Theory of soft and disordered excitonic nano-materials.

具有非平凡电子特性的软无序纳米材料是分子科学与工程的“未知领域”。尽管人们正在认真地尝试理解和操纵它们的行为，但这类材料对实验和理论都提出了相当大的挑战，而且对它们知之甚少。例如，无定形偶联聚合物和光学或磁响应蛋白就属于这一类。它们的机械灵活性、生物相容性、蛋白质对外部刺激的反应性以及非晶聚合物形态对外部条件的敏感性，使它们成为能源、医疗和电子工业应用的有希望的候选者。然而，在大多数情况下，潜在的分子机制尚不清楚，这一事实阻碍了此类应用设备的设计。我的研究项目旨在模拟和解释大型无序聚合物系统中电子激发的行为，在这些系统中，分子水平的无序不是一个扰动，而是整个故事。作为我的第一步，我将为这些系统的多尺度量子/经典混合模拟构建一个定制的计算平台，其中现有的最先进的方法将被我的团队开发的新方法所补充。我的创新工作将集中在：1。利用新兴的机器学习算法和计算架构对聚合物聚集体的设备级配置进行采样的方法；2. 在两种具有挑战性的情况下光激发动力学的算法：a.用于非常大但弱相关的电子系统，b.用于嵌入在感兴趣的极化环境中的小但强相关的电子系统。然后，我将使用这些计算工具来执行计算实验，这将帮助我们识别关键复杂系统的特征行为，解释没有足够的分子水平洞察力就无法解释的实验观察，并最终概念化形态对动力学的影响和光激发在这类材料中的命运。这项研究将发展强无序光电物质的概念词汇，并有助于释放有机和生物电子学的潜力。

Soft and disordered nano-materials with non-trivial electronic properties are a `terra incognita' of molecular science and engineering. Although there are ongoing serious attempts to understand and manipulate their behavior, this class of materials presents a considerable challenge to both experiment and theory, and little is firmly known about them. For example, amorphous pi-conjugated polymers, and optically or magnetically responsive proteins fall into this category. Their mechanical flexibility, biological compatibility, proteins' responsiveness to external stimuli, and the sensitivity of the morphology of amorphous polymers to external conditions, make them promising candidates for applications in energy, medical and electronics industries. The design of devices for such applications is, however, hindered by the fact that in most cases the underlying molecular mechanisms are not known. My research program aims to model and explain the behavior of electronic excitations in large and disordered polymeric systems in which molecular level disorder is not a perturbation but the entire story. As my first step, I will construct a custom computational platform for the multi-scale quantum/classical hybrid simulation of such systems where existing state of the art methods will be complemented by new methods developed in my group. My innovation efforts will be focused on: 1. methods for sampling device-scale configurations of aggregates of polymers by leveraging the emerging machine learning algorithms and computational architectures; 2. algorithms for the dynamics of photo-excitations in two challenging scenarios: a. for very large but weakly correlated electronic systems, and b. for small but strongly correlated electronic systems embedded in polarizing environments of interest. I will then use these computational tools to perform computational experiments which will help us identify the characteristic behaviors of key complex systems, explain experimental observations which cannot be explained without sufficient molecular level insight, and finally conceptualize the effects of morphology on the dynamics and the fate of photo-excitations in this class of materials. This research is poised to develop the conceptual vocabulary for strongly disordered optoelectronic matter and help unlock the potential of organic and bio- electronics.