{"id":"W4302424500","doi":"10.1038/s41467-022-33049-7","title":"Solar reduction of carbon dioxide on copper-tin electrocatalysts with energy conversion efficiency near 20%","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Argonne National Laboratory; Office of Science; Gebert Rüf Stiftung; Xi’an Jiaotong University; École Polytechnique Fédérale de Lausanne; Canadian Light Source; U.S. Department of Energy; European Commission; Xi'an Jiaotong University","keywords":"Tin; Copper; Carbon monoxide; Materials science; Tin oxide; Inorganic chemistry; Electrochemical reduction of carbon dioxide; Catalysis; Copper oxide; Oxide; Carbon fibers; Faraday efficiency; Monoxide; Chemical engineering; Chemistry; Electrode; Metallurgy; Electrochemistry; Composite material; Organic 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":[0.0001402916,0.000380809,0.0002833472,0.0003933532,0.0002201433,0.0003217217,0.0004355803,0.0003221621,0.0008360338],"category_scores_gemma":[0.0002252247,0.0001730214,0.0001780313,0.0004670508,0.0001694379,0.0002332208,0.0002423791,0.0003164155,0.000254907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373853,"about_ca_system_score_gemma":0.0002175743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001902957,"about_ca_topic_score_gemma":0.006271637,"domain_scores_codex":[0.999785,0.00001185185,0.00001184426,0.00004960937,0.00009843879,0.00004332201],"domain_scores_gemma":[0.9999518,0.000009447189,0.000007620398,0.000007071401,0.0000167476,0.000007336494],"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":[0.00003430813,0.00002162879,0.0001587322,0.00006240331,0.000007284281,0.00006640018,0.00001080614,0.0001238522,0.9950953,0.0001248349,0.0001908293,0.004103695],"study_design_scores_gemma":[0.000003228723,0.0000470381,0.0006989683,0.000002327133,0.00000625452,0.00004293537,0.000006589076,0.001260542,0.9967241,0.00001283535,0.001193192,0.000002068366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901613,0.0009153263,0.002479123,0.00006868366,0.00008014746,0.00003111072,0.000226914,0.0001583189,0.005879132],"genre_scores_gemma":[0.9912429,0.0006698444,0.003783779,0.00002890097,0.00001255392,0.00001718672,0.0003498589,0.00003781628,0.003857114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001902957,"threshold_uncertainty_score":0.003783703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007851628713283666,"score_gpt":0.2409323301931163,"score_spread":0.2330807014798326,"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."}}