{"id":"https://openalex.org/W7160257529","doi":"https://doi.org/10.48550/arxiv.2605.00868","title":"Autonomous Reliability Qualification of Ga$_2$O$_3$-based diode sensors via Safe Active Learning","display_name":"Autonomous Reliability Qualification of Ga$_2$O$_3$-based diode sensors via Safe Active Learning","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7160257529","doi":"https://doi.org/10.48550/arxiv.2605.00868"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.00868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00868","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.2605.00868","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134491436","display_name":"Davi F\u00e9bba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Febba, Davi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048949384","display_name":"William A. Callahan","orcid":"https://orcid.org/0000-0002-8701-1508"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Callahan, William A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056524322","display_name":"A. Sacchi","orcid":"https://orcid.org/0000-0002-2824-7684"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sacchi, Anna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135394664","display_name":"Andriy Zakutayev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zakutayev, Andriy","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/T12529","display_name":"Ga2O3 and related materials","score":0.8288999795913696,"subfield":{"id":"https://openalex.org/subfields/2504","display_name":"Electronic, Optical and Magnetic Materials"},"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/T12529","display_name":"Ga2O3 and related materials","score":0.8288999795913696,"subfield":{"id":"https://openalex.org/subfields/2504","display_name":"Electronic, Optical and Magnetic Materials"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.08079999685287476,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.005900000222027302,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/rectification","display_name":"Rectification","score":0.8709999918937683},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.7059000134468079},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.5476999878883362},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5242999792098999},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.4828000068664551},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4311000108718872},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.39010000228881836},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.36340001225471497}],"concepts":[{"id":"https://openalex.org/C50942859","wikidata":"https://www.wikidata.org/wiki/Q4967193","display_name":"Rectification","level":3,"score":0.8709999918937683},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.7059000134468079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.583299994468689},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.5476999878883362},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5242999792098999},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4505000114440918},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3199000060558319},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3068000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C127757376","wikidata":"https://www.wikidata.org/wiki/Q2056514","display_name":"Active safety","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C118530786","wikidata":"https://www.wikidata.org/wiki/Q1134732","display_name":"Instrumentation (computer programming)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C9628104","wikidata":"https://www.wikidata.org/wiki/Q788009","display_name":"Autonomous system (mathematics)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C132835097","wikidata":"https://www.wikidata.org/wiki/Q7663745","display_name":"System safety","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26089999079704285},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.00868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00868","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.2605.00868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00868","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Ultra-wide":[0],"bandgap":[1],"(UWBG)":[2],"Ga$_2$O$_3$":[3],"is":[4,22,28,200],"a":[5,34,53,104,134,138,195,207],"promising":[6],"semiconductor":[7],"for":[8,59,125,194],"high-power":[9],"and":[10,41,70,110,116,146,159,179,181],"high-temperature":[11,100],"electronics.":[12],"Reliable":[13],"qualification":[14],"of":[15,63,108,129],"these":[16],"devices":[17],"under":[18,67],"extreme":[19],"operating":[20],"conditions":[21],"essential,":[23],"yet":[24],"conventional":[25],"reliability":[26,61],"testing":[27],"inherently":[29],"time-consuming.":[30],"Autonomous":[31],"experimentation":[32],"offers":[33],"new":[35],"paradigm":[36],"by":[37],"enabling":[38],"measurement":[39],"planning":[40],"model":[42,184],"refinement":[43],"to":[44,202],"evolve":[45],"in":[46,48,77,214],"parallel":[47],"real":[49],"time.":[50],"We":[51,73],"present":[52],"Safe":[54],"Active":[55],"Learning":[56],"(SAL)":[57],"framework":[58],"autonomous":[60],"characterization":[62],"Ga$_2$O$_3$-based":[64,197],"diode":[65,106,131],"sensors":[66],"coupled":[68],"thermal":[69],"hydrogen":[71],"stress.":[72],"first":[74],"evaluate":[75],"SAL":[76,95,157,199],"simulation,":[78],"where":[79],"it":[80],"safely":[81],"expands":[82],"the":[83,88,122,130,156,182],"explored":[84],"region":[85],"while":[86],"learning":[87],"evolving":[89],"rectification":[90],"surface.":[91],"Second,":[92],"we":[93,120],"demonstrate":[94],"experimentally":[96],"on":[97],"an":[98,160],"automated":[99],"probe-station":[101],"platform":[102],"using":[103,155],"Pt/Cr$_2$O$_3$:Mg/$\u03b2$-Ga$_2$O$_3$":[105],"sensor":[107],"H$_2$":[109,115,172],"temperature,":[111],"spanning":[112,164],"0-800":[113],"ppm":[114],"350-550":[117],"\u00b0C.":[118],"Finally,":[119],"use":[121],"SAL-generated":[123],"dataset":[124,163,175],"offline":[126],"long-horizon":[127],"forecasting":[128],"current":[132],"at":[133,167],"target":[135],"voltage":[136],"with":[137,152],"structured":[139],"Gaussian-process":[140],"model.":[141],"Its":[142],"condition-dependent":[143],"Kohlrausch--Williams--Watts":[144],"mean":[145],"residual":[147],"covariance":[148],"kernel":[149,177],"were":[150],"engineered":[151],"artificial-intelligence":[153],"assistance":[154],"data":[158],"auxiliary":[161],"validation":[162],"1,000":[165],"hours":[166],"400":[168],"\u00b0C":[169],"across":[170],"multiple":[171],"concentrations.":[173],"This":[174],"guided":[176],"design":[178],"validation,":[180],"resulting":[183],"captures":[185],"its":[186],"long-time,":[187],"saturating":[188],"degradation":[189],"trends.":[190],"Although":[191],"demonstrated":[192],"here":[193],"rectifying":[196],"diode,":[198],"applicable":[201],"other":[203],"device":[204],"classes":[205],"whenever":[206],"suitable":[208],"safety":[209],"observable":[210],"can":[211],"be":[212],"measured":[213],"situ.":[215]},"counts_by_year":[],"updated_date":"2026-08-12T07:12:00.856984","created_date":"2026-05-06T00:00:00"}