XtalOpt: An open-source evolutionary algorithm for crystal structure prediction

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• 作者：David C. Lonie ; Eva Zurek
• 关键词：Structure prediction ; Evolutionary algorithm ; Genetic algorithm ; Crystal structures ; Titanium dioxide
• 刊名：Computer Physics Communications
• 出版年：2011
• 出版时间：February 2011
• 年：2011
• 卷：182
• 期：2
• 页码：372-387
• 全文大小：2566 K

文摘

The implementation and testing of XtalOpt, an evolutionary algorithm for crystal structure prediction, is outlined. We present our new periodic displacement (ripple) operator which is ideally suited to extended systems. It is demonstrated that hybrid operators, which combine two pure operators, reduce the number of duplicate structures in the search. This allows for better exploration of the potential energy surface of the system in question, while simultaneously zooming in on the most promising regions. A continuous workflow, which makes better use of computational resources as compared to traditional generation based algorithms, is employed. Various parameters in XtalOpt are optimized using a novel benchmarking scheme. XtalOpt is available under the GNU Public License, has been interfaced with various codes commonly used to study extended systems, and has an easy to use, intuitive graphical interface.

Program summary

Program title: XtalOpt

Catalogue identifier: AEGX_v1_0

Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEGX_v1_0.html

Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland

Licensing provisions: GPL v2.1 or later [1]

No. of lines in distributed program, including test data, etc.: 36 849

No. of bytes in distributed program, including test data, etc.: 1 149 399

Distribution format: tar.gz

Programming language: C++

Computer: PCs, workstations, or clusters

Operating system: Linux

Classification: 7.7

External routines: QT [2], OpenBabel [3], AVOGADRO [4], SPGLIB [8] and one of: VASP [5], PWSCF [6], GULP [7].

Nature of problem: Predicting the crystal structure of a system from its stoichiometry alone remains a grand challenge in computational materials science, chemistry, and physics.

Solution method: Evolutionary algorithms are stochastic search techniques which use concepts from biological evolution in order to locate the global minimum on their potential energy surface. Our evolutionary algorithm, XtalOpt, is freely available to the scientific community for use and collaboration under the GNU Public License.

Running time: User dependent. The program runs until stopped by the user.

References:

[1] http://www.gnu.org/licenses/gpl.html.

[2] http://www.trolltech.com/.

[3] http://openbabel.org/.

[4] http://avogadro.openmolecules.net.

[5] http://cms.mpi.univie.ac.at/vasp.

[6] http://www.quantum-espresso.org.

[7] https://www.ivec.org/gulp.

[8] http://spglib.sourceforge.net.