{"title":"利用虚拟节点提升图神经网络，预测声子特性。","authors":"","doi":"10.1038/s43588-024-00665-w","DOIUrl":null,"url":null,"abstract":"A graph neural network using virtual nodes is proposed to predict the properties of complex materials with variable dimensions or dimensions that depend on the input. The method is used to accurately and quickly predict phonon dispersion relations in complex solids and alloys.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":null,"pages":null},"PeriodicalIF":12.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Boosting graph neural networks with virtual nodes to predict phonon properties\",\"authors\":\"\",\"doi\":\"10.1038/s43588-024-00665-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A graph neural network using virtual nodes is proposed to predict the properties of complex materials with variable dimensions or dimensions that depend on the input. The method is used to accurately and quickly predict phonon dispersion relations in complex solids and alloys.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-024-00665-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-024-00665-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Boosting graph neural networks with virtual nodes to predict phonon properties
A graph neural network using virtual nodes is proposed to predict the properties of complex materials with variable dimensions or dimensions that depend on the input. The method is used to accurately and quickly predict phonon dispersion relations in complex solids and alloys.
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