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CAREER: Toward Reliable Nonadiabatic Dynamics in Condensed Matter and Nanoscale Systems

职业：在凝聚态物质和纳米级系统中实现可靠的非绝热动力学

基本信息

批准号：
2045204
负责人：
Alexey Akimov
金额：
$ 65万
依托单位：
SUNY at Buffalo
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-06-01 至 2026-05-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045204&HistoricalAwards=false
关键词：
CAREER Toward Reliable Nonadiabatic Dynamics

项目摘要

Alexey Akimov of the State University of New York at Buffalo is supported by a CAREER award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry for theoretical research aimed to advance the reliability and efficiency of quantum dynamics methods for condensed matter and nanoscale systems. Understanding the kinetics and mechanisms of quantum processes such as charge and energy transfer is critical for rationally designing a wide variety of materials such as photovoltaic, photocatalytic, or energy-storage systems, optoelectronic and quantum materials. The computational modeling of the quantum processes in such complex systems at the atomistic level inevitably involves approximations that challenge the reliability of the computational predictions. The computational complexity also limits the range of the processes that can be studied from first principles. In this project, Akimov and his group will develop new theoretical frameworks, computational methodologies, and open-source software to lift the current limitations of quantum dynamics simulations in nanoscale systems. This project will explore the quality of the presently-used simplified approaches, re-evaluate them from more rigorous grounds, and bring the state of quantum dynamics calculations in large systems to a new level of rigor and practicality, unreachable before. The open-source software developed in this project will enable researchers to study new, previously inaccessible, classes of solar energy materials, contributing toward sustainable and renewable energy economy development. Dr. Akimov’s research program is closely integrated with his outreach and educational programs, including workshops on theoretical chemistry for graduate students and a virtual international seminar series for a broad scientific audience.In this project, the Akimov group will develop and study reliable and efficient methods for modeling quantum nonadiabatic dynamics in condensed matter and nanoscale systems. The nonlinear dimensionality reduction and machine learning strategies will be explored to enable computing many nanosecond-long quantum trajectories, without expensive ab initio calculations. These strategies are expected to help obtain the converged statistics of electronic transitions and estimate the error bars in computed properties. They will also enable modeling intrinsically slow quantum processes and infrequent events and help accelerate nonadiabatic dynamics modeling of large systems. The project aims to identify the “effective” low-dimensional coordinates that can be used to facilitate the analysis of photoexcited dynamics in various materials. New techniques for nonadiabatic dynamics in large systems will be developed based on the formally-exact hierarchy of equations of motion method. These developments enable the accurate description of the bath-induced decoherence, and thermalization of excited states in complex systems, in a non-perturbative way. New nonadiabatic dynamics methods for computing electronic state couplings and energies at the many-body level, beyond the commonly-used single-particle picture, will be developed and implemented in open-source codes. These advancements seek to enable computational material scientists to model excitonic dynamics in quantum-confined systems and capture slow dynamics with infrequent electronic transitions. The nonadiabatic dynamics approaches resulting from this project will be validated against the model and experimental references. These efforts aim to assess modern approximate quantum-classical methods for extended systems and bring them to a new level of rigor and reliability.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.

纽约州立大学布法罗分校的Alexey Akimov获得了化学系化学理论、模型和计算方法项目颁发的职业奖，以表彰旨在提高凝聚态和纳米系统量子动力学方法的可靠性和效率的理论研究。了解电荷和能量转移等量子过程的动力学和机制，对于合理设计各种材料，如光伏、光催化或储能系统、光电子和量子材料至关重要。在原子水平上对这种复杂系统中的量子过程进行计算建模不可避免地涉及到对计算预测的可靠性提出质疑的近似。计算的复杂性也限制了可以从第一原理研究的过程的范围。在这个项目中，阿基莫夫和他的团队将开发新的理论框架、计算方法和开源软件，以解除目前纳米系统中量子动力学模拟的限制。这个项目将探索目前使用的简化方法的质量，从更严格的基础上重新评估它们，并将大系统中的量子动力学计算的状态带到以前无法企及的严谨和实用的新水平。该项目开发的开源软件将使研究人员能够研究以前无法获得的新型太阳能材料，为可持续和可再生能源经济发展做出贡献。阿基莫夫博士的研究计划与他的推广和教育计划紧密结合在一起，包括为研究生举办的理论化学研讨会，以及为广大科学受众举办的虚拟国际研讨会系列。在这个项目中，阿基莫夫团队将开发和研究可靠而有效的方法，对凝聚态和纳米系统中的量子非绝热动力学进行建模。将探索非线性降维和机器学习策略，以实现计算许多纳秒长的量子轨迹，而不需要昂贵的从头计算。这些策略有望帮助获得电子跃迁的收敛统计，并估计计算性质中的误差条。它们还将使建模本质上缓慢的量子过程和罕见事件成为可能，并有助于加速大型系统的非绝热动力学建模。该项目旨在确定可用于分析各种材料中的光激发动力学的“有效”低维坐标。大系统中非绝热动力学的新技术将基于形式上精确的运动方程组方法而发展。这些发展使得能够以非微扰的方式准确地描述复杂体系中由浴诱导的退相干和激发态的热化。将开发新的非绝热动力学方法，用于计算多体水平上的电子态耦合和能量，而不是通常使用的单粒子图像，并将在开放源代码中实现。这些进展旨在使计算材料科学家能够对量子受限系统中的激子动力学进行建模，并捕捉具有罕见电子跃迁的慢动力学。本项目所产生的非绝热动力学方法将根据模型和实验参考资料进行验证。这些努力旨在评估扩展系统的现代近似量子经典方法，并将其提高到一个新的严密性和可靠性水平。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。