{"id":"W4323923748","doi":"10.1021/acsmaterialslett.2c01026","title":"2D-Material-Based Volatile and Nonvolatile Memristive Devices for Neuromorphic Computing","year":2023,"lang":"en","type":"article","venue":"ACS Materials Letters","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Nanjing University of Posts and Telecommunications; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Neuromorphic engineering; Von Neumann architecture; Computer science; Unconventional computing; Bottleneck; Reservoir computing; Memristor; Artificial neural network; Computer architecture; Artificial intelligence; Distributed computing; Electronic engineering; Embedded system; Engineering; Recurrent neural network","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":[0.0001610788,0.0004004215,0.0003618691,0.0005827884,0.0002472027,0.0007932709,0.0006353841,0.001143688,0.002818274],"category_scores_gemma":[0.0002878587,0.0003231816,0.0003826187,0.0005271856,0.0003432468,0.001259108,0.0005064831,0.000917185,0.0008896239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003958115,"about_ca_system_score_gemma":0.000245515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001315847,"about_ca_topic_score_gemma":0.0003528437,"domain_scores_codex":[0.9998831,0.00001365366,0.00001039818,0.00003097894,0.00004843887,0.00001348101],"domain_scores_gemma":[0.999918,0.00003364579,0.00001745889,0.000009771493,0.00001471521,0.000006474769],"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":[0.0001060797,0.0001428298,0.0008727766,0.007234748,0.00008510092,0.001107853,0.0001945367,0.005665609,0.6150525,0.1657539,0.01286828,0.1909158],"study_design_scores_gemma":[0.00004129192,0.0004145553,0.001411886,0.0005341733,0.0001054711,0.002890037,0.0001404961,0.04434631,0.4768781,0.02760161,0.445511,0.0001251377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2116303,0.4388686,0.2126554,0.00430683,0.005320052,0.0003017502,0.001714418,0.00145203,0.1237506],"genre_scores_gemma":[0.691798,0.1664482,0.1138104,0.001480327,0.0007831897,0.0005351939,0.000873803,0.0001635354,0.02410728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002818274,"threshold_uncertainty_score":0.009428084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02406638366099272,"score_gpt":0.2373675625918239,"score_spread":0.2133011789308311,"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."}}