{"id":"https://openalex.org/W7139070971","doi":"https://doi.org/10.48550/arxiv.2603.16959","title":"Machine intelligence supports the full chain of 2D dendrite synthesis","display_name":"Machine intelligence supports the full chain of 2D dendrite synthesis","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7139070971","doi":"https://doi.org/10.48550/arxiv.2603.16959"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16959","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16959","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.16959","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005341890","display_name":"Wendy Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huang, Wenqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129999744","display_name":"Susu Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Susu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012306825","display_name":"Xuhang Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Xuhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130136315","display_name":"Shen'ao Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Shen'ao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130167991","display_name":"Huanhuan Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Huanhuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130028665","display_name":"Junjie Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Junjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047030187","display_name":"Junying Zhang","orcid":"https://orcid.org/0000-0002-8910-6236"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Junying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101299664","display_name":"Shen Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Shen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129815318","display_name":"Zheng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Zheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129850832","display_name":"Jin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031504246","display_name":"Fei-Hong Ouyang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ouyang, Fangping","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129812021","display_name":"Shanshan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shanshan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5005341890"],"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":0.9606999754905701,"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":0.9606999754905701,"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/T11784","display_name":"CO2 Reduction Techniques and Catalysts","score":0.004000000189989805,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11825","display_name":"Catalysis and Oxidation Reactions","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/1503","display_name":"Catalysis"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5881999731063843},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5170999765396118},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.489300012588501},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45100000500679016},{"id":"https://openalex.org/keywords/chain","display_name":"Chain (unit)","score":0.4481000006198883},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4099000096321106},{"id":"https://openalex.org/keywords/experimental-data","display_name":"Experimental data","score":0.39489999413490295},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3903000056743622}],"concepts":[{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5881999731063843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5461000204086304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5252000093460083},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5170999765396118},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C199185054","wikidata":"https://www.wikidata.org/wiki/Q552299","display_name":"Chain (unit)","level":2,"score":0.4481000006198883},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.42640000581741333},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4099000096321106},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C84248122","wikidata":"https://www.wikidata.org/wiki/Q5256671","display_name":"Dendrite (mathematics)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C26546657","wikidata":"https://www.wikidata.org/wiki/Q1412452","display_name":"Fractal dimension","level":3,"score":0.34630000591278076},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3402999937534332},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.299699991941452},{"id":"https://openalex.org/C19351080","wikidata":"https://www.wikidata.org/wiki/Q1395034","display_name":"New product development","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C107908354","wikidata":"https://www.wikidata.org/wiki/Q4781456","display_name":"Applicability domain","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C57410435","wikidata":"https://www.wikidata.org/wiki/Q505668","display_name":"Chemical vapor deposition","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.2587999999523163},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C74859849","wikidata":"https://www.wikidata.org/wiki/Q2466686","display_name":"Non-equilibrium thermodynamics","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16959","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16959","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.16959","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16959","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Exemplified":[0],"by":[1,140],"the":[2,33,56,64,83,126,163,169,174],"chemical":[3],"vapor":[4],"deposition":[5],"growth":[6,65],"of":[7,37,66,82,116,128,142,158],"two-dimensional":[8],"dendrites,":[9],"which":[10,76,124],"has":[11],"potential":[12,171],"applications":[13],"in":[14,151],"catalysis":[15],"and":[16,21,47,112,148,153,177],"presents":[17],"a":[18,28,88,98,105,135],"parameter-intensive,":[19],"data-scarce":[20],"reaction":[22],"process-complex":[23],"model":[24,139],"problem,":[25],"we":[26,133],"devise":[27],"machine":[29,100],"intelligence-empowered":[30],"framework":[31],"for":[32,63,78],"full":[34],"chain":[35],"support":[36],"material":[38,182],"synthesis,":[39,46],"encompassing":[40],"rapid":[41],"process":[42,110,160],"optimization,":[43],"accurate":[44],"customized":[45],"comprehensive":[48],"mechanism":[49,138],"deciphering.First,":[50],"active":[51],"learning":[52,101],"is":[53,94,178],"integrated":[54],"into":[55],"experimental":[57],"workflow,":[58],"identifying":[59],"an":[60],"optimal":[61],"recipe":[62],"highly-branched,":[67],"electrocatalytically-active":[68],"ReSe2":[69,117],"dendrites":[70,118],"through":[71],"60":[72],"experiments":[73],"(4":[74],"iterations),":[75],"account":[77],"less":[79],"than":[80],"1.3%":[81],"numerous":[84],"possible":[85],"parameter":[86],"combinations.Then,":[87],"prediction":[89],"accuracy-guided":[90],"data":[91],"augmentation":[92],"strategy":[93],"developed":[95],"combined":[96],"with":[97,119],"tree-based":[99],"(ML)":[102],"algorithm,":[103],"unveiling":[104],"non-linear":[106],"correlation":[107],"between":[108],"5":[109],"variables":[111],"fractal":[113],"dimension":[114],"(DF)":[115],"only":[120],"9":[121],"experiment":[122],"additions,":[123],"guides":[125],"synthesis":[127],"various":[129],"user-defined":[130],"DF.":[131],"Finally,":[132],"construct":[134],"data-knowledge":[136],"dual-driven":[137],"integration":[141],"cross-scale":[143],"characterizations,":[144],"interpretable":[145],"ML":[146,170],"models,":[147],"domain":[149],"knowledge":[150],"thermodynamics":[152],"kinetics,":[154],"unraveling":[155],"synergistic":[156],"contributions":[157],"multiple":[159],"parameters":[161],"to":[162,172,180],"product":[164],"morphology.":[165],"This":[166],"work":[167],"demonstrates":[168],"transform":[173],"research":[175],"paradigm":[176],"adaptable":[179],"broader":[181],"synthesis.":[183]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}