As a new type of green energy, lithium-ion battery(LIB) has been widely used in various electric portable devices because of its high-voltage, large specific capacity, long cycle life and environmental friendliness [1...As a new type of green energy, lithium-ion battery(LIB) has been widely used in various electric portable devices because of its high-voltage, large specific capacity, long cycle life and environmental friendliness [1,2]. However, today’s anode materials of commercial LIBs cannot meet the further development requirements of smart devices and electric car due to the limitations of the electrode capacity(e.g. 372 mAh g-1 for graphite).展开更多
This study aims to develop a chloride diffusion simulation method that considers the hydration microstructure and pore solution properties during the hydration of tricalcium silicate(C3S).The method combines the hydra...This study aims to develop a chloride diffusion simulation method that considers the hydration microstructure and pore solution properties during the hydration of tricalcium silicate(C3S).The method combines the hydration simulation,thermodynamic calculation,and finite element analysis to examine the effects of pore solution,including effect of electrochemical potential,effect of chemical activity,and effect of mechanical interactions between ions,on the chloride effective diffusion coefficient of hydrated C3S paste.The results indicate that the effect of electrochemical potential on chloride diffusion becomes stronger with increasing hydration age due to the increase in the content of hydrated calcium silicate;as the hydration age increases,the effect of chemical activity on chloride diffusion weakens when the number of diffusible elements decreases;the effect of mechanical interactions between ions on chloride diffusion decreases with the increase of hydration age.展开更多
The search for safer next-generation lithium-ion batteries(LIBs)has driven significant research on non-toxic,non-flammable solid electrolytes.However,their electrochemical performance often falls short.This work prese...The search for safer next-generation lithium-ion batteries(LIBs)has driven significant research on non-toxic,non-flammable solid electrolytes.However,their electrochemical performance often falls short.This work presents a simple,one-step photopolymerization process for synthesizing biphasic liquid–solid ionogel electrolytes using acrylic acid monomer and P_(111i4)FSI ionic liquid.We investigated the impact of lithium salt concentration and temperature on ion diffusion,particularly lithium-ion(Li^(+))mobility,within these ionogels.Pulsed-field gradient nuclear magnetic resonance(PFG-NMR)revealed enhanced Li^(+)diffusion in the acrylic acid(AA)-based ionogels compared to their non-confined ionic liquid counterparts.Remarkably,Li^(+)diffusion remained favorable in the ionogels regardless of salt concentration.These AA-based ionogels demonstrate very good ionic conductivity(>1 mS cm^(-1) at room temperature)and a wide electrochemical window(up to 5.3 V vs Li^(+)/Li^(0)).These findings suggest significant promise for AA-based ionogels as polymer solid electrolytes in future solid-state battery applications.展开更多
The Lithium-ion deintercalation induces a significant volume change in battery electrodes during charging and discharging processes,which in turn generates a large diffusion-induced stress(DIS).This stress can cause m...The Lithium-ion deintercalation induces a significant volume change in battery electrodes during charging and discharging processes,which in turn generates a large diffusion-induced stress(DIS).This stress can cause microstructural damage,consequently degrading battery performance.This work simplifies the particles making up the electrode into spheres and studies the impact of the surface microstructure on the distribution of diffusion-induced stress.A mechanical-chemical coupling model was established to study the DIS in secondary particles,which were constructed by adding convex particles to the ball-shaped particle surfaces of the electrode material.It is observed that an increase in the number of convex particles results in a higher concentration of lithium ions within the electrode material,along with the first principal stresses within the material particles.In addition,the convex particles increase the local stresses around the ball-shaped particle surface.Therefore,a round surface on the electrode material particles is beneficial for preventing potential fractures.展开更多
A numerical study analyzed double diffusion caused by convective and radiative heat transfer in a greenhouse with and without internal humidity sources.Two cases were examined:one considering temperature and mass conc...A numerical study analyzed double diffusion caused by convective and radiative heat transfer in a greenhouse with and without internal humidity sources.Two cases were examined:one considering temperature and mass concentration gradients on vertical walls and another incorporating internal humidity sources,enhancing convective and diffusive flows.Four configurations were analyzed by varying the length of the greenhouse,and the Rayleigh number was calculated over a range from 2.29×10^(10) to 6.07×10^(12).Simulations modeled the greenhouse interior six times a day(8:00 a.m.to 7:00 p.m.),accounting for external temperature,humidity,and solar radiation.The Finite Volume Method solved the governing equations using the k-εturbulence model for the turbulent flow regime.Results showed a maximum temperature of 50℃ at 2:50 p.m.and a relative humidity of 84.12%.Adjusting inlet temperature and humidity effectively mitigated external weather effects.Adding humidity sources improved greenhouse performance,increasing humidity concentration by 4.93 to 5.35 times,particularly at 2:50 and 4:20 p.m.Convective and radiative Nusselt and Sherwood numbers were plotted for both cases,revealing higher humidity levels with internal sources,highlighting their importance in optimizing greenhouse microclimates.展开更多
