{"id":"W4412403640","doi":"10.1021/acscatal.5c03710","title":"Atomically Dispersed Ni–Cu Dual Sites: Efficient Electrocatalytic Conversion of 4-Nitrophenol to <i>p</i>-Aminophenol in a Hybrid Acid/Alkali Flow Electrolyzer","year":2025,"lang":"en","type":"article","venue":"ACS Catalysis","topic":"Nanomaterials for catalytic reactions","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"Shaanxi Science and Technology Association; Yulin University; Natural Science Foundation of Fujian Province; Chinese Academy of Sciences; National Natural Science Foundation of China; Yulin Science and Technology Bureau; National Key Research and Development Program of China; Fuzhou Science and Technology Bureau","keywords":"Electrolysis; Alkali metal; Electrocatalyst; Catalysis; Dual (grammatical number); Chemistry; Inorganic chemistry; Materials science; Chemical engineering; Combinatorial chemistry; Electrochemistry; Electrode; Organic chemistry; Physical 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002700347,0.0004859574,0.0009175242,0.0007146103,0.0001321643,0.00007241036,0.0006517367,0.000197542,0.0003158858],"category_scores_gemma":[0.0003533204,0.000500837,0.0003197808,0.001625406,0.0001438154,0.0001504653,0.0003137653,0.000310793,0.0002458765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007599308,"about_ca_system_score_gemma":0.0003278475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004909467,"about_ca_topic_score_gemma":0.00008759322,"domain_scores_codex":[0.996668,0.00004187329,0.001015095,0.0009111842,0.0005331825,0.0008306439],"domain_scores_gemma":[0.9978685,0.0001743734,0.0002663661,0.001303087,0.0001874176,0.0002001953],"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":[0.0003813381,0.0004919552,0.001254996,0.0002479805,0.0003556349,0.00003993803,0.0003220506,0.0003692566,0.9952673,0.00005601332,0.0006462466,0.0005672493],"study_design_scores_gemma":[0.00161814,0.00005967125,0.0003592924,0.0001068201,0.0005116244,0.00002278582,0.0002646062,0.00284312,0.9931978,0.00006530049,0.0005091401,0.0004416904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969032,0.0002331676,0.0005649749,0.0002555914,0.000150585,0.000350434,0.0001713121,0.0001392735,0.001231439],"genre_scores_gemma":[0.9975275,0.00001991474,0.0002693806,0.0001427706,0.00006445784,0.0001342027,0.0008818152,0.00005994816,0.0009000256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002473864,"threshold_uncertainty_score":0.9997443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005251675125261719,"score_gpt":0.2201282428131439,"score_spread":0.2148765676878822,"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."}}