In anode free batteries(AFBs), the current collector acts as anode simultaneously and has large volume expansion which is generally considered as a negative effect decreasing the structural stability of a battery. Mor...In anode free batteries(AFBs), the current collector acts as anode simultaneously and has large volume expansion which is generally considered as a negative effect decreasing the structural stability of a battery. Moreover, despite many studies on the fast lithium diffusion in the current collector materials of AFB such as copper and aluminum, the involved Li diffusion mechanism in these materials remains poorly understood. Through first-principles calculation and stress-assisted diffusion equations, here we study the Li diffusion mechanism in several current collectors and related alloys and clarify the effect of volume expansion on Li diffusion respectively. It is suggested that due to the lower Li migration barriers in aluminum and tin, they should be more suitable to be used as AFB anodes, compared to copper, silver, and lead. The Li diffusion facilitation in copper with a certain number of vacancies is proposed to explain why the use of copper with a thickness≤100 nm as the protective coating on the anode improves the lifetime of the batteries. We show that the volume expansion has a positive effect on Li diffusion via mechanical–electrochemical coupling. Namely, the volume expansion caused by Li diffusion will further induce stress which in turn affects the diffusion. These findings not only provide in-depth insight into the operating principle of AFBs, but also open a new route toward design of improved anode through utilizing the positive effect of mechanical–electrochemical coupling.展开更多
Nanostructuring, structure distortion, and/or disorder are the main manipulation techniques to reduce the lattice thermal conductivity and improve the figure of merit of thermoelectric materials. A single-phase α-MgA...Nanostructuring, structure distortion, and/or disorder are the main manipulation techniques to reduce the lattice thermal conductivity and improve the figure of merit of thermoelectric materials. A single-phase α-MgAgSb sample, MgAg0.97Sb0.99, with high thermoelectric performance in near room temperature region was synthesized through a high-energy ball milling with a hot-pressing method. Here, we report the average grain size of 24–28 nm and the accurate structure distortion, which are characterized by high-resolution neutron diffraction and synchrotron x-ray diffraction with Rietveld refinement data analysis. Both the small grain size and the structure distortion have a contribution to the low lattice thermal conductivity in MgAg0.97Sb0.99.展开更多
The Monte Carlo(MC)method is widely used to simulate kinetic processes involving particle hopping through probabilistic modeling and stochastic sampling,particularly in contexts relevant to electrochemical energy stor...The Monte Carlo(MC)method is widely used to simulate kinetic processes involving particle hopping through probabilistic modeling and stochastic sampling,particularly in contexts relevant to electrochemical energy storage,spanning material synthesis,microstructural evolution,and device-level operation.However,the broader applicability of MC simulations is often limited by the requirement for customized definitions of key parameters for each specific physical system.To address this limitation,we propose an adaptive Monte Carlo simulation framework(AMCSF),which adjusts hopping rates,interaction energies,and configuration state parameters on-the-fly in response to updating system states.We provide three representative examples of the kinetic process simulation to demonstrate its potential utility and broad applications,including effective carrier ion concentration analysis in garnet-type electrolytes,voltage plateau formation in phosphate-based mixed ionic conductor electrodes,and oxygen release in lithium-rich layered oxide cathodes.The work provides a paradigm towards synergizing modeling and experiments into the understanding of complex materials kinetics and lays the groundwork for hierarchically bridging multiscale modeling methods.展开更多
Rational design of solid-state electrolytes(SSEs)with high ionic conductivity and low activation energy(Ea)is vital for all solid-state batteries.Machine learning(ML)techniques have recently been successful in predict...Rational design of solid-state electrolytes(SSEs)with high ionic conductivity and low activation energy(Ea)is vital for all solid-state batteries.Machine learning(ML)techniques have recently been successful in predicting Li^(+) conduction property in SSEs with various descriptors and accelerating the development of SSEs.In this work,we extend the previous efforts and introduce a framework of ML prediction for E_(a) in SSEs with hierarchically encoding crystal structure-based(HECS)descriptors.Taking cubic Li-argyrodites as an example,an Ea prediction model is developed to the coefficient of determination(R^(2))and rootmean-square error(RMSE)values of 0.887 and 0.02 eV for training dataset,and 0.820 and 0.02 eV for test dataset,respectively by partial