Literature DB >> 33689344

Analytical Time-Dependent Long-Range Corrected Density Functional Tight Binding (TD-LC-DFTB) Gradients in DFTB+: Implementation and Benchmark for Excited-State Geometries and Transition Energies.

Monja Sokolov1, Beatrix M Bold1, Julian J Kranz1, Sebastian Höfener1, Thomas A Niehaus2, Marcus Elstner1,3.   

Abstract

The absorption and emission of light is a ubiquitous process in chemical and biological processes, making a theoretical description inevitable for understanding and predicting such properties. Although ab initio and DFT methods are capable of describing excited states with good accuracy in many cases, the investigation of dynamical processes and the need to sample the phase space in complex systems often requires methods with reduced computational costs but still sufficient accuracy. In the present work, we report the derivation and implementation of analytical nuclear gradients for time-dependent long-range corrected density functional tight binding (TD-LC-DFTB) in the DFTB+ program. The accuracy of the TD-LC-DFTB potential-energy surfaces is benchmarked for excited-state geometries and adiabatic as well as vertical transition energies. The benchmark set consists of more than 100 organic molecules taken as subsets from available benchmark sets. The reported method yields a mean deviation of 0.31 eV for adiabatic excitation energies with respect to CC2. In order to study more subtle effects, seminumerical second derivatives based on the analytical gradients are employed to simulate vibrationally resolved UV/vis spectra. This extensive test exhibits few problematic cases, which can be traced back to the parametrization of the repulsive potential.

Entities:  

Year:  2021        PMID: 33689344     DOI: 10.1021/acs.jctc.1c00095

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  3 in total

1.  Excited-State Properties for Extended Systems: Efficient Hybrid Density Functional Methods.

Authors:  Anna-Sophia Hehn; Beliz Sertcan; Fabian Belleflamme; Sergey K Chulkov; Matthew B Watkins; Jürg Hutter
Journal:  J Chem Theory Comput       Date:  2022-06-27       Impact factor: 6.578

2.  Absorption Properties of Large Complex Molecular Systems: The DFTB/Fluctuating Charge Approach.

Authors:  Piero Lafiosca; Sara Gómez; Tommaso Giovannini; Chiara Cappelli
Journal:  J Chem Theory Comput       Date:  2022-02-20       Impact factor: 6.006

3.  Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules.

Authors:  Jong Youl Choi; Pei Zhang; Kshitij Mehta; Andrew Blanchard; Massimiliano Lupo Pasini
Journal:  J Cheminform       Date:  2022-10-17       Impact factor: 8.489

  3 in total

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