Theoretical Studies of Surface Reaction Dynamics

在化学结构、动力学和机理（CSDM-A）和化学系化学理论、模型和计算方法（CTMC）项目的支持下，新墨西哥大学郭华教授和他的研究小组旨在利用计算方法促进对原子和分子与金属和半导体表面相互作用动力学的基本理解。郭教授和他的研究小组将专注于吸附、解吸、散射、扩散和反应等基本过程的计算表征，为表面反应动力学提供系统和全面的见解。从这些基础研究中获得的知识有可能帮助建立界面现象的关键原理和预测模型，从而更好地阐明表面上的重要化学和物理过程，包括腐蚀、设备制造和多相催化。从事这项工作的学生将获得宝贵的计算研究经验，这些经验将通过与实验人员的合作而得到加强。利用密度泛函理论（DFT）、机器学习以及经典、半经典和量子力学方法，寻求通过绝热和非绝热途径在表面过程中能量耗散的准确描述。DFT将用于理解界面系统的电子结构；机器学习将用于表示高维势能面和其他属性，而经典、半经典和量子力学方法的组合也将用于模拟核动力学。由于表面上的声子和电子空穴对改变了绝热和非绝热途径，郭教授和他的团队将研究金属和半导体界面上的能量流动和键形成/断裂事件的变化。这包括热吸附的能量耗散、半导体表面的原子散射、金属表面的eley - ideal反应的振动激发效应、金属表面分解/解吸反应的后过渡态动力学以及金属表面反应速率的量子效应。具体目标包括更好地理解非玻恩-奥本海默效应、核量子效应以及反应性和能量处置中的模式特异性。与实验小组的合作将有助于指导计算研究，以便更好地理解固体表面上能量传递和化学转化的复杂相互作用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the Chemical Structure, Dynamics, and Mechanisms-A (CSDM-A) and the Chemical Theory, Models, and Computational Methods (CTMC) Programs in the Division of Chemistry, Professor Hua Guo of the University of New Mexico and his research team aim to advance the fundamental understanding of dynamics for atomic and molecular interactions with metal and semiconductor surfaces using computational methods. Professor Guo and his research group will focus on the computational characterization of elementary processes such as adsorption, desorption, scattering, diffusion, and reaction to provide systematic and comprehensive insights into surface reaction dynamics. The knowledge gained from these fundamental studies has the potential to help establish key principles and predictive models for interfacial phenomena thus allowing for better elucidation of important chemical and physical processes at surfaces ranging from corrosion, device fabrication, and heterogeneous catalysis. The students engaged in this work will gain valuable experience in computational research, which will be enhanced through collaborations with experimentalists. An accurate description of energy dissipation in surface processes via both adiabatic and nonadiabatic pathways is sought using density functional theory (DFT), machine learning, as well as classical, semi-classical, and quantum mechanical methods. DFT will be used for understanding the electronic structure of interfacial systems; machine learning will be used for representing high-dimensional potential energy surfaces and other properties, while a combination of classical, semi-classical, and quantum mechanical methods will also be used for simulating nuclear dynamics. Because adiabatic and nonadiabatic pathways are altered by phonons and electron-hole pairs at surfaces, Professor Guo and his group will investigate how energy flow and bond forming/breaking events vary at metal and semiconductor interfaces. This includes investigations of energy dissipation of hot adsorbates, atomic scattering from semiconductor surfaces, vibrational excitation effects in Eley-Rideal reactions on metals, post-transition state dynamics in decomposition/desorption reactions from metal surfaces, and quantum effects in surface reaction rates on metals. Specific objectives include a better understanding of non-Born-Oppenheimer effects, nuclear quantum effects, and mode specificity in reactivity and energy disposal. Collaboration with experimentalists groups will help guide the computational studies so that the complex interplay of energy transfer and chemical transformation on solid surfaces can be better understood.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.