{"id":"W3037943471","doi":"10.1002/adma.202002297","title":"Boosting Neutral Water Oxidation through Surface Oxygen Modulation","year":2020,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Beijing Synchrotron Radiation Facility; Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning; E-Institutes of Shanghai Municipal Education Commission; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China; Ministry of Science and Technology of the People's Republic of China; Canadian Light Source","keywords":"Oxygen evolution; Overpotential; Inorganic chemistry; Electrochemistry; Catalysis; Materials science; Oxide; Electrolyte; Electrolysis; Bulk electrolysis; Electrolysis of water; Adsorption; Photochemistry; Chemistry; Electrode; Physical chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007600167,0.0003281031,0.0001618128,0.0001504423,0.00007929109,0.0002692914,0.000302215,0.0002260547,0.001028985],"category_scores_gemma":[0.0001332312,0.0001218664,0.0001148674,0.00009697641,0.0002305729,0.0003818894,0.0002644349,0.0003037172,0.0002812156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001733259,"about_ca_system_score_gemma":0.00007966093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000337963,"about_ca_topic_score_gemma":0.0007102029,"domain_scores_codex":[0.9999326,0.000004353631,0.000003560875,0.00001944701,0.00002408732,0.00001585957],"domain_scores_gemma":[0.9999527,0.000009089978,0.00001305622,0.000004250213,0.00001362687,0.000007287589],"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":[0.00001666731,0.000005784511,0.00003903803,0.00002410884,0.000001489788,0.00000988991,0.000005737591,0.00005670089,0.9984248,0.00009793271,0.00003914401,0.001278695],"study_design_scores_gemma":[0.000004628423,0.0000450253,0.0001970884,0.000001463314,0.000003217029,0.00001309971,0.000006965136,0.001194816,0.9973184,0.00003386538,0.001179313,0.000002032117],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826486,0.001197473,0.01113955,0.0001432845,0.00007812376,0.00002627719,0.00008704222,0.000330464,0.004349198],"genre_scores_gemma":[0.9960957,0.0002805273,0.002321574,0.00003826369,0.00001171634,0.00000936591,0.00004425546,0.00002056712,0.001177922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001028985,"threshold_uncertainty_score":0.003442287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693136567656708,"score_gpt":0.2351638614961342,"score_spread":0.2182324958195672,"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."}}