Method and device for predicting properties of metal material based on machine learning force field and medium
The invention relates to the technical field of metal material property prediction, in particular to a method, equipment and medium for predicting metal material properties based on a machine learning force field, which can realize calculation efficiency close to empirical potential, obtain a simula...
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| creator | LI TONG QIU HAO YANG LI SU HANG SUN XU MI ZHISHAN LIU HEPING CHENG TING |
| description | The invention relates to the technical field of metal material property prediction, in particular to a method, equipment and medium for predicting metal material properties based on a machine learning force field, which can realize calculation efficiency close to empirical potential, obtain a simulation track through first principle molecular dynamics and an empirical force field and extract a configuration. A database capable of representing the microstructure evolution of the metal material is obtained, so that a metal material machine learning force field for accurately representing the microstructure evolution process of the metal material is established; the problems that a molecular dynamics force field model used for microstructure evolution simulation of the metal material in the hydrogen environment is poor in precision and incomplete in force field are solved, the problem that current metal material molecular dynamics simulation is low in precision is solved, meanwhile, the defect that the first pri |
| format | Patent |
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A database capable of representing the microstructure evolution of the metal material is obtained, so that a metal material machine learning force field for accurately representing the microstructure evolution process of the metal material is established; the problems that a molecular dynamics force field model used for microstructure evolution simulation of the metal material in the hydrogen environment is poor in precision and incomplete in force field are solved, the problem that current metal material molecular dynamics simulation is low in precision is solved, meanwhile, the defect that the first pri</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; PHYSICS</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240604&DB=EPODOC&CC=CN&NR=118136186A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240604&DB=EPODOC&CC=CN&NR=118136186A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LI TONG</creatorcontrib><creatorcontrib>QIU HAO</creatorcontrib><creatorcontrib>YANG LI</creatorcontrib><creatorcontrib>SU HANG</creatorcontrib><creatorcontrib>SUN XU</creatorcontrib><creatorcontrib>MI ZHISHAN</creatorcontrib><creatorcontrib>LIU HEPING</creatorcontrib><creatorcontrib>CHENG TING</creatorcontrib><title>Method and device for predicting properties of metal material based on machine learning force field and medium</title><description>The invention relates to the technical field of metal material property prediction, in particular to a method, equipment and medium for predicting metal material properties based on a machine learning force field, which can realize calculation efficiency close to empirical potential, obtain a simulation track through first principle molecular dynamics and an empirical force field and extract a configuration. 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A database capable of representing the microstructure evolution of the metal material is obtained, so that a metal material machine learning force field for accurately representing the microstructure evolution process of the metal material is established; the problems that a molecular dynamics force field model used for microstructure evolution simulation of the metal material in the hydrogen environment is poor in precision and incomplete in force field are solved, the problem that current metal material molecular dynamics simulation is low in precision is solved, meanwhile, the defect that the first pri</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS |
| title | Method and device for predicting properties of metal material based on machine learning force field and medium |
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