{"id":"https://openalex.org/W7155421116","doi":"https://doi.org/10.48550/arxiv.2604.20304","title":"LLM-guided phase diagram construction through high-throughput experimentation","display_name":"LLM-guided phase diagram construction through high-throughput experimentation","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155421116","doi":"https://doi.org/10.48550/arxiv.2604.20304"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.20304","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134417690","display_name":"Ryo Tamura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tamura, Ryo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134375776","display_name":"Haruhiko Morito","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morito, Haruhiko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134392746","display_name":"Yuna Oikawa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oikawa, Yuna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058501030","display_name":"Guillaume Deffrennes","orcid":"https://orcid.org/0000-0002-3752-2537"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deffrennes, Guillaume","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000033987","display_name":"Sh\u00f4ichi Matsuda","orcid":"https://orcid.org/0000-0002-0640-3404"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matsuda, Shoichi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019451422","display_name":"Naruki Yoshikawa","orcid":"https://orcid.org/0000-0003-1546-8709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshikawa, Naruki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134438733","display_name":"Tomoaki Takayama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takayama, Tomoaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027537776","display_name":"Taichi Abe","orcid":"https://orcid.org/0000-0002-5065-0939"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abe, Taichi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134442155","display_name":"Koji Tsuda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsuda, Koji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134435882","display_name":"Kei Terayama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Terayama, Kei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9939000010490417,"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":0.9939000010490417,"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/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13552","display_name":"Advanced Materials Characterization Techniques","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/phase-diagram","display_name":"Phase diagram","score":0.8636000156402588},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.692300021648407},{"id":"https://openalex.org/keywords/diagram","display_name":"Diagram","score":0.5958999991416931},{"id":"https://openalex.org/keywords/ternary-plot","display_name":"Ternary plot","score":0.5913000106811523},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.5651000142097473},{"id":"https://openalex.org/keywords/ternary-operation","display_name":"Ternary operation","score":0.5496000051498413}],"concepts":[{"id":"https://openalex.org/C85906118","wikidata":"https://www.wikidata.org/wiki/Q186693","display_name":"Phase diagram","level":3,"score":0.8636000156402588},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.692300021648407},{"id":"https://openalex.org/C186399060","wikidata":"https://www.wikidata.org/wiki/Q959962","display_name":"Diagram","level":2,"score":0.5958999991416931},{"id":"https://openalex.org/C139478118","wikidata":"https://www.wikidata.org/wiki/Q1257468","display_name":"Ternary plot","level":3,"score":0.5913000106811523},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C64452783","wikidata":"https://www.wikidata.org/wiki/Q1524945","display_name":"Ternary operation","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48669999837875366},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4092000126838684},{"id":"https://openalex.org/C207114421","wikidata":"https://www.wikidata.org/wiki/Q133900","display_name":"Diffraction","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C122247533","wikidata":"https://www.wikidata.org/wiki/Q1056486","display_name":"Ternary numeral system","level":3,"score":0.25780001282691956},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.20304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5437566041946411}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Constructing":[0],"phase":[1,28,59,69,106,209],"diagrams":[2],"for":[3,27,44,208],"multicomponent":[4],"alloys":[5],"requires":[6],"extensive":[7],"experimental":[8,25,40,206],"measurements":[9,129],"and":[10,56,82],"is":[11],"a":[12,34,50,101,163,169,179],"time-consuming":[13],"task.":[14],"Here":[15],"we":[16,64],"investigate":[17],"whether":[18],"large":[19],"language":[20],"models":[21],"(LLMs)":[22],"can":[23],"guide":[24],"planning":[26],"diagram":[29,70,107,210],"construction.":[30,211],"In":[31,157,177],"our":[32],"framework,":[33,63],"general-purpose":[35,117,160],"LLM":[36,103,161,184,192],"serves":[37],"as":[38,205],"the":[39,67,72,92,111,116,127,135,138,142,154,159,183,191],"planner,":[41],"suggesting":[42],"compositions":[43,94],"measurement":[45],"at":[46,75],"each":[47],"cycle":[48],"in":[49,90,134,153,174],"closed":[51],"loop":[52],"with":[53],"high-throughput":[54],"synthesis":[55,81],"X-ray":[57],"diffraction":[58],"identification.":[60],"Using":[61],"this":[62],"experimentally":[65],"constructed":[66],"ternary":[68,139,155],"of":[71,137,145,172],"Co-Al-Ge":[73],"system":[74],"900":[76],"degree":[77],"C":[78],"through":[79],"iterative":[80],"characterization.":[83],"We":[84],"compared":[85],"two":[86,120],"strategies":[87,121],"that":[88,150,190,200],"differ":[89],"how":[91],"initial":[93,128],"are":[95],"selected:":[96],"one":[97],"uses":[98],"predictions":[99],"from":[100],"domain-specific":[102],"trained":[104],"on":[105,115],"data":[108],"(aLLoyM),":[109],"while":[110],"other":[112],"relies":[113],"solely":[114],"LLM.":[118],"The":[119,197],"exhibited":[122],"complementary":[123],"strengths.":[124],"aLLoyM":[125],"directed":[126],"toward":[130],"compositionally":[131],"complex":[132],"regions":[133],"interior":[136],"diagram,":[140],"enabling":[141],"earliest":[143],"discovery":[144],"all":[146],"three":[147],"novel":[148],"phases":[149,173],"form":[151],"only":[152],"system.":[156],"contrast,":[158],"adopted":[162],"textbook-like":[164],"approach":[165],"which":[166],"efficiently":[167],"identified":[168],"larger":[170],"number":[171],"fewer":[175],"cycles.":[176],"addition,":[178],"simulated":[180],"benchmark":[181],"comparing":[182],"against":[185],"conventional":[186],"machine":[187],"learning":[188],"confirmed":[189],"achieves":[193],"more":[194],"efficient":[195],"exploration.":[196],"results":[198],"demonstrate":[199],"LLMs":[201],"have":[202],"high":[203],"potential":[204],"planners":[207]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-24T00:00:00"}
