{"id":"https://openalex.org/W7106685796","doi":"https://doi.org/10.48550/arxiv.2511.19335","title":"High-throughput validation of phase formability and simulation accuracy of Cantor alloys","display_name":"High-throughput validation of phase formability and simulation accuracy of Cantor alloys","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7106685796","doi":"https://doi.org/10.48550/arxiv.2511.19335"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.19335","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.19335","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.19335","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Cheng, Changjun","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Cheng, Changjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Persaud, Daniel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Persaud, Daniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Li, Kangming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Kangming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Moorehead, Michael J.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moorehead, Michael J.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Page, Natalie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Page, Natalie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lavoie, Christian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lavoie, Christian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Moreno, Beatriz Diaz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moreno, Beatriz Diaz","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Couet, Adrien","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Couet, Adrien","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lofland, Samuel E","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lofland, Samuel E","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Hattrick-Simpers, Jason","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hattrick-Simpers, Jason","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11143","display_name":"High Entropy Alloys Studies","score":0.6568999886512756,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11143","display_name":"High Entropy Alloys Studies","score":0.6568999886512756,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.22339999675750732,"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/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.033799998462200165,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/formability","display_name":"Formability","score":0.7692000269889832},{"id":"https://openalex.org/keywords/calphad","display_name":"CALPHAD","score":0.6251999735832214},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.5547000169754028},{"id":"https://openalex.org/keywords/experimental-data","display_name":"Experimental data","score":0.5051000118255615},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.49410000443458557},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.48240000009536743},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4763000011444092},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/phase-diagram","display_name":"Phase diagram","score":0.4472000002861023}],"concepts":[{"id":"https://openalex.org/C79127381","wikidata":"https://www.wikidata.org/wiki/Q5469940","display_name":"Formability","level":2,"score":0.7692000269889832},{"id":"https://openalex.org/C93501709","wikidata":"https://www.wikidata.org/wiki/Q4035558","display_name":"CALPHAD","level":4,"score":0.6251999735832214},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.5547000169754028},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.5051000118255615},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.46950000524520874},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C85906118","wikidata":"https://www.wikidata.org/wiki/Q186693","display_name":"Phase diagram","level":3,"score":0.4472000002861023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39480000734329224},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3605000078678131},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C2777959984","wikidata":"https://www.wikidata.org/wiki/Q8564653","display_name":"Forming limit diagram","level":3,"score":0.302700012922287},{"id":"https://openalex.org/C207114421","wikidata":"https://www.wikidata.org/wiki/Q133900","display_name":"Diffraction","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.2574000060558319},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2554999887943268},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.19335","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.19335","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.19335","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.19335","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"High-throughput":[0],"methods":[1],"enable":[2],"accelerated":[3],"discovery":[4],"of":[5,33,39,45,52,85,88,150],"novel":[6],"materials":[7],"in":[8,60,99,172],"complex":[9],"systems":[10],"such":[11],"as":[12,42],"high-entropy":[13],"alloys,":[14],"which":[15],"exhibit":[16],"intricate":[17],"phase":[18,34,40,140,151],"stability":[19],"across":[20],"vast":[21],"compositional":[22],"spaces.":[23],"Computational":[24],"approaches,":[25],"including":[26],"Density":[27],"Functional":[28],"Theory":[29],"(DFT)":[30],"and":[31,47,78,132,163],"calculation":[32],"diagrams":[35],"(CALPHAD),":[36],"facilitate":[37],"screening":[38],"formability":[41],"a":[43,68,82,143,147],"function":[44],"composition":[46],"temperature.":[48],"However,":[49],"the":[50,74,86,130],"integration":[51],"computational":[53],"predictions":[54,77,174],"with":[55],"experimental":[56,79,102,105],"validation":[57],"remains":[58],"challenging":[59],"high-throughput":[61,110],"studies.":[62],"In":[63],"this":[64],"work,":[65],"we":[66],"introduce":[67],"quantitative":[69,83],"confidence":[70,87],"metric":[71],"to":[72,125,178],"assess":[73],"agreement":[75,160],"between":[76,129,161],"observations,":[80],"providing":[81],"measure":[84],"machine":[89],"learning":[90],"models":[91],"trained":[92],"on":[93,115],"either":[94,138],"DFT":[95],"or":[96,142],"CALPHAD":[97],"input":[98],"accounting":[100],"for":[101],"evidence.":[103],"The":[104],"dataset":[106],"was":[107,135],"generated":[108],"via":[109],"in-situ":[111],"synchrotron":[112],"X-ray":[113],"diffraction":[114],"compositionally":[116],"varied":[117],"FeNiMnCr":[118],"alloy":[119],"libraries,":[120],"heated":[121],"from":[122],"room":[123],"temperature":[124],"~1000":[126],"\u00b0C.":[127],"Agreement":[128],"observed":[131],"predicted":[133],"phases":[134],"evaluated":[136],"using":[137],"temperature-independent":[139],"classification":[141],"model":[144,181],"that":[145],"incorporates":[146],"temperature-dependent":[148],"probability":[149],"formation.":[152],"This":[153],"integrated":[154],"approach":[155],"demonstrates":[156],"where":[157],"strong":[158],"overall":[159],"computation":[162],"experiment":[164],"exists,":[165],"while":[166],"also":[167],"identifying":[168],"key":[169],"discrepancies,":[170],"particularly":[171],"FCC/BCC":[173],"at":[175],"Mn-rich":[176],"regions":[177],"inform":[179],"future":[180],"refinement.":[182]},"counts_by_year":[],"updated_date":"2025-11-27T01:16:37.896743","created_date":"2025-11-27T00:00:00"}
