich oxide cathodes are emerging as primary contenders for the next generation rechargeable batteries,owing to their superior safety and energy density.However,the all-solid-state batteries with nickel-rich oxide cathodes suffer from performance degradation due to the reactions between the highly reactive surface oxygen of the cathode and the electrolyte,as well as the instability of the bulk oxygen structure in the cathode.Herein,we propose a synergistic modification design scheme to adjust the oxygen activity from surface to bulk.The LiBO_(2)coating inhibits the reactivity of surface lattice oxygen ions.Meanwhile,Zr doping in the bulk phase forms strong Zr-O covalent bonds that stabilize the bulk lattice oxygen structure.The synergistic effect of these modifications prevents the release of oxygen,thus avoiding the degradation of the cathode/SE interface.Additionally,the regulation of surface-to-bulk oxygen activity establishes a highly stable interface,thereby enhancing the lithium ion diffusion kinetics and mechanical stability of the cathode.Consequently,cathodes modified with this synergistic strategy exhibit outstanding performance in sulfide-based ASSLBs,including an ultra-long cycle life of 100,000 cycles,ultra-high rate capability at 45C,and 85% high active material content in the composite cathode.Additionally,ASSLB exhibits stable cycling under high loading conditions of 82.82 mg cm^(-2),achieving an areal capacity of 17.90 mA h cm^(-2).These encouraging results pave the way for practical applications of ASSLBs in fast charging,long cycle life,and high energy density in the future.展开更多
Carbon nanotubes(CNTs)have many excellent properties that make them ideally suited for use in lithium-ion batteries(LIBs).In this review,the recent research on applications of CNTs in LIBs,including their usage as fre...Carbon nanotubes(CNTs)have many excellent properties that make them ideally suited for use in lithium-ion batteries(LIBs).In this review,the recent research on applications of CNTs in LIBs,including their usage as freestanding anodes,conductive additives,and current collectors,are discussed.Challenges,strategies,and progress are analyzed by selecting typical examples.Particularly,when CNTs are used with relatively large mass fractions,the relevant interfacial electrochemistry in such a CNT-based electrode,which dictates the quality of the resulting solid-electrolyte interface,becomes a concern.Hence,in this review the different lithium-ion adsorption and insertion mechanisms inside and outside of CNTs are compared;the influence of not only CNT structural features(including their length,defect density,diameter,and wall thickness)but also the electrolyte composition on the solid-electrolyte interfacial reactions is analyzed in detail.Strategies to optimize the solid-solid interface between CNTs and the other solid components in various composite electrodes are also covered.By emphasizing the importance of such a structure-performance relationship,the merits and weaknesses of various applications of CNTs in various advanced LIBs are clarified.展开更多
The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconci...The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconcile this contradiction,two Mg-0.1Sc-0.1Y-0.1Ag anodes with different residual strain distribution through extrusion with/without annealing are fabricated.The results indicate that annealing can significantly lessen the“pseudo-anode”regions,thereby changing the dissolution mode of the matrix and achieving an effective dissolution during discharge.Additionally,p-type semiconductor characteristic of discharge productfilm could suppress the self-corrosion reaction without reducing the polarization of anode.The magnesium-air battery utilizing annealed Mg-0.1Sc-0.1Y-0.1Ag as anode achieves a synergistic improvement in specific capacity(1388.89 mA h g^(-1))and energy density(1960.42 mW h g^(-1)).This anode modification method accelerates the advancement of high efficiency and long lifespan magnesium-air batteries,offering renewable and cost-effective energy solutions for electronics and emergency equipment.展开更多
The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose s...The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose significant challenges for battery development.These conditions drive the need for specialized designs in deep-sea batteries,incorporating critical aspects of power generation,protection,distribution,and management.Over time,deep-sea battery technology has evolved through multiple generations,with lithium(Li)batteries emerging in recent decades as the preferred power source due to their high energy and reduced operational risks.Although the rapid progress of Li batteries has notably advanced the capabilities of underwater vehicles,critical technical issues remain unresolved.This review first systematically presents the whole picture of deep-sea battery manufacturing,focusing on Li batteries as the current mainstream solution for underwater power.It examines the key aspects of deep-sea Li battery development,including materials selection informed by electro-chemo-mechanics models,component modification and testing,and battery management systems specialized in software and hardware.Finally,it discusses the main challenges limiting the utilization of deep-sea batteries and outlines promising directions for future development.Based on the systematic reflection on deep-sea batteries and discussion on deep-sea Li batteries,this review aims to provide a research foundation for developing underwater power tailored for extreme environmental exploration.展开更多
