In this research,we present a comprehensive investigation on the catalyst screening,reaction mechanism,and electrocatalytic properties of two-dimensional monoatomic metalloporphyrinoid(MPor)materials for the oxygen re...In this research,we present a comprehensive investigation on the catalyst screening,reaction mechanism,and electrocatalytic properties of two-dimensional monoatomic metalloporphyrinoid(MPor)materials for the oxygen reduction reaction(ORR).Through a combination of high-throughput screening,first-principles DFT calculations,and molecular dynamics simulations,we uncovered some promising oxygen reduction catalysts with limiting potentials of 0.60,0.57,0.56 V under acidic medium,and-0.17,-0.20,-0.21 V under basic medium for M=Co,Fe,Mn,respectively.Full reaction pathway search demonstrates that Co Por is a special case with 2e^(–)and 4e^(–)paths under both acidic and basic media,and for Fe Por and Mn Por,only 4e^(–)path is viable.In-depth analyses indicate that the adsorption free energy of OH and limiting potential shows the volcano curve relationship,which can guide the design and optimization of the ORR catalysts.The crystal orbital Hamiltonian population(COHP)between M and O in O_(2)-MPor can well explain why only Co Por has a 2e^(–)path,while other metals do not,because the Co–O bond is much weaker compared to other M–O bonds.Our research will shed some insights on designing efficient ORR catalysts,and stimulate the experimental efforts in this direction.展开更多
Metal-organic frameworks(MOFs)have attracted a lot of attention due to their diverse structures,favorable porous properties,and tunable chemical compositions in the multiple fields.Notably,MOF-based materials(includin...Metal-organic frameworks(MOFs)have attracted a lot of attention due to their diverse structures,favorable porous properties,and tunable chemical compositions in the multiple fields.Notably,MOF-based materials(including pristine MOFs,MOF composites,and their derivatives)play the vital role in electrochemical energy storage and conversion systems,due to their ability for regulating chemical composition at the molecular level and their highly porous frameworks for facilitating the mass and charge transfer.Supercapacitors and fuel cells are used as one of energy storage and conversion systems respectively,and it is unstoppable to design and synthesize high-efficiency electrode materials for them.This review starts with the strategies for designing targeted MOF-based materials in electrochemical energy storage and conversion applications followed by the state-ofthe-art MOF-based materials discussed as to their potential applications in supercapacitors and electrocatalytic oxygen reduction reaction(ORR).Finally,the challenges and perspectives of MOF-based materials applied for supercapacitors and electrocatalytic ORR are discussed.展开更多
Artificial intelligence(AI)-assisted approaches are powerful means for advancing catalyst design,as they can significantly accelerate the development of novel catalysts.However,the underlying mechanisms of these appro...Artificial intelligence(AI)-assisted approaches are powerful means for advancing catalyst design,as they can significantly accelerate the development of novel catalysts.However,the underlying mechanisms of these approaches often remain elusive,which may lead to unreliable results due to a lack of clear understanding of the involved processes.Herein,we present an AI strategy that combines machine learning(ML)and data mining(DM)to identify high-performance catalysts while elucidating the key factors that govern catalytic performance in complex reactions.Applying this AI strategy to evaluate the electrocatalytic oxygen reduction performance of 10,179 single-atom catalysts(SACs),we identified several high-performance SACs and determined the critical influencers of their activity.Experimental validations further confirm the effectiveness of the AI strategy,with the optimal target Co-S2N2/g-SAC achieving a high half-wave potential of 0.92 V.This AI-assisted approach significantly enhances the transparency and reliability of data-driven discoveries,providing new insights that benefit the rational design of materials.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2021YFA1600800)the National Natural Science Foundation of China(Nos.22073033,21873032,21673087,and 21903032)+3 种基金the startup fund(Nos.2006013118 and 3004013105)from Huazhong University of Science and Technologythe Fundamental Research Funds for the Central Universities(No.2019kfy RCPY116)the Innovation and Talent Recruitment Base of New Energy Chemistry and Device(No.B21003)support from the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515010382)。
文摘In this research,we present a comprehensive investigation on the catalyst screening,reaction mechanism,and electrocatalytic properties of two-dimensional monoatomic metalloporphyrinoid(MPor)materials for the oxygen reduction reaction(ORR).Through a combination of high-throughput screening,first-principles DFT calculations,and molecular dynamics simulations,we uncovered some promising oxygen reduction catalysts with limiting potentials of 0.60,0.57,0.56 V under acidic medium,and-0.17,-0.20,-0.21 V under basic medium for M=Co,Fe,Mn,respectively.Full reaction pathway search demonstrates that Co Por is a special case with 2e^(–)and 4e^(–)paths under both acidic and basic media,and for Fe Por and Mn Por,only 4e^(–)path is viable.In-depth analyses indicate that the adsorption free energy of OH and limiting potential shows the volcano curve relationship,which can guide the design and optimization of the ORR catalysts.The crystal orbital Hamiltonian population(COHP)between M and O in O_(2)-MPor can well explain why only Co Por has a 2e^(–)path,while other metals do not,because the Co–O bond is much weaker compared to other M–O bonds.Our research will shed some insights on designing efficient ORR catalysts,and stimulate the experimental efforts in this direction.