During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Jan...During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Janus sphere possesses two distinct surfaces.These two surfaces elicit different hydrodynamic interactions with ambient fluids or other interactions in response to environmental stimuli,such as chemical gradients,magnetic fields,and even light.The diffusion of Janus spheres,particularly when controlled by a remotely applied field,has inspired various applications,ranging from the design of micro-swimmers and novel procedures for probing the mechanical properties of suspensions to the fabrication of composites with enhanced performance.In this work,we report a systematic analysis of field-controlled diffusion of Janus spheres.Commencing with stochastic differential equations of motion at the microscale,we derive a coarse-grained Fokker-Planck equation at the macroscale,describing the evolution of the probability distribution function of the Janus sphere in terms of its position and orientation.Leveraging the concept of the hydrodynamic center,we derive,for the first time,explicit generalized Stokes-Einstein relations for long-time effective diffusivity,incorporating the effects of both the surface discontinuity of the Janus sphere and the external fields.The formulae enable predictions of the effective diffusivity as it varies with the slip length and characteristic angle of Janus spheres,and reveal the impact of an aligning potential field on the diffusion coefficients both parallel and perpendicular to the direction of the field.This work not only deepens the understanding of field-controlled diffusion of Janus particles,but also holds a meaningful impact on the future applications in microfluidics and related fields.展开更多
Weak turbulence often occurs during heavy pollution events in eastern China(EC).However,existing mesoscale meteorology models cannot accurately simulate turbulent diffusion under weakened turbulence,particularly under...Weak turbulence often occurs during heavy pollution events in eastern China(EC).However,existing mesoscale meteorology models cannot accurately simulate turbulent diffusion under weakened turbulence,particularly under the nocturnal stable boundary layer(SBL),often leading to significant turbulent diffusivity underestimation and surface aerosol overestimation.In this study,a new parameterization of minimum turbulent diffusivity coefficient(Kz_(min))was tested and applied to PM_(2.5)simulations in EC under SBL conditions in WRF-Chem.The original model overestimated the PM_(2.5)simulation and the simulation performance can be improved by adding Kz_(min).Sensitivity experiments revealed different ranges of available Kz_(min)values over the northern(0.8 to 1.2 m^(2)/s)and southern(1.0 to 1.5 m^(2)/s)regions of EC.The geographically related Kz_(min)was parameterized by sensible heat flux(H)and latent heat flux(LE),which also exhibited regional differences related to the climate and underlying surface.Furthermore,we assign physical significance to the parameterized formula Kz_(min)and found that our proposed Kz_(min)scheme can reasonably yield dynamic Kz_(min)values over EC.The revised Kz_(min)scheme(EXP_(NEW))enhanced the turbulent diffusion(north:0.93 m^(2)/s,south:1.10 m^(2)/s on average)in the SBL,simultaneously improving the PM_(2.5)simulations on the surface(north:65.78 to 0.67μg/m^(3);south 30.48 to 12.86μg/m^(3))and upper SBL.A process analysis showed that vertical mixing was the key process for improving PM_(2.5)simulations on the surface in EXP_(NEW).This study highlighted the importance of improving turbulent diffusion in current mesoscale models under SBL and has great significance for aerosol simulation.展开更多
Strategies for achieving high-energy-density lithium-ion batteries include using high-capacity materials such as high-nickel NCM,increasing the active material content in the electrode by utilizing high-conductivity c...Strategies for achieving high-energy-density lithium-ion batteries include using high-capacity materials such as high-nickel NCM,increasing the active material content in the electrode by utilizing high-conductivity carbon nanotubes(CNT)conductive materials,and electrode thickening.However,these methods are still limited due to the limitation in the capacity of high-nickel NCM,aggregation of CNT conductive materials,and nonuniform material distribution of thick-film electrodes,which ultimately damage the mechanical and electrical integrity of the electrode,leading to a decrease in electrochemical performance.Here,we present an integrated binder-CNT composite dispersion solution to realize a high-solids-content(>77 wt%)slurry for high-mass-loading electrodes and to mitigate the migration of binder and conductive additives.Indeed,the approach reduces solvent usage by approximately 30%and ensures uniform conductive additive-binder domain distribution during electrode manufacturing,resulting in improved coating quality and adhesive strength for high-mass-loading electrodes(>12 mAh cm^(−2)).In terms of various electrode properties,the presented electrode showed low resistance and excellent electrochemical properties despite the low CNT contents of 0.6 wt%compared to the pristine-applied electrode with 0.85 wt%CNT contents.Moreover,our strategy enables faster drying,which increases the coating speed,thereby offering potential energy savings and supporting carbon neutrality in wet-based electrode manufacturing processes.展开更多
Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expa...Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expansion during cycling.Here,we synthesized a novel silicon/carbon(Si/C)anode doped with ZnO via a template-derived method and high-temperature carbonization.The carbon structure,originated from metal-organic frameworks(MOFs)and ZnO doping,substantially enhanced the electrochemical properties of the composite material.It exhibited an initial capacity of 2100.3 mA h g^(-1)at a current density of 0.2 A g^(-1)and demonstrated excellent capacity retention over successive cycles.Moreover,the composite material displayed superior rate performance at higher current densities of 2 A g^(-1)and 3 A g^(-1).To address the low initial Coulombic efficiency(ICE)of siliconbased materials,we adopted a direct contact prelithiation approach and optimized the lithiation process by controlling the prelithiation time.After 30 min of prelithiation,the ICE reached 97.9%,thereby reducing the initial irreversible capacity loss(ICL)and realizing stable discharge-charge in subsequent cycles.This rational design provides valuable insights for achieving high-performance silicon anode.展开更多
Battery energy storage systems bolster power grids’absorption capacity,however,battery safety issues remain a formidable challenge.Timely and pre-cise fault diagnosis,coupled with early-stage fault warn-ings,is cruci...Battery energy storage systems bolster power grids’absorption capacity,however,battery safety issues remain a formidable challenge.Timely and pre-cise fault diagnosis,coupled with early-stage fault warn-ings,is crucial.This study introduces an eigen decompo-sition-based multi-fault diagnosis approach for lithi-umion battery packs,enabling online diagnosis of short circuits,electrical connection faults,and voltage sensor malfunctions.By incorporating an interleaved measurement topology,precise fault type differentiation is achieved.Eigenvector matching analysis is employed to increase sensitivity to fault characteristics and enhance robustness.The interleaved topology can be seamlessly integrated using common voltage measurement solutions,eliminating the need for additional design complexities,while sensor number redundancy enhances fault tolerance of battery management systems(BMS).A cloud-side collaboration method is proposed,where the BMS functions as an edge device for specific data computations,while the parameters are fine-tuned by the server through big data analytics.This approach circumvents cumbersome server calculations,thereby curbing server cost escalation.The edge computing process is divided into two steps,with partial calculations often sufficient to evaluate battery safety,thus reducing the computational load on edge devices.Several battery tests are conducted,and the results confirm the method’s capability,feasibility,and validity in early-stage fault diagnosis.展开更多
With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stabil...With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.展开更多
The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches ...The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches often suffer from reduced accuracy under dynamically uncertain state-of-charge(SOC)operating ranges and heterogeneous aging stresses.This study presents a unified SOH estimation framework that integrates physics-informed modeling,subspace identification,and Transformer-based learning.A reduced-order model is derived from simplified electrochemical dynamics,providing an interpretable and computationally efficient representation of battery behavior.Subspace identification across a wide SOC and SOH range yields degradation-sensitive features,which the Transformer uses to capture long-range aging dynamics via multi-head self-attention.Experiments on LiFePO4 cells under joint-cell training show consistently accurate SOH estimation,with a maximum error of 1.39%,demonstrating the framework’s effectiveness in decoupling SOC and SOH effects.In cross-cell validation,where training and validation are performed on different cells,the model maintains a maximum error of 2.06%,confirming strong generalization to unseen aging trajectories.Comparative experiments on LiFePO_(4)and public LiCoO_(2)datasets confirm the framework’s cross-chemistry applicability.By extracting low-dimensional,physically interpretable features via subspace identification,the framework significantly reduces training cost while maintaining high SOH estimation accuracy,outperforming conventional data-driven models lacking physical guidance.展开更多
Lithium-ion(Li-ion)batteries stand as the dominant energy storage solution,despite their widespread adoption,precisely determining the state of charge(SOC)continues to pose significant difficulties,with direct implica...Lithium-ion(Li-ion)batteries stand as the dominant energy storage solution,despite their widespread adoption,precisely determining the state of charge(SOC)continues to pose significant difficulties,with direct implications for battery safety,operational reliability,and overall performance.Current SOC estimation techniques often demonstrate limited accuracy,particularly when confronted with complex operational scenarios and wide temperature variations,where their generalization capacity and dynamic adaptation prove insufficient.To address these shortcomings,this work presents a PSO-TCN-Transformer network model for SOC estimation.This research uses the Particle Swarm Optimization(PSO)method to automatically configure the architectural parameters of the Temporal Convolutional Network(TCN)and Transformer components.This automated optimization enhances the model’s ability to represent the dynamically evolving nature of SOC.Additionally,this integrated framework significantly increases the model’s capacity to capture SOC dynamics in complex operational scenarios.During training and evaluation using a comprehensive dataset that covers complex operating conditions and a broad temperature spanning from−20℃ to 40℃,the proposed model achieves a root mean square error(RMSE)of less than 0.6%,a maximum absolute error(MAXE)below 4.0%,and a coefficient of determination(R^(2))of 99.99%.Additional comparative experiments on data from an energy storage company further verify the model’s superior performance,with an RMSE of 1.18%and an MAXE of 1.95%.The implications of this work extend to the development of optimization strategies and hybrid architectures,providing insights that can be adapted for state estimation across a range of complex dynamic systems.展开更多
