{"id":"https://openalex.org/W7223035964","doi":"https://doi.org/10.3390/ma19204411","title":"Predicting Thermal Conductivity of Foamed Concrete via Physics-Informed Neural Networks Coupled with the Maxwell\u2013Eucken Model","display_name":"Predicting Thermal Conductivity of Foamed Concrete via Physics-Informed Neural Networks Coupled with the Maxwell\u2013Eucken Model","publication_year":2026,"publication_date":"2026-10-20","ids":{"openalex":"https://openalex.org/W7223035964","doi":"https://doi.org/10.3390/ma19204411","pmid":"https://pubmed.ncbi.nlm.nih.gov/42941152","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13707292"},"language":"en","primary_location":{"id":"doi:10.3390/ma19204411","doi":"https://doi.org/10.3390/ma19204411","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ma19204411","pdf_url":null,"source":{"id":"https://openalex.org/S18714766","display_name":"Materials","issn_l":"1996-1944","issn":["1996-1944"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Materials","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/ma19204411","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060549240","display_name":"Pengfei Pan","orcid":"https://orcid.org/0000-0002-4476-8367","observed_orcids":["https://orcid.org/0000-0002-4476-8367"]},"institutions":[{"id":"https://openalex.org/I4405281681","display_name":"Xinhua College of Ningxia University","ror":"https://ror.org/04qj1ts81","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278","https://openalex.org/I4405281681"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Pan","raw_affiliation_strings":["Ningxia Center for Research on Earthquake Protection and Disaster Mitigation in Civil Engineering, Yinchuan 750021, China","Xinhua College of Ningxia University, Yinchuan 750021, China"],"raw_orcid":"https://orcid.org/0000-0002-4476-8367","affiliations":[{"raw_affiliation_string":"Ningxia Center for Research on Earthquake Protection and Disaster Mitigation in Civil Engineering, Yinchuan 750021, China","institution_ids":[]},{"raw_affiliation_string":"Xinhua College of Ningxia University, Yinchuan 750021, China","institution_ids":["https://openalex.org/I4405281681"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388200","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-6730-4805","observed_orcids":["https://orcid.org/0000-0002-6730-4805"]},"institutions":[{"id":"https://openalex.org/I4391767679","display_name":"State Key Laboratory Fluid Power and Mechatronic Systems","ror":"https://ror.org/01h0g5x34","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391767679","https://openalex.org/I76130692"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yakun Zhang","raw_affiliation_strings":["State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China","institution_ids":["https://openalex.org/I4391767679","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448606","display_name":"Rui Li","orcid":"https://orcid.org/0000-0003-1512-0403","observed_orcids":["https://orcid.org/0000-0003-1512-0403"]},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Li","raw_affiliation_strings":["School of Mechanical Engineering, Ningxia University, Yinchuan 750021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Ningxia University, Yinchuan 750021, China","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5159119214","display_name":"Zheng Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405281681","display_name":"Xinhua College of Ningxia University","ror":"https://ror.org/04qj1ts81","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278","https://openalex.org/I4405281681"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Xinhua College of Ningxia University, Yinchuan 750021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinhua College of Ningxia University, Yinchuan 750021, China","institution_ids":["https://openalex.org/I4405281681"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138834207","display_name":"Xiaolong Ma","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405281681","display_name":"Xinhua College of Ningxia University","ror":"https://ror.org/04qj1ts81","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278","https://openalex.org/I4405281681"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaolong Ma","raw_affiliation_strings":["Xinhua College of Ningxia University, Yinchuan 750021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinhua College of Ningxia University, Yinchuan 