{"id":"W3128248242","doi":"10.1002/advs.202003400","title":"Hierarchical Micro‐Nanoclusters of Bimetallic Layered Hydroxide Polyhedrons as Advanced Sulfur Reservoir for High‐Performance Lithium–Sulfur Batteries","year":2021,"lang":"en","type":"article","venue":"Advanced Science","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":130,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; State Key Laboratory of Reliability and Intelligence of Electrical Equipment; Hebei University of Technology; Hebei University; University of Waterloo; Natural Science Foundation of Hebei Province; Ministry of Education of the People's Republic of China","keywords":"Nanoclusters; Bimetallic strip; Sulfur; Hydroxide; Materials science; Lithium (medication); Lithium–sulfur battery; Lithium hydroxide; Chemical engineering; Nanotechnology; Inorganic chemistry; Chemistry; Metallurgy; Ion; Organic chemistry; Engineering; Electrochemistry; Ion exchange; Metal; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002870539,0.0003799039,0.0005607108,0.0002591131,0.0003156453,0.00008049313,0.0009060185,0.000125007,0.00003982844],"category_scores_gemma":[0.0004327959,0.0003684266,0.00009832348,0.001148713,0.0009717389,0.001281462,0.0003523371,0.0002346082,0.00001771708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001314636,"about_ca_system_score_gemma":0.0001745835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006318353,"about_ca_topic_score_gemma":0.00001384574,"domain_scores_codex":[0.9972604,0.00002426286,0.0006482712,0.0007237826,0.000416097,0.0009271674],"domain_scores_gemma":[0.9983591,0.0002037987,0.0001551835,0.0008989214,0.0002409484,0.0001420449],"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":[0.00007187233,0.00002979653,0.00007843382,0.0002007503,0.00001693584,0.00001270215,0.00009620233,0.03827264,0.9516056,0.001347183,0.00002005054,0.00824789],"study_design_scores_gemma":[0.0007661696,0.0002029622,0.001601979,0.0001667815,0.00001273754,0.00004335796,0.0002180038,0.001087781,0.9882299,0.004551123,0.002675108,0.0004440879],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880638,0.0005872712,0.008521993,0.0005416567,0.0008692417,0.0003889452,0.00009610883,0.0005347329,0.0003962427],"genre_scores_gemma":[0.9259618,0.0004781217,0.07276538,0.000134817,0.00003868655,0.0001326528,0.00002163958,0.00005802741,0.0004089052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06424338,"threshold_uncertainty_score":0.9998768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01015013868066212,"score_gpt":0.2393630426920938,"score_spread":0.2292129040114317,"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."}}