{"id":"W4399723978","doi":"10.1615/tfec2024.nmf.049908","title":"COMPUTATIONAL ANALYSIS OF A COMBINED NOVEL PIN-FIN HEAT SINK AND GRAPHENE NANOPLATELETS BASED NANOFLUID FOR COOLING ENHANCEMENT OF IGBT MODULES IN ELECTRIC VEHICLES","year":2024,"lang":"en","type":"article","venue":"","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Calgary","funders":"","keywords":"Nanofluid; Heat sink; Materials science; Fin; Insulated-gate bipolar transistor; Graphene; Thermal management of electronic devices and systems; Exfoliated graphite nano-platelets; Optoelectronics; Composite material; Mechanical engineering; Nanotechnology; Electrical engineering; Nanoparticle; Engineering; Voltage","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001747635,0.0003288685,0.000534225,0.0002919754,0.0005944587,0.0006051449,0.0007482569,0.001063981,0.003084295],"category_scores_gemma":[0.0005251359,0.0003201774,0.0005130072,0.0002523794,0.0004495163,0.0005038088,0.000341554,0.0004599129,0.0001860591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008403359,"about_ca_system_score_gemma":0.001026559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01086131,"about_ca_topic_score_gemma":0.01156031,"domain_scores_codex":[0.9999449,0.000008440747,0.000001270486,0.000009734689,0.00001495829,0.00002070532],"domain_scores_gemma":[0.9998191,0.0001085009,0.00001485275,0.000009911375,0.00003168973,0.00001587971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007929574,0.000059768,0.0006900897,0.00008108418,0.00002039949,0.00009338778,0.00001869103,0.9891827,0.005956055,0.001748228,0.0003718261,0.00169855],"study_design_scores_gemma":[0.00001365462,0.00003189606,0.0001948413,0.000003054726,0.000006180509,0.000005636328,0.00001110032,0.9982633,0.00116481,0.0001345486,0.00016775,0.000003210632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9294631,0.0004977294,0.03877996,0.0005535143,0.0001217998,0.00007643628,0.0004505934,0.0001909667,0.02986597],"genre_scores_gemma":[0.9908152,0.00008237616,0.005706229,0.00004587806,0.000009817978,0.00005456282,0.0001191696,0.00003198349,0.003134732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01086131,"threshold_uncertainty_score":0.02159619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00951970850011219,"score_gpt":0.223102570598873,"score_spread":0.2135828620987608,"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."}}