{"id":"https://openalex.org/W4416787768","doi":"https://doi.org/10.1007/s44163-025-00620-2","title":"Machine learning enhanced prediction of sensible heat storage potential based on thermogravimetric analysis","display_name":"Machine learning enhanced prediction of sensible heat storage potential based on thermogravimetric analysis","publication_year":2025,"publication_date":"2025-11-28","ids":{"openalex":"https://openalex.org/W4416787768","doi":"https://doi.org/10.1007/s44163-025-00620-2"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00620-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00620-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00620-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00620-2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089772044","display_name":"Abubakar D. Maiwada","orcid":null},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Abubakar D. Maiwada","raw_affiliation_strings":["Material Science and Engineering Department, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Material Science and Engineering Department, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064566125","display_name":"Abdullahi Adamu","orcid":"https://orcid.org/0000-0003-3377-8612"},"institutions":[{"id":"https://openalex.org/I919958821","display_name":"Bayero University Kano","ror":"https://ror.org/049pzty39","country_code":"NG","type":"education","lineage":["https://openalex.org/I919958821"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Abdullahi A. Adamu","raw_affiliation_strings":["Mechanical Engineering Department, Bayero University, Kano, Nigeria"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, Bayero University, Kano, Nigeria","institution_ids":["https://openalex.org/I919958821"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072286524","display_name":"Jamilu Usman","orcid":"https://orcid.org/0000-0002-3800-423X"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Jamilu Usman","raw_affiliation_strings":["Interdisciplinary Research Center for Membrane and Water Security, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Interdisciplinary Research Center for Membrane and Water Security, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059132448","display_name":"Umar Danjuma Maiwada","orcid":"https://orcid.org/0000-0001-7679-3674"},"institutions":[{"id":"https://openalex.org/I327500432","display_name":"Umaru Musa Yar'adua University","ror":"https://ror.org/05gwcqj56","country_code":"NG","type":"education","lineage":["https://openalex.org/I327500432"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Umar D. Maiwada","raw_affiliation_strings":["Umaru Musa \u2018Yar\u2019adua University, Katsina State, Nigeria","Umaru Musa 'Yar'adua University, Katsina State, Nigeria"],"affiliations":[{"raw_affiliation_string":"Umaru Musa \u2018Yar\u2019adua University, Katsina State, Nigeria","institution_ids":["https://openalex.org/I327500432"]},{"raw_affiliation_string":"Umaru Musa 'Yar'adua University, Katsina State, Nigeria","institution_ids":["https://openalex.org/I327500432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015567086","display_name":"S Abdulrahman","orcid":"https://orcid.org/0000-0002-4650-869X"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Suleiman Abdulrahman","raw_affiliation_strings":["Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062007467","display_name":"Sani I. Abba","orcid":"https://orcid.org/0000-0001-9356-2798"},"institutions":[{"id":"https://openalex.org/I138564716","display_name":"Prince Mohammad bin Fahd University","ror":"https://ror.org/03d64na34","country_code":"SA","type":"education","lineage":["https://openalex.org/I138564716"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Sani I. Abba","raw_affiliation_strings":["Department of Civil Engineering, Prince Mohammad Bin Fahd University, 31952, Al Khobar, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Prince Mohammad Bin Fahd University, 31952, Al Khobar, Saudi Arabia","institution_ids":["https://openalex.org/I138564716"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5062007467","https://openalex.org/A5089772044"],"corresponding_institution_ids":["https://openalex.org/I134085113","https://openalex.org/I138564716"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39467173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10938","display_name":"Phase Change Materials Research","score":0.5521000027656555,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10938","display_name":"Phase Change Materials Research","score":0.5521000027656555,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11774","display_name":"Adsorption and Cooling Systems","score":0.28529998660087585,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11225","display_name":"Geothermal Energy Systems and Applications","score":0.019600000232458115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6729999780654907},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6449000239372253},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6327000260353088},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5333999991416931},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4426000118255615},{"id":"https://openalex.org/keywords/sensible-heat","display_name":"Sensible heat","score":0.4343999922275543},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.43209999799728394},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4316999912261963},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6729999780654907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6617000102996826},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6449000239372253},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6327000260353088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5379999876022339},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5333999991416931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48420000076293945},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C59242433","wikidata":"https://www.wikidata.org/wiki/Q1480581","display_name":"Sensible heat","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.375900000333786},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C183287310","wikidata":"https://www.wikidata.org/wiki/Q2142963","display_name":"Thermal energy storage","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C170964787","wikidata":"https://www.wikidata.org/wiki/Q7611170","display_name":"Stepwise regression","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27549999952316284},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2623000144958496},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00620-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00620-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00620-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:14d3e84faf55488ea00b5b0f865745f2","is_oa":true,"landing_page_url":"https://doaj.org/article/14d3e84faf55488ea00b5b0f865745f2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-24 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00620-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00620-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00620-2.