Carbon coatings for silicon(Si)-based anode materials are essential for designing high-performance Li-ion batteries(LIBs).The coatings prevent direct contact with the electrolyte and enhance anode performance.However,...Carbon coatings for silicon(Si)-based anode materials are essential for designing high-performance Li-ion batteries(LIBs).The coatings prevent direct contact with the electrolyte and enhance anode performance.However,conventional carbon coatings are limited by their volume expansion and structural degradation,which lead to capacity fading and reduced durability.This study introduces a scalable and practical one-step carbon-coating strategy for directly coating silicon suboxide(SiO_(x))-based materials using aqueous quasi-defect-free reduced graphene oxide(QrGO)without post-treatment,unlike conventional graphene oxide(GO)-based coating methods.This simple process enables uniform encapsulation with QrGO for a highly adhesive and conductive coating.The QrGO-based composite anode material has several advantages,including reduced cracking due to volume expansion and enhanced charge carrier transport,as well as an increased Si content of 20 wt.%compared to the 5 wt.%in typical commercial Si-based active materials.In particular,the capacity retention of the QrGO-coated Si electrodes dramatically increases at high C-rate.The full cell exhibited long-term stability and capacity that were twice that of commercial SiO_(x)-based cells.Therefore,the QrGO-based one-step coating process represents a scalable,transformative,and commercially viable strategy for developing high-performance LIBs.展开更多
Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been i...Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.展开更多
Commercial carbonate electrolytes suffer from ion transport difficulty in bulk electrolytes and interphase at low temperatures,bringing challenges to the application of lithium-ion batteries(LIBs)at low temperatures.H...Commercial carbonate electrolytes suffer from ion transport difficulty in bulk electrolytes and interphase at low temperatures,bringing challenges to the application of lithium-ion batteries(LIBs)at low temperatures.Herein,the ester solvent of methyl propionate(MP)with low melting point and low viscosity was used to tackle ion transport difficulty in electrolytes.Fluorinated ester was further added to accelerate interfacial transport through intermolecular interactions.The influence of fluorinated esters with different fluorination degrees on the solvation structure of electrolytes and the performance of batteries was further studied.As a result,methyl pentafluoropropionate(M5F)with five fluorine atoms was selected for its optimal interactions with both Li+and MP solvent in the primary solvation structure,contributing to desired solvation structure for fast interfacial transport.The LiFePO_(4)(LFP)||graphite cell with LiFSI-MP-M5F electrolyte exhibited a high cyclability of 85.8%after 120 cycles and retained 81.2%of room-temperature capacity when charged and discharged at−30℃.1 Ah LFP||graphite pouch cell with high cathode loading(20 mg/cm^(2))in LiFSI-MP-M5F electrolyte exhibited 0.85 Ah capacity when charged and discharged at−20℃.This work provides a guidance for electrolyte design by synergistic fluorinated and non-fluorinated solvents for LIBs at low-temperature application.展开更多
Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently wor...Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently worth concentrating,which can dilate the interlayer spacing of graphite to adjust the electrochemical storage performance in carbon anodes.However,the reported doping strategies of the modified HC have only resulted in limited improvement,especially unobvious effects on tuning porous structure.In this study,tannin extract and K_(2)SO_(4) are respectively utilized as carbon source and sulfur source for the fabrication of HC,in which K_(2)SO_(4) can contribute to the heteroatom doping,and the pore forming as well.The tannin-derived sulfur-doped carbon anode shows the excellent cycle stability,achieving a high reversible capacity of 520.5 mAh/g at a current density of 100 mA/g.Even after 500 cycles at a current density of 3 A/g,a high specific capacity of 236.7 mAh/g and a capacity retention rate of 92.6%can be reserved.Compared with the initial carbon,the adsorption energy of Na^(+)is multifold times higher,whereas Na^(+)diffusion energy barriers manyfold decrease.Moreover,the full battery assembled with Na_(3)V_(2)(PO_(4))_(3)/tannin-based HC demonstrates a stable cycling performance.This work can manifest the potentiality of the tannin-based electrode as anode for a high-performance sodium-ion batteries(SIBs),which could especially offer an explanation of Na^(+)storage and solid-electrolyte interface(SEI)stability to the electrochemical performance.展开更多
基金supported by National Key Research and Development Program of China (No.2017YFB0702100)the National Natural Science Foundation of China (No.11404017)+4 种基金Technology Foundation for Selected Overseas Chinese Scholar, Ministry of Human Resources and Social Security of China, Beijing Natural Science Foundation (No.20192029)supported by the European Regional Development Fund in the IT4Innovations National Supercomputing Center-Path to Exascale project, No.CZ.02.1.01/ 0.0/0.0/16_013/0001791 within the Operational Programme Research, Development and Education by the Ministry of Education, Youth, and Sport of the Czech Republicgrant No.17-27790S of the Czech Science FoundationsMobility grant No.8J18DE004 of the Ministry of Education, Youngth and Sports of the Czech RepublicSGS No.SP2019/110。
文摘As a new type of green energy, lithium-ion battery(LIB) has been widely used in various electric portable devices because of its high-voltage, large specific capacity, long cycle life and environmental friendliness [1,2]. However, today’s anode materials of commercial LIBs cannot meet the further development requirements of smart devices and electric car due to the limitations of the electrode capacity(e.g. 372 mAh g-1 for graphite).