least squares(PLS)analysis,proving the prediction power of HECSdescriptors.The variable importance in projection(VIP)scores demonstrate the combined effects of the global and local Li^(+) conduction environments,especially the anion size and the resultant structural changes associated with anion site disorder.The developed E_(a) prediction model directs us to optimize and design new Li-argyrodites with lower Ea,such as Li_(6–x)PS_(5–x)Cl_(1+x)(<0.322 eV),Li_(6+x)PS_(5+x)Br_(1–x)(<0.273 eV),Li_(6+x)PS_(5+x)Br_(0.25)I_(0.75–x)(<0.352 eV),Li_(6+(5–n)y)P_(1–y)N_(y)S_(5)I(<0.420 eV),Li_(6+(5–n)y)As_(1–y)N_(y)S_(5)I(<0.371 eV),Li_(6+(5–n)y)As_(1–y)NySe_(5)I(<0.450 eV),by broadening bottleneck size,invoking site disorder and activating concerted Li+conduction.This analysis shows great potential in promoting rational design of advanced SSEs and the same approach can be applied to other types of materials.展开更多
Generative Artificial Intelligence(GAI)is attracting the increasing attention of materials community for its excellent capability of generating required contents.With the introduction of Prompt paradigm and reinforcem...Generative Artificial Intelligence(GAI)is attracting the increasing attention of materials community for its excellent capability of generating required contents.With the introduction of Prompt paradigm and reinforcement learning from human feedback(RLHF),GAI shifts from the task-specific to general pattern gradually,enabling to tackle multiple complicated tasks involved in resolving the structure-activity relationships.Here,we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of methodology.The applications of task-specific generative models involving materials inverse design and data augmentation are also dissected.Taking ChatGPT as an example,we explore the potential applications of general GAI in generating multiple materials content,solving differential equation as well as querying materials FAQs.Furthermore,we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding solutions.This work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development.展开更多
Inorganic-polymer composite solid electrolytes(IPCSEs)obtained by filling the polymer matrix with inorganic materials usually have higher ionic conductivity compared with individual phases.This important increase in i...Inorganic-polymer composite solid electrolytes(IPCSEs)obtained by filling the polymer matrix with inorganic materials usually have higher ionic conductivity compared with individual phases.This important increase in ionic conductivity is explained in terms of the new percolation paths formed by the highly conductive interface between inorganic filler and polymer.The conduction in such systems can be investigated using the effective medium theory(EMT)and random resistance model(RRM).EMT can be used to analyze the effect of filler size on the ionic conductivity of disordered IPCSEs,while RRM can describe the composites with inorganic fillers of various shapes(nano-particles,nano-wires,nano-sheets,and nano-networks)in ordered or disordered arrangement.Herein,we present software evaluating the ionic conductivity in IPCSEs by combining EMT and RRM.The approach is illustrated by considering the size,shapes,and arrangements of inorganic fillers.The ionic conductivities of different types of IPCSEs are predicted theoretically and found in good agreement with the experimental values.The software can be used as an auxiliary tool to design composite electrolytes.展开更多
Solventless mechanochemical synthesis by manual grinding was applied to grow organic proton conducting salts,imidazole-succinic acid(C_(3)H_(4)N_(2)-HOOC(CH_(2))_(2)COOH)and imidazole-glutaric acid(C_(3)H_(4)N_(2)-HOO...Solventless mechanochemical synthesis by manual grinding was applied to grow organic proton conducting salts,imidazole-succinic acid(C_(3)H_(4)N_(2)-HOOC(CH_(2))_(2)COOH)and imidazole-glutaric acid(C_(3)H_(4)N_(2)-HOOC(CH_(2))_(3)COOH).This synthesis method induces crystallization and provides the phase-pure compounds.The compounds exhibit different electric conducting behavior and activation energies Ea compared with the reported single crystals obtained from the solution method.The difference in conducting property can be related to intrinsic defects and structural disorder introduced by mechanochemical grinding,indicating that the mechanochemical method bears strong capability for tuning conductivities.Moreover,complete deuteration of the organic salts is achieved by the method.The mechanochemical synthesis of organic salts also holds high potential for the actual industrialized large-scale production.展开更多
基金National Natural Science Foundation of China(Grant Nos.11874254,51802187,and 51622207)Shanghai Sailing Program,China(Grant No.18YF1408700)+3 种基金Shanghai Pujiang Program,China(Grant No.2019PJD016)Open Project of the State Key Laboratory of Advanced Special Steel,Shanghai University,China(Grant No.SKLASS2018-01)the Project of the State Key Laboratory of Advanced Special Steel,Shanghai University,China(Grant No.SKLASS2019-Z023)the Science and Technology Commission of Shanghai Municipality,China(Grant No.19DZ2270200).
