{"id":"https://openalex.org/W4411383431","doi":"https://doi.org/10.1021/acs.jcim.4c02255","title":"General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction","display_name":"General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4411383431","doi":"https://doi.org/10.1021/acs.jcim.4c02255","pmid":"https://pubmed.ncbi.nlm.nih.gov/40525220"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.4c02255","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c02255","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Information and Modeling","raw_type":"journal-article"},"type":"article","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/A5016129116","display_name":"Muhammad Nouman","orcid":"https://orcid.org/0000-0003-4957-3240"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miguel Nouman","raw_affiliation_strings":["Department of Chemical Engineering","Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering","institution_ids":[]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036375800","display_name":"Richard B. Canty","orcid":"https://orcid.org/0000-0002-2347-2743"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard B. Canty","raw_affiliation_strings":["Department of Chemical Engineering","Massachusetts Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0002-2347-2743","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering","institution_ids":[]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079049661","display_name":"Brent A. Koscher","orcid":"https://orcid.org/0000-0001-8233-0852"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brent A. Koscher","raw_affiliation_strings":["Department of Chemical Engineering","Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering","institution_ids":[]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068637400","display_name":"Matthew A. McDonald","orcid":"https://orcid.org/0000-0002-9444-3253"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew A. McDonald","raw_affiliation_strings":["Department of Chemical Engineering","Massachusetts Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0002-9444-3253","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering","institution_ids":[]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071010920","display_name":"Klavs F. Jensen","orcid":"https://orcid.org/0000-0001-7192-580X"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Klavs F. Jensen","raw_affiliation_strings":["Department of Chemical Engineering","Massachusetts Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0001-7192-580X","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering","institution_ids":[]},{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071010920"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":4.1432,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94268194,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"65","issue":"13","first_page":"6499","last_page":"6512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12327","display_name":"Various Chemistry Research Topics","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/atom","display_name":"Atom (system on chip)","score":0.5350519418716431},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4527651071548462},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4204866588115692},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.4105411767959595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40199384093284607},{"id":"https://openalex.org/keywords/computational-chemistry","display_name":"Computational chemistry","score":0.36456191539764404},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.0869455337524414}],"concepts":[{"id":"https://openalex.org/C58312451","wikidata":"https://www.wikidata.org/wiki/Q4817200","display_name":"Atom (system on chip)","level":2,"score":0.5350519418716431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4527651071548462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4204866588115692},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.4105411767959595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40199384093284607},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.36456191539764404},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0869455337524414}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077318","descriptor_name":"Density Functional Theory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077318","descriptor_name":"Density Functional Theory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.4c02255","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c02255","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Information and Modeling","raw_type":"journal-article"},{"id":"pmid:40525220","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40525220","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,"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 