基金Funded by the Natural Science Foundation of Jiangsu Province(No.BK20241529)China Postdoctoral Science Foundation(No.2024M750736)。
文摘This study aims to develop a chloride diffusion simulation method that considers the hydration microstructure and pore solution properties during the hydration of tricalcium silicate(C3S).The method combines the hydration simulation,thermodynamic calculation,and finite element analysis to examine the effects of pore solution,including effect of electrochemical potential,effect of chemical activity,and effect of mechanical interactions between ions,on the chloride effective diffusion coefficient of hydrated C3S paste.The results indicate that the effect of electrochemical potential on chloride diffusion becomes stronger with increasing hydration age due to the increase in the content of hydrated calcium silicate;as the hydration age increases,the effect of chemical activity on chloride diffusion weakens when the number of diffusible elements decreases;the effect of mechanical interactions between ions on chloride diffusion decreases with the increase of hydration age.
基金funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions COFUND—Grant Agreement No:945357.
文摘The search for safer next-generation lithium-ion batteries(LIBs)has driven significant research on non-toxic,non-flammable solid electrolytes.However,their electrochemical performance often falls short.This work presents a simple,one-step photopolymerization process for synthesizing biphasic liquid–solid ionogel electrolytes using acrylic acid monomer and P_(111i4)FSI ionic liquid.We investigated the impact of lithium salt concentration and temperature on ion diffusion,particularly lithium-ion(Li^(+))mobility,within these ionogels.Pulsed-field gradient nuclear magnetic resonance(PFG-NMR)revealed enhanced Li^(+)diffusion in the acrylic acid(AA)-based ionogels compared to their non-confined ionic liquid counterparts.Remarkably,Li^(+)diffusion remained favorable in the ionogels regardless of salt concentration.These AA-based ionogels demonstrate very good ionic conductivity(>1 mS cm^(-1) at room temperature)and a wide electrochemical window(up to 5.3 V vs Li^(+)/Li^(0)).These findings suggest significant promise for AA-based ionogels as polymer solid electrolytes in future solid-state battery applications.
基金supported by the Science and Technology Project of the Hebei Education Department(JZX2023004)the Research Program of Local Science and Technology Development under the Guidance of Central China(246Z1808G)the support from the“Yuanguang”Scholar Program of Hebei University of Technology.
文摘The Lithium-ion deintercalation induces a significant volume change in battery electrodes during charging and discharging processes,which in turn generates a large diffusion-induced stress(DIS).This stress can cause microstructural damage,consequently degrading battery performance.This work simplifies the particles making up the electrode into spheres and studies the impact of the surface microstructure on the distribution of diffusion-induced stress.A mechanical-chemical coupling model was established to study the DIS in secondary particles,which were constructed by adding convex particles to the ball-shaped particle surfaces of the electrode material.It is observed that an increase in the number of convex particles results in a higher concentration of lithium ions within the electrode material,along with the first principal stresses within the material particles.In addition,the convex particles increase the local stresses around the ball-shaped particle surface.Therefore,a round surface on the electrode material particles is beneficial for preventing potential fractures.
文摘A numerical study analyzed double diffusion caused by convective and radiative heat transfer in a greenhouse with and without internal humidity sources.Two cases were examined:one considering temperature and mass concentration gradients on vertical walls and another incorporating internal humidity sources,enhancing convective and diffusive flows.Four configurations were analyzed by varying the length of the greenhouse,and the Rayleigh number was calculated over a range from 2.29×10^(10) to 6.07×10^(12).Simulations modeled the greenhouse interior six times a day(8:00 a.m.to 7:00 p.m.),accounting for external temperature,humidity,and solar radiation.The Finite Volume Method solved the governing equations using the k-εturbulence model for the turbulent flow regime.Results showed a maximum temperature of 50℃ at 2:50 p.m.and a relative humidity of 84.12%.Adjusting inlet temperature and humidity effectively mitigated external weather effects.Adding humidity sources improved greenhouse performance,increasing humidity concentration by 4.93 to 5.35 times,particularly at 2:50 and 4:20 p.m.Convective and radiative Nusselt and Sherwood numbers were plotted for both cases,revealing higher humidity levels with internal sources,highlighting their importance in optimizing greenhouse microclimates.
基金Project supported by the National Natural Science Foundation of China(Nos.12302079 and 11521202)the National Natural Science Foundation of U.S.A.(No.DMS-2306254)。
文摘During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Janus sphere possesses two distinct surfaces.These two surfaces elicit different hydrodynamic interactions with ambient fluids or other interactions in response to environmental stimuli,such as chemical gradients,magnetic fields,and even light.The diffusion of Janus spheres,particularly when controlled by a remotely applied field,has inspired various applications,ranging from the design of micro-swimmers and novel procedures for probing the mechanical properties of suspensions to the fabrication of composites with enhanced performance.In this work,we report a systematic analysis of field-controlled diffusion of Janus spheres.Commencing with stochastic differential equations of motion at the microscale,we derive a coarse-grained Fokker-Planck equation at the macroscale,describing the evolution of the probability distribution function of the Janus sphere in terms of its position and orientation.Leveraging the concept of the hydrodynamic center,we derive,for the first time,explicit generalized Stokes-Einstein relations for long-time effective diffusivity,incorporating the effects of both the surface discontinuity of the Janus sphere and the external fields.The formulae enable predictions of the effective diffusivity as it varies with the slip length and characteristic angle of Janus spheres,and reveal the impact of an aligning potential field on the diffusion coefficients both parallel and perpendicular to the direction of the field.This work not only deepens the understanding of field-controlled diffusion of Janus particles,but also holds a meaningful impact on the future applications in microfluidics and related fields.
