{"id":"W4391152256","doi":"10.1016/j.nanoen.2024.109332","title":"Engineered MXene quantum dots for micro-supercapacitors with excellent capacitive behaviors","year":2024,"lang":"en","type":"article","venue":"Nano Energy","topic":"MXene and MAX Phase Materials","field":"Materials Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Agency for Science, Technology and Research; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Supercapacitor; Materials science; Quantum dot; Capacitance; Nanotechnology; Heteroatom; Capacitive sensing; Energy storage; Electrolyte; Electrochemistry; Optoelectronics; Chemistry; Electrode; Power (physics); Electrical engineering","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":[0.00006392508,0.0001919991,0.00009851384,0.000101342,0.00012001,0.0002715517,0.0001982673,0.000260562,0.001258534],"category_scores_gemma":[0.0001053995,0.0001079227,0.00006482849,0.0001198928,0.0001083364,0.00043253,0.0001931772,0.0002337662,0.0002963055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000283505,"about_ca_system_score_gemma":0.0000695804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000240934,"about_ca_topic_score_gemma":0.0009664394,"domain_scores_codex":[0.9999614,0.000002520977,0.000002371181,0.00001330075,0.00001340125,0.000007036621],"domain_scores_gemma":[0.9999648,0.000007285593,0.000006816113,0.000004551188,0.000009331523,0.000007217227],"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":[0.00002524418,0.00001631821,0.00009432804,0.00003209224,0.000003799506,0.00004291592,0.00002083659,0.0002675901,0.9956124,0.001705766,0.0002684684,0.001910248],"study_design_scores_gemma":[0.000005522021,0.00004170731,0.000308407,0.000003040025,0.000002649469,0.00003194537,0.00001329744,0.003987821,0.9930615,0.0002301627,0.002308878,0.000005059155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773137,0.0008659307,0.01293934,0.0002399135,0.00007653966,0.00003232605,0.0003651057,0.0002301301,0.007936983],"genre_scores_gemma":[0.992273,0.0002186748,0.004710952,0.00002546317,0.000004620457,0.00001985206,0.00008748296,0.00002102541,0.002638739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001258534,"threshold_uncertainty_score":0.004210174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297481810118079,"score_gpt":0.2370423048494341,"score_spread":0.2240674867482533,"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."}}