Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the lon...Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the long-standing challenges in the application of AI to scientific problems.To meet this challenge in the burgeoning field of AI for chemistry,we may adopt the paradigm of knowledge graph.Herein,focusing on catalytic chemical reactions,we have developed a semantic knowledge graph framework based on both structured and unstructured data,the latter of which are extracted from the text of 220,000articles on catalysts for organic molecules.The framework captures the latent knowledge of reactant-catalyst-product relationships and can therefore provide accurate recommendation on potential catalysts for targeted reaction,which especially facilitates the research involving large molecules.This study presents a viable pathway towards the implementation of literature-based data management in a catalyst recommendation platform.展开更多
Garnet-type oxide is one of the most promising solid-state electrolytes(SSEs)for solid-state lithium-metal batteries(SSLMBs).However,the Li dendrite formation in garnet oxides obstructs the further development of the ...Garnet-type oxide is one of the most promising solid-state electrolytes(SSEs)for solid-state lithium-metal batteries(SSLMBs).However,the Li dendrite formation in garnet oxides obstructs the further development of the SSLMBs seriously.Here,we report a high-performance garnet oxide by using AlN as a sintering additive and Li as an anode interface layer.AlN with high thermal conductivity can promote the sintering activity of the garnet oxides,resulting in larger particle size and higher relative density.Moreover,Li3N with high ionic conductivity formed at grain boundaries and interface can also improve Li-ion transport kinetics.As a result,the garnet oxide electrolytes with AlN show enhanced thermal conductivity,improved ionic conductivity,reduced electronic conductivity,and increased critical current density(CCD),compared with the counterpart using Al_(2)O_(3) sintering aid.In addition,Li symmetric cells and Li|LiFePO_(4)(Li|LFP)half cells using the garnet electrolyte with the AlN additive exhibit good electrochemical performances.This work provides a simple and effective strategy for high-performance SSEs.展开更多
基金supported by Guangdong Basic and Applied Basic Research Foundation(2023A1515011391 and 2020A1515110843)the Soft Science Research Project of Guangdong Province(2017B030301013)+2 种基金the National Key Research and Development Program of China(2022YFB2702301)the Key-Area Research and Development Program of Guangdong Province(2020B0101090003)the Major Science and Technology Infrastructure Project of Material Genome Big-science Facilities Platform supported by Municipal Development and Reform Commission of Shenzhen
文摘Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the long-standing challenges in the application of AI to scientific problems.To meet this challenge in the burgeoning field of AI for chemistry,we may adopt the paradigm of knowledge graph.Herein,focusing on catalytic chemical reactions,we have developed a semantic knowledge graph framework based on both structured and unstructured data,the latter of which are extracted from the text of 220,000articles on catalysts for organic molecules.The framework captures the latent knowledge of reactant-catalyst-product relationships and can therefore provide accurate recommendation on potential catalysts for targeted reaction,which especially facilitates the research involving large molecules.This study presents a viable pathway towards the implementation of literature-based data management in a catalyst recommendation platform.
基金the National Key R&D Program of China(No.2019YFA0210600)the National Natural Science Foundation of China(No.21805185)+2 种基金Shanghai Science and Technology Plan(No.21DZ2260400)Shanghai Rising-Star Program(No.20QA1406600)Center for High-resolution Electron Microscopy,SPST of ShanghaiTech University(No.EM02161943)for support.
文摘Garnet-type oxide is one of the most promising solid-state electrolytes(SSEs)for solid-state lithium-metal batteries(SSLMBs).However,the Li dendrite formation in garnet oxides obstructs the further development of the SSLMBs seriously.Here,we report a high-performance garnet oxide by using AlN as a sintering additive and Li as an anode interface layer.AlN with high thermal conductivity can promote the sintering activity of the garnet oxides,resulting in larger particle size and higher relative density.Moreover,Li3N with high ionic conductivity formed at grain boundaries and interface can also improve Li-ion transport kinetics.As a result,the garnet oxide electrolytes with AlN show enhanced thermal conductivity,improved ionic conductivity,reduced electronic conductivity,and increased critical current density(CCD),compared with the counterpart using Al_(2)O_(3) sintering aid.In addition,Li symmetric cells and Li|LiFePO_(4)(Li|LFP)half cells using the garnet electrolyte with the AlN additive exhibit good electrochemical performances.This work provides a simple and effective strategy for high-performance SSEs.
