{"id":"W3027405519","doi":"10.1021/acs.chemmater.0c00235","title":"Insights into Multiphase Reactions during Self-Discharge of Li-S Batteries","year":2020,"lang":"en","type":"article","venue":"Chemistry of Materials","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Waterloo Institute for Nanotechnology, University of Waterloo; Science and Engineering Research Board; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Waterloo","keywords":"Self-discharge; Polysulfide; Battery (electricity); Cathode; Anode; Materials science; Solubility; Depth of discharge; Energy storage; Capacity loss; Lithium (medication); Chemical engineering; Nuclear engineering; Chemistry; Thermodynamics; Electrolyte; Electrode; Power (physics); Organic chemistry; Physical chemistry","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":[0.0002054066,0.0004664143,0.0004108342,0.0002583279,0.0002939188,0.0004845792,0.0004789657,0.0005387109,0.001495484],"category_scores_gemma":[0.0003361568,0.0003112828,0.000528392,0.0001836115,0.0003630731,0.0009626009,0.0002948438,0.0004058385,0.0002910339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008263875,"about_ca_system_score_gemma":0.0004693112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002217637,"about_ca_topic_score_gemma":0.001806774,"domain_scores_codex":[0.9999129,0.000008615581,0.000005792017,0.00001802523,0.00003645513,0.00001821146],"domain_scores_gemma":[0.999925,0.00003801521,0.0000128048,0.000007213121,0.00001060139,0.000006347746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002739962,0.0003633827,0.008357225,0.0005050433,0.00005945939,0.0008323138,0.000477908,0.571173,0.3890265,0.01540588,0.0004794676,0.01304599],"study_design_scores_gemma":[0.00003155119,0.0002052827,0.002510435,0.00001502993,0.00001561815,0.0001351358,0.0001189373,0.8856815,0.1059178,0.003199325,0.002142944,0.00002649102],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709932,0.001290738,0.0217424,0.00015684,0.00003342229,0.00008371432,0.0004141924,0.0001511533,0.005134344],"genre_scores_gemma":[0.9956657,0.0008978021,0.00209383,0.00002523181,0.000004296902,0.0000394877,0.0001508829,0.00001898721,0.0011039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002217637,"threshold_uncertainty_score":0.00599587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008911725690854222,"score_gpt":0.2058131259610469,"score_spread":0.1969014002701927,"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."}}