Theory of soft and disordered excitonic nano-materials.

具有非平凡电子性质的柔软无序纳米材料是分子科学与工程领域的一个“未知领域”。虽然有正在进行的认真尝试，以了解和操纵他们的行为，这类材料提出了一个相当大的挑战，实验和理论，并很少有人确切地知道他们。例如，无定形π-缀合的聚合物和光学或磁性响应蛋白属于这一类。它们的机械柔性、生物相容性、蛋白质对外界刺激的响应性以及无定形聚合物形态对外界条件的敏感性，使它们在能源、医疗和电子工业中具有应用前景。然而，在大多数情况下，潜在的分子机制是未知的，这一事实阻碍了这种应用的设备的设计。我的研究项目旨在模拟和解释大型无序聚合物系统中的电子激发行为，其中分子水平的无序不是扰动，而是整个故事。作为我的第一步，我将构建一个自定义计算平台，用于对此类系统进行多尺度量子/经典混合模拟，其中现有的最先进方法将由我的团队开发的新方法进行补充。我的创新努力将集中在：1。通过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规模配置进行采样的方法; 2.在两种具有挑战性的情况下用于光激发的动力学的算法：a.对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偏振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进行计算实验，这将有助于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，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。这项研究准备为强无序光电物质开发概念词汇，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.