{"id":"https://openalex.org/W4405457459","doi":"https://doi.org/10.1021/acs.jcim.4c00989","title":"Machine-Learning-Enabled Thermochemistry Estimator","display_name":"Machine-Learning-Enabled Thermochemistry Estimator","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405457459","doi":"https://doi.org/10.1021/acs.jcim.4c00989","pmid":"https://pubmed.ncbi.nlm.nih.gov/39680848"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.4c00989","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c00989","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/A5034813990","display_name":"Tianjun Xie","orcid":"https://orcid.org/0000-0003-1985-3073"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianjun Xie","raw_affiliation_strings":["Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States"],"affiliations":[{"raw_affiliation_string":"Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044670426","display_name":"Gerhard R. Wittreich","orcid":"https://orcid.org/0000-0002-3968-7642"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerhard R. Wittreich","raw_affiliation_strings":["Department of Chemical and Biomolecular Engineering, University of Delaware, 221 Academy Street, Newark, Delaware 19716, United States"],"affiliations":[{"raw_affiliation_string":"Department of Chemical and Biomolecular Engineering, University of Delaware, 221 Academy Street, Newark, Delaware 19716, United States","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054853131","display_name":"Matthew T. Curnan","orcid":"https://orcid.org/0000-0001-7999-9272"},"institutions":[{"id":"https://openalex.org/I4210127102","display_name":"Korea Institute of Energy Research","ror":"https://ror.org/0298pes53","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I4210127102","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Matthew T. Curnan","raw_affiliation_strings":["Department of Energy Engineering, Korea Institute of Energy Technology (KENTECH), Naju 58330, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Energy Engineering, Korea Institute of Energy Technology (KENTECH), Naju 58330, Republic of Korea","institution_ids":["https://openalex.org/I4210127102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078798665","display_name":"Geun Ho Gu","orcid":"https://orcid.org/0000-0001-8795-7558"},"institutions":[{"id":"https://openalex.org/I4210127102","display_name":"Korea Institute of Energy Research","ror":"https://ror.org/0298pes53","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I4210127102","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Geun Ho Gu","raw_affiliation_strings":["Department of Energy Engineering, Korea Institute of Energy Technology (KENTECH), Naju 58330, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Energy Engineering, Korea Institute of Energy Technology (KENTECH), Naju 58330, Republic of Korea","institution_ids":["https://openalex.org/I4210127102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023254655","display_name":"Kevin Seals","orcid":null},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kayla N. Seals","raw_affiliation_strings":["Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States"],"affiliations":[{"raw_affiliation_string":"Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115498273","display_name":"Justin S. Tolbert","orcid":null},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin S. Tolbert","raw_affiliation_strings":["Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States"],"affiliations":[{"raw_affiliation_string":"Department of Chemical, Biological and Bioengineering, North Carolina A&T State University, Greensboro, North Carolina 27411, United States","institution_ids":["https://openalex.org/I35777872"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034813990"],"corresponding_institution_ids":["https://openalex.org/I35777872"],"apc_list":null,"apc_paid":null,"fwci":0.3508,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57406372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"65","issue":"1","first_page":"214","last_page":"222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":1.0,"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":1.0,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9945999979972839,"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/T11784","display_name":"CO2 Reduction Techniques and Catalysts","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/thermochemistry","display_name":"Thermochemistry","score":0.7550562620162964},{"id":"https://openalex.org/keywords/density-functional-theory","display_name":"Density functional theory","score":0.6525534987449646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5821748971939087},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4711764454841614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44714343547821045},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4217016100883484},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4129820764064789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3631160855293274},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.24132227897644043},{"id":"https://openalex.org/keywords/computational-chemistry","display_name":"Computational