Computational Methods for Determining Structure and Dynamics in DNA-Scaffolded Molecular Networks

Abstract

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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Document Details

Document Type
Technical Report
Publication Date
Dec 16, 2022
Accession Number
AD1189416

Entities

People

  • Brian S. Rolczynski

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Chemistry
  • Computational Science
  • Computations
  • Computers
  • Data Science
  • Energy Levels
  • Energy Transfer
  • Equations Of Motion
  • Frequency
  • Genetic Algorithms
  • Information Processing
  • Information Science
  • Machine Learning
  • Materials
  • Physics
  • Quantum Computers
  • Quantum Computing
  • Quantum Information
  • Quantum Information Science
  • Spectra
  • Spectroscopy
  • Two Dimensional

Readers

  • Military History
  • Nanocomposite Materials Science
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.

Technology Areas

  • AI & ML
  • Biotechnology
  • Quantum Computing