Data-driven Design of Quantum Photonic Devices
Aaron Sisto, Stanford University
Technologies inspired by natural photosynthetic processes have the potential to revolutionize device capabilities and illuminate a broad range of undiscovered products and materials. However, further progress in the realization and practical implementation of such molecular devices has been hindered by the inability to understand and intelligently design materials with the requisite properties and structural compatibility. In many cases, the complex interrelation between atomic structure and emergent functionality remains elusive. Here, we present an embarrassingly parallel empirical exciton framework that directly relates atomistic structural features of light-harvesting systems to macroscopic, observable quantities such as linear absorption spectra. The flexible parameterization of critical model features allows for a unique, systematically improvable description of virtually any molecular system, irrespective of size or conformation. Furthermore, the exciton model framework accurately captures the dynamical evolution of the electronic and nuclear wave functions, governing unique aspects of the light-matter interactions. Detailed inspection of multidimensional energy transfer pathways provides new insight into the underlying mechanisms behind energy transfer efficiency and light absorption in complex biological systems.
As an initial validation, the exciton model has proven to accurately predict the experimental absorption spectrum of light-harvesting complex II and for the first time has yielded a detailed perspective of the atomistic energy transfer dynamics in this naturally occurring photosynthetic complex. These results reveal new mechanistic design principles and the potential to construct artificial photosynthetic devices with advanced light-absorption and energy-transfer efficiencies.
Abstract Author(s): Aaron Sisto