QUANTUM SIMULATION OF CHEMICAL DYNAMICS IN CONDENSED PHASES

来自德克萨斯大学奥斯汀分校的Peter Rossky得到了化学理论，模型和计算方法项目的支持，该项目的研究重点是在原子水平上理解化学变化发生在液体溶液或非结构化固体材料中时的分子排列和时间依赖性过程。这些变化包括生物材料、半导体材料和塑料中发生的变化。 虽然计算建模越来越能够描述这些过程，但仍然存在严重的挑战。 例如，能够理解通过吸收光而沉积在分子中的能量发生了什么是非常重要的。 这些知识是我们理解材料降解、太阳能电池功能和光合作用等生物过程的关键要素。本研究的具体目标是开发新的、普遍适用的理论和计算模型和方法，这些模型和方法可以充分描述涉及非常轻的原子和电子的化学，其中必须调用量子力学。正在开发的算法可以直接应用于先进材料，药物发现和纳米工程设计的计算工具。 它们还可以影响关键的实际问题，包括可负担得起的太阳能捕获可持续能源和可持续气候。这项工作产生的外联活动有助于科学工作者未来的稳定性，以及公众参与科学政策的能力，研究工作正在开发新的模拟算法，用于核运动的量子力学描述，在关键方面超越了目前可用的实用方法。新的方法是基于动态的维格纳变换变量，是一个相当直接的推广早期的线性化路径积分（“经典维格纳”）的方法。新方法保留了直接评估非线性算子动态的能力（例如，在非弹性X射线散射中），并且描述了没有与模拟算法相关联的非物理分量的振动动力学。此外，由于新方法直接传播相空间点（与基于路径积分的方法相反），因此有充分的理由相信它可以集成到非绝热电子动力学协议中。应用相对良好的表征分子系统正在被用来测试新方法的能力。引导我们找到具有所需功能的新材料或洞察自然解决方案所需的分子尺度洞察力将来自先进计算科学的实施，并与揭示性实验探针相协调。由此产生的能力形成了未来常规建模方法的基础，就像过去50年的基础研究通常为今天的实验研究人员提供的一样。项目工作加强了各级教育，包括研究生和博士后学生的专业发展，使他们成为研究人员和教育工作者，及时掌握计算解决物理问题的技能。

Peter Rossky from the University of Texas at Austin is supported by the Chemical Theory, Models and Computational Methods Program in research focused on understanding, at the level of atoms, the molecular arrangements and time-dependent processes that occur when chemical changes take place in liquid solutions or in unstructured solid materials. These include the changes that occur in biological materials, in semiconductor materials, and in plastics. Although computational modeling is increasingly able to describe these processes, serious challenges remain. For example, it is very important to be able to understand what happens to the energy that is deposited in molecules through the absorption of light. Such knowledge is a critical element for our understanding of the degradation of materials, of the functioning of solar cells, and of biological processes such as photosynthesis. The specific objective of the present studies is the development of new, generally applicable, theoretical and computational models and methods that can fully describe chemistry involving very light atoms and electrons, where quantum mechanics must be invoked. The algorithms being developed can be directly applied as computational tools for the design of advanced materials, pharmaceutical discovery, and nanoscale engineering. They can also impact critical practical issues, including affordable solar energy capture for sustainable energy and a sustainable climate. Outreach activities stemming from this work contribute to the future stability of the scientific workforce, as well as to the public's ability to participate in science policy.The research efforts are developing new simulation algorithms for the quantum mechanical description of nuclear motion that go beyond presently available practical methods in key respects. The novel method is based on the dynamics of Wigner transform variables and is a rather direct generalization of an earlier linearized path integral ("classical Wigner") approach. The new approach retains the ability to directly evaluate the dynamics of non-linear operators (e.g., in inelastic X-ray scattering) and describes vibrational dynamics without unphysical components associated with the simulation algorithm. Further, since the new method directly propagates the phase space points (in contrast to path-integral based approaches), there is good reason to believe that it can be integrated into a non-adiabatic electronic dynamics protocol. Applications to relatively well-characterized molecular systems are being used to test the capability of new methods. The molecular-scale insight needed to guide us to new materials with desired functions or insight into Nature's solutions will follow from the implementation of advanced computational science, coordinated with revealing experimental probes. The resulting capabilities form the basis for what may be the routine modeling methods of the future, just as the basic research of the last 50 years routinely provides for today's experimental researcher. Project efforts enhance education at all levels, including the professional development of graduate and postdoctoral students as researchers and educators with timely skills in the computational solution of physical problems.