Combining Graphics Processing Units, Simplified Time-Dependent Density Functional Theory, and Finite-Difference Couplings to Accelerate Nonadiabatic Molecular Dynamics

Peters, Laurens D. M. ; Kussmann, Jörg und Ochsenfeld, Christian (6. Mai 2020): Combining Graphics Processing Units, Simplified Time-Dependent Density Functional Theory, and Finite-Difference Couplings to Accelerate Nonadiabatic Molecular Dynamics. In: The Journal of Physical Chemistry Letters, Bd. 11, Nr. 10: S. 3955-3961

Abstract

Starting from our recently published implementation of nonadiabatic molecular dynamics (NAMD) on graphics processing units (GPUs), we explore further approaches to accelerate ab initio NAMD calculations at the time-dependent density functional theory (TDDFT) level of theory. We employ (1) the simplified TDDFT schemes of Grimme et al. and (2) the Hammes-Schiffer−Tully approach to obtain nonadiabatic couplings from finite-difference calculations. The resulting scheme delivers an accurate physical picture while virtually eliminating the two computationally most demanding steps of the algorithm. Combined with our GPU-based integral routines for SCF, TDDFT, and TDDFT derivative calculations, NAMD simulations of systems of a few hundreds of atoms at a reasonable time scale become accessible on a single compute node. To demonstrate this and to present a first, illustrative example, we perform TDDFT/MM-NAMD simulations of the rhodopsin protein.

• Dokumententyp: Zeitschriftenartikel
• EU Funded Grant Agreement Number: 765739
• EU-Projekte: Horizon 2020 > Marie Skłodowska Curie Actions > Marie Skłodowska-Curie Innovative Training Networks > 765739: COSINE - Training network for COmputational Spectroscopy In Natural sciences and Engineering
• Publikationsform: Publisher's Version
• Keywords: Time dependant density functional theory; Energy; Nonadiabatic coupling; Chemical calculations; Computational chemistry
• Fakultät: Chemie und Pharmazie > Department Chemie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 540 Chemie
• ISSN: 1948-7185
• Sprache: Englisch