{"id":"W2945414860","doi":"10.1016/j.ijhydene.2019.03.127","title":"Thermal management of metal hydride hydrogen storage reservoir using phase change materials","year":2019,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"Hydrogen Storage and Materials","field":"Materials Science","cited_by":128,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Fonds de recherche du Québec – Nature et technologies; China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Hydride; Hydrogen storage; Thermal conductivity; Materials science; Hydrogen; Phase-change material; Thermal energy storage; Metal foam; Aluminium; Latent heat; Metal; Cryo-adsorption; Enthalpy of fusion; Thermodynamics; Phase change; Metallurgy; Composite material; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004667253,0.0001080418,0.0001599157,0.00008138201,0.0001651642,0.0002231266,0.000271604,0.0001381954,0.001207481],"category_scores_gemma":[0.0000698777,0.0000854426,0.0001018789,0.00007864805,0.0001156385,0.0003321695,0.000136438,0.00017403,0.0001637913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001306894,"about_ca_system_score_gemma":0.0001251758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001488637,"about_ca_topic_score_gemma":0.0003804892,"domain_scores_codex":[0.9999751,0.000002215241,0.000001178864,0.000005804731,0.000007557047,0.00000818027],"domain_scores_gemma":[0.9999763,0.000005233742,0.00000550066,0.000003657101,0.000005854284,0.000003529923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002848161,0.00005213602,0.0004054987,0.0001499932,0.000006536925,0.0001217819,0.00004076187,0.001663989,0.9851218,0.000786791,0.0003775349,0.01098832],"study_design_scores_gemma":[0.00001256004,0.0002288206,0.0004701506,0.000003487647,0.000007076924,0.00006270091,0.00002836712,0.01339412,0.9840731,0.00009027562,0.00162366,0.000005739025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915558,0.0005756555,0.005200225,0.00008752216,0.00003933558,0.00002218244,0.00006541244,0.0001502422,0.002303533],"genre_scores_gemma":[0.9974425,0.000103144,0.001407599,0.00001182487,0.000006733265,0.000007970871,0.00003124334,0.000008773972,0.0009801333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001207481,"threshold_uncertainty_score":0.004039407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03642118259401807,"score_gpt":0.30446081933574,"score_spread":0.268039636741722,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}