750021, China","institution_ids":["https://openalex.org/I4405281681"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100448606","https://openalex.org/A5138834207"],"corresponding_institution_ids":["https://openalex.org/I21642278","https://openalex.org/I4405281681"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62271194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"20","first_page":"4411","last_page":"4411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.7523999810218811,"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":0.7523999810218811,"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/T12105","display_name":"Hygrothermal properties of building materials","score":0.0406000018119812,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10033","display_name":"Concrete and Cement Materials Research","score":0.02410000003874302,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/foam-concrete","display_name":"foam concrete","score":0.9710000157356262},{"id":"https://openalex.org/keywords/thermal-conductivity-prediction","display_name":"thermal conductivity prediction","score":0.8980000019073486},{"id":"https://openalex.org/keywords/physics-informed-neural-networks","display_name":"physics-informed neural networks","score":0.9760000109672546},{"id":"https://openalex.org/keywords/maxwell-eucken-model","display_name":"Maxwell-Eucken model","score":0.9779999852180481},{"id":"https://openalex.org/keywords/effective-medium-theory","display_name":"effective medium theory","score":0.8140000104904175},{"id":"https://openalex.org/keywords/bulk-density","display_name":"bulk density","score":0.6759999990463257},{"id":"https://openalex.org/keywords/porosity","display_name":"porosity","score":0.9909999966621399},{"id":"https://openalex.org/keywords/hybrid-physics-data-driven-modeling","display_name":"hybrid physics-data models","score":0.5239999890327454}],"concepts":[{"id":"https://openalex.org/C97346530","wikidata":"https://www.wikidata.org/wiki/Q487005","display_name":"Thermal conductivity","level":2,"score":0.701200008392334},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6726999878883362},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5522000193595886},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.5023000240325928},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4171000123023987},{"id":"https://openalex.org/C105569014","wikidata":"https://www.wikidata.org/wiki/Q3271208","display_name":"Porous medium","level":3,"score":0.40220001339912415},{"id":"https://openalex.org/C6648577","wikidata":"https://www.wikidata.org/wiki/Q622669","display_name":"Porosity","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3978999853134155},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.38510000705718994},{"id":"https://openalex.org/C133199616","wikidata":"https://www.wikidata.org/wiki/Q25386885","display_name":"Empirical modelling","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C2779736610","wikidata":"https://www.wikidata.org/wiki/Q6884140","display_name":"Mixture theory","level":3,"score":0.34619998931884766},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.28619998693466187},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C202973686","wikidata":"https://www.wikidata.org/wiki/Q1937401","display_name":"Constitutive equation","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26989999413490295},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26499998569488525},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.260699987411499},{"id":"https://openalex.org/C31555180","wikidata":"https://www.wikidata.org/wiki/Q3523867","display_name":"Material properties","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ma19204411","doi":"https://doi.org/10.3390/ma19204411","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ma19204411","pdf_url":null,"source":{"id":"https://openalex.org/S18714766","display_name":"Materials","issn_l":"1996-1944","issn":["1996-1944"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Materials","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13707292","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13707292/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13707292/pdf/materials-19-04411.pdf","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,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Materials (Basel)","raw_type":"Text"},{"id":"pmid:42941152","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42941152","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":"Materials (Basel, Switzerland)","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.3390/ma19204411","doi":"https://doi.org/10.3390/ma19204411","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ma19204411","pdf_url":null,"source":{"id":"https://openalex.org/S18714766","display_name":"Materials","issn_l":"1996-1944","issn":["1996-1944"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Materials","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311003","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61"},{"id":"https://openalex.org/F4320322877","display_name":"Natural Science Foundation of Ningxia Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7223035964.pdf","grobid_xml":"https://content.openalex.org/works/W7223035964.