基金supported by the National Natural Science Foundation of China(Nos.92044302 and 42275115)the Natural Science Foundation of Jiangsu Province(No.BK20241711)the Postgraduate Research and Practice Innovation of Jiangsu Province Program(No.KYCX20_0952)。
文摘Weak turbulence often occurs during heavy pollution events in eastern China(EC).However,existing mesoscale meteorology models cannot accurately simulate turbulent diffusion under weakened turbulence,particularly under the nocturnal stable boundary layer(SBL),often leading to significant turbulent diffusivity underestimation and surface aerosol overestimation.In this study,a new parameterization of minimum turbulent diffusivity coefficient(Kz_(min))was tested and applied to PM_(2.5)simulations in EC under SBL conditions in WRF-Chem.The original model overestimated the PM_(2.5)simulation and the simulation performance can be improved by adding Kz_(min).Sensitivity experiments revealed different ranges of available Kz_(min)values over the northern(0.8 to 1.2 m^(2)/s)and southern(1.0 to 1.5 m^(2)/s)regions of EC.The geographically related Kz_(min)was parameterized by sensible heat flux(H)and latent heat flux(LE),which also exhibited regional differences related to the climate and underlying surface.Furthermore,we assign physical significance to the parameterized formula Kz_(min)and found that our proposed Kz_(min)scheme can reasonably yield dynamic Kz_(min)values over EC.The revised Kz_(min)scheme(EXP_(NEW))enhanced the turbulent diffusion(north:0.93 m^(2)/s,south:1.10 m^(2)/s on average)in the SBL,simultaneously improving the PM_(2.5)simulations on the surface(north:65.78 to 0.67μg/m^(3);south 30.48 to 12.86μg/m^(3))and upper SBL.A process analysis showed that vertical mixing was the key process for improving PM_(2.5)simulations on the surface in EXP_(NEW).This study highlighted the importance of improving turbulent diffusion in current mesoscale models under SBL and has great significance for aerosol simulation.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2022M3H4A6A0103720142)the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL24011-000)+1 种基金the Technology Innovation Program(RS-2024-00404165)through the Korea Planning&Evaluation Institute of Industrial Technology(KEIT)funded by the Ministry of Trade,Industry&Energy(MOTIE,Korea)supported by the Samsung SDI Co.Ltd.and the Korea Institute of Science and Technology(KIST)institutional program(2E33942,2E3394B)。
文摘Strategies for achieving high-energy-density lithium-ion batteries include using high-capacity materials such as high-nickel NCM,increasing the active material content in the electrode by utilizing high-conductivity carbon nanotubes(CNT)conductive materials,and electrode thickening.However,these methods are still limited due to the limitation in the capacity of high-nickel NCM,aggregation of CNT conductive materials,and nonuniform material distribution of thick-film electrodes,which ultimately damage the mechanical and electrical integrity of the electrode,leading to a decrease in electrochemical performance.Here,we present an integrated binder-CNT composite dispersion solution to realize a high-solids-content(>77 wt%)slurry for high-mass-loading electrodes and to mitigate the migration of binder and conductive additives.Indeed,the approach reduces solvent usage by approximately 30%and ensures uniform conductive additive-binder domain distribution during electrode manufacturing,resulting in improved coating quality and adhesive strength for high-mass-loading electrodes(>12 mAh cm^(−2)).In terms of various electrode properties,the presented electrode showed low resistance and excellent electrochemical properties despite the low CNT contents of 0.6 wt%compared to the pristine-applied electrode with 0.85 wt%CNT contents.Moreover,our strategy enables faster drying,which increases the coating speed,thereby offering potential energy savings and supporting carbon neutrality in wet-based electrode manufacturing processes.
基金supported by the National Key R&D Program of China(No.2022YFA1504100)the Anhui Provincial Major Science and Technology Project(No.202203a05020017)+4 种基金the National Natural Science Foundation of China(Nos.52222210,51925207,U1910210,52161145101,51972067,51902062,and 52002083)the“Transformational Technologies for Clean Energy and Demonstration”Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA21000000)the National Synchrotron Radiation Laboratory(No.KY2060000173)the Joint Fund of the Yulin University and the Dalian National Laboratory for Clean Energy(No.YLU-DNL Fund 2021002)the Fundamental Research Funds for the Central Universities(No.WK2060140026)。
文摘Silicon possesses a high theoretical capacity,making it a potential contender for lithium-ion battery(LIB)anodes.Nonetheless,its practical usage is challenged by low electrical conductivity and significant volume expansion during cycling.Here,we synthesized a novel silicon/carbon(Si/C)anode doped with ZnO via a template-derived method and high-temperature carbonization.The carbon structure,originated from metal-organic frameworks(MOFs)and ZnO doping,substantially enhanced the electrochemical properties of the composite material.It exhibited an initial capacity of 2100.3 mA h g^(-1)at a current density of 0.2 A g^(-1)and demonstrated excellent capacity retention over successive cycles.Moreover,the composite material displayed superior rate performance at higher current densities of 2 A g^(-1)and 3 A g^(-1).To address the low initial Coulombic efficiency(ICE)of siliconbased materials,we adopted a direct contact prelithiation approach and optimized the lithiation process by controlling the prelithiation time.After 30 min of prelithiation,the ICE reached 97.9%,thereby reducing the initial irreversible capacity loss(ICL)and realizing stable discharge-charge in subsequent cycles.This rational design provides valuable insights for achieving high-performance silicon anode.
