{"id":"https://openalex.org/W7223178190","doi":"https://doi.org/10.26434/chemrxiv.15010837/v1","title":"Multi-Agent Scheduling of Instrument-Time for High-Throughput Palladium-Catalysed Cross-Coupling","display_name":"Multi-Agent Scheduling of Instrument-Time for High-Throughput Palladium-Catalysed Cross-Coupling","publication_year":2026,"publication_date":"2026-10-22","ids":{"openalex":"https://openalex.org/W7223178190","doi":"https://doi.org/10.26434/chemrxiv.15010837/v1"},"language":"en","primary_location":{"id":"doi:10.26434/chemrxiv.15010837/v1","doi":"https://doi.org/10.26434/chemrxiv.15010837/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15010837/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010837/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010837/v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135573148","display_name":"Yuhang Shao","orcid":"https://orcid.org/0009-0008-9000-8052","observed_orcids":["https://orcid.org/0009-0008-9000-8052"]},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Shao","raw_affiliation_strings":["Kunming University of Science and Technology , Kunming , Yunnan , China"],"raw_orcid":"https://orcid.org/0009-0008-9000-8052","affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology , Kunming , Yunnan , China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130387598","display_name":"Siqi Meng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Meng","raw_affiliation_strings":["Kunming University of Science and Technology , Kunming , Yunnan , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology , Kunming , Yunnan , China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5159236393","display_name":"Yutian Luo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutian Luo","raw_affiliation_strings":["Kunming University of Science and Technology , Kunming , Yunnan , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology , Kunming , Yunnan , China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138278057","display_name":"Jiawei Tan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Tan","raw_affiliation_strings":["Kunming University of Science and Technology , Kunming , Yunnan , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology , Kunming , Yunnan , China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5159224152","display_name":"Chengyu He","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengyu He","raw_affiliation_strings":["Kunming University of Science and Technology , Kunming , Yunnan , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology , Kunming , Yunnan , China","institution_ids":["https://openalex.org/I10660446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10660446"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.4796999990940094,"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":0.4796999990940094,"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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.10999999940395355,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10548","display_name":"Catalytic Cross-Coupling Reactions","score":0.05420000106096268,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic 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/multi-agent-scheduling","display_name":"multi-agent scheduling","score":0.8289999961853027},{"id":"https://openalex.org/keywords/high-throughput-experimentation","display_name":"high-throughput experimentation","score":0.7680000066757202},{"id":"https://openalex.org/keywords/palladium-catalyzed-cross-coupling","display_name":"palladium-catalyzed cross-coupling","score":0.9509999752044678},{"id":"https://openalex.org/keywords/buchwald-hartwig-amination","display_name":"Buchwald-Hartwig amination","score":0.8489999771118164},{"id":"https://openalex.org/keywords/suzuki-miyaura-coupling","display_name":"Suzuki coupling","score":0.9639999866485596},{"id":"https://openalex.org/keywords/liquid-handling-robot","display_name":"liquid handling robot","score":0.8460000157356262},{"id":"https://openalex.org/keywords/compatibility-graph","display_name":"compatibility graph","score":0.8339999914169312},{"id":"https://openalex.org/keywords/tennessee-eastman-process","display_name":"Tennessee Eastman process","score":0.7699999809265137},{"id":"https://openalex.org/keywords/fault-injection","display_name":"fault