Long-Lived Hot Electron in a Metallic Particle for Plasmonics and Catalysis: Ab Initio Nonadiabatic Molecular Dynamics with Machine Learning
Long-Lived Hot Electron in a Metallic Particle for Plasmonics and Catalysis: Ab Initio Nonadiabatic Molecular Dynamics with Machine Learning
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DOI：
10.1021/acsnano.0c04736
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发表时间：
2020-08-25
期刊：
影响因子：
17.1
通讯作者：
Prezhdo, Oleg, V
中科院分区：
文献类型：
--
作者：
Chu, Weibin;Saidi, Wissam A.;Prezhdo, Oleg, V
多个实验为涉及热的光伏、催化、光电和等离子体过程提供了证据，纳米级材料中的高能电子。然而，这种过程的机制仍然难以捉摸，因为电子通过密集的状态流形弛豫而迅速失去能量。我们证明了一个长寿命的热电子状态在Pt纳米团簇吸附在MoS 2衬底上。为此，我们开发了一种模拟技术，结合经典的分子动力学的基础上，机器学习的潜力与从头算非绝热分子动力学和实时含时密度泛函理论。选择Pt-20/MoS 2作为一个原型系统，我们发现在50 ps的时间尺度上发生的Pt粒子的顶部原子的频繁移位。这种扭曲破坏了粒子的对称性，产生了不饱和的化学键。与断裂的键相关的局域态的寿命增强了3倍。热电子聚集在移动的原子附近并形成催化反应中心。我们的研究结果证明，即使是单个原子的扭曲也会对纳米级催化和等离子体产生重要影响，并为利用机器学习潜力加速凝聚态系统激发态动力学的从头算研究提供了见解。
Multiple experiments provide evidence for photovoltaic, catalytic, optoelectronic, and plasmonic processes involving hot, i.e., high energy, electrons in nanoscale materials. However, the mechanisms of such processes remain elusive, because electrons rapidly lose energy by relaxation through dense manifolds of states. We demonstrate a long-lived hot electron state in a Pt nanocluster adsorbed on the MoS2 substrate. For this purpose, we develop a simulation technique, combining classical molecular dynamics based on machine learning potentials with ab initio nonadiabatic molecular dynamics and real-time time-dependent density functional theory. Choosing Pt-20/MoS2 as a prototypical system, we find frequent shifting of a top atom in the Pt particle occurring on a 50 ps time scale. The distortion breaks particle symmetry and creates unsaturated chemical bonds. The lifetime of the localized state associated with the broken bonds is enhanced by a factor of 3. Hot electrons aggregate near the shifted atom and form a catalytic reaction center. Our findings prove that distortion of even a single atom can have important implications for nanoscale catalysis and plasmonics and provide insights for utilizing machine learning potentials to accelerate ab initio investigations of excited state dynamics in condensed matter systems.