{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000476422,0.0001714219,0.0001327802,0.000130073,0.00009441561,0.000259135,0.0002065623,0.0001649036,0.0008970684],"category_scores_gemma":[0.00008946154,0.0001476138,0.0001548124,0.00009687954,0.0001142051,0.0002028827,0.000249052,0.0002011599,0.0003316101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000205591,"about_ca_system_score_gemma":0.0001091266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002992449,"about_ca_topic_score_gemma":0.0006474297,"domain_scores_codex":[0.9999502,0.000005359393,0.000004297154,0.00001208474,0.0000151822,0.00001293608],"domain_scores_gemma":[0.9999624,0.00000388046,0.000008988689,0.000005985343,0.000006235256,0.00001249236],"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":[0.0001091215,0.00004566175,0.0003320562,0.0001064774,0.00001942893,0.0000857678,0.00003096543,0.002829171,0.9883496,0.0008237953,0.0002883238,0.006979756],"study_design_scores_gemma":[0.00004068884,0.0004799709,0.002263961,0.000009851829,0.00003040887,0.0001007488,0.00005930596,0.03168031,0.9598294,0.0002056152,0.005266194,0.00003344806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859458,0.0006168598,0.009215611,0.000071244,0.00003399041,0.00003294429,0.000214785,0.000394138,0.00347464],"genre_scores_gemma":[0.9946194,0.0001625001,0.004157484,0.00001746393,0.000003532266,0.00002203123,0.0001259886,0.00001487015,0.0008767164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008970684,"threshold_uncertainty_score":0.003001034,"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."}}