基金This work was supported by the National Key Research and Development Program of China(No.2019YFA0210300)the Natural Science Foundation of China(No.21922802)+3 种基金the Beijing Natural Science Foundation(No.JQ19007)Talent Cultivation and Open Project(No.OIC-201801007)of State Key Laboratory of Organic-Inorganic Composites“Double-First-Class”Construction Projects(Nos.XK180301 and XK1804-02)the Distinguished Scientist Program at BUCT(No.buctylkxj02).
文摘Metal-organic frameworks(MOFs)have attracted a lot of attention due to their diverse structures,favorable porous properties,and tunable chemical compositions in the multiple fields.Notably,MOF-based materials(including pristine MOFs,MOF composites,and their derivatives)play the vital role in electrochemical energy storage and conversion systems,due to their ability for regulating chemical composition at the molecular level and their highly porous frameworks for facilitating the mass and charge transfer.Supercapacitors and fuel cells are used as one of energy storage and conversion systems respectively,and it is unstoppable to design and synthesize high-efficiency electrode materials for them.This review starts with the strategies for designing targeted MOF-based materials in electrochemical energy storage and conversion applications followed by the state-ofthe-art MOF-based materials discussed as to their potential applications in supercapacitors and electrocatalytic oxygen reduction reaction(ORR).Finally,the challenges and perspectives of MOF-based materials applied for supercapacitors and electrocatalytic ORR are discussed.
基金supported by the National Key Research and Development Program of China(2023YFA1506902)the National Nature Science Foundation of China(U23A2086,22302173,and 52261145700)+3 种基金the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang(2023R01007)the Qingdao New Energy Shandong Laboratory Open Project(QNESL OP202307)the Fundamental Research for the Central University,and National Research Foundation of Korea(NRF)grants funded by the Korean government(RS-2023-00243788 and RS-2023-00235596)support from the Hong Kong Global STEM Professorship Scheme and the Guangdong Basic and Applied Basic Research Foundation(2024A1515012307).
文摘Artificial intelligence(AI)-assisted approaches are powerful means for advancing catalyst design,as they can significantly accelerate the development of novel catalysts.However,the underlying mechanisms of these approaches often remain elusive,which may lead to unreliable results due to a lack of clear understanding of the involved processes.Herein,we present an AI strategy that combines machine learning(ML)and data mining(DM)to identify high-performance catalysts while elucidating the key factors that govern catalytic performance in complex reactions.Applying this AI strategy to evaluate the electrocatalytic oxygen reduction performance of 10,179 single-atom catalysts(SACs),we identified several high-performance SACs and determined the critical influencers of their activity.Experimental validations further confirm the effectiveness of the AI strategy,with the optimal target Co-S2N2/g-SAC achieving a high half-wave potential of 0.92 V.This AI-assisted approach significantly enhances the transparency and reliability of data-driven discoveries,providing new insights that benefit the rational design of materials.
