封面：通过物理信息机器学习潜力和粒子群优化加速不同Bi-Pt纳米团簇的结构探索（chemphyscheme 19/2025）

IF 2.2 3区化学 Q3 CHEMISTRY, PHYSICAL

Chemphyschem Pub Date : 2025-10-07 DOI:10.1002/cphc.70107

Raphaël Vangheluwe, Carine Clavaguéra, Minh-Tue Truong, Dominik Domin, Huy Cong Pham, Mihai-Cosmin Marinica, Nguyen-Thi Van-Oanh

{"title":"封面：通过物理信息机器学习潜力和粒子群优化加速不同Bi-Pt纳米团簇的结构探索（chemphyscheme 19/2025）","authors":"Raphaël Vangheluwe, Carine Clavaguéra, Minh-Tue Truong, Dominik Domin, Huy Cong Pham, Mihai-Cosmin Marinica, Nguyen-Thi Van-Oanh","doi":"10.1002/cphc.70107","DOIUrl":null,"url":null,"abstract":"<p><b>The Front Cover</b> evokes particle swarm optimization applied to Bi–Pt bimetallic nanoparticles. Each bird represents a candidate nanoparticle structure. The lake and its shorelines represent the potential energy surface, generated using the ChiMES physics-informed machine learning potential. The surrounding mountains symbolize transition states, while the dark whirlpool at the lake’s center is the global energy minimum. More information can be found in the Research Article by N. T. Van-Oanh and co-workers (DOI: 10.1002/cphc.202500268).\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":9819,"journal":{"name":"Chemphyschem","volume":"26 19","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://chemistry-europe.onlinelibrary.wiley.com/doi/epdf/10.1002/cphc.70107","citationCount":"0","resultStr":"{\"title\":\"Front Cover: Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics-Informed Machine Learning Potential and Particle Swarm Optimization (ChemPhysChem 19/2025)\",\"authors\":\"Raphaël Vangheluwe, Carine Clavaguéra, Minh-Tue Truong, Dominik Domin, Huy Cong Pham, Mihai-Cosmin Marinica, Nguyen-Thi Van-Oanh\",\"doi\":\"10.1002/cphc.70107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><b>The Front Cover</b> evokes particle swarm optimization applied to Bi–Pt bimetallic nanoparticles. Each bird represents a candidate nanoparticle structure. The lake and its shorelines represent the potential energy surface, generated using the ChiMES physics-informed machine learning potential. The surrounding mountains symbolize transition states, while the dark whirlpool at the lake’s center is the global energy minimum. More information can be found in the Research Article by N. T. Van-Oanh and co-workers (DOI: 10.1002/cphc.202500268).\\n <figure>\\n <div><picture>\\n <source></source></picture><p></p>\\n </div>\\n </figure></p>\",\"PeriodicalId\":9819,\"journal\":{\"name\":\"Chemphyschem\",\"volume\":\"26 19\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://chemistry-europe.onlinelibrary.wiley.com/doi/epdf/10.1002/cphc.70107\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemphyschem\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cphc.70107\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemphyschem","FirstCategoryId":"92","ListUrlMain":"https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cphc.70107","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}

引用次数: 0

摘要

封面唤起粒子群优化应用于双铂双金属纳米粒子。每只鸟代表一个候选的纳米粒子结构。湖泊及其海岸线代表势能面，使用ChiMES物理信息机器学习潜力生成。周围的山脉象征着过渡状态，而湖中心的黑暗漩涡则是全球能量的最小值。更多信息可以在n.t. Van-Oanh及其同事的研究文章中找到（DOI: 10.1002/cphc.202500268）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Front Cover: Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics-Informed Machine Learning Potential and Particle Swarm Optimization (ChemPhysChem 19/2025)

查看原文本刊更多论文

Front Cover: Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics-Informed Machine Learning Potential and Particle Swarm Optimization (ChemPhysChem 19/2025)

The Front Cover evokes particle swarm optimization applied to Bi–Pt bimetallic nanoparticles. Each bird represents a candidate nanoparticle structure. The lake and its shorelines represent the potential energy surface, generated using the ChiMES physics-informed machine learning potential. The surrounding mountains symbolize transition states, while the dark whirlpool at the lake’s center is the global energy minimum. More information can be found in the Research Article by N. T. Van-Oanh and co-workers (DOI: 10.1002/cphc.202500268).

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Chemphyschem 化学-物理：原子、分子和化学物理

CiteScore

4.60

自引率

3.40%

发文量

425

审稿时长

1.1 months

期刊介绍： ChemPhysChem is one of the leading chemistry/physics interdisciplinary journals (ISI Impact Factor 2018: 3.077) for physical chemistry and chemical physics. It is published on behalf of Chemistry Europe, an association of 16 European chemical societies. ChemPhysChem is an international source for important primary and critical secondary information across the whole field of physical chemistry and chemical physics. It integrates this wide and flourishing field ranging from Solid State and Soft-Matter Research, Electro- and Photochemistry, Femtochemistry and Nanotechnology, Complex Systems, Single-Molecule Research, Clusters and Colloids, Catalysis and Surface Science, Biophysics and Physical Biochemistry, Atmospheric and Environmental Chemistry, and many more topics. ChemPhysChem is peer-reviewed.