Computational microscopy of excited aggregates

Abstract

The delicate processes following the photoexcitation underpin technologies and applications related to light utilization and conversion. However, understanding the relaxation mechanisms of excited states, especially in aggregates, remains challenging. In a recent study published in Chem, Prof. Li and co-workers combined machine learning techniques with multiscale theoretical calculation methods to create a powerful “computational microscopy,” enabling direct observation of the excited-state dynamics in aggregates and identification of the origin of reduced non-radiative decay in aggregation-induced emission.