Entropy in catalyst dynamics under confinement.

Autor: Fan QY; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn.; Engineering Research Center of Ministry of Education for Fine Chemicals, School of Chemistry and Chemical Engineering, Shanxi Key Laboratory of Coal-based Value-added Chemicals Green Catalysis Synthesis, Shanxi University Taiyuan 030006 China., Liu YP; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn., Zhu HX; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn., Gong FQ; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn., Wang Y; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn., E W; Center for Machine Learning Research, School of Mathematical Sciences, Peking University Beijing 100871 China.; AI for Science Institute Beijing 100084 China., Bao X; Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China., Tian ZQ; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn.; Laboratory of AI for Electrochemistry (AI4EC), IKKEM Xiamen 361005 China., Cheng J; State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China Chengjun@xmu.edu.cn.; Laboratory of AI for Electrochemistry (AI4EC), IKKEM Xiamen 361005 China.; Institute of Artificial Intelligence, Xiamen University Xiamen 361005 China.
Jazyk: angličtina
Zdroj: Chemical science [Chem Sci] 2024 Oct 17. Date of Electronic Publication: 2024 Oct 17.
DOI: 10.1039/d4sc05399k
Abstrakt: Entropy during the dynamic structural evolution of catalysts has a non-trivial influence on chemical reactions. Confinement significantly affects the catalyst dynamics and thus impacts the reactivity. However, a full understanding has not been clearly established. To investigate catalyst dynamics under confinement, we utilize the active learning scheme to effectively train machine learning potentials for computing free energies of catalytic reactions. The scheme enables us to compute the reaction free energies and entropies of O 2 dissociation on Pt clusters with different sizes confined inside a carbon nanotube (CNT) at the timescale of tens of nanoseconds while keeping ab initio accuracy. We observe an entropic effect owing to liquid-to-solid phase transitions of clusters at finite temperatures. More importantly, the confinement effect enhances the structural dynamics of the cluster and leads to a lower melting temperature than those of the bare cluster and cluster outside the CNT, consequently facilitating the reaction to occur at lower temperatures and preventing the catalyst from forming unfavorable oxides. Our work reveals the important influence of confinement on structural dynamics, providing useful insight into entropy in dynamic catalysis.
Competing Interests: There are no conflicts to declare.
(This journal is © The Royal Society of Chemistry.)
Databáze: MEDLINE
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