{"id":"W4321371918","doi":"10.3390/nano13040778","title":"Synthesis of 3D Porous Cu Nanostructures on Ag Thin Film Using Dynamic Hydrogen Bubble Template for Electrochemical Conversion of CO2 to Ethanol","year":2023,"lang":"en","type":"article","venue":"Nanomaterials","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tafel equation; Electrocatalyst; Materials science; Nanostructure; Catalysis; Electrochemistry; Chemical engineering; Nanomaterials; Faraday efficiency; Nanotechnology; Electrolyte; Porosity; Electrode; Chemistry; Organic 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":[0.00008570895,0.0002936594,0.0002358813,0.0002400132,0.0001644147,0.0002558966,0.0004439413,0.0004478812,0.0004640672],"category_scores_gemma":[0.0001904338,0.0002759607,0.0002435995,0.0001921593,0.0001554502,0.0002415741,0.0001999671,0.0003156321,0.0002254858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003343656,"about_ca_system_score_gemma":0.0002033985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001584554,"about_ca_topic_score_gemma":0.003667794,"domain_scores_codex":[0.9998941,0.000006179175,0.000009020629,0.000032418,0.0000336971,0.00002445954],"domain_scores_gemma":[0.9999359,0.00001111212,0.00001475837,0.000009779489,0.0000179954,0.00001045579],"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":[0.00002114702,0.00001494889,0.00006612104,0.00004582557,0.000004952121,0.000102004,0.00001862614,0.0002786594,0.9965556,0.0001193938,0.00007673402,0.00269609],"study_design_scores_gemma":[0.000003989995,0.00005532425,0.0004288375,0.000002257942,0.000006471746,0.0000686087,0.000009878921,0.003462914,0.9951939,0.0000229502,0.0007390586,0.00000559389],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758897,0.00144334,0.01714306,0.000125371,0.000107625,0.00005987385,0.0003264314,0.0006422469,0.004262418],"genre_scores_gemma":[0.9879982,0.0004121494,0.01029914,0.0000243922,0.000009619386,0.00003434403,0.0001363351,0.00002972285,0.001056017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001584554,"threshold_uncertainty_score":0.003150642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438058828136913,"score_gpt":0.2720006189070731,"score_spread":0.2576200306257039,"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."}}