Battery technology plays a crucial role across various sectors,powering devices from smartphones to electric vehicles and supporting grid-scale energy storage.To ensure their safety and efficiency,batteries must be ev...Battery technology plays a crucial role across various sectors,powering devices from smartphones to electric vehicles and supporting grid-scale energy storage.To ensure their safety and efficiency,batteries must be evaluated under diverse operating conditions.Traditional modeling techniques,which often rely on first principles and atomic-level calculations,struggle with practical applications due to incomplete or noisy data.Furthermore,the complexity of battery dynamics,shaped by physical,chemical,and electrochemical interactions,presents substantial challenges for precise and efficient modeling.The Transformer model,originally designed for natural language processing,has proven effective in time-series analysis and forecasting.It adeptly handles the extensive,complex datasets produced during battery cycles,efficiently filtering out noise and identifying critical features without extensive preprocessing.This capability positions Transformers as potent tools for tackling the intricacies of battery data.This review explores the application of customized Transformers in battery state estimation,emphasizing crucial aspects such as charging,health assessment,lifetime prediction,and safety monitoring.It highlights the distinct advantages of Transformer-based models and addresses ongoing challenges and future opportunities in the field.By combining data-driven AI techniques with empirical insights from battery analysis,these pre-trained models can deliver precise diagnostics and comprehensive monitoring,enhancing performance metrics like health monitoring,anomaly detection,and early-warning systems.This integrated approach promises significant improvements in battery technology management and application.展开更多
The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the ra...The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the rapid battery performance degradation.Here,we customize two SEIs with different spatial structures(bilayer and mosaic)by simply regulating the proportion of additive fluoroethylene carbonate.Surprisingly,due to the uniform distribution of dense inorganic nano-crystals in the inner,the bilayer SEI exhibits low-swelling and excellent mechanical properties,so the undesirable side reactions of the electrolyte are effectively suppressed.In addition,we put forward the growth rate of swelling ratio(GSR)as a key indicator to reveal the swelling change in SEI.The GSR of bilayer SEI merely increases from1.73 to 3.16 after the 300th cycle,which enables the corresponding graphite‖Li battery to achieve longer cycle stability.The capacity retention is improved by 47.5% after 300 cycles at 0.5 C.The correlation among SEI spatial structure,swelling behavior,and battery performance provides a new direction for electrolyte optimization and interphase structure design of high energy density batteries.展开更多
Succinonitrile has shown significant promise for application in polymer electrolytes for solid-state lithium metal batteries due to its high ionic conductivity at low-temperature.However,the use of Succinonitrile is l...Succinonitrile has shown significant promise for application in polymer electrolytes for solid-state lithium metal batteries due to its high ionic conductivity at low-temperature.However,the use of Succinonitrile is limited due to its corrosion of Li metal.Herein,we report a solid polymer electrolyte with high ionic conductivity(2.17×10^(−3)S cm^(−1),35°C)enhanced by Ti_(3)C_(2)T_(x).Corrosion of the Li anode is prevented due to the Succinonitrile molecules being efficiently anchored by Ti_(3)C_(2)T_(x).Meanwhile,the coordination environment of Li^(+)is weakened due to the introduction of competitive coordination induction effects into the polymer electrolyte,resulting in efficient Li^(+)conduction.Furthermore,the mechanical properties of the electrolyte are enhanced by modulating the ratio of Ti_(3)C_(2)T_(x)to suppress the growth of Li dendrites.Therefore,Li||Li symmetric batteries deliver stable cycling up to 8000 h at 28°C.LiFePO4||Li full batteries exhibit excellent cycling stability of 151.7 mAh g^(−1)with a capacity retention of 99.3%after 300 cycles.This work not only presents a new idea to suppress the corrosion of the Li anode by Succinonitrile but also provides a simple,feasible,and scalable strategy for high-performance Li metal batteries.展开更多
As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as l...As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.展开更多
This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode sche...This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.展开更多
The lithium-oxygen battery(LOB)is a promising source of green energy due to its energy density.However,the development of this technology is limited by the insoluble discharge product it produces.In this work,a cathod...The lithium-oxygen battery(LOB)is a promising source of green energy due to its energy density.However,the development of this technology is limited by the insoluble discharge product it produces.In this work,a cathode material with a p-n heterostructure of polyaniline(PANI)/ZnS is prepared to trap visible light,utilizing a ZnS quantum dot(ZnS QD)network to form a large number of photogenerated electron–hole pairs,thus promoting the generation and decomposition of Li_(2)O_(2).The prepared PANI/ZnS has an ultra-low overpotential of 0.06 V under illumination.Furthermore,density functional theory theoretical calculation has demonstrated the ability of the heterostructures to adsorb oxygen-containing intermediates,which not only facilitates the growth of Li_(2)O_(2),but also reduces the reaction energy required to decompose Li_(2)O_(2).The present work provides a solution to the problem of insolubility of discharge products in photo-assisted LOB.展开更多
基金supported by the financial support from the National Research Foundation,Singapore,under its Singapore-China Joint Flagship Project(Clean Energy).
