{"id":"W3020018237","doi":"10.1002/pssb.202000019","title":"Negative Differential Resistance and Hysteresis in Self‐Assembled Nanoscale Networks with Tunable Molecule‐to‐Nanoparticle Ratios","year":2020,"lang":"en","type":"article","venue":"physica status solidi (b)","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hysteresis; Materials science; Nanoparticle; Quantum tunnelling; Nanotechnology; Nanoscopic scale; Electrode; Planar; Molecular electronics; Molecule; Electronic circuit; Chemical physics; Nanoelectronics; Topology (electrical circuits); Optoelectronics; Condensed matter physics; Computer science; Chemistry; Electrical engineering; Physics","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":[0.0001620416,0.0001983385,0.000141078,0.0001599658,0.00009657783,0.0002554247,0.000271308,0.0002212286,0.000397497],"category_scores_gemma":[0.0005068603,0.0001726239,0.00008748197,0.0001130263,0.0002667153,0.0003683236,0.0001643659,0.0002658569,0.00008924596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002773249,"about_ca_system_score_gemma":0.00006287979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001996246,"about_ca_topic_score_gemma":0.0004480635,"domain_scores_codex":[0.9998635,0.00002455698,0.000006148039,0.00003470571,0.0000481887,0.00002283877],"domain_scores_gemma":[0.9996734,0.0001462611,0.00009283244,0.00002414719,0.00003943957,0.00002397722],"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":[0.00002981315,0.00001651819,0.0001888943,0.00002755166,0.000005504385,0.00003843995,0.00002599571,0.000406541,0.9979583,0.0002292384,0.00001876548,0.001054429],"study_design_scores_gemma":[0.000008563517,0.0001251007,0.001145265,0.000002593054,0.00001044749,0.00005059016,0.0000128996,0.008551153,0.9895867,0.00007733412,0.0004252219,0.000003968923],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970861,0.0002765112,0.001765432,0.00003327208,0.00001171194,0.000005648946,0.00001852936,0.00004186069,0.0007608922],"genre_scores_gemma":[0.9987108,0.0001092047,0.0007850157,0.000009357118,0.000002602822,0.000005662717,0.00001936177,0.000005435643,0.0003526394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000397497,"threshold_uncertainty_score":0.002012134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005171878672279012,"score_gpt":0.1874081195744841,"score_spread":0.1822362409022051,"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."}}