Layer pseudospins,exhibiting quantum coherence and precise multistate controllability,present significant potential for the advancement of future computing technologies.In this work,we propose an in-memory probabilist...Layer pseudospins,exhibiting quantum coherence and precise multistate controllability,present significant potential for the advancement of future computing technologies.In this work,we propose an in-memory probabilistic computing scheme based on the electrical manipulation of layer pseudospins in layered materials,by exploiting the interaction between real spins and layer pseudospins.展开更多
With the rapid advancement of AI technologies,generative models have been increasingly employed in the exploration of novel materials.By integrating traditional computational approaches such as density functional theo...With the rapid advancement of AI technologies,generative models have been increasingly employed in the exploration of novel materials.By integrating traditional computational approaches such as density functional theory(DFT)and molecular dynamics(MD),existing generative models—including diffusion models and autoregressive models—have demonstrated remarkable potential in the discovery of novel materials.However,their efficiency in goal-directed materials design remains suboptimal.In this work we developed a highly transferable,efficient and robust conditional generation framework,PODGen,by integrating a general generative model with multiple property prediction models.Based on PODGen,we designed a workflow for the high-throughput crystals conditional generation which is used to search new topological insulators(TIs).Our results show that the success rate of generating TIs using our framework is approximately 5 times higher than that of the unconstrained approach.This demonstrates that conditional generation significantly enhances the efficiency of targeted material discovery.Using this method,we generated tens of thousands of new topological materials and conducted further first-principles calculations on those with promising application potential.Furthermore,we identified promising,synthesizable topological(crystalline)insulators such as CsHgSb,NaLaB_(12),Bi_(4)Sb_(2)Se_(3),Be_(3)Ta_(2)Si and Be_(2)W.展开更多
As alternatives to conventional rocking-chair lithium-ion batteries(LIBs),novel rechargeable batteries utilizing abundant elements(such as sodium-ion batteries,potassium-ion batteries,and magnesium-ion batteries)have ...As alternatives to conventional rocking-chair lithium-ion batteries(LIBs),novel rechargeable batteries utilizing abundant elements(such as sodium-ion batteries,potassium-ion batteries,and magnesium-ion batteries)have shown excellent performance.Nevertheless,these emerging batteries still face several challenges,including sluggish kinetics,limited reversibility,and a lack of suitable electrode materials.By incorporating carrier ions with different properties,hybrid-ion batteries(HIBs)based on multi-ion strategies have garnered extensive attention for their potential to solve most of these problems.However,with the increasing number of carrier ions that have been demonstrated to be suitable for multi-ion strategies,there exists deficiency in clarity regarding the nomenclature and classification of HIBs.For this reason,this comprehensive review offers an in-depth analysis of the fundamental configurations of HIBs according to the reaction mechanisms of the different carrier ions involved in the electrochemical redox reaction.Then,we systematically review the electrode materials for practical implementation on the basis of the energy storage mechanisms.Moreover,the challenges confronted by the current multi-ion strategies and promising future directions for overcoming these challenges are proposed for further research.The primary objective of this review is to inspire researchers in the rational design of highly efficient electrode materials for advanced HIBs.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12322407,62122036,and 62034004)the Natural Science Foundation of Jiangsu Province(Grant No.BK20233001)+5 种基金the National Key R&D Program of China(Grant Nos.2023YFF0718400 and 2023YFF1203600)the Leading-edge Technology Program of Jiangsu Natural Science Foundation(Grant No.BK20232004)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB44000000)Innovation Program for Quantum Science and Technologysupport from the Fundamental Research Funds for the Central Universities(Grant Nos.020414380227,020414380240,and 020414380242)the e-Science Center of Collaborative Innovation Center of Advanced Microstructures。
文摘Layer pseudospins,exhibiting quantum coherence and precise multistate controllability,present significant potential for the advancement of future computing technologies.In this work,we propose an in-memory probabilistic computing scheme based on the electrical manipulation of layer pseudospins in layered materials,by exploiting the interaction between real spins and layer pseudospins.
基金supported by the Science Center of the National Natural Science Foundation of China(Grant No.12188101)the National Key Research and Development Program of China(Grant No.2023YFA1607400,2022YFA1403800)+1 种基金the National Natural Science Foundation of China(Grant No.12274436,11921004,11925408)H.W.acknowledge support from the New Cornerstone Science Foundation through the XPLORER PRIZE.The AI-driven experiments,simulations and model training were performed on the robotic AI-Scientist platform of Chinese Academy of Science.
文摘With the rapid advancement of AI technologies,generative models have been increasingly employed in the exploration of novel materials.By integrating traditional computational approaches such as density functional theory(DFT)and molecular dynamics(MD),existing generative models—including diffusion models and autoregressive models—have demonstrated remarkable potential in the discovery of novel materials.However,their efficiency in goal-directed materials design remains suboptimal.In this work we developed a highly transferable,efficient and robust conditional generation framework,PODGen,by integrating a general generative model with multiple property prediction models.Based on PODGen,we designed a workflow for the high-throughput crystals conditional generation which is used to search new topological insulators(TIs).Our results show that the success rate of generating TIs using our framework is approximately 5 times higher than that of the unconstrained approach.This demonstrates that conditional generation significantly enhances the efficiency of targeted material discovery.Using this method,we generated tens of thousands of new topological materials and conducted further first-principles calculations on those with promising application potential.Furthermore,we identified promising,synthesizable topological(crystalline)insulators such as CsHgSb,NaLaB_(12),Bi_(4)Sb_(2)Se_(3),Be_(3)Ta_(2)Si and Be_(2)W.
基金supported by the National Natural Science Foundation of China(grant nos.22379015,22279009,and 22075028)the Beijing Institute of Technology Research Fund Program for Young Scholars(no.XSQD-202108005).
文摘As alternatives to conventional rocking-chair lithium-ion batteries(LIBs),novel rechargeable batteries utilizing abundant elements(such as sodium-ion batteries,potassium-ion batteries,and magnesium-ion batteries)have shown excellent performance.Nevertheless,these emerging batteries still face several challenges,including sluggish kinetics,limited reversibility,and a lack of suitable electrode materials.By incorporating carrier ions with different properties,hybrid-ion batteries(HIBs)based on multi-ion strategies have garnered extensive attention for their potential to solve most of these problems.However,with the increasing number of carrier ions that have been demonstrated to be suitable for multi-ion strategies,there exists deficiency in clarity regarding the nomenclature and classification of HIBs.For this reason,this comprehensive review offers an in-depth analysis of the fundamental configurations of HIBs according to the reaction mechanisms of the different carrier ions involved in the electrochemical redox reaction.Then,we systematically review the electrode materials for practical implementation on the basis of the energy storage mechanisms.Moreover,the challenges confronted by the current multi-ion strategies and promising future directions for overcoming these challenges are proposed for further research.The primary objective of this review is to inspire researchers in the rational design of highly efficient electrode materials for advanced HIBs.