文摘Aqueous Zn-iodine batteries(ZIBs)face the formidable challenges towards practical implementation,including metal corrosion and rampant dendrite growth on the Zn anode side,and shuttle effect of polyiodide species from the cathode side.These challenges lead to poor cycle stability and severe self-discharge.From the fabrication and cost point of view,it is technologically more viable to deploy electrolyte engineering than electrode protection strategies.More importantly,a synchronous method for modulation of both cathode and anode is pivotal,which has been often neglected in prior studies.In this work,cationic poly(allylamine hydrochloride)(Pah^(+))is adopted as a low-cost dual-function electrolyte additive for ZIBs.We elaborate the synchronous effect by Pah^(+)in stabilizing Zn anode and immobilizing polyiodide anions.The fabricated Zn-iodine coin cell with Pah^(+)(ZnI_(2) loading:25 mg cm^(−2))stably cycles 1000 times at 1 C,and a single-layered 3.4 cm^(2) pouch cell(N/P ratio~1.5)with the same mass loading cycles over 300 times with insignificant capacity decay.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金supported by the National Natural Science Foundation(52302284,22002086,22204096)Shanghai Sailing Program(23YF1412200)the Fundamental Research Funds for the Central Universities(22120240314).
文摘Single-atom catalysts(SACs)have garnered significant attention in lithium-sulfur(Li-S)batteries for their potential to mitigate the severe polysulfide shuttle effect and sluggish redox kinetics.However,the development of highly efficient SACs and a comprehensive understanding of their structure-activity relationships remain enormously challenging.Herein,a novel kind of Fe-based SAC featuring an asymmetric FeN_(5)-TeN_(4) coordination structure was precisely designed by introducing Te atom adjacent to the Fe active center to enhance the catalytic activity.Theoretical calculations reveal that the neighboring Te atom modulates the local coordination environment of the central Fe site,elevating the d-band center closer to the Fermi level and strengthening the d-p orbital hybridization between the catalyst and sulfur species,thereby immobilizing polysulfides and improving the bidirectional catalysis of Li-S redox.Consequently,the Fe-Te atom pair catalyst endows Li-S batteries with exceptional rate performance,achieving a high specific capacity of 735 mAh g^(−1) at 5 C,and remarkable cycling stability with a low decay rate of 0.038%per cycle over 1000 cycles at 1 C.This work provides fundamental insights into the electronic structure modulation of SACs and establishes a clear correlation between precisely engineered atomic configurations and their enhanced catalytic performance in Li-S electrochemistry.
基金supported by the National Natural Science Foundation of China(No.62464010)Spring City Plan-Special Program for Young Talents(K202005007)+2 种基金Yunnan Talents Support Plan for Young Talents(XDYC-QNRC-2022-0482)Yunnan Local Colleges Applied Basic Research Projects(202101BA070001-138)Frontier Research Team of Kunming University 2023.
