{"id":"W4410202546","doi":"10.1016/j.nanoen.2025.111118","title":"A thermally regenerative battery with sulfur electrodes realizing efficient thermoelectric conversion with low-grade waste heat","year":2025,"lang":"en","type":"article","venue":"Nano Energy","topic":"Advanced Thermoelectric Materials and Devices","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Chongqing; China Scholarship Council; National Natural Science Foundation of China","keywords":"Materials science; Thermoelectric effect; Battery (electricity); Electrode; Sulfur; Waste heat; Waste heat recovery unit; Thermoelectric materials; Energy storage; Nanotechnology; Waste management; Metallurgy; Thermal conductivity; Composite material; Mechanical engineering; Heat exchanger","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002691328,0.0003727757,0.0004435322,0.0002278699,0.000485462,0.0001317442,0.0003870026,0.00008402174,0.0001117182],"category_scores_gemma":[0.000009401568,0.000246853,0.0000538743,0.0008549365,0.0001141979,0.0001283569,0.0001002517,0.0001142819,0.000009009148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001929107,"about_ca_system_score_gemma":0.000298857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004855511,"about_ca_topic_score_gemma":0.00009736993,"domain_scores_codex":[0.9975595,0.0002973496,0.0003237604,0.0006824865,0.0004497058,0.0006871434],"domain_scores_gemma":[0.9990582,0.0001182681,0.0001754147,0.0004075084,0.0001547392,0.00008586054],"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":[0.0008961373,0.000112826,0.00002795588,0.00004259388,0.00003945455,0.00003252983,0.0001143726,0.02220629,0.9689493,0.0068994,0.0001566494,0.0005225071],"study_design_scores_gemma":[0.001031099,0.0006058553,0.00003743099,0.0001378317,0.0000446101,0.00004026561,0.0001540059,0.002133818,0.9945034,0.0001534365,0.0008077362,0.0003504963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734248,0.001090521,0.02140448,0.0002697564,0.0001696885,0.0002287825,0.00001329418,0.0001687715,0.003229912],"genre_scores_gemma":[0.9969187,0.00005888326,0.0005684478,0.0008573796,0.0001082773,0.0001251228,0.00001880611,0.00004516962,0.001299211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02555414,"threshold_uncertainty_score":0.9999984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004230855336521092,"score_gpt":0.2058474079022858,"score_spread":0.2016165525657647,"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."}}