{"title":"XtalOpt version 13: Multi-objective evolutionary search for novel functional materials","authors":"Samad Hajinazar, Eva Zurek","doi":"10.1016/j.cpc.2024.109306","DOIUrl":null,"url":null,"abstract":"<div><p>Version 13 of <span>XtalOpt</span>, an evolutionary algorithm for crystal structure prediction, is now available for download from the CPC program library or the <span>XtalOpt</span> website, <span><span>https://xtalopt.github.io</span><svg><path></path></svg></span>. In the new version of the <span>XtalOpt</span> code, a general platform for multi-objective global optimization is implemented. This functionality is designed to facilitate the search for (meta)stable phases of functional materials through minimization of the enthalpy of a crystalline system coupled with the simultaneous optimization of any desired properties that are specified by the user. The code is also able to perform a constrained search by filtering the parent pool of structures based on a user-specified feature, while optimizing multiple objectives. Here, we present the implementation and various technical details, and we provide a brief overview of additional improvements that have been introduced in the new version of <span>XtalOpt</span>.</p></div><div><h3>Program summary</h3><p><em>Program Title:</em> XtalOpt</p><p><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/jt5pvnnm39.4</span><svg><path></path></svg></span></p><p><em>Developer's repository link:</em> <span><span>https://github.com/xtalopt/XtalOpt</span><svg><path></path></svg></span></p><p><em>Licensing provisions:</em> BSD 3-clause</p><p><em>Programming language:</em> C++.</p><p><em>Journal reference of previous version:</em> Comput. Phys. Commun. 237 (2019) 274–275.</p><p><em>Does the new version supersede the previous version?:</em> Yes.</p><p><em>Reasons for the new version:</em> Implementation of a multi-objective evolutionary search within the XtalOpt program package.</p><p><em>Summary of revisions:</em> Implemented a general user-friendly multi-objective search capability, made various improvements to user interface and functionalities, performed bug fixes.</p><p><em>Nature of problem:</em> The XtalOpt algorithm is designed to search for (meta)stable crystal structures, optionally with specific functionalities – a grand challenge in computational materials science, chemistry and physics.</p><p><em>Solution method:</em> A generalized scalar fitness function, where a set of user-specified objectives contribute to the fitness value for candidate structures, is implemented within XtalOpt. This generalized fitness biases the search towards the discovery of (meta)stable phases with structural motifs that are key for the desired characteristics. As a result, the evolutionary search explores regions of the energy landscape of higher relevance in terms of target properties.</p></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"304 ","pages":"Article 109306"},"PeriodicalIF":7.2000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465524002297","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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Abstract
Version 13 of XtalOpt, an evolutionary algorithm for crystal structure prediction, is now available for download from the CPC program library or the XtalOpt website, https://xtalopt.github.io. In the new version of the XtalOpt code, a general platform for multi-objective global optimization is implemented. This functionality is designed to facilitate the search for (meta)stable phases of functional materials through minimization of the enthalpy of a crystalline system coupled with the simultaneous optimization of any desired properties that are specified by the user. The code is also able to perform a constrained search by filtering the parent pool of structures based on a user-specified feature, while optimizing multiple objectives. Here, we present the implementation and various technical details, and we provide a brief overview of additional improvements that have been introduced in the new version of XtalOpt.
Program summary
Program Title: XtalOpt
CPC Library link to program files:https://doi.org/10.17632/jt5pvnnm39.4
Does the new version supersede the previous version?: Yes.
Reasons for the new version: Implementation of a multi-objective evolutionary search within the XtalOpt program package.
Summary of revisions: Implemented a general user-friendly multi-objective search capability, made various improvements to user interface and functionalities, performed bug fixes.
Nature of problem: The XtalOpt algorithm is designed to search for (meta)stable crystal structures, optionally with specific functionalities – a grand challenge in computational materials science, chemistry and physics.
Solution method: A generalized scalar fitness function, where a set of user-specified objectives contribute to the fitness value for candidate structures, is implemented within XtalOpt. This generalized fitness biases the search towards the discovery of (meta)stable phases with structural motifs that are key for the desired characteristics. As a result, the evolutionary search explores regions of the energy landscape of higher relevance in terms of target properties.
期刊介绍：
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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