文摘Rechargeable Zn/Sn-air batteries have received considerable attention as promising energy storage devices.However,the electrochemical performance of these batteries is significantly constrained by the sluggish electrocatalytic reaction kinetics at the cathode.The integration of light energy into Zn/Sn-air batteries is a promising strategy for enhancing their performance.However,the photothermal and photoelectric effects generate heat in the battery under prolonged solar irradiation,leading to air cathode instability.This paper presents the first design and synthesis of Ni_(2)-1,5-diamino-4,8-dihydroxyanthraquinone(Ni_(2)DDA),an electronically conductiveπ-d conjugated metal-organic framework(MOF).Ni_(2)DDA exhibits both photoelectric and photothermal effects,with an optical band gap of~1.14 eV.Under illumination,Ni_(2)DDA achieves excellent oxygen evolution reaction performance(with an overpotential of 245 mV vs.reversible hydrogen electrode at 10 mA cm^(−2))and photothermal stability.These properties result from the synergy between the photoelectric and photothermal effects of Ni_(2)DDA.Upon integration into Zn/Sn-air batteries,Ni_(2)DDA ensures excellent cycling stability under light and exhibits remarkable performance in high-temperature environments up to 80℃.This study experimentally confirms the stable operation of photo-assisted Zn/Sn-air batteries under high-temperature conditions for the first time and provides novel insights into the application of electronically conductive MOFs in photoelectrocatalysis and photothermal catalysis.
基金supported by National Natural Science Foundation of China(52302034,52402060,52202201,52021006)Beijing National Laboratory for Molecular Sciences(BNLMS-CXTD202001)+1 种基金Shenzhen Science and Technology Innovation Commission(KQTD20221101115627004)China Postdoctoral Science Foundation(2024T170972)。
文摘Graphdiyne(GDY)is a two-dimensional carbon allotrope with exceptional physical and chemical properties that is gaining increasing attention.However,its efficient and scalable synthesis remains a significant challenge.We present a microwave-assisted approach for its continuous,large-scale production which enables synthesis at a rate of 0.6 g/h,with a yield of up to 90%.The synthesized GDY nanosheets have an average diameter of 246 nm and a thickness of 4 nm.We used GDY as a stable coating for potassium(K)metal anodes(K@GDY),taking advantage of its unique molecular structure to provide favorable paths for K-ion transport.This modification significantly inhibited dendrite formation and improved the cycling stability of K metal batteries.Full-cells with perylene-3,4,9,10-tetracarboxylic dianhydride(PTCDA)cathodes showed the clear superiority of the K@GDY anodes over bare K anodes in terms of performance,stability,and cycle life.The K@GDY maintained a stable voltage plateau and gave an excellent capacity retention after 600 cycles with nearly 100%Coulombic efficiency.This work not only provides a scalable and efficient way for GDY synthesis but also opens new possibilities for its use in energy storage and other advanced technologies.
基金supported by the National Key R&D Program of China(No.2022YFE0207400)supported by the Xiaomi Young Talents Programsupported by the Youth Innovation Promotion Association CAS(No.Y201768)。
文摘Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.
基金the financial support by the National Nat-ural Science Foundation of China(Nos.52201282,52071281,52371239)the China Postdoctoral Science Foundation(No.2023M742945)+4 种基金Hebei Provincial Postdoctoral Science Foundation(No.B2023003023)the Science Research Project of Hebei Education Department(No.BJK2022033)the Natural Science Foundation of Hebei Province(No.C2022203003)the Inner Mongolia Science and Technology Major Project(No.2020ZD0012)the Baotou Science and Technology Planning Project(No.XM2022BT09).
文摘La-Mg-Ni-based hydrogen storage alloys with superlattice structures are the new generation anode material for nickel metal hydride(Ni-MH)batteries owing to the advantages of high capacity and exceptional activation properties.However,the cycling stability is not currently satisfactory enough which plagues its application.Herein,a strategy of partially substituting La with the Y element is proposed to boost the capacity durability of La-Mg-Ni-based alloys.Furthermore,phase structure regulation is implemented simultaneously to obtain the A5 B19-type alloy with good crystal stability specifically.It is found that Y promotes the phase formation of the Pr5 Co19-type phase after annealing at 985℃.The alloy containing Y contributes to the superior rate capability resulting from the promoted hydrogen diffusion rate.Notably,Y substitution enables strengthening the anti-pulverization ability of the alloy in terms of increasing the volume match between[A_(2)B_(4)]and[AB5]subunits,and effectively enhances the anti-corrosion ability of the alloy due to high electronegativity,realizing improved long-term cycling stability of the alloy from 74.2%to 78.5%after cycling 300 times.The work is expected to shed light on the composition and structure design of the La-Mg-Ni-based hydrogen storage alloy for Ni-MH batteries.