基金supported in part by the National Natural Science Foundation of China(No.62133007)Shandong Provincial Key Research and Development Program(No.2024CXPT052).
文摘Battery energy storage systems bolster power grids’absorption capacity,however,battery safety issues remain a formidable challenge.Timely and pre-cise fault diagnosis,coupled with early-stage fault warn-ings,is crucial.This study introduces an eigen decompo-sition-based multi-fault diagnosis approach for lithi-umion battery packs,enabling online diagnosis of short circuits,electrical connection faults,and voltage sensor malfunctions.By incorporating an interleaved measurement topology,precise fault type differentiation is achieved.Eigenvector matching analysis is employed to increase sensitivity to fault characteristics and enhance robustness.The interleaved topology can be seamlessly integrated using common voltage measurement solutions,eliminating the need for additional design complexities,while sensor number redundancy enhances fault tolerance of battery management systems(BMS).A cloud-side collaboration method is proposed,where the BMS functions as an edge device for specific data computations,while the parameters are fine-tuned by the server through big data analytics.This approach circumvents cumbersome server calculations,thereby curbing server cost escalation.The edge computing process is divided into two steps,with partial calculations often sufficient to evaluate battery safety,thus reducing the computational load on edge devices.Several battery tests are conducted,and the results confirm the method’s capability,feasibility,and validity in early-stage fault diagnosis.
基金supported by the National Natural Science Foundation of China(52477222)the Key Research and Development Program of Shaanxi Province(2024GX-YBXM-442)the Xinjiang Uygur Autonomous Region Key R&D Program under Grant(2022B01019-2)。
文摘With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.
基金supported by the National Natural Science Foundation of China(No.52207228)the Beijing Natural Science Foundation,China(No.3224070)the National Natural Science Foundation of China(No.52077208).
文摘The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches often suffer from reduced accuracy under dynamically uncertain state-of-charge(SOC)operating ranges and heterogeneous aging stresses.This study presents a unified SOH estimation framework that integrates physics-informed modeling,subspace identification,and Transformer-based learning.A reduced-order model is derived from simplified electrochemical dynamics,providing an interpretable and computationally efficient representation of battery behavior.Subspace identification across a wide SOC and SOH range yields degradation-sensitive features,which the Transformer uses to capture long-range aging dynamics via multi-head self-attention.Experiments on LiFePO4 cells under joint-cell training show consistently accurate SOH estimation,with a maximum error of 1.39%,demonstrating the framework’s effectiveness in decoupling SOC and SOH effects.In cross-cell validation,where training and validation are performed on different cells,the model maintains a maximum error of 2.06%,confirming strong generalization to unseen aging trajectories.Comparative experiments on LiFePO_(4)and public LiCoO_(2)datasets confirm the framework’s cross-chemistry applicability.By extracting low-dimensional,physically interpretable features via subspace identification,the framework significantly reduces training cost while maintaining high SOH estimation accuracy,outperforming conventional data-driven models lacking physical guidance.
基金funded in part by the Doctoral Scientific Research Foundation of Beijing University of Civil Engineering and Architecture under Grant ZF15054in part by the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture under Grant GJZJ20220802in part by the BUCEA Post Graduate Innovation Project under Grant PG2024095.
文摘Lithium-ion(Li-ion)batteries stand as the dominant energy storage solution,despite their widespread adoption,precisely determining the state of charge(SOC)continues to pose significant difficulties,with direct implications for battery safety,operational reliability,and overall performance.Current SOC estimation techniques often demonstrate limited accuracy,particularly when confronted with complex operational scenarios and wide temperature variations,where their generalization capacity and dynamic adaptation prove insufficient.To address these shortcomings,this work presents a PSO-TCN-Transformer network model for SOC estimation.This research uses the Particle Swarm Optimization(PSO)method to automatically configure the architectural parameters of the Temporal Convolutional Network(TCN)and Transformer components.This automated optimization enhances the model’s ability to represent the dynamically evolving nature of SOC.Additionally,this integrated framework significantly increases the model’s capacity to capture SOC dynamics in complex operational scenarios.During training and evaluation using a comprehensive dataset that covers complex operating conditions and a broad temperature spanning from−20℃ to 40℃,the proposed model achieves a root mean square error(RMSE)of less than 0.6%,a maximum absolute error(MAXE)below 4.0%,and a coefficient of determination(R^(2))of 99.99%.Additional comparative experiments on data from an energy storage company further verify the model’s superior performance,with an RMSE of 1.18%and an MAXE of 1.95%.The implications of this work extend to the development of optimization strategies and hybrid architectures,providing insights that can be adapted for state estimation across a range of complex dynamic systems.
