2017 New Investigator Grant
Noa Marom, Ph.D. Assistant Professor, Materials Science and Engineering, Carnegie Mellon University
Singlet Fission: Deriving Fundamental Insights from Computation
When a molecule absorbs a photon with sufficient energy, an electron is promoted from an occupied state to an empty state, leaving a positively charged hole behind. This bound electron-hole pair is called an exciton. Singlet fission (SF) is the conversion of one singlet (opposite spin) exciton into two triplet (same spin) excitons, centered on different molecules. SF was first discovered in molecular crystals in 1965. For decades it remained underexplored and poorly understood. Recently, there has been a surge of renewed interest in SF thanks to its potential to lead to a twofold increase in the efficiency of organic solar cells by harvesting two charge carriers from one photon. However, the realization of SF solar cells is hindered by the dearth of suitable materials. SF is a complex collective quantum mechanical process involving electrons and holes whose correlation functions may extend over several molecules. The proposed research seeks to advance the fundamental understanding of the SF process by addressing three primary questions: (i) What are the conditions for SF in terms of the excitonic quantum states involved, their energies, and the nature of their wave-functions? (ii) What structural features and other ground state descriptors correlate with high SF efficiency? And finally, (iii) how can we design a molecular crystal (including the molecular species and their packing) to generate the desired excitonic quantum states? This will be achieved by developing a unique interdisciplinary computational approach integrating concepts from quantum chemistry, many-body physics, materials engineering, and data science. Structural features and other ground state descriptors that correlate strongly with SF efficiency will be revealed by applying machine learning algorithms for feature selection to a purpose-built first-principles dataset. To develop physical models and theories that explain the causal mechanisms behind these correlations further investigations will be conducted using many-body perturbation theory. The descriptors we identify will be used to make experimentally verifiable predictions of new SF materials. Ultimately, gaining fundamental understanding of SF may aid the discovery and design of better SF materials and the development of more efficient organic solar cells.