Automatized Parameterization of DFTB Using Particle Swarm Optimization

Chien Pin Chou; Yoshifumi Nishimura; Chin Chai Fan; Grzegorz Mazur; Stephan Irle; Henryk A. Witek

doi:10.1021/acs.jctc.5b00673

Automatized Parameterization of DFTB Using Particle Swarm Optimization

Chien Pin Chou, Yoshifumi Nishimura, Chin Chai Fan, Grzegorz Mazur, Stephan Irle, Henryk A. Witek^*

^*Corresponding author for this work

Department of Applied Chemistry

Research output: Contribution to journal › Article › peer-review

55 Scopus citations

Abstract

We present a novel density-functional tight-binding (DFTB) parametrization toolkit developed to optimize the parameters of various DFTB models in a fully automatized fashion. The main features of the algorithm, based on the particle swarm optimization technique, are discussed, and a number of initial pilot applications of the developed methodology to molecular and solid systems are presented.

Original language	English
Pages (from-to)	53-64
Number of pages	12
Journal	Journal of Chemical Theory and Computation
Volume	12
Issue number	1
DOIs	https://doi.org/10.1021/acs.jctc.5b00673
State	Published - 12 Jan 2016

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10.1021/acs.jctc.5b00673

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abstract = "We present a novel density-functional tight-binding (DFTB) parametrization toolkit developed to optimize the parameters of various DFTB models in a fully automatized fashion. The main features of the algorithm, based on the particle swarm optimization technique, are discussed, and a number of initial pilot applications of the developed methodology to molecular and solid systems are presented.",

author = "Chou, {Chien Pin} and Yoshifumi Nishimura and Fan, {Chin Chai} and Grzegorz Mazur and Stephan Irle and Witek, {Henryk A.}",

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AU - Irle, Stephan

AU - Witek, Henryk A.

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AB - We present a novel density-functional tight-binding (DFTB) parametrization toolkit developed to optimize the parameters of various DFTB models in a fully automatized fashion. The main features of the algorithm, based on the particle swarm optimization technique, are discussed, and a number of initial pilot applications of the developed methodology to molecular and solid systems are presented.

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Automatized Parameterization of DFTB Using Particle Swarm Optimization

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