chemistry","score":0.2127504050731659},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2061796486377716},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.18860694766044617},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17839205265045166},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.13516104221343994},{"id":"https://openalex.org/keywords/physical-chemistry","display_name":"Physical chemistry","score":0.09695303440093994}],"concepts":[{"id":"https://openalex.org/C29563950","wikidata":"https://www.wikidata.org/wiki/Q183410","display_name":"Thermochemistry","level":2,"score":0.7550562620162964},{"id":"https://openalex.org/C152365726","wikidata":"https://www.wikidata.org/wiki/Q1048589","display_name":"Density functional theory","level":2,"score":0.6525534987449646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5821748971939087},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4711764454841614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44714343547821045},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4217016100883484},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4129820764064789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3631160855293274},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.24132227897644043},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.2127504050731659},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2061796486377716},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.18860694766044617},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17839205265045166},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.13516104221343994},{"id":"https://openalex.org/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.09695303440093994},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"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":"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":false},{"descriptor_ui":"D000077318","descriptor_name":"Density Functional Theory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077318","descriptor_name":"Density Functional Theory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077318","descriptor_name":"Density Functional Theory","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008956","descriptor_name":"Models, Chemical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008956","descriptor_name":"Models, Chemical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.4c00989","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c00989","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:39680848","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39680848","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":[{"display_name":"Life in Land","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G2983405144","display_name":null,"funder_award_id":"RS-2024-00429941","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G3400742099","display_name":null,"funder_award_id":"20224000000320","funder_id":"https://openalex.org/F4320335199","funder_display_name":"Korea Institute of Energy Technology Evaluation and Planning"},{"id":"https://openalex.org/G463533322","display_name":null,"funder_award_id":"1736173","funder_id":"https://openalex.org/F4320338055","funder_display_name":"Division of Equity for Excellence in STEM"}],"funders":[{"id":"https://openalex.org/F4320310587","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335199","display_name":"Korea Institute of Energy Technology Evaluation and Planning","ror":"https://ror.org/02zq38y32"},{"id":"https://openalex.org/F4320338055","display_name":"Division of Equity for Excellence in STEM","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1787802707","https://openalex.org/W1971705458","https://openalex.org/W1973634181","https://openalex.org/W1975147762","https://openalex.org/W1979275139","https://openalex.org/W1979544533","https://openalex.org/W1981368803","https://openalex.org/W1981952456","https://openalex.org/W1991629012","https://openalex.org/W2001916293","https://openalex.org/W2007395042","https://openalex.org/W2007970949","https://openalex.org/W2016366655","https://openalex.org/W2029301032","https://openalex.org/W2029413789","https://openalex.org/W2031558918","https://openalex.org/W2033428036","https://openalex.org/W2033638126","https://openalex.org/W2036113194","https://openalex.org/W2040263394","https://openalex.org/W2041773932","https://openalex.org/W2051456244","https://openalex.org/W2059970897","https://openalex.org/W2061939373","https://openalex.org/W2069970015","https://openalex.org/W2083222334","https://openalex.org/W2090564140","https://openalex.org/W2090918273","https://openalex.org/W2096747776","https://openalex.org/W2102807619","https://openalex.org/W2122534729","https://openalex.org/W2123969193","https://openalex.org/W2133406747","https://openalex.org/W2151324716","https://openalex.org/W2277091242","https://openalex.org/W2316918811","https://openalex.org/W2341535801","https://openalex.org/W2588859413","https://openalex.org/W2593855134","https://openalex.org/W2734520197","https://openalex.org/W2754790651","https://openalex.org/