文摘In anode free batteries(AFBs), the current collector acts as anode simultaneously and has large volume expansion which is generally considered as a negative effect decreasing the structural stability of a battery. Moreover, despite many studies on the fast lithium diffusion in the current collector materials of AFB such as copper and aluminum, the involved Li diffusion mechanism in these materials remains poorly understood. Through first-principles calculation and stress-assisted diffusion equations, here we study the Li diffusion mechanism in several current collectors and related alloys and clarify the effect of volume expansion on Li diffusion respectively. It is suggested that due to the lower Li migration barriers in aluminum and tin, they should be more suitable to be used as AFB anodes, compared to copper, silver, and lead. The Li diffusion facilitation in copper with a certain number of vacancies is proposed to explain why the use of copper with a thickness≤100 nm as the protective coating on the anode improves the lifetime of the batteries. We show that the volume expansion has a positive effect on Li diffusion via mechanical–electrochemical coupling. Namely, the volume expansion caused by Li diffusion will further induce stress which in turn affects the diffusion. These findings not only provide in-depth insight into the operating principle of AFBs, but also open a new route toward design of improved anode through utilizing the positive effect of mechanical–electrochemical coupling.
基金Project supported by the National Natural Science Foundation of China(Grant No.11675255)the National Key R&D Program of China(Grant No.2016YFA0401503).
文摘Nanostructuring, structure distortion, and/or disorder are the main manipulation techniques to reduce the lattice thermal conductivity and improve the figure of merit of thermoelectric materials. A single-phase α-MgAgSb sample, MgAg0.97Sb0.99, with high thermoelectric performance in near room temperature region was synthesized through a high-energy ball milling with a hot-pressing method. Here, we report the average grain size of 24–28 nm and the accurate structure distortion, which are characterized by high-resolution neutron diffraction and synchrotron x-ray diffraction with Rietveld refinement data analysis. Both the small grain size and the structure distortion have a contribution to the low lattice thermal conductivity in MgAg0.97Sb0.99.
基金supported by the National Natural Science Foundation of China(Nos.92472207,52372208,52472223)the Science and Technology Commission of Shanghai Municipality(Grant No.22160730100)+1 种基金the High Performance Computing Center of Shanghai University,Shanghai Engineering Research Center of Intelligent Computing System(Grant No.19DZ2252600)the Shanghai Technical Service Center for Advanced Ceramics Structure Design and Precision Manufacturing(Grant No.20DZ2294000)。
文摘The Monte Carlo(MC)method is widely used to simulate kinetic processes involving particle hopping through probabilistic modeling and stochastic sampling,particularly in contexts relevant to electrochemical energy storage,spanning material synthesis,microstructural evolution,and device-level operation.However,the broader applicability of MC simulations is often limited by the requirement for customized definitions of key parameters for each specific physical system.To address this limitation,we propose an adaptive Monte Carlo simulation framework(AMCSF),which adjusts hopping rates,interaction energies,and configuration state parameters on-the-fly in response to updating system states.We provide three representative examples of the kinetic process simulation to demonstrate its potential utility and broad applications,including effective carrier ion concentration analysis in garnet-type electrolytes,voltage plateau formation in phosphate-based mixed ionic conductor electrodes,and oxygen release in lithium-rich layered oxide cathodes.The work provides a paradigm towards synergizing modeling and experiments into the understanding of complex materials kinetics and lays the groundwork for hierarchically bridging multiscale modeling methods.
基金the National Key Research and Development Program of China(2017YFB0701600)the National Natural Science Foundation of China(11874254,51622207,and U1630134)。
文摘Rational design of solid-state electrolytes(SSEs)with high ionic conductivity and low activation energy(Ea)is vital for all solid-state batteries.Machine learning(ML)techniques have recently been successful in predicting Li^(+) conduction property in SSEs with various descriptors and accelerating the development of SSEs.In this work,we extend the previous efforts and introduce a framework of ML prediction for E_(a) in SSEs with hierarchically encoding crystal structure-based(HECS)descriptors.Taking cubic Li-argyrodites as an example,an Ea prediction model is developed to the coefficient of determination(R^(2))and rootmean-square error(RMSE)values of 0.887 and 0.02 eV for training dataset,and 0.820 and 0.02 eV for test dataset,respectively by partial least squares(PLS)analysis,proving the prediction power of HECSdescriptors.The variable importance in projection(VIP)scores demonstrate the combined effects of the global and local Li^(+) conduction environments,especially the anion size and the resultant structural changes associated with anion site disorder.The developed E_(a) prediction model directs us to optimize and design new Li-argyrodites with lower Ea,such as Li_(6–x)PS_(5–x)Cl_(1+x)(<0.322 eV),Li_(6+x)PS_(5+x)Br_(1–x)(<0.273 eV),Li_(6+x)PS_(5+x)Br_(0.25)I_(0.75–x)(<0.352 eV),Li_(6+(5–n)y)P_(1–y)N_(y)S_(5)I(<0.420 eV),Li_(6+(5–n)y)As_(1–y)N_(y)S_(5)I(<0.371 eV),Li_(6+(5–n)y)As_(1–y)NySe_(5)I(<0.450 eV),by broadening bottleneck size,invoking site disorder and activating concerted Li+conduction.This analysis shows great potential in promoting rational design of advanced SSEs and the same approach can be applied to other types of materials.