文摘This study shows that sulfide solid-state electrolytes,β-Li_(3)PS_(4)and Li_(6)PS_(5)Cl,are flammable solids.Both solid-state electrolytes release sulfur vapor in a dry,oxidizing environment at elevated temperature<300℃.Sulfur vapor is a highly flammable gas,which then auto-ignites to produce a flame.This behavior suggests that an O_(2)-S gas-gas reaction mechanism may contribute to all-solid-state battery thermal runaway.To improve all-solid-state battery safety,current work focuses on eliminating the O_(2)source by changing the cathode active material.The conclusion of this study suggests that all-solidstate battery safety can also be realized by the development of solid-state electrolytes with less susceptibility to sulfur volatilization.
基金National Natural Science Foundation of China (52075420)Fundamental Research Funds for the Central Universities (xzy022023049)National Key Research and Development Program of China (2023YFB3408600)。
文摘The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.
基金supported by the National Natural Science Foundation of China(No.52207229)the Key Research and Development Program of Ningxia Hui Autonomous Region of China(No.2024BEE02003)+1 种基金the financial support from the AEGiS Research Grant 2024,University of Wollongong(No.R6254)the financial support from the China Scholarship Council(No.202207550010).
文摘Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.
基金financially supported by the National Natural Science Foundation of China (52474338,22109084 and 52304338)the Hunan Provincial Key Research and Development Program (2024JK2093,2023GK2016)supported in part by the High Performance Computing Center of Central South University.
文摘Sulfide-based all-solid-state lithium batteries(ASSLBs) with nickel-rich oxide cathodes are emerging as primary contenders for the next generation rechargeable batteries,owing to their superior safety and energy density.However,the all-solid-state batteries with nickel-rich oxide cathodes suffer from performance degradation due to the reactions between the highly reactive surface oxygen of the cathode and the electrolyte,as well as the instability of the bulk oxygen structure in the cathode.Herein,we propose a synergistic modification design scheme to adjust the oxygen activity from surface to bulk.The LiBO_(2)coating inhibits the reactivity of surface lattice oxygen ions.Meanwhile,Zr doping in the bulk phase forms strong Zr-O covalent bonds that stabilize the bulk lattice oxygen structure.The synergistic effect of these modifications prevents the release of oxygen,thus avoiding the degradation of the cathode/SE interface.Additionally,the regulation of surface-to-bulk oxygen activity establishes a highly stable interface,thereby enhancing the lithium ion diffusion kinetics and mechanical stability of the cathode.Consequently,cathodes modified with this synergistic strategy exhibit outstanding performance in sulfide-based ASSLBs,including an ultra-long cycle life of 100,000 cycles,ultra-high rate capability at 45C,and 85% high active material content in the composite cathode.Additionally,ASSLB exhibits stable cycling under high loading conditions of 82.82 mg cm^(-2),achieving an areal capacity of 17.90 mA h cm^(-2).These encouraging results pave the way for practical applications of ASSLBs in fast charging,long cycle life,and high energy density in the future.
基金Xiamen Science and Technology Project,Grant/Award Number:3502Z20231057National Key Research and Development Program of China,Grant/Award Number:3502Z20231057National Natural Science Foundation of China,Grant/Award Numbers:22279107,22288102。
文摘Carbon nanotubes(CNTs)have many excellent properties that make them ideally suited for use in lithium-ion batteries(LIBs).In this review,the recent research on applications of CNTs in LIBs,including their usage as freestanding anodes,conductive additives,and current collectors,are discussed.Challenges,strategies,and progress are analyzed by selecting typical examples.Particularly,when CNTs are used with relatively large mass fractions,the relevant interfacial electrochemistry in such a CNT-based electrode,which dictates the quality of the resulting solid-electrolyte interface,becomes a concern.Hence,in this review the different lithium-ion adsorption and insertion mechanisms inside and outside of CNTs are compared;the influence of not only CNT structural features(including their length,defect density,diameter,and wall thickness)but also the electrolyte composition on the solid-electrolyte interfacial reactions is analyzed in detail.Strategies to optimize the solid-solid interface between CNTs and the other solid components in various composite electrodes are also covered.By emphasizing the importance of such a structure-performance relationship,the merits and weaknesses of various applications of CNTs in various advanced LIBs are clarified.
基金the National Natural Science:Foundation of China(52375370)the Open Project of Salt Lake Chemical Engineering Research Complex,Qinghai University(2023-DXSSKF-Z02)+2 种基金the Nat-ural Science Foundation of Shanxi(202103021224049)GDAS Projects of International cooperation platform of Sci-ence and Technology(2022GDASZH-2022010203-003)Guangdong province Science and Technology Plan Projects(2023B1212060045).
