Ab-initio Density-matrix Exascale-Parallelized Transport for Spin-Selectivity (ADEPTS) is a DOE Computational Chemical Sciences center, aiming at developing first-principles quantum dynamics and transport softwares with exascale computing capabilities and a focus on spin-related phenomena in solids.
The capability to control chemical reactions using the spin of electrons, in the rapidly emerging field of “Spin Chemistry”, provides exciting opportunities to produce desired molecules and solids with high selectivity and enhance the energy efficiency of chemical synthesis. Simultaneously, the increased focus on manipulating spin in materials for quantum information is leading to advanced techniques for precise spin control, which can further advance the potential of spin-dependent catalysis. Realizing the promise of spin chemistry now requires a mechanistic understanding of the effects of spin on chemical reactivity, in turn necessitating computational prediction of the generation, dynamics and chemical impact of spin in materials.
The overarching goal of this research program is to quantitatively predict out-of-equilibrium quantum dynamics and transport, targeting spin-selective chemistry, with four main objectives:
1. Develop first-principles open quantum dynamics, by time evolution of reduced density matrices to capture coherent and incoherent dynamics due to interactions with the environment (phonon, impurities, and solvent)
2. Develop quantum transport for spin and electrons with ab-initio scattering and many-body interactions, with time and spatial resolution.
3. Develop spin and chiral spectroscopic signatures: circularly-polarized pump-probe spectroscopy, circular dichroism (CD), circular (spin) photogalvanic effect, and time-resolved Kerr rotation measurements
4. Quantum dynamics in solvated environments, accounting for both coherent and incoherent impact of solvation on the dynamics.
Team
- Yuan Ping (University of Wisconsin-Madison)
- Ravishankar Sundararaman (Rensselaer Polytechnic Institute)
Software
Support
We acknowledge the support from Department of Energy, Basic Energy Science, Computational Chemical Sciences program under grant No. DE-SC0023301
