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arXiv 2502.02429physics.chem-phphysics.comp-ph
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用下一代扩展拉格朗日量子分子动力学模拟固液界面上的反应

Modeling Reactions on the Solid-Liquid Interface With Next Generation Extended Lagrangian Quantum-Based Molecular Dynamics

Los Alamos National Laboratory(洛斯阿拉莫斯国家实验室);University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)

Rae A. Corrigan Grove, Kevin G. Kleiner, Joshua Finkelstein, Ivana Matanovic, Michael E. Wall, Travis E. Jones, Anders M. N. Niklasson, Christian F. A. Negre

AI总结:

该研究采用XL-BOMD框架模拟ORR,发现偏压会改变反应机制,其动力学与常用理论有差异,为电催化过程提供了预测性原子级洞察。

摘要:

我们提出了一系列氧还原反应(ORR)的模拟,采用了一种用于电化学偏压下表面催化的原子级模拟新框架。该框架利用量子力学扩展拉格朗日玻恩-奥本海默分子动力学(XL-BOMD)模拟,可为电极和电解质的显式原子级处理提供所需的速度和精度。我们对氮掺杂石墨烯(NG)附近溶剂化的O₂进行了模拟,以深入了解ORR,观察到不同的机制取决于所施加的偏压。在较高偏压下,ORR通过外球机制发生,O₂不吸附在NG上,在该机制中,催化剂与O₂之间的电子转移由溶剂介导;在较低偏压下,ORR通过涉及O₂吸附在NG上的内球机制发生,导致直接电子转移。我们广泛的全原子量子力学分子动力学模拟还显示,在该理想可极化电极上的ORR动力学与常用动力学理论之间存在明显差异,从而为不同过电位下的机制变化提供了新的见解。XL-BOMD结合了量子精度、显式溶剂化和静电势偏压,为电催化过程的预测性原子级洞察开辟了一条途径,ORR的实例证明了这一点。

英文摘要:

We present a series of simulations of the oxygen reduction reaction (ORR) using a novel framework for atomistic simulations of surface catalysis under electrochemical bias. The framework makes use of quantum-mechanical extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) simulations, which provide the speed and accuracy required for explicit atomistic treatment of both electrode and electrolyte. Simulations of solvated O$_2$ near nitrogen-doped graphene (NG) were performed to gain insight into the ORR, and different mechanisms were observed, depending on the applied bias. Under higher bias the ORR occurred by an outer-sphere mechanism, without adsorption of O$_2$ to NG. In this mechanism, electron transfer between the catalyst and the O$_2$ was mediated by the solvent. Under lower bias the ORR occurred by an inner-sphere mechanism involving adsorption of O$_2$ to NG, leading to direct electron transfer. Our extensive, all-atom quantum-mechanical molecular dynamics simulations also show clear differences between the kinetics of the ORR on this ideally polarizable electrode and commonly used kinetic theories, leading to new insights regarding mechanistic changes with varied overpotentials. Combining quantum accuracy with explicit solvation and electrostatic potential bias, XL-BOMD opens a route to predictive, atomistic insight into electrocatalytic processes, as demonstrated with the ORR.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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