{"id":"W2938899632","doi":"10.1016/j.joule.2019.03.022","title":"Stabilizing Solid Electrolyte-Anode Interface in Li-Metal Batteries by Boron Nitride-Based Nanocomposite Coating","year":2019,"lang":"en","type":"article","venue":"Joule","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":342,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec","funders":"Brookhaven National Laboratory; Air Force Office of Scientific Research; China Scholarship Council; National Natural Science Foundation of China; Research Corporation for Science Advancement; National Science Foundation","keywords":"Boron nitride; Materials science; Electrolyte; Anode; Nanocomposite; Coating; Inert; Chemical engineering; Nitride; Fast ion conductor; Metal; Boron; Energy storage; Nanotechnology; Metallurgy; Electrode; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002285477,0.0002414859,0.0003570131,0.0001025219,0.00003336326,0.00007895719,0.0002046156,0.0000783674,0.0004906013],"category_scores_gemma":[0.00002411231,0.0002591021,0.0000356429,0.0001296063,0.0000232858,0.0003671276,0.00006169156,0.0001989542,0.0001895734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002218772,"about_ca_system_score_gemma":0.00001599961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002031171,"about_ca_topic_score_gemma":0.00001284587,"domain_scores_codex":[0.9985862,0.00005647419,0.0004581106,0.000254928,0.0001768983,0.0004673657],"domain_scores_gemma":[0.9994708,0.00009077554,0.00007948937,0.0002944462,0.0000207367,0.00004370927],"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":[0.0000303411,0.00002762132,0.003776749,0.0001106905,0.0000175715,0.000002145227,0.0001557803,0.0358042,0.9594162,0.000003607837,0.0004156641,0.0002394624],"study_design_scores_gemma":[0.0007306099,0.00009258756,0.000458024,0.000114705,0.000009924654,0.000002382568,0.00005929033,0.008764377,0.9867527,0.00003910448,0.002662228,0.0003140244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908093,0.0003127422,0.007040944,0.00006909228,0.0005833623,0.0003245609,0.00003989396,0.0002229004,0.000597218],"genre_scores_gemma":[0.9979004,0.00000666931,0.001565382,0.0001815881,0.00004927253,0.00003771486,0.00002579588,0.0000755653,0.0001576395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02733657,"threshold_uncertainty_score":0.9999861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006203799377944724,"score_gpt":0.2412534303684601,"score_spread":0.2350496309905154,"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."}}