Theory of soft and disordered excitonic nano-materials.

具有非平凡电学性质的软而无序的纳米材料是分子科学和工程领域中的“隐形领域”。尽管人们一直在认真尝试理解和操纵它们的行为，但这类材料对实验和理论都构成了相当大的挑战，而且人们对它们知之甚少。例如，无定形的pi共轭聚合物和光学或磁性响应蛋白质就属于这一类。它们的机械灵活性、生物相容性、蛋白质对外界刺激的响应性以及非晶态聚合物的形态对外部条件的敏感性，使其在能源、医疗和电子工业中有很好的应用前景。然而，在大多数情况下，潜在的分子机制并不为人所知，这一事实阻碍了用于此类应用的设备的设计。我的研究计划旨在模拟和解释大型无序聚合系统中的电子激发行为，在这些系统中，分子级无序不是一种扰动，而是整个故事。作为我的第一步，我将为这类系统的多尺度量子/经典混合模拟构建一个定制的计算平台，其中现有的最先进方法将由我的团队开发的新方法来补充。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体系结构对聚合物聚集体的设备规模配置进行采样的方法；2.在两种具有挑战性的场景中用于光激发动力学的算法：A.用于非常大但弱关联的电子系统，以及B.用于嵌入在感兴趣的极化环境中的小型但强关联的电子系统。然后，我将使用这些计算工具进行计算实验，这些实验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就无法解释的实验观察，最后概念化形态对这类材料中光激发的动力学和命运的影响。这项研究准备开发强烈无序的光电子物质的概念词汇，并帮助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.