{"title":"Constructing one-dimensional supramolecular polymer structures using particle swarm optimization technique","authors":"","doi":"10.1007/s00214-024-03095-z","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>In the realm of studying supramolecular polymers using computer simulations, the task of generating appropriate initial structures poses a significant challenge, primarily owing to the extensive range of potential configurations. In this study, we introduce <em>StackGen</em>, an open-source framework designed to efficiently create energy-optimized one-dimensional supramolecular polymer structures with minimal computational overhead. This tool utilizes the particle swarm optimization (PSO) algorithm in conjunction with a semiempirical quantum mechanical approach to identify low-energy supramolecular stack configurations from a diverse set of possibilities. These configurations result from the translational and rotational adjustments of adjacent molecules around monomers along various axes. The tool also considers various structural factors, including the presence of functional side groups and the extent of intermolecular <span> <span>\\(\\pi\\)</span> </span>–<span> <span>\\(\\pi\\)</span> </span> stacking interactions. Extensive testing across different molecules demonstrates <em>StackGen</em>’s ability to produce low-energy structures with negligible computational costs. Additionally, the tool incorporates features for optimizing PSO hyperparameters in real-time, thus improving convergence. The tool provides a convenient means of generating structures suitable for both molecular simulations and quantum mechanical calculations.</p>","PeriodicalId":23045,"journal":{"name":"Theoretical Chemistry Accounts","volume":"5 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Chemistry Accounts","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s00214-024-03095-z","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
In the realm of studying supramolecular polymers using computer simulations, the task of generating appropriate initial structures poses a significant challenge, primarily owing to the extensive range of potential configurations. In this study, we introduce StackGen, an open-source framework designed to efficiently create energy-optimized one-dimensional supramolecular polymer structures with minimal computational overhead. This tool utilizes the particle swarm optimization (PSO) algorithm in conjunction with a semiempirical quantum mechanical approach to identify low-energy supramolecular stack configurations from a diverse set of possibilities. These configurations result from the translational and rotational adjustments of adjacent molecules around monomers along various axes. The tool also considers various structural factors, including the presence of functional side groups and the extent of intermolecular \(\pi\)–\(\pi\) stacking interactions. Extensive testing across different molecules demonstrates StackGen’s ability to produce low-energy structures with negligible computational costs. Additionally, the tool incorporates features for optimizing PSO hyperparameters in real-time, thus improving convergence. The tool provides a convenient means of generating structures suitable for both molecular simulations and quantum mechanical calculations.
期刊介绍：
TCA publishes papers in all fields of theoretical chemistry, computational chemistry, and modeling. Fundamental studies as well as applications are included in the scope. In many cases, theorists and computational chemists have special concerns which reach either across the vertical borders of the special disciplines in chemistry or else across the horizontal borders of structure, spectra, synthesis, and dynamics. TCA is especially interested in papers that impact upon multiple chemical disciplines.
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