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416787768.pdf","grobid_xml":"https://content.openalex.org/works/W4416787768.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W2092466978","https://openalex.org/W2149905014","https://openalex.org/W2576683119","https://openalex.org/W2584137105","https://openalex.org/W3008568533","https://openalex.org/W3013886262","https://openalex.org/W3016350595","https://openalex.org/W3037647569","https://openalex.org/W3044134577","https://openalex.org/W3135028703","https://openalex.org/W3171141561","https://openalex.org/W3179987986","https://openalex.org/W3201316396","https://openalex.org/W3217465674","https://openalex.org/W4200454878","https://openalex.org/W4221062742","https://openalex.org/W4224085459","https://openalex.org/W4282981314","https://openalex.org/W4286265175","https://openalex.org/W4379645831","https://openalex.org/W4383982237","https://openalex.org/W4385602869","https://openalex.org/W4386006872","https://openalex.org/W4386142022","https://openalex.org/W4386541762","https://openalex.org/W4387342012","https://openalex.org/W4388439911","https://openalex.org/W4389113368","https://openalex.org/W4389513437","https://openalex.org/W4390819368","https://openalex.org/W4391914276","https://openalex.org/W4399559108","https://openalex.org/W4399880211","https://openalex.org/W4400120992","https://openalex.org/W4400496074","https://openalex.org/W4400953042","https://openalex.org/W4401562809","https://openalex.org/W4403865906","https://openalex.org/W4404527653","https://openalex.org/W4405471377","https://openalex.org/W4406829077","https://openalex.org/W4407902003","https://openalex.org/W4409553409","https://openalex.org/W4410050200"],"related_works":[],"abstract_inverted_index":{"The":[0,183,203,239],"challenge":[1,28,38],"of":[2,10,17,50,186,200,282],"efficiently":[3],"predicting":[4],"the":[5,14,23,47,135,196,279,283],"sensible":[6,18],"heat":[7,19],"storage":[8,20,65,227],"potential":[9,60,181],"natural":[11,201,222],"materials,":[12,24],"including":[13,73],"accurate":[15],"prediction":[16],"capacity":[21],"in":[22,154],"presents":[25],"a":[26,40,211],"critical":[27],"for":[29,215,235,259],"sustainable":[30,225],"thermal":[31,48,64,198,216,226],"energy":[32,243],"systems.":[33],"This":[34],"study":[35],"addresses":[36],"this":[37],"through":[39,254],"comprehensive":[41],"machine":[42],"learning(ML)":[43],"approach":[44],"to":[45,61,194,277],"model":[46,233],"behavior":[49,199],"Dawakin":[51],"Tofa":[52],"clay,":[53],"an":[54],"abundant":[55],"and":[56,89,108,114,126,229,274],"eco-friendly":[57],"material":[58,236,270],"with":[59,144,257],"replace":[62],"synthetic":[63,263],"media.":[66],"We":[67],"systematically":[68],"evaluate":[69],"twelve":[70],"predictive":[71,139],"models,":[72,188],"four":[74,95],"linear":[75],"approaches":[76],"(Interactive":[77],"Linear":[78,82,86],"Regression":[79,83,87],"(ILR),":[80],"Stepwise":[81],"(SWLR),":[84],"Robust":[85],"(RLR),":[88],"Kernel":[90],"Support":[91],"Vector":[92],"Machine":[93],"(KSVM),":[94],"nonlinear":[96,187],"methods":[97],"(G-Matern":[98],"5/2":[99],"(GM5/2),":[100],"Trilayered":[101],"Neural":[102,111,127],"Network":[103,128],"(TNN),":[104],"Boosted":[105],"Trees":[106],"(BoT),":[107],"Bagged":[109],"Tree":[110],"Networks":[112],"(BTNN),":[113],"three":[115,207],"ensemble":[116],"techniques":[117],"(Simple":[118],"Average":[119,123],"Ensemble":[120,124,129],"(SAE),":[121],"Weighted":[122],"(WAE),":[125],"(NNE).":[130],"Experimental":[131],"validation":[132],"reveals":[133,159],"that":[134,160],"NNE":[136],"demonstrates":[137],"exceptional":[138],"performance,":[140],"achieving":[141],"near-perfect":[142],"accuracy":[143],"minimal":[145],"error":[146],"metrics":[147],"(MSE":[148],"=":[149,152,169,178],"0.0001696,":[150],"RMSE":[151,168],"0.01302":[153],"testing":[155],"phase).":[156],"Comparative":[157],"analysis":[158,276],"SAE":[161],"offers":[162],"moderate":[163],"yet":[164],"stable":[165],"generalization":[166],"(test":[167],"0.0187),":[170],"whereas":[171],"WAE":[172],"exhibits":[173],"higher":[174],"variance":[175],"(RMSE":[176],"train-test":[177],"0.0098),":[179],"suggesting":[180],"overfitting.":[182],"superior":[184],"performance":[185],"particularly":[189],"NNE,":[190],"underscores":[191],"their":[192],"ability":[193],"capture":[195],"complex":[197],"materials.":[202],"present":[204],"work":[205],"makes":[206],"key":[208],"contributions,":[209],"namely,":[210],"robust":[212],"ML":[213],"framework":[214],"property":[217],"prediction,":[218],"quantitative":[219],"evidence":[220],"supporting":[221],"clay":[223],"as":[224],"media,":[228],"methodological":[230],"insights":[231],"into":[232],"selection":[234],"science":[237],"applications.":[238],"findings":[240],"advance":[241],"renewable":[242],"research":[244,266],"by":[245],"demonstrating":[246],"how":[247],"locally":[248],"available":[249],"materials":[250],"can":[251],"be":[252],"optimized":[253],"computational":[255],"modeling,":[256],"implications":[258],"reducing":[260],"reliance":[261],"on":[262],"alternatives.":[264],"Future":[265],"directions":[267],"should":[268],"investigate":[269],"modifications,":[271],"multi-scale":[272],"validation,":[273],"techno-economic":[275],"facilitate":[278],"practical":[280],"implementation":[281],"technologies.":[284]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-11-28T00:00:00"}
