{"id":"https://openalex.org/W7138990047","doi":"https://doi.org/10.1021/acs.jcim.6c00365","title":"Hybrid Graph\u2013Machine Learning Framework for Accurate and Interpretable Band Gap Prediction","display_name":"Hybrid Graph\u2013Machine Learning Framework for Accurate and Interpretable Band Gap Prediction","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7138990047","doi":"https://doi.org/10.1021/acs.jcim.6c00365","pmid":"https://pubmed.ncbi.nlm.nih.gov/41855083"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.6c00365","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.6c00365","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.6c00365?ref=article_openPDF","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":true,"oa_status":"hybrid","oa_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.6c00365?ref=article_openPDF","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ayhan Ayd\u0131n","orcid":"https://orcid.org/0000-0001-7938-0509"},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Ayhan Ayd\u0131n","raw_affiliation_strings":["Ankara University","Department of Computer Engineering, Faculty of Engineering"],"raw_orcid":"https://orcid.org/0000-0001-7938-0509","affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129906824","display_name":"\u00dcmit Kaya Ery\u0131lmaz","orcid":null},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"\u00dcmit Kaya Ery\u0131lmaz","raw_affiliation_strings":["Ankara University","Department of Mathematics, Faculty of Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Department of Mathematics, Faculty of Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130034814","display_name":"Onur Bahattin Alkan","orcid":null},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Onur Bahattin Alkan","raw_affiliation_strings":["Ankara University","Department of Computer Engineering, Faculty of Engineering"],"raw_orcid":"https://orcid.org/0009-0001-4210-4030","affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129959351","display_name":"P\u0131nar Kocag\u00f6z","orcid":null},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","TR"],"is_corresponding":false,"raw_author_name":"P\u0131nar Kocag\u00f6z","raw_affiliation_strings":["Ankara University","Department of Artificial Intelligence and Data Engineering, Faculty of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Department of Artificial Intelligence and Data Engineering, Faculty of Engineering","institution_ids":["https://openalex.org/I4210164862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011357504","display_name":"Fatih Ekinci","orcid":"https://orcid.org/0000-0002-1011-1105"},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Fatih Ekinci","raw_affiliation_strings":["Ankara University","Institute of Artificial Intelligence"],"raw_orcid":"https://orcid.org/0000-0002-1011-1105","affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Institute of Artificial Intelligence","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129973456","display_name":"Mehmet Serdar G\u00fczel","orcid":null},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mehmet Serdar G\u00fczel","raw_affiliation_strings":["Ankara University","Department of Computer Engineering, Faculty of Engineering"],"raw_orcid":"https://orcid.org/0000-0002-3408-0083","affiliations":[{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149218525"],"apc_list":null,"apc_paid":null,"fwci":2.5795,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87644655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"66","issue":"7","first_page":"3787","last_page":"3802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9965000152587891,"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":0.9965000152587891,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12557","display_name":"Inorganic Chemistry and Materials","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1604","display_name":"Inorganic 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/interpretability","display_name":"Interpretability","score":0.7875999808311462},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6139000058174133},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5637000203132629},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5374000072479248},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5273000001907349},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4763000011444092},{"id":"https://openalex.org/keywords/band-gap","display_name":"Band gap","score":0.37470000982284546}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7875999808311462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.734000027179718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6517999768257141},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6139000058174133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5957000255584717},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5637000203132629},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5273000001907349},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C181966813","wikidata":"https://www.wikidata.org/wiki/Q806352","display_name":"Band gap","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C84947059","wikidata":"https://www.wikidata.org/wiki/Q5191417","display_name":"Crystal structure