{"id":"W4404485594","doi":"10.3390/engproc2024076083","title":"Valorization of Methane for Ethylene Production Through Oxidative Coupling: An Application of Density Functional Theory and Data Analytics in Catalyst Design for Improved Methane Conversion","year":2024,"lang":"en","type":"article","venue":"","topic":"Catalysis and Oxidation Reactions","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Oxidative coupling of methane; Methane; Catalysis; Ethylene; Density functional theory; Coupling (piping); Analytics; Production (economics); Environmental science; Oxidative phosphorylation; Chemistry; Chemical engineering; Computer science; Materials science; Process engineering; Waste management; Photochemistry; Organic chemistry; Database; Engineering; Computational chemistry; Composite material","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":[0.0004085177,0.0002516278,0.0002045012,0.0003379698,0.0001604335,0.0003571225,0.000338041,0.000214667,0.0004509165],"category_scores_gemma":[0.0005008169,0.0001429933,0.0003188009,0.0002631334,0.0001682546,0.0002831657,0.0002067274,0.000295395,0.00005441745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000308651,"about_ca_system_score_gemma":0.0004224501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001410557,"about_ca_topic_score_gemma":0.00282573,"domain_scores_codex":[0.9999394,0.00001863903,0.000002580089,0.000006339483,0.00002402558,0.000008916621],"domain_scores_gemma":[0.9999121,0.00005362509,0.00000762469,0.000009513038,0.00001263376,0.000004463666],"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":[0.0002954166,0.0004734109,0.006832876,0.0009492286,0.000182794,0.0002923198,0.0001557635,0.7386012,0.1016784,0.05050272,0.001008775,0.09902705],"study_design_scores_gemma":[0.00001084803,0.00005789832,0.0004001189,0.000008913898,0.00001202725,0.00001266571,0.00002014939,0.9825393,0.01394514,0.002325985,0.0006608567,0.000006096458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8314905,0.001170532,0.1581213,0.0004578752,0.00003528503,0.00008584755,0.0003047914,0.0003125698,0.008021443],"genre_scores_gemma":[0.9671409,0.0004571537,0.03184897,0.00002180149,0.000003567975,0.00003424202,0.0001216516,0.00001468812,0.0003569128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001410557,"threshold_uncertainty_score":0.002804697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06451300696543003,"score_gpt":0.3138901325137206,"score_spread":0.2493771255482906,"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."}}