Quantum effects in dynamics of nuclei 
Quantum-mechanical effects in molecular dynamics are essential for accurate description
                                 and understanding of many chemical processes, such as those in surface reactions,
                                 photochemistry, in interactions of molecules with electric field, in chemistry of
                                 polymers, clusters and liquids. QM effects are the most pronounced in processes involving
                                 atomic and molecular hydrogen. For example, the isotope effects in water are manifested
                                 in such basic properties as melting point, which is 3.82C for the deuterated water,
                                 and the temperature of maximum density in liquid state, which is 4C for water and
                                 11.2C for the deuterated water. Our theoretical work is guided by the ultimate goal
                                 -- to study dynamics of complex molecular systems using an accurate and efficient
                                 method which incorporates the nuclear  quantum effects and is compatible with classical
                                 molecular dynamics. Applications include the  proton transfer processes in enzymes
                                 and other bio- and nano-environments, the electron transport in open quantum systems,
                                 and properties of hybrid materials.  
The trajectory-based quantum dynamics
The time-dependent Schrodinger equation can be recast in terms of the wavefunction
                                 amplitude and phase associated with the trajectories evolving in time according to
                                 Hamilton's equations of motion. All quantum effects are expressed through the action
                                 of quantum potential dependent on the amplitude and its derivatives, acting on a trajectory
                                 in addition to the external "classical'' potential. For general problems, the exact
                                 determination of the quantum potential is at least as difficult as the solution of
                                 the standard Schrodinger equation. We develop global approximations to the quantum
                                 potential which capture the nuclear quantum effects (the zero-point energy, tunneling)
                                 in a computationally efficient manner. Our high-dimensional quantum trajectory code
                                 with on-the-fly force calculations has been applied to study the proton transfer in
                                 material (Fig. 1) and biological environments.   We are also developing  exact quantum
                                 methods such as the Quantum-Trajectory guided Adaptable Gaussian (QTAG) bases  (Fig.
                                 2), and the Factorized electron-nuclear dynamics (FENDy). 
The Nuclear Quantum Effect in chemical systems
Recent experiments show that small effects in the changes in the zero-point energy
                                 of OH and OD affects properties of large molecular systems such as crystallization
                                 properties of P3HT this films (Fig. 3), photovoltaic properties of P3HT/CPBM blend
                                 developed for the solar cell applications, the proton conductance through atomically
                                 thin films of graphene, hexagonal boron nitride and others.  We are working closely
                                 with experimental groups, i.e. the  Shustova, L. Shimizu and C. Tang   groups at USC,
                                 and the Makris group at NC State University, investigating the properties of complex
                                 molecular systems  (Fig. 4) and mechanisms of the charge, energy, hydrogen (Fig. 5)
                                 and hydroxide transfer in complex molecular environments using chemical theory, computations
                                 and machine learning.