{"id":"W4323306363","doi":"10.1073/pnas.2217703120","title":"Free-standing membrane incorporating single-atom catalysts for ultrafast electroreduction of low-concentration nitrate","year":2023,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"U.S. Department of Energy; Brookhaven National Laboratory; Office of Science; National Science Foundation","keywords":"Selectivity; Catalysis; Chemistry; Membrane; Dissociation (chemistry); Adsorption; Electrochemistry; Inorganic chemistry; Nitrate; Carbon nanotube; Oxide; Hydrogen; Chemical engineering; Materials science; Electrode; Nanotechnology; 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":[0.0001520646,0.0003923987,0.0002490138,0.0002114131,0.0001999153,0.0002628945,0.0005714543,0.0007860478,0.0004364153],"category_scores_gemma":[0.0002347879,0.0001909998,0.0003278774,0.0001695735,0.0002185223,0.0004378433,0.0002777038,0.0003373361,0.0002480236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003893313,"about_ca_system_score_gemma":0.0002219069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006432725,"about_ca_topic_score_gemma":0.001093986,"domain_scores_codex":[0.9998581,0.00001408987,0.00001160204,0.00003167193,0.00005524531,0.00002931981],"domain_scores_gemma":[0.9998928,0.00002403558,0.00003395047,0.00001255267,0.00002175193,0.00001491595],"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":[0.000013424,0.000009935127,0.00007183803,0.00002924444,0.000003479664,0.00002427209,0.000008104068,0.00007759029,0.9988926,0.00005588885,0.00001455195,0.0007989947],"study_design_scores_gemma":[0.000002748855,0.00004539183,0.0004866887,0.000002169556,0.000007144608,0.00004880684,0.000008365983,0.001463559,0.9974217,0.00001768199,0.0004911122,0.000004619941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903655,0.0005198788,0.008256327,0.00007559074,0.00003694138,0.00001868792,0.00007194425,0.00009425137,0.0005608586],"genre_scores_gemma":[0.9870379,0.0005803234,0.01084524,0.00002772933,0.000009622453,0.0000239478,0.0001122902,0.00002175994,0.00134114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007860478,"threshold_uncertainty_score":0.002824843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03741082643902006,"score_gpt":0.2716798987762857,"score_spread":0.2342690723372656,"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."}}