{"id":"https://openalex.org/W4409438855","doi":"https://doi.org/10.1021/acs.jctc.5c00090","title":"Learning Pairwise Interaction for Extrapolative and Interpretable Machine Learning Interatomic Potentials with Physics-Informed Neural Network","display_name":"Learning Pairwise Interaction for Extrapolative and Interpretable Machine Learning Interatomic Potentials with Physics-Informed Neural Network","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4409438855","doi":"https://doi.org/10.1021/acs.jctc.5c00090","pmid":"https://pubmed.ncbi.nlm.nih.gov/40223580"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jctc.5c00090","doi":"https://doi.org/10.1021/acs.jctc.5c00090","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jctc.5c00090","pdf_url":null,"source":{"id":"https://openalex.org/S189701308","display_name":"Journal of Chemical Theory and Computation","issn_l":"1549-9618","issn":["1549-9618","1549-9626"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-2","ki-jl-2","medline","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Theory and Computation","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034081562","display_name":"Hoje Chun","orcid":"https://orcid.org/0000-0003-0624-536X","observed_orcids":["https://orcid.org/0000-0003-0624-536X"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hoje Chun","raw_affiliation_strings":["Department of Chemical and Biomolecular Engineering","Yonsei University"],"raw_orcid":"https://orcid.org/0000-0003-0624-536X","affiliations":[{"raw_affiliation_string":"Department of Chemical and Biomolecular Engineering","institution_ids":[]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031124222","display_name":"Minjoon Hong","orcid":"https://orcid.org/0009-0001-5848-4154","observed_orcids":["https://orcid.org/0009-0001-5848-4154"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minjoon Hong","raw_affiliation_strings":["Department of Chemical and Biomolecular Engineering","Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical and Biomolecular Engineering","institution_ids":[]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008646117","display_name":"Seung Hyo Noh","orcid":"https://orcid.org/0000-0002-7491-4038","observed_orcids":["https://orcid.org/0000-0002-7491-4038"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seung Hyo Noh","raw_affiliation_strings":["Hyundai Motor Company","Materials Research & Engineering Center, Advanced Vehicle Platform Division"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hyundai Motor Company","institution_ids":[]},{"raw_affiliation_string":"Materials Research & Engineering Center, Advanced Vehicle Platform Division","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036749276","display_name":"Byungchan Han","orcid":"https://orcid.org/0000-0002-2325-6733","observed_orcids":["https://orcid.org/0000-0002-2325-6733","https://orcid.org/0000-0002-7565-7096"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Byungchan Han","raw_affiliation_strings":["Department of Chemical and Biomolecular Engineering","Yonsei University"],"raw_orcid":"https://orcid.org/0000-0002-2325-6733","affiliations":[{"raw_affiliation_string":"Department of Chemical and Biomolecular Engineering","institution_ids":[]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5036749276"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":{"value":4500,"currency":"USD","value_usd":4500},"apc_paid":null,"fwci":1.0652,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7048366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"21","issue":"8","first_page":"4030","last_page":"4039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10002","display_name":"Advanced Chemical Physics Studies","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12044","display_name":"Advanced Physical and Chemical Molecular Interactions","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1606","display_name":"Physical and Theoretical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning-interatomic-potentials","display_name":"machine learning interatomic potentials","score":0.9750000238418579},{"id":"https://openalex.org/keywords/physics-informed-neural-networks","display_name":"physics-informed neural networks","score":0.9259999990463257},{"id":"https://openalex.org/keywords/bond-order-potential","display_name":"bond-order potential","score":0.9089999794960022},{"id":"https://openalex.org/keywords/extrapolation","display_name":"extrapolation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7749999761581421},{"id":"https://openalex.org/keywords/atomistic-simulation","display_name":"atomistic simulation","score":0.7519999742507935},{"id":"https://openalex.org/keywords/deprotonation","display_name":"deprotonation","score":0.7450000047683716},{"id":"https://openalex.org/keywords/sn2-reaction","display_name":"SN2 reaction","score":0.7770000100135803},{"id":"https://openalex.org/keywords/reactive-systems","display_name":"reactive systems","score":0.5289999842643738},{"id":"https://openalex.org/keywords/data-scarce-conditions","display_name":"data-scarce