Electronic Structure Theory and Quantum Chemistry

Our research interests range from small molecules to large, condensed phase systems, and from methods development to applications (i.e., drug or materials discovery and design).

One particular area of emphasis is the acceleration quantum chemistry calculations using (1) Grassmannians from differential geometry, (2) fragmentations from set theory, and (3) machine learning.

(1) Accelerating Quantum Chemistry Calculations Using Grassmannians:

  • K. U. Lao, K. Wickramasinghe, and J. A. Tan. J. Chem. Phys. 163, 144114 (2025).
  • J. A. Tan and K. U. Lao. Phys. Chem. Chem. Phys. 26, 1436 (2024).
  • J. A. Tan and K. U. Lao. J. Chem. Phys. 158, 214104 (2023).
  • J. A. Tan and K. U. Lao. J. Chem. Phys. 158, 051101 (2023).

(2) Accelerating Quantum Chemistry Calculations Using Fragmentations:

  • K. U. Lao and D. Wang. ChemPhysChem 26, e202500094 (2025).
  • F. Ballesteros and K. U. Lao. Phys. Chem. Chem. Phys. 26, 4386 (2024).
  • F. Ballesteros, J. A. Tan, and K. U. Lao. J. Chem. Phys. 159, 074107 (2023). [Selected as a JCP Editor’s Choice 2023, Selected in 2023 JCP Emerging Investigators Special Collection, and as a JCP Editor’s Pick]
  • F. Ballesteros and K. U. Lao. J. Chem. Theory Comput. 18, 179 (2022).

(3) Accelerating Quantum Chemistry Calculations Using Machine Learning:

  • K. U. Lao and C. Villot. J. Chem. Phys. 160, 184108 (2024). [Selected in 2024 JCP Emerging Investigators Special Collection]
  • C. Villot and K. U. Lao. J. Chem. Phys. 160, 184103 (2024). The model is freely available on GitHub. [Selected in 2024 JCP Emerging Investigators Special Collection, and as a JCP Editor’s Pick]
  • C. Villot, T. Huang, and K. U. Lao. J. Chem. Phys. 159, 044103 (2023). The model is freely available on GitHub.

Another particular area of emphasis is the accurate and efficient calculation of noncovalent interactions in large and/or complex systems, which is a challenging problem for electronic structure theory. Tuning noncovalent interactions in drug binding and organic molecular materials is a key step in controlling the efficacy of drug molecules and function of molecular materials. In many cases, it is prohibitively expensive to investigate large numbers of potential molecules and structures experimentally. For other cases, an analysis of atomistic details of interest helps interpret ambiguous experimental data or resolve dissimilar models. Our research goal is to develop fast and accurate approaches for gaining a fundamental understanding of the factors governing the drug binding and molecular materials packing in order to provide a basis for the development of new drug molecules and functionalized molecular materials. Furthermore, adapting the methodology we are going to develop to the rapid evolution of machine-learning techniques offers a unique opportunity to generate new noncovalent molecular electronics and drug molecules through large-scale computational screening and design since the combination of different strategies to functionalize molecules is seemingly infinite.

(4) Investigating Noncovalent Interactions in Large and/or Complex Systems:

  • K. U. Lao. Nanotechnology 36, 095704 (2025).
  • K. U. Lao. J. Chem. Phys. 161, 234103 (2024). [Selected in 2024 JCP Emerging Investigators Special Collection]
  • C. Villot and K. U. Lao. J. Chem. Phys. 158, 094301 (2023).
  • C. Villot, F. Ballesteros, D. Wang, and K. U. Lao. J. Phys. Chem. A 126, 4326 (2022). [Featured on cover]
  • F. Ballesteros, S. Dunivan, and K. U. Lao. J. Chem. Phys. 154, 154104 (2021).

Our group primarily works with a quantum chemistry software program called Q-Chem, to which we contribute new methods and algorithms.

We sincerely acknowledge the following funding supports for our research:

  • National Science Foundation, CAREER, CTMC program, 2025-2029
  • National Science Foundation, Division of Chemistry, CSD program, 2025-2027
  • The VCU Breakthroughs Fund, 2024-2026
  • The VCU College of Humanities and Sciences Seed Awards program, 2024-2025
  • National Science Foundation, Office of Advanced Cyberinfrastructure, MRI program, 2023-2026
  • The VCU College of Humanities and Sciences Seed Awards program, 2023-2024
  • National Science Foundation, Division of Chemistry, CAT program, 2022-2025
  • National Science Foundation, Division of Materials Research, EPM program, 2022-2025
  • The VCU Presidential Research Quest Fund, 2021-2022
  • American Chemical Society Petroleum Research Fund, 2020-2024
  • The VCU Honors Summer Undergraduate Research Program, 2020
  • Higher Education Equipment Trust Fund, 2019-2020