{"id":"https://openalex.org/W4285347563","doi":"https://doi.org/10.1109/aipr52630.2021.9762145","title":"Reinforcement Learning based Carbon Nanotube Growth Automation","display_name":"Reinforcement Learning based Carbon Nanotube Growth Automation","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4285347563","doi":"https://doi.org/10.1109/aipr52630.2021.9762145"},"language":"en","primary_location":{"id":"doi:10.1109/aipr52630.2021.9762145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr52630.2021.9762145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103259236","display_name":"Ashish Pandey","orcid":"https://orcid.org/0000-0002-8910-8864"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ashish Pandey","raw_affiliation_strings":["University of Missouri-Columbia,Dept. of Electrical Engineering and Computer Science,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri-Columbia,Dept. of Electrical Engineering and Computer Science,USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047152183","display_name":"Ramakrishna Surya","orcid":"https://orcid.org/0000-0001-7868-9045"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramakrishna Surya","raw_affiliation_strings":["University of Missouri-Columbia,Dept. of Mechanical and Aerospace Engineering,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri-Columbia,Dept. of Mechanical and Aerospace Engineering,USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064742249","display_name":"Matthew R. Maschmann","orcid":"https://orcid.org/0000-0002-0740-6228"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Maschmann","raw_affiliation_strings":["University of Missouri-Columbia,Dept. of Mechanical and Aerospace Engineering,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri-Columbia,Dept. of Mechanical and Aerospace Engineering,USA","institution_ids":["https://openalex.org/I76835614"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072008189","display_name":"Prasad Calyam","orcid":"https://orcid.org/0000-0002-7666-5389"},"institutions":[{"id":"https://openalex.org/I76835614","display_name":"University of Missouri","ror":"https://ror.org/02ymw8z06","country_code":"US","type":"education","lineage":["https://openalex.org/I76835614"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasad Calyam","raw_affiliation_strings":["University of Missouri-Columbia,Dept. of Electrical Engineering and Computer Science,USA"],"affiliations":[{"raw_affiliation_string":"University of Missouri-Columbia,Dept. of Electrical Engineering and Computer Science,USA","institution_ids":["https://openalex.org/I76835614"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103259236"],"corresponding_institution_ids":["https://openalex.org/I76835614"],"apc_list":null,"apc_paid":null,"fwci":0.3154,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.50716661,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10074","display_name":"Carbon Nanotubes in Composites","score":0.9977999925613403,"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/T10074","display_name":"Carbon Nanotubes in Composites","score":0.9977999925613403,"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/T10923","display_name":"Force Microscopy Techniques and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7617782354354858},{"id":"https://openalex.org/keywords/carbon-nanotube","display_name":"Carbon nanotube","score":0.6435835361480713},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.5984877347946167},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5827060341835022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4020261764526367},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.39400625228881836},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.3497871160507202},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3246948719024658},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.22464245557785034},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.154570072889328}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7617782354354858},{"id":"https://openalex.org/C513720949","wikidata":"https://www.wikidata.org/wiki/Q1778729","display_name":"Carbon