{"id":"https://openalex.org/W7117781900","doi":"https://doi.org/10.48550/arxiv.2512.23284","title":"Revealing design archetypes and flexibility in e-molecule import pathways using Modeling to Generate Alternatives and interpretable machine learning","display_name":"Revealing design archetypes and flexibility in e-molecule import pathways using Modeling to Generate Alternatives and interpretable machine learning","publication_year":2025,"publication_date":"2025-12-29","ids":{"openalex":"https://openalex.org/W7117781900","doi":"https://doi.org/10.48550/arxiv.2512.23284"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2512.23284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.23284","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":null,"license_id":null,"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.2512.23284","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121628377","display_name":"Mahdi Kchaou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kchaou, Mahdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121676087","display_name":"Francesco Contino","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Contino, Francesco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121645251","display_name":"Diederik Coppitters","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Coppitters, Diederik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":0.2281000018119812,"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":0.2281000018119812,"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/T11007","display_name":"Hybrid Renewable Energy Systems","score":0.13199999928474426,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"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/T11593","display_name":"Carbon dioxide utilization in catalysis","score":0.11479999870061874,"subfield":{"id":"https://openalex.org/subfields/1508","display_name":"Process Chemistry and Technology"},"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/flexibility","display_name":"Flexibility (engineering)","score":0.6377999782562256},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5248000025749207},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4828999936580658},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.31859999895095825},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.27730000019073486},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.27160000801086426}],"concepts":[{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6377999782562256},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5810999870300293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5454000234603882},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5184999704360962},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C72161134","wikidata":"https://www.wikidata.org/wiki/Q5421219","display_name":"Expert elicitation","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2512.23284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.23284","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2512.23284","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.23284","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.7145008444786072,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Given":[0],"the":[1,9,89,131],"central":[2],"role":[3],"of":[4,62,130],"green":[5],"e-molecule":[6],"imports":[7],"in":[8,44],"European":[10],"energy":[11],"transition,":[12],"many":[13],"studies":[14],"optimize":[15],"import":[16,99],"pathways":[17,100],"and":[18,36,47,105,120],"identify":[19],"a":[20,59,111],"single":[21],"cost-optimal":[22,50],"solution.":[23],"However,":[24],"cost":[25,68,132],"optimality":[26],"is":[27,82,95],"fragile,":[28],"as":[29,107],"real-world":[30],"implementation":[31],"depends":[32],"on":[33],"regulatory,":[34],"spatial,":[35],"stakeholder":[37],"constraints":[38,135],"that":[39],"are":[40,122],"difficult":[41],"to":[42,72,85,97,126],"represent":[43],"optimization":[45],"models":[46],"can":[48],"render":[49],"designs":[51],"infeasible.":[52],"To":[53],"address":[54],"this":[55],"limitation,":[56],"we":[57],"generate":[58],"diverse":[60],"set":[61],"near-cost-optimal":[63],"alternatives":[64],"within":[65,128],"an":[66],"acceptable":[67],"margin":[69],"using":[70],"Modeling":[71],"Generate":[73],"Alternatives,":[74],"accounting":[75],"for":[76],"unmodeled":[77],"uncertainties.":[78],"Interpretable":[79],"machine":[80],"learning":[81],"then":[83],"applied":[84,96],"extract":[86],"insights":[87],"from":[88],"resulting":[90],"solution":[91],"space.":[92],"The":[93],"approach":[94],"hydrogen":[98],"considering":[101],"hydrogen,":[102],"ammonia,":[103],"methane,":[104],"methanol":[106,138],"carriers.":[108],"Results":[109],"reveal":[110],"broad":[112],"near-optimal":[113],"space":[114],"with":[115],"great":[116],"flexibility:":[117],"solar,":[118],"wind,":[119],"storage":[121,142],"not":[123],"strictly":[124],"required":[125],"remain":[127],"10%":[129],"optimum.":[133],"Wind":[134],"favor":[136],"solar-storage":[137],"pathways,":[139],"while":[140],"limited":[141],"favors":[143],"wind-based":[144],"ammonia":[145],"or":[146],"methane":[147],"pathways.":[148]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-31T00:00:00"}