{"id":"W4392351325","doi":"10.1016/j.commatsci.2024.112914","title":"Study of lithium transport in Li2O component of the solid electrolyte interphase in lithium-ion batteries","year":2024,"lang":"en","type":"article","venue":"Computational Materials Science","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec","keywords":"Monte Carlo method; Kinetic Monte Carlo; Electrolyte; Diffusion; Chemistry; Ion; Density functional theory; Chemical physics; Lithium (medication); Vacancy defect; Materials science; Thermodynamics; Atomic physics; Computational chemistry; Physical chemistry; Physics; Crystallography; Electrode","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":[0.0006830618,0.0001352385,0.0002742854,0.0002799298,0.00003023457,0.00004737636,0.0003968034,0.00002489388,0.00005939409],"category_scores_gemma":[0.00002117381,0.0001094397,0.00001701832,0.0005759487,0.0002289886,0.0003266394,0.00008081745,0.00006658981,0.000004381223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001041395,"about_ca_system_score_gemma":0.0000682516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002412769,"about_ca_topic_score_gemma":0.00001370942,"domain_scores_codex":[0.9983966,0.00006505474,0.0007017505,0.0002381509,0.0003881222,0.000210258],"domain_scores_gemma":[0.999612,0.0000760931,0.00006747686,0.0001731595,0.0000501565,0.00002110455],"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":[0.0000310852,0.0001153615,0.001012906,0.0001756907,0.00000659661,0.000007940803,0.002388909,0.1642884,0.8316421,0.0002526485,0.000008134108,0.00007026787],"study_design_scores_gemma":[0.0004631019,0.000145041,0.09334205,0.0004898951,0.000009058352,0.00001017785,0.0002094301,0.005146328,0.8977146,0.002287059,0.00001967827,0.0001635941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996354,0.00005111037,0.001399347,0.00005222586,0.001615569,0.0003830427,0.00004509955,0.00004075909,0.00005882188],"genre_scores_gemma":[0.9994622,0.000003407518,0.0004177247,0.00002118686,0.00003178999,0.00003474721,0.000006131684,0.00001455762,0.000008250401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.159142,"threshold_uncertainty_score":0.446282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01478176973151975,"score_gpt":0.2808139727538665,"score_spread":0.2660322030223468,"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."}}