{"id":"W2801482969","doi":"10.1016/j.ensm.2018.04.019","title":"One-step nonlinear electrochemical synthesis of TexSy@PANI nanorod materials for Li-TexSy battery","year":2018,"lang":"en","type":"article","venue":"Energy storage materials","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Science Foundation of Zhejiang Province; Vehicle Technologies Office; China National Funds for Distinguished Young Scientists; U.S. Department of Energy; Office of Energy Efficiency and Renewable Energy; Office of Science; National Natural Science Foundation of China","keywords":"Materials science; Polyaniline; Cathode; Nanorod; Electrochemistry; Battery (electricity); Chemical engineering; Current density; Tellurium; Lithium-ion battery; Ion; Nanotechnology; Composite material; Electrode; Polymer; Metallurgy; Physical chemistry; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008363876,0.0002372902,0.0001793112,0.0001023898,0.0001646886,0.0001683918,0.0002494291,0.0002363541,0.002234885],"category_scores_gemma":[0.000118413,0.0001523437,0.0001326194,0.0001437321,0.0000979846,0.0003220961,0.0001883693,0.0003844447,0.0004825265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002448143,"about_ca_system_score_gemma":0.0001743602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002756757,"about_ca_topic_score_gemma":0.001277518,"domain_scores_codex":[0.9999561,0.000003099384,0.000004123188,0.00001228072,0.00001342944,0.00001085793],"domain_scores_gemma":[0.9999694,0.000005751534,0.000007545166,0.000005797749,0.000006892486,0.000004673476],"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":[0.00003207441,0.00001219122,0.00004647658,0.0001428688,0.000004247997,0.00004307425,0.00002994532,0.000164012,0.9951846,0.0004569397,0.000138514,0.003745087],"study_design_scores_gemma":[0.000005629578,0.00006094865,0.0002162827,0.000002672863,0.000002845825,0.00004263541,0.00001180026,0.001004934,0.9969993,0.00004618162,0.001602916,0.000003908281],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764463,0.001326624,0.01107503,0.0001982782,0.00006497421,0.0000728708,0.0004239442,0.0002291955,0.01016294],"genre_scores_gemma":[0.9825975,0.0006123034,0.01185266,0.00004667215,0.000008496769,0.00006159631,0.0002447863,0.00005482032,0.00452106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002234885,"threshold_uncertainty_score":0.007476389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009905871258439817,"score_gpt":0.22414353861735,"score_spread":0.2142376673589101,"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."}}