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Computational Methods for Determining Structure and Dynamics in DNA-Scaffolded Molecular Networks
This memorandum describes the research conducted by Dr. Brian Rolczynski (Code 6816) during his Jerome and Isabella Karle Distinguished Scholar Fellowship. This research developed computational methods to understand the nanoscale structural characteristics, energy levels, couplings, and related parameters for DNA-scaffolded molecular networks. Three methods are described: (1) a genetic algorithm approach to deduce the structures and Hamiltonians of molecular networks; (2) an approach based on the hierarchical equations of motion to calculate the vibronic dynamics and corresponding heat currents, which impact quantum-mechanical dephasing in these systems; (3) a Random Forest machine-learning algorithm to analyze the roles of particular molecular arrangements on the functional energy-transport processes. These methods collectively reveal the structure-dynamics-function relationships in DNA-scaffolded molecular networks, which is an important step toward optimizing these materials for uses such as quantum-mechanical technology or light-harvesting materials.
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