全维分子与分子间坐标空间中单线态裂分速率筛选的功能性优化
Functionality Optimization for Singlet Fission Rate Screening in the Full-Dimensional Molecular and Intermolecular Coordinate Space
AI总结：
提出受基态能量约束并基于算法微分的功能性优化方法，用于在全维结构空间中筛选高单线态裂分速率的PBI二聚体构型。
摘要：
在计算化学中，准确预测表现出特定性质的分子构型仍是一项关键挑战。其复杂性在分子聚集体研究中尤为明显，因为光诱导功能与分子间高度依赖结构的电子耦合相关。在此，我们提出一种利用“功能性优化”技术对结构空间进行定向筛选的高效策略，其中选定的描述符在基态能量表达式的约束下被优化。所选的算法微分（AD）框架能够自动获得梯度，而无需繁琐的实现。我们通过识别具有增强SF速率的苝二酰亚胺（PBI）二聚体基序，证明了该方法的有效性。研究结果表明，PBI单体的某些结构修饰，如螺旋扭曲和弯曲，以及滑移-旋转堆积排列，可显著提高SF速率。
英文摘要：
In computational chemistry, accurately predicting molecular configurations that exhibit specific properties remains a critical challenge. Its intricacies become especially evident in the study of molecular aggregates, where the light-induced functionality is tied to highly structure-dependent electronic couplings between molecules. Here, we present an efficient strategy for the targeted screening of the structural space employing a "functionality optimization" technique, in which a chosen descriptor, constrained by the ground state energy expression, is optimized. The chosen algorithmic differentiation (AD) framework allows to automatically obtain gradients without its tedious implementation. We demonstrate the effectiveness of the approach by identifying Perylene Bisiimide (PBI) dimer motifs with enhanced SF rate. Our findings reveal that certain structural modifications of the PBI monomer, such as helical twisting and bending, as well as slipped-rotated packing arrangements, can significantly increase the SF rate.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
