{"id":"W4288428512","doi":"10.1002/adma.202201838","title":"Self‐Formation CoO Nanodots Catalyst in Co(TFSI)<sub>2</sub>‐Modified Electrolyte for High Efficient Li‐O<sub>2</sub> Batteries","year":2022,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Overpotential; Electrolyte; Materials science; Catalysis; Cathode; Passivation; Chemical engineering; Cobalt; Inorganic chemistry; Electrode; Nanotechnology; Electrochemistry; Physical chemistry; Organic chemistry; Chemistry; Metallurgy; Layer (electronics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004023837,0.0002428463,0.0001917978,0.0001414699,0.0001007277,0.0002327596,0.0002391388,0.0002477421,0.0005441933],"category_scores_gemma":[0.0001151016,0.000117566,0.0001249223,0.0001024443,0.0001155214,0.0001964277,0.0001467592,0.0001751206,0.00018664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003368504,"about_ca_system_score_gemma":0.0001378217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009026612,"about_ca_topic_score_gemma":0.001692381,"domain_scores_codex":[0.9999554,0.000002110187,0.000003475873,0.00001122028,0.00001813313,0.000009677827],"domain_scores_gemma":[0.9999551,0.000005405643,0.00001179799,0.000003019383,0.00001403941,0.0000106538],"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":[0.00003517052,0.00001006227,0.0001151866,0.00003449717,0.000003758827,0.00003359687,0.000005501306,0.0002044516,0.9981651,0.00005936523,0.00005224254,0.001281087],"study_design_scores_gemma":[0.000005955784,0.00003094224,0.0004815009,0.000001658391,0.000007077601,0.00003868533,0.000006565172,0.002331699,0.9960381,0.00001082742,0.001043648,0.000003332568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910893,0.001062628,0.005913711,0.00006490554,0.00007671306,0.0000201374,0.0001352926,0.0001746953,0.00146258],"genre_scores_gemma":[0.9938214,0.0003706483,0.004259058,0.00002393524,0.000009057594,0.00001384196,0.0001060936,0.00002013137,0.001375901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009026612,"threshold_uncertainty_score":0.002444088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005943713674976748,"score_gpt":0.2017754174475376,"score_spread":0.1958317037725609,"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."}}