Extending the Range of Nonadiabatic Processes that Can Be Treated with Analytic Representations of Coupled Potential Energy Surfaces

扩展可以用耦合势能面的解析表示处理的非绝热过程的范围

基本信息

批准号：
1954723
负责人：
David Yarkony
金额：
$ 45万
依托单位：
Johns Hopkins University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1954723&HistoricalAwards=false
关键词：
Extending Range Nonadiabatic Processes Treated

项目摘要

David R. Yarkony of Johns Hopkins University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry. The goal of the award is to build computational models of processes that convert light energy into chemical energy, but can not produce the reverse reaction. These are called nonadiabatic processes. Nonadiabatic processes are involved in many important processes including vision, photosynthesis and protecting our DNA against the dangers of the ultraviolet component of sunlight. Professor Yarkony and his research group produce computational models using high speed digital computers. The tools they develop add subtle but important interactions to their existing model that can alter the outcome of a predicted nonadiabatic event. Scientists frequently use light energy in an attempt to manipulate the outcome of a chemical reaction. If the computational model is sufficiently accurate, computer simulations can guide and inform experiments. If the model is inaccurate, incorrect inferences are obtained. Professor Yarkony has identified a class of light induced molecular breakup processes for which a decades-old standard model fails. His group continues to study this failure to establish its prevalence and the consequences of the errors. Professor Yarkony mentors a group of students and postdocs. Together they develop software that can be used by the community to explore the new methods.The Yarkony group is using fit coupled diabatic state electronic Hamiltonians to study nonadiabatic processes. They take advantage of the key strengths of fit representations, which is the use of wave functions that include both static and dynamic correlations. Nuclear quantum effects including the geometric phase (GP) and tunneling are calculated. In order to treat intense laser fields and spin-changing processes, dipole and spin orbit coupling terms must also be represented. The Yarkony group uses a two-step approach in which Gaussian Process Regression is used followed by the application of neural network techniques. The ability to extend the range of problems that can be treated in this way provides an important new tool to treat nonadiabatic processes. The accuracy of the diabatic potential energy matrix is improved, while quantum tunneling can be treated rigorously and the GP is properly included in full and reduced dimensionality representations.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.

约翰·霍普金斯大学的 David R. Yarkony 获得了化学系化学理论、模型和计算方法项目的奖项支持。该奖项的目标是建立将光能转化为化学能但不能产生逆反应的过程的计算模型。这些称为非绝热过程。非绝热过程涉及许多重要过程，包括视觉、光合作用以及保护我们的 DNA 免受阳光紫外线成分的危害。 Yarkony 教授和他的研究小组使用高速数字计算机创建计算模型。他们开发的工具为现有模型添加了微妙但重要的交互作用，可以改变预测的非绝热事件的结果。科学家经常使用光能来尝试操纵化学反应的结果。如果计算模型足够准确，计算机模拟可以指导和指导实验。如果模型不准确，就会得到错误的推论。亚科尼教授发现了一类光诱导的分子分解过程，几十年前的标准模型无法解释这一过程。他的团队继续研究这种失败，以确定其普遍性以及错误的后果。 Yarkony 教授指导着一群学生和博士后。他们共同开发了可供社区用来探索新方法的软件。Yarkony 小组正在使用拟合耦合非绝热态电子哈密顿量来研究非绝热过程。它们利用了拟合表示的关键优势，即使用包含静态和动态相关性的波函数。计算了核量子效应，包括几何相位（GP）和隧道效应。为了处理强激光场和自旋变化过程，还必须表示偶极子和自旋轨道耦合项。 Yarkony 小组采用两步方法，其中使用高斯过程回归，然后应用神经网络技术。扩大以这种方式处理的问题范围的能力为处理非绝热过程提供了重要的新工具。非绝热势能矩阵的精度得到提高，同时可以严格对待量子隧道效应，并且将 GP 适当地包含在全维和降维表示中。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力评估进行评估，认为值得支持。优点和更广泛的影响审查标准。