Time-Dependent Density Functional Theory

• We implemented Surface Hopping within real-time TDDFT in the Kohn-Sham representation, allowing us to study large, condensed phase systems and long timescales all the way to thermal (Boltzmann) equilibration.

C. F. Craig, W. R. Duncan, O. V. Prezhdo “Trajectory surface hopping in the time-dependent Kohn-Sham theory for electron-nuclear dynamics”, Phys. Rev. Lett., 95 163001 (2005). 

• We developed the classical path approximation for real-time TDDFT. It works with many condensed phase systems and processes, as exemplified in the applications sections.

A. V. Akimov, O. V. Prezhdo “The PYXAID program for non-adiabatic molecular dynamics in condensed matter systems”, J. Chem. Theor. Comp., 9, 4959 (2013).

A. V. Akimov, O. V. Prezhdo “Advanced capabilities of the PYXAID program: integration schemes, decoherence effects, multiexcitonic states, and field-matter interaction”, J. Chem. Theor. Comp., 10, 789 (2014).

• We developed real-time TDDFT methodologies to study Auger type processes driven by Coulomb interactions. Such processes are very common in nano-confined materials, metals, etc.

G. Zhou, G. Lu, O. V. Prezhdo, “Modeling Auger Processes with Nonadiabatic Molecular Dynamics”, Nano Lett., 21, 756–761 (2021)

S. Gumber, O. V. Prezhdo, “Energy-Conserving Surface Hopping for Auger Processes”, J. Chem. Theor. Comp., 20, 5408-5417 (2024); DOI: 10.1021/acs.jctc.4c00562

• We implemented Nonadiabatic Molecular Dynamics methods within self-consistent tight-binding TDDFT, making it applicable to thousand atom systems.

S. Pal, D. J. Trivedi, A. V. Akimov, B. Aradi, T. Frauenheim, O. V. Prezhdo, “Nonadiabatic molecular dynamics for thousand atom systems: a tight-binding approach toward PYXAID”, J. Chem. Theor. Comp., 12, 1436-1448 (2016).

• We developed Nonadiabatic Molecular Dynamics based on machine learning DFT, making it applicable to thousand atom systems and nanosecond timescales, and providing a general way to obtain DFT parameters for different materials.

D. Liu, B. Wang, Y. Wu, A. S. Vasenko, O. V. Prezhdo, “Breaking the Size Limitation of Non-Adiabatic Molecular Dynamics in Condensed Matter Systems with Local Descriptor Machine Learning”, Proc. Nat. Acad. Sci. USA, 121, e2403497121 (2024)