Literature DB >> 31255076

Semiclassical vibrational spectroscopy with Hessian databases.

Riccardo Conte1, Fabio Gabas1, Giacomo Botti1, Yu Zhuang2, Michele Ceotto1.   

Abstract

We report on a new approach to ease the computational overhead of ab initio "on-the-fly" semiclassical dynamics simulations for vibrational spectroscopy. The well known bottleneck of such computations lies in the necessity to estimate the Hessian matrix for propagating the semiclassical pre-exponential factor at each step along the dynamics. The procedure proposed here is based on the creation of a dynamical database of Hessians and associated molecular geometries able to speed up calculations while preserving the accuracy of results at a satisfactory level. This new approach can be interfaced to both analytical potential energy surfaces and on-the-fly dynamics, allowing one to study even large systems previously not achievable. We present results obtained for semiclassical vibrational power spectra of methane, glycine, and N-acetyl-L-phenylalaninyl-L-methionine-amide, a molecule of biological interest made of 46 atoms.

Entities:  

Year:  2019        PMID: 31255076     DOI: 10.1063/1.5109086

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  2 in total

1.  Quantum Calculations on a New CCSD(T) Machine-Learned Potential Energy Surface Reveal the Leaky Nature of Gas-Phase Trans and Gauche Ethanol Conformers.

Authors:  Apurba Nandi; Riccardo Conte; Chen Qu; Paul L Houston; Qi Yu; Joel M Bowman
Journal:  J Chem Theory Comput       Date:  2022-08-11       Impact factor: 6.578

2.  Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields.

Authors:  Fabio Gabas; Riccardo Conte; Michele Ceotto
Journal:  J Chem Theory Comput       Date:  2020-05-20       Impact factor: 6.006

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.