W2793372905","https://openalex.org/W2804446681","https://openalex.org/W2890961624","https://openalex.org/W2949095042","https://openalex.org/W2967701456","https://openalex.org/W2982215879","https://openalex.org/W2999792520","https://openalex.org/W3022711947","https://openalex.org/W3028161385","https://openalex.org/W3035965352","https://openalex.org/W3093999435","https://openalex.org/W3099878876","https://openalex.org/W3100541053","https://openalex.org/W3113496643","https://openalex.org/W3116783766","https://openalex.org/W3164099261","https://openalex.org/W3185391990","https://openalex.org/W4205961996","https://openalex.org/W4225000192","https://openalex.org/W4232072350","https://openalex.org/W4252878700","https://openalex.org/W4282016929","https://openalex.org/W4285087570","https://openalex.org/W4306179830","https://openalex.org/W4309419448","https://openalex.org/W4321085451","https://openalex.org/W4376277765","https://openalex.org/W4385671288"],"related_works":["https://openalex.org/W1572943104","https://openalex.org/W4244514184","https://openalex.org/W3092398131","https://openalex.org/W4400788730","https://openalex.org/W409089612","https://openalex.org/W4245507131","https://openalex.org/W2067924393","https://openalex.org/W1968667497","https://openalex.org/W2610402949","https://openalex.org/W4245238065"],"abstract_inverted_index":{"Modeling":[0],"adsorbates":[1],"on":[2,64,148,219,240,310],"single-crystal":[3],"metals":[4],"is":[5,79,162,202],"critical":[6],"in":[7],"rational":[8],"catalyst":[9],"design":[10],"and":[11,49,75,97,182,196,214,227,232,243,260,278],"other":[12],"research":[13,304],"that":[14,89,209],"requires":[15],"detailed":[16],"thermochemistry.":[17],"First-principles":[18],"simulations":[19],"via":[20],"density":[21],"functional":[22],"theory":[23,222],"(DFT)":[24],"are":[25,39],"among":[26],"the":[27,102,115,153,165,194,203,212,220,224,252,267,288,293,305],"prevalent":[28],"tools":[29],"to":[30,71,100,156,172,191,206,250,287,303],"acquire":[31],"such":[32,186,256],"information":[33,112],"about":[34],"surface":[35,238],"species.":[36],"While":[37],"they":[38],"highly":[40],"dependable,":[41],"DFT":[42,106,116],"calculations":[43],"often":[44],"require":[45],"intensive":[46],"computational":[47],"resources":[48],"runtime.":[50],"These":[51],"limiting":[52],"factors":[53],"become":[54],"particularly":[55],"pronounced":[56],"when":[57,285],"investigating":[58],"large":[59],"sets":[60,143],"of":[61,104,144,254,307],"complex":[62,308],"molecules":[63,125],"heavy":[65],"noble":[66],"metals.":[67],"Consequently,":[68],"our":[69,123,139,207,234,296],"ability":[70],"explore":[72],"these":[73],"species":[74,239,309],"their":[76],"corresponding":[77],"energetics":[78,253],"limited.":[80],"In":[81],"this":[82],"work,":[83],"we":[84,109,121,137,178],"establish":[85],"a":[86,130,283],"novel":[87,294],"framework":[88],"utilizes":[90],"techniques":[91],"including":[92],"molecular":[93],"encoding,":[94],"descriptor":[95],"synthesis,":[96],"machine":[98,183],"learning":[99,184],"overcome":[101],"limitation":[103],"costly":[105],"simulations.":[107],"Simultaneously,":[108],"estimate":[110],"thermochemical":[111],"efficiently":[113],"at":[114,263,282],"accuracy":[117],"level.":[118],"More":[119],"specifically,":[120],"translated":[122],"training":[124,140,277],"into":[126],"text-based":[127],"identifiers":[128],"through":[129],"simplified":[131],"molecular-input":[132],"line-entry":[133],"system.":[134],"Following":[135],"that,":[136],"parametrize":[138],"matrices":[141],"with":[142,164,236],"short-range":[145],"descriptors":[146,167],"based":[147,218],"group":[149,221,290],"methods,":[150],"applying":[151],"first":[152,204,213],"nearest":[154,170,216],"neighbors":[155,171,217],"account":[157,173],"for":[158,174],"linear":[159,180,195],"contributions.":[160],"This":[161,201],"coupled":[163],"long-range":[166],"characterizing":[168],"second":[169,215],"nonlinear":[175,197],"corrections.":[176],"Finally,":[177],"use":[179],"regression":[181],"techniques,":[185],"as":[187,257],"Gaussian":[188],"process":[189],"regressions":[190],"regress":[192],"over":[193],"matrix":[198],"systems,":[199],"respectively.":[200],"work":[205],"knowledge":[208],"encompasses":[210],"both":[211],"throughout":[223],"featurization,":[225],"training,":[226],"deployment":[228],"stages.":[229],"We":[230],"trained":[231],"validated":[233],"models":[235],"459":[237],"Pt(111),":[241],"Ru(0001),":[242],"Ir(111)":[244],"surfaces.":[245],"Results":[246],"exhibit":[247],"robust":[248],"performance":[249],"reproduce":[251],"interest,":[255],"enthalpies,":[258],"entropies,":[259],"heat":[261],"capacities,":[262],"various":[264],"temperatures.":[265],"Notably,":[266],"mean":[268],"absolute":[269],"errors":[270],"can":[271],"be":[272],"reduced":[273],"by":[274],"48%":[275],"during":[276,280],"19%":[279],"prediction":[281],"minimum,":[284],"compared":[286],"classical":[289],"method.":[291],"Leveraging":[292],"framework,":[295],"machine-learning-enabled":[297],"thermochemistry":[298,306],"estimator":[299],"significantly":[300],"empowers":[301],"us":[302],"metal":[311],"catalysts.":[312]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
