{"id":"W4321003453","doi":"10.1021/acsami.2c17476","title":"Salt-Induced Doping and Templating of Laser-Induced Graphene Supercapacitors","year":2023,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Government of Ontario; Ontario Centres of Excellence","keywords":"Materials science; Supercapacitor; Graphene; Polyimide; Carbonization; Nanotechnology; Capacitance; Chemical engineering; Carbon fibers; Kapton; Doping; Conductivity; Electrode; Optoelectronics; Composite material; Composite number; Layer (electronics); Scanning electron microscope","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":[0.00009285159,0.0002852945,0.0002135414,0.00026743,0.0001692822,0.0003273214,0.0003954004,0.0002531214,0.0006987196],"category_scores_gemma":[0.0003410402,0.0001988531,0.0001825702,0.0002244564,0.0002587457,0.0003868339,0.0003389854,0.0003740589,0.0002633611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002935525,"about_ca_system_score_gemma":0.0001432336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004781676,"about_ca_topic_score_gemma":0.001166126,"domain_scores_codex":[0.9998235,0.00001356157,0.00001772317,0.0000321832,0.00008270476,0.000030274],"domain_scores_gemma":[0.9998627,0.00002871497,0.00002959091,0.00002364847,0.00003332803,0.00002201307],"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":[0.00002182544,0.000008574519,0.0001243662,0.00002840299,0.000002958243,0.00004659687,0.00002882447,0.0002432287,0.9977242,0.0001245339,0.00004307953,0.001603375],"study_design_scores_gemma":[0.000001137478,0.000015155,0.0001906041,8.755317e-7,0.000001340395,0.00001572716,0.000005388983,0.001152111,0.9982967,0.00001816061,0.0003003403,0.000002403726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922047,0.0003608642,0.00485164,0.00008254158,0.0000375163,0.0000319674,0.0001639126,0.0001883803,0.002078585],"genre_scores_gemma":[0.9946451,0.0002462918,0.003919446,0.00002336781,0.000006446168,0.0000216977,0.00008615162,0.00003091309,0.001020691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006987196,"threshold_uncertainty_score":0.002337456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03340992906821325,"score_gpt":0.2618578748637362,"score_spread":0.2284479457955229,"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."}}