prediction","level":3,"score":0.37139999866485596},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3059999942779541},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.2590999901294708}],"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":"D000098422","descriptor_name":"Graph Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098422","descriptor_name":"Graph Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1021/acs.jcim.6c00365","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.6c00365","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.6c00365?ref=article_openPDF","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:41855083","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41855083","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},{"id":"pmh:oai:pubmedcentral.nih.gov:13080991","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13080991/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Chem Inf Model","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1021/acs.jcim.6c00365","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.6c00365","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.6c00365?ref=article_openPDF","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138990047.pdf","grobid_xml":"https://content.openalex.org/works/W7138990047.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1992985800","https://openalex.org/W1995875735","https://openalex.org/W2015197254","https://openalex.org/W2131253515","https://openalex.org/W2133254377","https://openalex.org/W2230728100","https://openalex.org/W2294798173","https://openalex.org/W2295598076","https://openalex.org/W2295984635","https://openalex.org/W2464725281","https://openalex.org/W2523228111","https://openalex.org/W2766856748","https://openalex.org/W2899370105","https://openalex.org/W2911964244","https://openalex.org/W2949095042","https://openalex.org/W2949676527","https://openalex.org/W3006346191","https://openalex.org/W3046139778","https://openalex.org/W3083285969","https://openalex.org/W3155362250","https://openalex.org/W3182706339","https://openalex.org/W3185631424","https://openalex.org/W3212512279","https://openalex.org/W4283071924","https://openalex.org/W4299959846","https://openalex.org/W4317830766","https://openalex.org/W4379232690","https://openalex.org/W4391842269","https://openalex.org/W4401592848","https://openalex.org/W4406976201","https://openalex.org/W4407247076","https://openalex.org/W4410615532","https://openalex.org/W4410779879","https://openalex.org/W4413243175","https://openalex.org/W4413383495","https://openalex.org/W4414714594"],"related_works":[],"abstract_inverted_index":{"High":[0],"Resolution":[1],"Image":[2],"Download":[3],"MS":[4],"PowerPoint":[5],"Slide":[6],"Accurate":[7],"prediction":[8],"of":[9,22,180],"the":[10,18,113,117,159,178,189,213],"electronic":[11],"band":[12,71,206],"gap":[13,72,207],"is":[14,155],"essential":[15],"for":[16,227,236],"accelerating":[17],"discovery":[19],"and":[20,24,39,68,82,96,104,128,140,149,172,197,219,243],"design":[21,246],"semiconducting":[23],"energy":[25],"materials.":[26],"Conventional":[27],"density":[28],"functional":[29],"theory":[30],"(DFT)":[31],"methods,":[32],"while":[33,167],"physically":[34,86,192],"rigorous,":[35],"remain":[36],"computationally":[37,69],"expensive":[38],"limited":[40],"in":[41,205],"scalability.":[42],"In":[43],"this":[44],"study,":[45],"we":[46],"propose":[47],"a":[48,223,234],"hybrid":[49,118],"artificial":[50,250],"intelligence":[51],"framework":[52,232],"that":[53,188,212],"combines":[54],"graph-based":[55],"deep":[56,216],"learning":[57,62,240],"embeddings":[58,77,218],"with":[59,85,195],"classical":[60,134,220],"machine":[61],"algorithms":[63,221],"to":[64,158,177],"achieve":[65],"high-accuracy,":[66],"interpretable,":[67],"efficient":[70],"prediction.":[73,208],"The":[74,152,230],"model":[75,119,162,190],"integrates":[76],"obtained":[78],"from":[79,112],"CGCNN,":[80],"MEGNet,":[81],"SchNet":[83],"architectures":[84],"meaningful":[87],"crystal":[88,92,110],"descriptors\u2500including":[89],"maximum":[90],"electronegativity,":[91],"system,":[93],"space":[94],"group,":[95],"spin\u2013orbit":[97],"coupling\u2500and":[98],"trains":[99],"them":[100],"using":[101],"optimized":[102],"gradient-boosting":[103],"neural":[105,143],"architectures.":[106],"Trained":[107],"on":[108],"136,000":[109],"structures":[111],"Materials":[114],"Project":[115],"database,":[116],"achieves":[120],"R":[121],"2":[122],"=":[123,126,130],"0.921,":[124],"MAE":[125],"0.191,":[127],"MSE":[129],"0.155,":[131],"outperforming":[132],"both":[133],"models":[135],"(Ward":[136],"et":[137,164],"al.,":[138,165],"2016)":[139],"standalone":[141],"graph":[142],"networks":[144],"such":[145],"as":[146,202],"CGCNN":[147],"(Xie":[148],"Grossman,":[150],"2018).":[151],"achieved":[153],"accuracy":[154],"statistically":[156],"comparable":[157],"state-of-the-art":[160],"ALIGNN":[161],"(Choudhary":[163],"2021),":[166],"requiring":[168],"lower":[169],"computational":[170],"resources":[171],"offering":[173],"enhanced":[174],"generalization":[175],"due":[176],"integration":[179],"multisource":[181],"structural":[182,217],"information.":[183],"SHAP-based":[184],"interpretability":[185],"analysis":[186],"highlights":[187],"captures":[191],"consistent":[193],"relationships,":[194],"metallicity":[196],"magnetic":[198],"site":[199],"features":[200],"emerging":[201],"dominant":[203],"factors":[204],"These":[209],"findings":[210],"demonstrate":[211],"synergy":[214],"between":[215],"provides":[222],"powerful,":[224],"scalable":[225],"approach":[226],"materials":[228,245],"informatics.":[229],"proposed":[231],"establishes":[233],"foundation":[235],"multiproperty":[237],"prediction,":[238],"transfer":[239],"across":[241],"databases,":[242],"inverse":[244],"driven":[247],"by":[248],"interpretable":[249],"intelligence.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2026-03-20T00:00:00"}