information and modeling","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4082023028","display_name":null,"funder_award_id":"HR00111920025","funder_id":"https://openalex.org/F4320337531","funder_display_name":"Defense Sciences Office, DARPA"}],"funders":[{"id":"https://openalex.org/F4320309369","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44"},{"id":"https://openalex.org/F4320337531","display_name":"Defense Sciences Office, DARPA","ror":"https://ror.org/0447fe631"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W60380939","https://openalex.org/W1963924875","https://openalex.org/W1966074629","https://openalex.org/W1968749056","https://openalex.org/W1975147762","https://openalex.org/W1988037271","https://openalex.org/W1993383767","https://openalex.org/W2010315761","https://openalex.org/W2021748110","https://openalex.org/W2044834685","https://openalex.org/W2071955309","https://openalex.org/W2092493635","https://openalex.org/W2096747776","https://openalex.org/W2097463517","https://openalex.org/W2131834573","https://openalex.org/W2143981217","https://openalex.org/W2156364948","https://openalex.org/W2471170444","https://openalex.org/W2472085920","https://openalex.org/W2613900957","https://openalex.org/W2775684663","https://openalex.org/W2777416523","https://openalex.org/W2883672905","https://openalex.org/W2901942917","https://openalex.org/W2911964244","https://openalex.org/W2938625151","https://openalex.org/W2943959866","https://openalex.org/W2965447776","https://openalex.org/W2966357564","https://openalex.org/W3000344858","https://openalex.org/W3098470619","https://openalex.org/W3106525532","https://openalex.org/W3123901912","https://openalex.org/W3146384714","https://openalex.org/W3197684580","https://openalex.org/W3208007731","https://openalex.org/W3208238119","https://openalex.org/W4200150051","https://openalex.org/W4210374662","https://openalex.org/W4213070269","https://openalex.org/W4220694746","https://openalex.org/W4226145240","https://openalex.org/W4240187346","https://openalex.org/W4283836015","https://openalex.org/W4309667870","https://openalex.org/W4310602585","https://openalex.org/W4322746608","https://openalex.org/W4360608424","https://openalex.org/W4386399680","https://openalex.org/W4391160649","https://openalex.org/W4392242805","https://openalex.org/W4392861329","https://openalex.org/W4400081387","https://openalex.org/W4401356519"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"We":[0,26,68],"demonstrate":[1],"the":[2,16,37,149,159,166,181],"usefulness":[3],"of":[4,18,39,106,170],"general":[5,22,75,132],"atom-":[6],"and":[7,35,42,63,74,99,111,118,134,145,186,201],"bond-level":[8],"density":[9],"functional":[10],"theory":[11],"(DFT)":[12],"descriptors":[13],"to":[14,81,108,139],"enhance":[15],"performance":[17,38],"neural":[19,40,124,152],"networks":[20,41,125],"for":[21,123,184],"reaction":[23,53,60],"condition":[24,28,61],"prediction.":[25],"treat":[27],"prediction":[29],"as":[30,45],"a":[31,51],"multiclass":[32],"classification":[33],"task":[34],"report":[36,104],"random":[43],"forests":[44],"evaluated":[46],"by":[47,71],"5-fold":[48],"cross-validation":[49],"on":[50,127,155],"69,935":[52],"data":[54,178],"set":[55],"with":[56,79,142,174,190],"296":[57],"distinct":[58],"single-component":[59],"classes":[62],"varying":[64],"input":[65,146],"embedding":[66,172,187],"compositions.":[67],"show":[69],"that":[70,197],"combining":[72],"structural":[73,89,135,140,162],"DFT":[76,133],"descriptors,":[77,136,189],"models":[78,141],"up":[80,107],"71%":[82],"fewer":[83],"trainable":[84],"parameter":[85],"than":[86,180],"their":[87],"purely":[88,161],"counterparts":[90],"can":[91],"provide":[92],"comparable":[93],"or":[94],"superior":[95],"weighted":[96,114],"precision,":[97,115],"top-1":[98,116],"top-3":[100],"accuracies.":[101],"Moreover,":[102],"we":[103],"improvements":[105],"5,":[109],"10,":[110],"11%":[112],"in":[113],"accuracy":[117],"F":[119],"1":[120],"score,":[121],"respectively,":[122],"trained":[126,154],"hybrid":[128,156,188],"representations":[129],"which":[130],"combine":[131],"when":[137],"compared":[138],"equivalent":[143],"architectures":[144],"sizes.":[147],"Remarkably,":[148],"best":[150,160],"performing":[151],"network":[153],"embeddings":[157],"outperforms":[158],"model":[163],"investigated":[164],"despite":[165],"latter":[167],"benefiting":[168],"from":[169],"an":[171],"strategy":[173],"267":[175],"times":[176],"more":[177],"points":[179],"one":[182],"used":[183],"generating":[185],"both":[191],"strategies":[192],"being":[193],"unsupervised":[194],"learning":[195],"algorithms":[196],"share":[198],"considerable":[199],"conceptual":[200],"architectural":[202],"similarities.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2025-10-10T00:00:00"}