{"id":"W2784971299","doi":"10.1021/acsami.7b14410","title":"Scalable High-Performance Ultraminiature Graphene Micro-Supercapacitors by a Hybrid Technique Combining Direct Writing and Controllable Microdroplet Transfer","year":2018,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Materials science; Graphene; Supercapacitor; Nanotechnology; Scalability; Optoelectronics; Capacitance; Electrode; Computer science","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":[0.0001293662,0.0004116926,0.0002310308,0.0003038954,0.0001453436,0.0002876436,0.0005643422,0.0003195681,0.0007075135],"category_scores_gemma":[0.0001550064,0.0001873005,0.0002076398,0.0002848341,0.0002435693,0.0004170664,0.0003348511,0.0004581072,0.0002496292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002405064,"about_ca_system_score_gemma":0.0001626933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000339013,"about_ca_topic_score_gemma":0.001213668,"domain_scores_codex":[0.9998115,0.00001025244,0.00001286297,0.00004542809,0.0001028035,0.00001718762],"domain_scores_gemma":[0.9998796,0.00003430857,0.00002948155,0.00002613665,0.0000184012,0.00001217209],"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":[0.00000588121,0.000007548952,0.00005287156,0.00003389251,0.000003234652,0.00003143843,0.00001354889,0.0001586144,0.9943027,0.0001959423,0.00007863615,0.005115684],"study_design_scores_gemma":[0.000003000246,0.00002786946,0.0002959456,0.000001610044,0.000004210412,0.00006905096,0.000006167353,0.002810755,0.99485,0.00006575411,0.001859374,0.000006175875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8161954,0.003570617,0.169394,0.0004452269,0.0001970396,0.0001807326,0.0006930617,0.001713157,0.007610846],"genre_scores_gemma":[0.8995745,0.001465375,0.09540293,0.00007111124,0.00006358074,0.0001222055,0.0002892866,0.00006716932,0.002943765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007075135,"threshold_uncertainty_score":0.002366841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006108170436019961,"score_gpt":0.2008876296917007,"score_spread":0.1947794592556807,"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."}}