文摘The dominated contradiction in optimizing the performance of magnesium-air battery anode lies in the difficulty of achieving a good balance between activation and passivation during discharge process.To further reconcile this contradiction,two Mg-0.1Sc-0.1Y-0.1Ag anodes with different residual strain distribution through extrusion with/without annealing are fabricated.The results indicate that annealing can significantly lessen the“pseudo-anode”regions,thereby changing the dissolution mode of the matrix and achieving an effective dissolution during discharge.Additionally,p-type semiconductor characteristic of discharge productfilm could suppress the self-corrosion reaction without reducing the polarization of anode.The magnesium-air battery utilizing annealed Mg-0.1Sc-0.1Y-0.1Ag as anode achieves a synergistic improvement in specific capacity(1388.89 mA h g^(-1))and energy density(1960.42 mW h g^(-1)).This anode modification method accelerates the advancement of high efficiency and long lifespan magnesium-air batteries,offering renewable and cost-effective energy solutions for electronics and emergency equipment.
基金support provided by National Key Research and Development Program of China(2023YFE0203000 and 2016YFC0300200)the NSAF(Grant No.U2330205)+3 种基金Full-Sea-Depth Battery Project(2020-XXXX-XX-246-00)Open project of Shaanxi Laboratory of Aerospace Power(2022ZY2-JCYJ-01-09)Fundamental Research Funds for the Central Universities,ND Basic Research Funds(G2022WD)the Innovation Team of Shaanxi Province。
文摘The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose significant challenges for battery development.These conditions drive the need for specialized designs in deep-sea batteries,incorporating critical aspects of power generation,protection,distribution,and management.Over time,deep-sea battery technology has evolved through multiple generations,with lithium(Li)batteries emerging in recent decades as the preferred power source due to their high energy and reduced operational risks.Although the rapid progress of Li batteries has notably advanced the capabilities of underwater vehicles,critical technical issues remain unresolved.This review first systematically presents the whole picture of deep-sea battery manufacturing,focusing on Li batteries as the current mainstream solution for underwater power.It examines the key aspects of deep-sea Li battery development,including materials selection informed by electro-chemo-mechanics models,component modification and testing,and battery management systems specialized in software and hardware.Finally,it discusses the main challenges limiting the utilization of deep-sea batteries and outlines promising directions for future development.Based on the systematic reflection on deep-sea batteries and discussion on deep-sea Li batteries,this review aims to provide a research foundation for developing underwater power tailored for extreme environmental exploration.
基金the support provided by the California Department of Transportation(Caltrans)through the Fiscal Year 2023-24 grant(65A0686)for the research project titled‘Revolutions in Battery technologies and Future Electric Vehicles’。
文摘Battery technology plays a crucial role across various sectors,powering devices from smartphones to electric vehicles and supporting grid-scale energy storage.To ensure their safety and efficiency,batteries must be evaluated under diverse operating conditions.Traditional modeling techniques,which often rely on first principles and atomic-level calculations,struggle with practical applications due to incomplete or noisy data.Furthermore,the complexity of battery dynamics,shaped by physical,chemical,and electrochemical interactions,presents substantial challenges for precise and efficient modeling.The Transformer model,originally designed for natural language processing,has proven effective in time-series analysis and forecasting.It adeptly handles the extensive,complex datasets produced during battery cycles,efficiently filtering out noise and identifying critical features without extensive preprocessing.This capability positions Transformers as potent tools for tackling the intricacies of battery data.This review explores the application of customized Transformers in battery state estimation,emphasizing crucial aspects such as charging,health assessment,lifetime prediction,and safety monitoring.It highlights the distinct advantages of Transformer-based models and addresses ongoing challenges and future opportunities in the field.By combining data-driven AI techniques with empirical insights from battery analysis,these pre-trained models can deliver precise diagnostics and comprehensive monitoring,enhancing performance metrics like health monitoring,anomaly detection,and early-warning systems.This integrated approach promises significant improvements in battery technology management and application.