基金supported by the National Natural Science Foundation of China(52073169 and 92270124)the National Key Research and Development Program of China(2021YFB3802100)the Key Research Project of Zhejiang Laboratory(2021PE0AC02).
基金National Natural Science Foundation of China[grant number 92270124,52073169]National Key Research and Development Program of China[grant number 2021YFB3802101]the Key Research Project of Zhejiang Laboratory[grant number 2021PE0AC02].
文摘Generative Artificial Intelligence(GAI)is attracting the increasing attention of materials community for its excellent capability of generating required contents.With the introduction of Prompt paradigm and reinforcement learning from human feedback(RLHF),GAI shifts from the task-specific to general pattern gradually,enabling to tackle multiple complicated tasks involved in resolving the structure-activity relationships.Here,we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of methodology.The applications of task-specific generative models involving materials inverse design and data augmentation are also dissected.Taking ChatGPT as an example,we explore the potential applications of general GAI in generating multiple materials content,solving differential equation as well as querying materials FAQs.Furthermore,we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding solutions.This work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development.
基金National Key Research and Development Program of China(No.2021YFB3802104)National Natural Science Foundation of China(Nos.U2030206 and 11874254)Shanghai Municipal Science and Technology Commission(No.19DZ2252600).
文摘Inorganic-polymer composite solid electrolytes(IPCSEs)obtained by filling the polymer matrix with inorganic materials usually have higher ionic conductivity compared with individual phases.This important increase in ionic conductivity is explained in terms of the new percolation paths formed by the highly conductive interface between inorganic filler and polymer.The conduction in such systems can be investigated using the effective medium theory(EMT)and random resistance model(RRM).EMT can be used to analyze the effect of filler size on the ionic conductivity of disordered IPCSEs,while RRM can describe the composites with inorganic fillers of various shapes(nano-particles,nano-wires,nano-sheets,and nano-networks)in ordered or disordered arrangement.Herein,we present software evaluating the ionic conductivity in IPCSEs by combining EMT and RRM.The approach is illustrated by considering the size,shapes,and arrangements of inorganic fillers.The ionic conductivities of different types of IPCSEs are predicted theoretically and found in good agreement with the experimental values.The software can be used as an auxiliary tool to design composite electrolytes.
基金support of the National Natural Science Foundation of China(No.12005243,22205239,U1930102 and 11805034)Guangdong Basic and Applied Basic Research Foundation(No.2022B1515120014 and 2022A1515110210)+1 种基金China Postdoctoral Science Foundation(No.2022M721906 and 2022M721909)The neutron diffraction experiments were carried out under the fast-track proposal at Australian Nuclear Science and Technology Organisation(ANSTO)and the general user program(No.P1622061700003)at China Spallation Neutron Source(CSNS).
文摘Solventless mechanochemical synthesis by manual grinding was applied to grow organic proton conducting salts,imidazole-succinic acid(C_(3)H_(4)N_(2)-HOOC(CH_(2))_(2)COOH)and imidazole-glutaric acid(C_(3)H_(4)N_(2)-HOOC(CH_(2))_(3)COOH).This synthesis method induces crystallization and provides the phase-pure compounds.The compounds exhibit different electric conducting behavior and activation energies Ea compared with the reported single crystals obtained from the solution method.The difference in conducting property can be related to intrinsic defects and structural disorder introduced by mechanochemical grinding,indicating that the mechanochemical method bears strong capability for tuning conductivities.Moreover,complete deuteration of the organic salts is achieved by the method.The mechanochemical synthesis of organic salts also holds high potential for the actual industrialized large-scale production.
