Theoretical Chemistry involves the development of new mathematical models to describe the properties of molecules, using techniques from quantum mechanics, statistical mechanics, and chemical dynamics. These models can be rather complex, and their application to chemical problems may require substantial computer resources. The School of Chemistry and Biochemistry has a strong group of faculty working in the development and application of theoretical chemistry methods. Research topics include improved molecular dynamics and Monte Carlo simulations, and electronic structure methods yielding a deeper understanding of intermolecular forces. Georgia Tech is one of the lead institutions in the development of the open-source electronic structure package Psi. Application areas include electrochemical energy storage materials, optical and electronic properties of organic materials, and how non-covalent interactions influence drug binding, biomolecular structure, and crystal packing. The School has access to over 1000 processor cores for demanding simulations.
Faculty
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Organic Electronics and Photonics; Pi-Conjugated Polymers, Oligomers, and Molecular Materials; Electronic Structure of Electrically and Optically Active Organic Materials; Organic Semiconductors; Charge Transport in Organic Materials; Organic Solar Cells; Organic Transistors; Organic Light-Emitting Diodes; Organic/Organic, Organic/Metal, and Organic/Oxide Interfaces; Molecular Mechanics/Dynamics Simulations of Active Layers in Organic Devices; Mixed-Valence Organic Compounds; Second-Order and Third-Order Nonlinear Optical Properties; Two-Photon Absorption; All-Optical Switching
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molecular dynamics simulations; protein dynamics; membrane proteins; protein synthesis; bacteria-specific systems and processes
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Theoretical chemistry; quantum dynamics; non-adiabatic dynamics; quantum chemistry; quantum embedding; charge transport; light-matter interactions
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Molecular dynamics, Monte Carlo, quantum chemistry, high-performance computing, electrochemistry, electrochemical energy storage, self-assembly, nanostructured materials, ab initio modeling, machine-learning
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Quantum chemistry; intermolecular forces; theoretical chemistry; algorithms; modeling; machine learning and data generation; software development; high-performance computing
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origin of life, protein structure and function prediction, modeling of cells and cellular networks, drug discovery, modeling of biological systems
