{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009737223,0.00009729346,0.000175263,0.0001538847,0.0001578665,0.00001626352,0.0003840233,0.00008434997,0.000002408417],"category_scores_gemma":[0.0006723765,0.00007562742,0.00009928188,0.001142065,0.0003069777,0.0004632627,0.00003965754,0.0001014711,3.803275e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006771016,"about_ca_system_score_gemma":0.00003076484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005828582,"about_ca_topic_score_gemma":9.287206e-8,"domain_scores_codex":[0.9984872,0.000004239211,0.0004414509,0.0002066645,0.0006884169,0.0001720824],"domain_scores_gemma":[0.9989322,0.0001404639,0.0005985976,0.00001081007,0.0002910516,0.00002684388],"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":[0.0000231822,0.00002450775,0.0003197385,0.0001759448,0.0000190111,1.464609e-9,0.0001581527,0.0009973969,0.9741973,0.02378149,0.00007705793,0.0002262234],"study_design_scores_gemma":[0.0001539664,0.00002980262,0.0004561552,0.0001488834,0.00001815716,0.000003680951,0.0003135275,0.0146517,0.974447,0.009697177,0.000006950092,0.00007307485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984652,0.00003889757,0.00004293387,0.000640401,0.0000355109,0.0002071119,0.00003492216,0.00003577951,0.0004991974],"genre_scores_gemma":[0.9983721,0.000007824225,0.00141319,0.000008635688,0.0001322402,0.00001912714,0.000001808028,0.000008178656,0.00003690146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01408431,"threshold_uncertainty_score":0.3083996,"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."}}