{"id":"W3087137869","doi":"10.1021/acs.nanolett.0c03340","title":"Bismuth Oxyhydroxide-Pt Inverse Interface for Enhanced Methanol Electrooxidation Performance","year":2020,"lang":"en","type":"article","venue":"Nano Letters","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Collaborative Innovation Center of Suzhou Nano Science and Technology; Natural Science Foundation of Jiangsu Province; Priority Academic Program Development of Jiangsu Higher Education Institutions; China Postdoctoral Science Foundation; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Methanol; X-ray photoelectron spectroscopy; Bismuth; Adsorption; Electrochemistry; Methanol fuel; X-ray absorption spectroscopy; Catalysis; Chemical engineering; Chemistry; Redox; Inorganic chemistry; Materials science; Absorption spectroscopy; Physical chemistry; Electrode; Organic chemistry","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":[0.00004769902,0.0001571489,0.0001455054,0.0001003807,0.00008948772,0.0001534718,0.0002471919,0.0002139655,0.000876547],"category_scores_gemma":[0.0000910324,0.0001069072,0.0001096628,0.00007813807,0.00009987039,0.000195063,0.0001663724,0.0002434549,0.0001778067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001643916,"about_ca_system_score_gemma":0.00009495392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002836802,"about_ca_topic_score_gemma":0.0005623705,"domain_scores_codex":[0.9999692,0.000002229691,0.000001941288,0.000006041354,0.00001455917,0.000006055568],"domain_scores_gemma":[0.9999877,0.000002862078,0.000002700844,0.000001409791,0.000003346034,0.000001924754],"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":[0.00004064927,0.00001489722,0.0002324114,0.00006426005,0.000005679684,0.00004996714,0.00001354885,0.0006302659,0.9952689,0.0007892683,0.00009611268,0.002793974],"study_design_scores_gemma":[0.00001101609,0.00007638112,0.0009220183,0.000003097722,0.000008360564,0.00008616243,0.00001946672,0.01304885,0.9844341,0.0001601758,0.00122631,0.000004117901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897741,0.0004135732,0.007523386,0.00008603266,0.00002499533,0.00001181255,0.00009683611,0.0001547992,0.001914487],"genre_scores_gemma":[0.9959936,0.0001518723,0.003339504,0.00001350027,0.000002265979,0.000007687098,0.00005466626,0.00001082208,0.000426031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000876547,"threshold_uncertainty_score":0.00293231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272100312920531,"score_gpt":0.2246197432642086,"score_spread":0.2118987401350032,"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."}}