基金supported by the National Natural Science Foundation of China(22369011)the Gansu Key Research and Development Program(23YFGA0053 and 24YFGA025)the Hongliu Outstanding Youth Talent Support Program of Lanzhou University of Technology and Postgraduate research exploration project of Lanzhou University of Technology(256017)。
文摘The swelling behavior and stability in solid electrolyte interphase(SEI)have been proved to determine the battery cycle life.A high swollen,unstable SEI shows a high permeability to electrolyte,which results in the rapid battery performance degradation.Here,we customize two SEIs with different spatial structures(bilayer and mosaic)by simply regulating the proportion of additive fluoroethylene carbonate.Surprisingly,due to the uniform distribution of dense inorganic nano-crystals in the inner,the bilayer SEI exhibits low-swelling and excellent mechanical properties,so the undesirable side reactions of the electrolyte are effectively suppressed.In addition,we put forward the growth rate of swelling ratio(GSR)as a key indicator to reveal the swelling change in SEI.The GSR of bilayer SEI merely increases from1.73 to 3.16 after the 300th cycle,which enables the corresponding graphite‖Li battery to achieve longer cycle stability.The capacity retention is improved by 47.5% after 300 cycles at 0.5 C.The correlation among SEI spatial structure,swelling behavior,and battery performance provides a new direction for electrolyte optimization and interphase structure design of high energy density batteries.
基金the Natural Sci-ence Foundation of Shandong Province(Nos.ZR2022QE014,ZR2021QH237)the Guangdong Provincial Key Laboratory of Elec-tronic Functional Materials and Devices(No.EFMD2022017M)+1 种基金the National Natural Science Foundation of China(Grant Nos.52401221,51971120,U1902221)the Medical StaffScience and Technology Plan of Shandong Province(No.SDYWZGKCJH2022073).
文摘Succinonitrile has shown significant promise for application in polymer electrolytes for solid-state lithium metal batteries due to its high ionic conductivity at low-temperature.However,the use of Succinonitrile is limited due to its corrosion of Li metal.Herein,we report a solid polymer electrolyte with high ionic conductivity(2.17×10^(−3)S cm^(−1),35°C)enhanced by Ti_(3)C_(2)T_(x).Corrosion of the Li anode is prevented due to the Succinonitrile molecules being efficiently anchored by Ti_(3)C_(2)T_(x).Meanwhile,the coordination environment of Li^(+)is weakened due to the introduction of competitive coordination induction effects into the polymer electrolyte,resulting in efficient Li^(+)conduction.Furthermore,the mechanical properties of the electrolyte are enhanced by modulating the ratio of Ti_(3)C_(2)T_(x)to suppress the growth of Li dendrites.Therefore,Li||Li symmetric batteries deliver stable cycling up to 8000 h at 28°C.LiFePO4||Li full batteries exhibit excellent cycling stability of 151.7 mAh g^(−1)with a capacity retention of 99.3%after 300 cycles.This work not only presents a new idea to suppress the corrosion of the Li anode by Succinonitrile but also provides a simple,feasible,and scalable strategy for high-performance Li metal batteries.
基金supported by the National Natural Science Foundation of China(Grant Nos.22225801,W2441009,22408228)。
文摘As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62204235。
文摘This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.52171206 and52271209)Key Project of Hebei Natural Science Foundation(Nos.F2024201031 and E20202201030)+4 种基金Beijing-Tianjin-Hebei Collaborative Innovation Community Construction Project(No.21344301D)the Second Batch of Young Talent of Hebei Province(Nos.70280016160250 and 70280011808)Key Fund in Hebei Province Department of Education China(No.ZD2021014)the Central Government Guide Local Funding Projects for Scientific and Technological Development(Nos.216Z4404G and 206Z4402G)Interdisciplinary Research Program of Natural Science of Hebei University(No.DXK202107)。
文摘The lithium-oxygen battery(LOB)is a promising source of green energy due to its energy density.However,the development of this technology is limited by the insoluble discharge product it produces.In this work,a cathode material with a p-n heterostructure of polyaniline(PANI)/ZnS is prepared to trap visible light,utilizing a ZnS quantum dot(ZnS QD)network to form a large number of photogenerated electron–hole pairs,thus promoting the generation and decomposition of Li_(2)O_(2).The prepared PANI/ZnS has an ultra-low overpotential of 0.06 V under illumination.Furthermore,density functional theory theoretical calculation has demonstrated the ability of the heterostructures to adsorb oxygen-containing intermediates,which not only facilitates the growth of Li_(2)O_(2),but also reduces the reaction energy required to decompose Li_(2)O_(2).The present work provides a solution to the problem of insolubility of discharge products in photo-assisted LOB.
