Led by Associate Professor Lan Li and Distinguished Research Fellow Bernard Yurke, the team develops and implements theory, numerical models, computational modeling, and machine learning techniques. The team also determines dye structure-property relationships, predicts dye aggregate-DNA interactions, and designs excitonic molecular quantum gates and entangled systems.
- Key parameters of interest: Excitonic hopping parameter Jm,n, & Exciton-exciton interaction energy Km,n,
- Frenkel/molecular aggregate model development and coding (quantum mechanical theory)
- Density Functional Theory (DFT) and Time Dependent (TD) DFT of dyes and dye aggregates
- Molecular Dynamics (MD) and hybrid Quantum Mechanics and Molecular Mechanics (QM/MM) of DNA-dye aggregates
- Machine learning – dye surveys