{"id":"W4392013985","doi":"10.1021/acs.jpcc.3c06417","title":"Unraveling the Enhanced N<sub>2</sub> Activity on CuNi Alloy Catalysts for Ammonia Production: Experiments, DFT, and Statistical Analysis","year":2024,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Japan Society for the Promotion of Science; Canada Research Chairs; Ministry of Education, Culture, Sports, Science and Technology; Canada Foundation for Innovation; Compute Canada","keywords":"Alloy; Ammonia production; Ammonia; Catalysis; Production (economics); Materials science; Metallurgy; Chemical engineering; Chemistry; Organic chemistry; Engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003233984,0.0001709468,0.0002864838,0.00002775062,0.00012831,0.00004867097,0.0001631601,0.00005048754,0.0000056088],"category_scores_gemma":[0.0001662601,0.00009707068,0.0002192738,0.0002394337,0.0001075814,0.00009210606,0.00003336158,0.0003867825,0.000002978883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008929668,"about_ca_system_score_gemma":0.00003537547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004604057,"about_ca_topic_score_gemma":5.361455e-7,"domain_scores_codex":[0.999062,0.00003748574,0.0002318061,0.000190062,0.0002921157,0.0001865515],"domain_scores_gemma":[0.9989785,0.0005274148,0.0001211841,0.0002110482,0.00007696783,0.0000848601],"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":[0.0001698012,0.00009040169,0.000001005657,0.00007183595,0.0006975075,0.00000188406,0.0003510068,0.001991146,0.9910815,0.00008753152,0.0001719655,0.005284369],"study_design_scores_gemma":[0.0001050034,0.00004164423,0.00003707758,0.00005890353,0.0008747699,0.00002273904,0.0001398028,0.01521152,0.9831559,0.0001424669,0.0001001052,0.0001100411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917347,0.0002955272,0.007173612,0.0005538298,0.00007914996,0.00008918848,0.00001404801,0.00002316832,0.00003679754],"genre_scores_gemma":[0.9985843,0.00003962417,0.0001249949,0.000007587562,0.001152304,0.00001284762,0.000004165103,0.00002186613,0.00005234624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01322037,"threshold_uncertainty_score":0.3958427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011823666756628,"score_gpt":0.2642363586125731,"score_spread":0.2524126918559451,"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."}}