{"id":"W4394827372","doi":"10.1039/d4mh00200h","title":"Advancing lithium–sulfur battery efficiency: utilizing a 2D/2D g-C<sub>3</sub>N<sub>4</sub>@MXene heterostructure to enhance sulfur evolution reactions and regulate polysulfides under lean electrolyte conditions","year":2024,"lang":"en","type":"article","venue":"Materials Horizons","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Mitacs; Ford Motor Company","keywords":"Heterojunction; Sulfur; Separator (oil production); Electrolyte; Materials science; Schematic; Electrode; Nanocomposite; Battery (electricity); Nanotechnology; Chemical engineering; Optoelectronics; Chemistry; Electrical engineering; Metallurgy; Engineering; Physical chemistry; Physics","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":[0.0003454155,0.0007055197,0.0007043849,0.0005887205,0.0005116397,0.0005469517,0.0002853306,0.0003674868,0.00002775635],"category_scores_gemma":[0.0001070125,0.0007154656,0.0001183148,0.0007023753,0.0001964502,0.0007667696,0.0002166405,0.0003929087,0.00008591176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004397688,"about_ca_system_score_gemma":0.00006761587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002219174,"about_ca_topic_score_gemma":0.0000832241,"domain_scores_codex":[0.9966733,0.00008477354,0.0008683716,0.0009405057,0.0002955496,0.001137535],"domain_scores_gemma":[0.9987505,0.0001619525,0.0001335796,0.0006664542,0.00008197124,0.0002055282],"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":[0.0000359113,0.00002122878,0.000005600916,0.0003373652,0.00009169018,0.00003213158,0.0001413302,0.005331703,0.9895965,0.001706574,0.0004102059,0.002289738],"study_design_scores_gemma":[0.0001549977,0.0001991043,0.001012303,0.000597421,0.0001022295,0.0001954311,0.0002129541,0.0002957355,0.9879054,0.008047411,0.0005209878,0.0007560128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600531,0.0008320829,0.03194181,0.0005755703,0.002592721,0.0006271938,0.0005630846,0.002754852,0.00005962556],"genre_scores_gemma":[0.9974985,0.0005850525,0.0007802856,0.00009601293,0.0004560614,0.0002361213,0.0001283008,0.0001980848,0.00002160825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03744541,"threshold_uncertainty_score":0.9995297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005312874038916809,"score_gpt":0.2263311776967437,"score_spread":0.2210183036578268,"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."}}