基金supported by Korea Electrotechnology Research Institute(KERI)Primary research program through the National Research Council of Science&Technology(NST)funded by the Ministry of Science and ICT(MSIT)(No.25A01015)by the Technology Innovation Program(20019091)funded by the Ministry of Trade,Industry&Energy(MOTIE,Korea)by the National Research Council of Science&Technology(NST)grant from the Korea government(MSIT)(No.GTL24012-000).
文摘Carbon coatings for silicon(Si)-based anode materials are essential for designing high-performance Li-ion batteries(LIBs).The coatings prevent direct contact with the electrolyte and enhance anode performance.However,conventional carbon coatings are limited by their volume expansion and structural degradation,which lead to capacity fading and reduced durability.This study introduces a scalable and practical one-step carbon-coating strategy for directly coating silicon suboxide(SiO_(x))-based materials using aqueous quasi-defect-free reduced graphene oxide(QrGO)without post-treatment,unlike conventional graphene oxide(GO)-based coating methods.This simple process enables uniform encapsulation with QrGO for a highly adhesive and conductive coating.The QrGO-based composite anode material has several advantages,including reduced cracking due to volume expansion and enhanced charge carrier transport,as well as an increased Si content of 20 wt.%compared to the 5 wt.%in typical commercial Si-based active materials.In particular,the capacity retention of the QrGO-coated Si electrodes dramatically increases at high C-rate.The full cell exhibited long-term stability and capacity that were twice that of commercial SiO_(x)-based cells.Therefore,the QrGO-based one-step coating process represents a scalable,transformative,and commercially viable strategy for developing high-performance LIBs.
基金supported by the Cultivation Program for Major Scientific Research Projects of Harbin Institute of Technology(ZDXMPY20180109).
文摘Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.
基金supported by the National Key R&D Program of China(No.2022YFB3803400)National Natural Science Foundation of China(Nos.52102054,52020105010,51927803,52188101 and 52072378)+1 种基金Liaoning Province Science and Technology Planning Project(No.2022-BS-007)Fujian Science and Technology Program(No.2023T3025).
文摘Commercial carbonate electrolytes suffer from ion transport difficulty in bulk electrolytes and interphase at low temperatures,bringing challenges to the application of lithium-ion batteries(LIBs)at low temperatures.Herein,the ester solvent of methyl propionate(MP)with low melting point and low viscosity was used to tackle ion transport difficulty in electrolytes.Fluorinated ester was further added to accelerate interfacial transport through intermolecular interactions.The influence of fluorinated esters with different fluorination degrees on the solvation structure of electrolytes and the performance of batteries was further studied.As a result,methyl pentafluoropropionate(M5F)with five fluorine atoms was selected for its optimal interactions with both Li+and MP solvent in the primary solvation structure,contributing to desired solvation structure for fast interfacial transport.The LiFePO_(4)(LFP)||graphite cell with LiFSI-MP-M5F electrolyte exhibited a high cyclability of 85.8%after 120 cycles and retained 81.2%of room-temperature capacity when charged and discharged at−30℃.1 Ah LFP||graphite pouch cell with high cathode loading(20 mg/cm^(2))in LiFSI-MP-M5F electrolyte exhibited 0.85 Ah capacity when charged and discharged at−20℃.This work provides a guidance for electrolyte design by synergistic fluorinated and non-fluorinated solvents for LIBs at low-temperature application.
基金supported by National Natural Science Foundation of China(Nos.32271791,32171709 and 22475053)Hunan Provincial Natural Science Foundation of China(No.2024JJ7643)Natural Science Foundation of Shanghai(No.22ZR1404100).
文摘Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently worth concentrating,which can dilate the interlayer spacing of graphite to adjust the electrochemical storage performance in carbon anodes.However,the reported doping strategies of the modified HC have only resulted in limited improvement,especially unobvious effects on tuning porous structure.In this study,tannin extract and K_(2)SO_(4) are respectively utilized as carbon source and sulfur source for the fabrication of HC,in which K_(2)SO_(4) can contribute to the heteroatom doping,and the pore forming as well.The tannin-derived sulfur-doped carbon anode shows the excellent cycle stability,achieving a high reversible capacity of 520.5 mAh/g at a current density of 100 mA/g.Even after 500 cycles at a current density of 3 A/g,a high specific capacity of 236.7 mAh/g and a capacity retention rate of 92.6%can be reserved.Compared with the initial carbon,the adsorption energy of Na^(+)is multifold times higher,whereas Na^(+)diffusion energy barriers manyfold decrease.Moreover,the full battery assembled with Na_(3)V_(2)(PO_(4))_(3)/tannin-based HC demonstrates a stable cycling performance.This work can manifest the potentiality of the tannin-based electrode as anode for a high-performance sodium-ion batteries(SIBs),which could especially offer an explanation of Na^(+)storage and solid-electrolyte interface(SEI)stability to the electrochemical performance.