injection","score":0.4790000021457672}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8174999952316284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615000009536743},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3472999930381775},{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.266400009393692},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2621999979019165},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.25769999623298645},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.26434/chemrxiv.15010837/v1","doi":"https://doi.org/10.26434/chemrxiv.15010837/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15010837/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010837/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.26434/chemrxiv.15010837/v1","doi":"https://doi.org/10.26434/chemrxiv.15010837/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15010837/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010837/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7223178190.pdf","grobid_xml":"https://content.openalex.org/works/W7223178190.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2004186751","https://openalex.org/W2511652057","https://openalex.org/W2728229829","https://openalex.org/W2784918212","https://openalex.org/W2785942661","https://openalex.org/W2889272453","https://openalex.org/W3042021489","https://openalex.org/W3092530885","https://openalex.org/W3112679685","https://openalex.org/W4225934396","https://openalex.org/W4411119699","https://openalex.org/W4412366573","https://openalex.org/W4416035220","https://openalex.org/W7131683559","https://openalex.org/W7134845483","https://openalex.org/W7154499347","https://openalex.org/W7161875529","https://openalex.org/W7166833224","https://openalex.org/W7202416182","https://openalex.org/W7212060147","https://openalex.org/W7212548570","https://openalex.org/W7213675703","https://openalex.org/W7214960001"],"related_works":["https://openalex.org/W2124049013","https://openalex.org/W4317389020","https://openalex.org/W64642002","https://openalex.org/W7166254344","https://openalex.org/W7167061792","https://openalex.org/W2614837496","https://openalex.org/W2522434274","https://openalex.org/W7128117241","https://openalex.org/W7020712891","https://openalex.org/W7165781205"],"abstract_inverted_index":{"NMR":[0],"time":[1],"and":[2,10,37,66,73,92,114,125,159,168],"a":[3,51,59,78,88,93,126,137],"shared":[4,138],"liquid-handling":[5],"robot":[6],"are":[7],"scarce,":[8],"noisy":[9],"only":[11,42,75],"partially":[12],"observable,":[13],"so":[14],"the":[15,110,121,145,152],"practical":[16],"question":[17],"is":[18],"which":[19,25],"experiment":[20],"to":[21,163],"run":[22],"next":[23],"on":[24],"instrument.":[26],"Existing":[27],"reaction-optimisation":[28],"benchmarks":[29,124],"measure":[30],"budgets":[31],"in":[32],"experiments":[33],"rather":[34],"than":[35],"instrumenthours,":[36],"they":[38],"learn":[39],"chemical":[40],"feasibility":[41,80],"by":[43],"paying":[44],"for":[45],"infeasible":[46,161],"runs.":[47],"We":[48],"present":[49],"CHASE,":[50],"centralised-training":[52],"decentralised-execution":[53],"scheduler":[54],"with":[55,87,155],"three":[56],"coupled":[57],"modules:":[58],"belief":[60],"encoder":[61],"(PEB)":[62],"infers":[63],"per-instrument":[64],"throughput":[65],"channel":[67],"health":[68],"from":[69],"local":[70],"event":[71],"histories":[72],"exchanges":[74],"low-bandwidth":[76],"summaries;":[77],"chemistry":[79],"gate":[81],"(CFG)":[82],"masks":[83],"chemically":[84],"impossible":[85],"actions":[86,162],"four-layer":[89],"compatibility":[90],"graph;":[91],"counterfactual":[94],"attribution":[95],"module":[96],"(CFA)":[97],"converts":[98],"delayed":[99],"campaign":[100],"reward":[101],"into":[102],"per-step":[103],"credit":[104],"through":[105],"leave-one-experiment-out":[106],"surrogate":[107],"scoring.":[108],"On":[109],"Buchwald\u2013Hartwig":[111],"(3,955":[112],"reactions)":[113],"Suzuki\u2013Miyaura":[115],"(5,760":[116],"nanomole-scale":[117],"conditions)":[118],"HTE":[119],"datasets,":[120],"ten":[122],"Olympus":[123],"plant-wide":[127],"Tennessee":[128],"Eastman":[129],"process,":[130],"CHASE":[131],"reaches":[132],"94.1%":[133],"best-found":[134],"yield":[135],"under":[136],"60":[139],"instrument-hour":[140],"budget,":[141],"+3.3":[142],"points":[143],"over":[144],"strongest":[146],"same-setting":[147],"baseline,":[148],"attains":[149],"90%":[150],"of":[151],"attainable":[153],"optimum":[154],"25.6%":[156],"fewer":[157],"experiments,":[158],"cuts":[160],"0.7\u20131.6%":[164],"across":[165],"plate,":[166],"flow":[167],"fault-injection":[169],"settings.":[170]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-10-22T00:00:00"}
