{"id":"W2902099111","doi":"10.1038/s41560-018-0296-8","title":"Multi-site electrocatalysts for hydrogen evolution in neutral media by destabilization of water molecules","year":2018,"lang":"en","type":"article","venue":"Nature Energy","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":706,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Argonne National Laboratory; Natural Sciences and Engineering Research Council of Canada; Office of Science; Connaught Fund; Canadian Light Source; University of Toronto; U.S. Department of Energy","keywords":"Catalysis; Overpotential; Dissociation (chemistry); Hydride; Electrolyte; Hydrogen; Chemical engineering; Platinum; Water splitting; Hydrogen production; Chemistry; Inorganic chemistry; Materials science; Electrolysis of water; Hydrogen fuel; Nanotechnology; Electrochemistry; Electrode; Electrolysis; Physical chemistry; Organic 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002432581,0.0002679517,0.0003049004,0.0003444167,0.00007899214,0.00001136903,0.0002981318,0.0006115881,0.00002398098],"category_scores_gemma":[0.0001354655,0.0002284834,0.0001313868,0.0005058144,0.0001170653,0.0002394498,0.00005651057,0.0002203605,0.00001012376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003474218,"about_ca_system_score_gemma":0.00006813739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001651264,"about_ca_topic_score_gemma":0.02440925,"domain_scores_codex":[0.9981162,0.00008913675,0.0004023875,0.0005026354,0.0003029114,0.0005867234],"domain_scores_gemma":[0.9989873,0.00007410243,0.0001219894,0.0003687106,0.0003598199,0.0000881082],"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":[0.0001870916,0.000111643,0.000305211,0.00001984541,0.00003215161,0.000001570474,0.0002199813,0.0008342598,0.9825513,0.014743,0.0003999175,0.000593987],"study_design_scores_gemma":[0.001226389,0.0001842467,0.0002023575,0.00002191101,0.00003708788,0.000005355204,0.00001578709,0.00792938,0.9808788,0.001718281,0.007517352,0.0002629954],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852092,0.001249368,0.01250694,0.0001063825,0.000289963,0.0001360693,0.00001067071,0.0001074003,0.0003840008],"genre_scores_gemma":[0.996694,0.00003158434,0.001056115,0.0001504185,0.0002046567,0.00005044632,0.001530192,0.00006639869,0.0002161425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02275798,"threshold_uncertainty_score":0.9933928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004333552166901926,"score_gpt":0.2188473210672039,"score_spread":0.2145137689003019,"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."}}