conditions","score":0.5720000267028809},{"id":"https://openalex.org/keywords/multicomponent-materials","display_name":"multicomponent materials","score":0.6510000228881836}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7603221535682678},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6483902335166931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.519184947013855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5191792249679565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4541652798652649},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3243027329444885}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jctc.5c00090","doi":"https://doi.org/10.1021/acs.jctc.5c00090","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jctc.5c00090","pdf_url":null,"source":{"id":"https://openalex.org/S189701308","display_name":"Journal of Chemical Theory and Computation","issn_l":"1549-9618","issn":["1549-9618","1549-9626"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-2","ki-jl-2","medline","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Theory and Computation","raw_type":"journal-article"},{"id":"pmid:40223580","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40223580","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of chemical theory and computation","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8140600650","display_name":null,"funder_award_id":"2022M3H4A04096482","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1966949133","https://openalex.org/W1970127494","https://openalex.org/W1975997599","https://openalex.org/W1977178778","https://openalex.org/W2025444507","https://openalex.org/W2031430816","https://openalex.org/W2050890227","https://openalex.org/W2080635178","https://openalex.org/W2083222334","https://openalex.org/W2333787883","https://openalex.org/W2541404351","https://openalex.org/W2585152223","https://openalex.org/W2601081289","https://openalex.org/W2620906374","https://openalex.org/W2776192919","https://openalex.org/W2788652239","https://openalex.org/W2886802770","https://openalex.org/W2899283552","https://openalex.org/W2923693308","https://openalex.org/W2993511937","https://openalex.org/W3042508420","https://openalex.org/W3045724025","https://openalex.org/W3090966844","https://openalex.org/W3119329252","https://openalex.org/W4225405705","https://openalex.org/W4306313211","https://openalex.org/W4311015808","https://openalex.org/W4318071628","https://openalex.org/W4319162181","https://openalex.org/W4391173672","https://openalex.org/W4394592985","https://openalex.org/W4405829046"],"related_works":["https://openalex.org/W3045724025","https://openalex.org/W7042732966","https://openalex.org/W7169626959","https://openalex.org/W4321748825","https://openalex.org/W2886802770","https://openalex.org/W2509678043","https://openalex.org/W4392559918","https://openalex.org/W4404718463","https://openalex.org/W4402386263","https://openalex.org/W7211879968"],"abstract_inverted_index":{"Achieving":[0],"both":[1],"robust":[2],"extrapolation":[3],"and":[4,74,93,131,145],"physical":[5,63],"interpretability":[6],"in":[7,21,128],"machine":[8],"learning":[9],"interatomic":[10,116],"potentials":[11],"(ML-IPs)":[12],"for":[13,91],"atomistic":[14],"simulation":[15],"remains":[16],"a":[17,38,119],"significant":[18],"challenge,":[19],"particularly":[20],"data-scarce":[22],"areas":[23],"such":[24],"as":[25,118],"chemical":[26],"reactions":[27],"or":[28],"complex,":[29],"multicomponent":[30],"materials":[31],"at":[32,68],"extreme":[33],"conditions.":[34],"Here,":[35],"we":[36],"present":[37],"pairwise-decomposed":[39],"physics-informed":[40],"neural":[41],"network":[42],"(P2Net)":[43],"that":[44],"parametrizes":[45],"an":[46],"analytical":[47],"bond-order":[48],"potential":[49],"(BOP)":[50],"layer":[51],"to":[52,111,143],"decouple":[53],"the":[54,88,113,139],"energy":[55,84,108],"contributions":[56],"of":[57,115,141],"atomic":[58,106],"pairs.":[59],"By":[60],"leveraging":[61],"fundamental":[62],"principles,":[64],"P2Net":[65],"demonstrates":[66],"excellence":[67],"extrapolating":[69],"beyond":[70],"its":[71],"training":[72],"regime":[73],"accurately":[75],"capturing":[76],"molecular":[77],"geometries":[78],"far":[79],"from":[80],"equilibrium.":[81],"The":[82,105],"pairwise":[83],"decomposition":[85],"further":[86],"empowers":[87],"bond":[89],"analyses":[90],"deprotonation":[92],"S":[94],"N":[95],"2":[96],"reactions,":[97],"which":[98],"is":[99],"not":[100],"easy":[101],"with":[102],"most":[103],"ML-IPs.":[104],"pair":[107],"offers":[109],"how":[110],"elucidate":[112],"evolution":[114],"interactions":[117],"reaction":[120],"proceeds.":[121],"Our":[122],"methodology":[123],"highlights":[124],"enhanced":[125],"data":[126],"efficiency":[127],"building":[129],"ML-IPs":[130,142],"facilitates":[132],"more":[133],"informative":[134],"postsimulation":[135],"analysis,":[136],"thereby":[137],"broadening":[138],"applicability":[140],"complex":[144],"reactive":[146],"systems.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-04-15T00:00:00"}