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1852093535","https://openalex.org/W1973243996","https://openalex.org/W1996412883","https://openalex.org/W2009094104","https://openalex.org/W2020544985","https://openalex.org/W2028012996","https://openalex.org/W2051289112","https://openalex.org/W2104187070","https://openalex.org/W2133631327","https://openalex.org/W2292814759","https://openalex.org/W2764289613","https://openalex.org/W2775031014","https://openalex.org/W2823135818","https://openalex.org/W2907687266","https://openalex.org/W3038114648","https://openalex.org/W3145102099","https://openalex.org/W3163265151","https://openalex.org/W3163993681","https://openalex.org/W4220717841","https://openalex.org/W4220953851","https://openalex.org/W4285794683","https://openalex.org/W4288039037","https://openalex.org/W4293087964","https://openalex.org/W4309548460","https://openalex.org/W4310398570","https://openalex.org/W4311629995","https://openalex.org/W4322743280","https://openalex.org/W4362469292","https://openalex.org/W4385504869","https://openalex.org/W4386197477","https://openalex.org/W4391089329","https://openalex.org/W4391811339","https://openalex.org/W4393334087","https://openalex.org/W4395085245","https://openalex.org/W4396601713","https://openalex.org/W4399293047","https://openalex.org/W4399565299","https://openalex.org/W4400145158","https://openalex.org/W4400340432","https://openalex.org/W4400800044","https://openalex.org/W4402327095","https://openalex.org/W4409613078","https://openalex.org/W4410595199"],"related_works":["https://openalex.org/W2364118846","https://openalex.org/W4401958604","https://openalex.org/W2384753314","https://openalex.org/W7103895169","https://openalex.org/W2042631574","https://openalex.org/W7115559938","https://openalex.org/W4361186460","https://openalex.org/W4411655123","https://openalex.org/W2008964147","https://openalex.org/W4375817017"],"abstract_inverted_index":{"This":[0],"study":[1,155],"investigates":[2],"a":[3,79],"neural":[4],"network":[5],"model":[6,59,77,91,149],"regularized":[7],"by":[8,21],"the":[9,14,24,32,48,63,74,88,96,114,118,123,140,157,160,165],"Maxwell\u2013Eucken":[10,90,131],"formulation":[11],"for":[12,127],"predicting":[13],"thermal":[15],"conductivity":[16],"of":[17,37,81,84,117,159],"foamed":[18],"concrete.":[19],"Backed":[20],"experimental":[22,39],"measurements,":[23],"modeling":[25,162],"workflow":[26],"incorporates":[27],"augmented":[28],"samples":[29],"derived":[30],"from":[31],"empirical":[33],"dataset.":[34],"A":[35],"total":[36],"30":[38],"records,":[40],"categorized":[41],"into":[42],"five":[43],"distinct":[44],"mixture":[45],"groups,":[46],"provide":[47],"foundational":[49],"data":[50],"basis.":[51],"Bulk":[52],"density":[53],"and":[54,95,171],"density-derived":[55],"porosity":[56],"serve":[57],"as":[58,134],"inputs,":[60],"both":[61],"reflecting":[62],"same":[64],"underlying":[65],"variation":[66],"in":[67],"material":[68,167],"density.":[69],"Evaluation":[70],"results":[71],"demonstrate":[72],"that":[73],"proposed":[75],"hybrid":[76,161],"achieves":[78],"coefficient":[80],"determination":[82],"(R2)":[83],"0.7701,":[85],"substantially":[86],"outperforming":[87],"standalone":[89],"(R2":[92,100],"=":[93,101],"0.4546)":[94],"effective":[97],"medium":[98],"theory":[99],"0.3041).":[102],"Although":[103],"these":[104],"indicators":[105],"reflect":[106],"an":[107,135],"improved":[108],"in-sample":[109],"fit,":[110],"they":[111],"neither":[112],"isolate":[113],"explicit":[115],"contribution":[116],"physics-informed":[119],"penalty":[120],"nor":[121],"establish":[122],"model\u2019s":[124],"predictive":[125],"capability":[126],"unseen":[128],"mixtures.":[129],"The":[130],"term":[132],"functions":[133],"approximate":[136],"constitutive":[137],"regularizer,":[138],"whereas":[139],"clustered":[141],"residuals":[142],"highlight":[143],"specific":[144],"boundary":[145],"conditions":[146],"where":[147],"further":[148],"refinement":[150],"is":[151],"warranted.":[152],"Overall,":[153],"this":[154],"validates":[156],"feasibility":[158],"approach":[163],"within":[164],"tested":[166],"domain;":[168],"group-separated":[169],"validation":[170],"comparative":[172],"benchmarks":[173],"against":[174],"purely":[175],"data-driven":[176],"models":[177],"are":[178],"required":[179],"to":[180],"assess":[181],"its":[182],"broader":[183],"generalizability.":[184]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-21T00:00:00"}
