{"id":"W3186665451","doi":"10.1109/ted.2021.3096178","title":"Exploiting Fringing Fields Created by High-<i>κ</i>Gate Insulators to Enhance the Performance of Ultrascaled 2-D-Material-Based Transistors","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Electron Devices","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science","keywords":"Quantum tunnelling; Leakage (economics); Optoelectronics; Time-dependent gate oxide breakdown; Materials science; Transistor; MOSFET; Gate oxide; Electrical engineering; Logic gate; Electronic engineering; Engineering; Voltage","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":[0.00009749733,0.0002409379,0.000151989,0.0001140341,0.000214172,0.0003695516,0.0003431788,0.0003164553,0.0006840249],"category_scores_gemma":[0.0001954442,0.0001313708,0.000202061,0.0001172737,0.0003024747,0.0003157603,0.0001602821,0.0002465509,0.00009103154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000458496,"about_ca_system_score_gemma":0.000278988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001821447,"about_ca_topic_score_gemma":0.003772503,"domain_scores_codex":[0.9999758,0.000002497562,8.535268e-7,0.000003367986,0.000009369704,0.000008088351],"domain_scores_gemma":[0.9999373,0.00002865685,0.00001612778,0.000007028686,0.000005182302,0.000005855686],"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":[0.0001307122,0.0002014894,0.004415482,0.0003111722,0.00006904041,0.0005428554,0.0001716423,0.2894998,0.6829461,0.01420774,0.0006444265,0.006859489],"study_design_scores_gemma":[0.00005717213,0.0001938187,0.003371445,0.00001954295,0.00002810293,0.000131539,0.00006856384,0.8539317,0.1368701,0.002971363,0.002323604,0.00003311246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769035,0.0003528033,0.01871371,0.00009866914,0.00004060782,0.00001794388,0.00009752213,0.0001145368,0.0036607],"genre_scores_gemma":[0.9934691,0.0001943314,0.005936358,0.00001843546,0.00000401481,0.00001066337,0.0000305478,0.00001485693,0.0003217109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001821447,"threshold_uncertainty_score":0.003621697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004644020142653645,"score_gpt":0.2080334739488305,"score_spread":0.2033894538061768,"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."}}