nanotube","level":2,"score":0.6435835361480713},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.5984877347946167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5827060341835022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4020261764526367},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.39400625228881836},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.3497871160507202},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3246948719024658},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.22464245557785034},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.154570072889328}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr52630.2021.9762145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr52630.2021.9762145","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G2108441746","display_name":null,"funder_award_id":"CMMI-2026847","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1985588689","https://openalex.org/W1996119109","https://openalex.org/W2018264522","https://openalex.org/W2031468982","https://openalex.org/W2108810927","https://openalex.org/W2115467250","https://openalex.org/W2529193383","https://openalex.org/W2558921396","https://openalex.org/W2917675345","https://openalex.org/W2951295438","https://openalex.org/W2972220753","https://openalex.org/W2999862950","https://openalex.org/W3013190220","https://openalex.org/W3035756007","https://openalex.org/W3165566836","https://openalex.org/W3167898434","https://openalex.org/W3195429586","https://openalex.org/W4210316282","https://openalex.org/W6807630041"],"related_works":["https://openalex.org/W1576739978","https://openalex.org/W2985840163","https://openalex.org/W2120609629","https://openalex.org/W1983849759","https://openalex.org/W2739992384","https://openalex.org/W4306904969","https://openalex.org/W2065626222","https://openalex.org/W1982847193","https://openalex.org/W2183598138","https://openalex.org/W2071466337"],"abstract_inverted_index":{"Experimental":[0],"research":[1],"such":[2,138],"as":[3,139],"cell":[4],"cultures":[5],"and":[6,50,65,112,147,172,220,245],"carbon":[7,217,250],"nanotube":[8,218],"(CNT)":[9],"growth":[10,48,120,128,141,159,170,187,191,248],"are":[11,25,60,69,152],"largely":[12],"governed":[13],"by":[14,188,206,234],"following":[15],"predefined":[16],"execution":[17],"protocols":[18],"with":[19],"fine-tuned":[20],"control":[21,136],"of":[22,40,114,165,169,178,196,202,215,230,242,247,249],"parameters.":[23,121],"There":[24],"promising":[26],"opportunities":[27],"to":[28,45,81,107,163,183],"apply":[29],"reinforcement":[30],"learning":[31,35,75],"(RL),":[32],"an":[33,104],"established":[34],"technique":[36],"in":[37,43,55,62,72,77,130,161,210],"the":[38,200,208,211,222,228,240],"area":[39],"artificial":[41],"intelligence,":[42],"order":[44,162],"automate":[46],"CNT":[47,82,97,116,127,158,186,256],"process":[49],"accelerate":[51],"related":[52],"scientific":[53],"breakthroughs":[54],"material":[56],"discovery.":[57],"Although":[58],"there":[59,68],"benefits":[61],"RL-based":[63],"exploration":[64],"exploitation":[66],"methodologies,":[67],"also":[70],"challenges":[71],"developing":[73,103],"relevant":[74],"policies":[76],"experimental":[78,96],"settings":[79],"relating":[80],"growth.":[83,98,257],"In":[84],"this":[85],"paper,":[86],"we":[87],"present":[88],"a":[89,131,166,194,216],"novel":[90],"data-driven":[91],"RL":[92,105,123,155,180,204,223,236],"approach":[93,100,205,237],"for":[94],"assisting":[95],"Our":[99,122,154,225],"focuses":[101],"on":[102],"model":[106,124,156,181],"learn":[108],"from":[109,126],"simulation-based":[110,132],"images":[111],"characteristics":[113],"temporal":[115],"growth,":[117],"considering":[118],"various":[119],"learns":[125],"variation":[129],"environment":[133],"where":[134],"critical":[135],"parameters,":[137],"density,":[140],"rate,":[142],"tube":[143,145],"radius,":[144],"stiffness,":[146],"Van":[148],"der":[149],"Waals":[150],"forces,":[151],"used.":[153],"enables":[157],"automation":[160],"explore":[164],"wider":[167],"range":[168],"conditions,":[171],"improve":[173],"reproducibility.":[174],"The":[175],"ultimate":[176],"goal":[177],"our":[179,203,235],"is":[182],"achieve":[184],"desired":[185],"dynamically":[189],"controlling":[190,239],"parameters":[192,241],"throughout":[193],"sequence":[195],"experiments.":[197],"We":[198],"evaluate":[199],"effectiveness":[201,229],"measuring":[207],"improvement":[209],"maximum":[212],"compressive":[213],"strength":[214],"\u2018with\u2019":[219],"\u2018without\u2019":[221],"model.":[224],"results":[226],"show":[227],"course":[231],"correction":[232],"recommended":[233],"when":[238,252],"angular":[243],"deviation":[244],"rate":[246],"nanotubes,":[251],"compared":[253],"against":[254],"non-regulated":[255]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
