{"id":"W4387037376","doi":"10.1016/j.carbon.2023.118472","title":"Boron carbon nitride nanosheets via induction plasma: Insights on synthesis, characterization, and control of band gap","year":2023,"lang":"en","type":"article","venue":"Carbon","topic":"Graphene research and applications","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Department of Chemical Engineering, Monash University; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Band gap; Raman spectroscopy; Nanosheet; Analytical Chemistry (journal); Spectroscopy; Scanning electron microscope; Ammonia borane; Boron nitride; Carbon fibers; Carbon nitride; Fourier transform infrared spectroscopy; Boron; Chemical engineering; Nanotechnology; Chemistry; Composite material; Optoelectronics; Hydrogen storage; Optics; Composite number; Photocatalysis","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":[0.0001301075,0.0001949644,0.0001527743,0.0001375994,0.000185963,0.0002922372,0.000199492,0.0002908103,0.000800172],"category_scores_gemma":[0.0001534002,0.0001207181,0.00009512519,0.0001154526,0.0002217005,0.0003117717,0.000193189,0.0003502928,0.0002109285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003615535,"about_ca_system_score_gemma":0.0001553037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004779734,"about_ca_topic_score_gemma":0.00110674,"domain_scores_codex":[0.9998951,0.000009388571,0.000003600828,0.00002073033,0.00004713715,0.00002416402],"domain_scores_gemma":[0.9999287,0.00002729318,0.00001475559,0.00001041374,0.00001177475,0.000006974374],"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":[0.00006140028,0.00001093017,0.00009118408,0.00004147619,0.000002286738,0.00002021005,0.00001959245,0.0001995988,0.9964294,0.0005146961,0.00007733623,0.002531952],"study_design_scores_gemma":[0.000005004593,0.00003596804,0.0004626384,0.000002771802,0.000001903842,0.0000266672,0.00001359431,0.001322355,0.9970137,0.0001174229,0.0009952009,0.000002774581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782645,0.001298607,0.0106144,0.0002683415,0.00004449003,0.00003317924,0.0002073392,0.0001602219,0.009108918],"genre_scores_gemma":[0.9942343,0.0004937393,0.003220786,0.00003962136,0.000009323496,0.00001796733,0.0001141457,0.00002836119,0.001841656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000800172,"threshold_uncertainty_score":0.002676785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702544675294438,"score_gpt":0.2402114245937418,"score_spread":0.2231859778407974,"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."}}