{"id":"W2469197191","doi":"10.1021/acs.nanolett.5b01011","title":"Molecular-Level Engineering of Adhesion in Carbon Nanomaterial Interfaces","year":2015,"lang":"en","type":"article","venue":"Nano Letters","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Army Research Office; Division of Civil, Mechanical and Manufacturing Innovation","keywords":"van der Waals force; Graphene; Intermolecular force; Carbon nanotube; Surface modification; Adhesive; Nanocomposite; Graphite; Materials science; Nanomaterials; Nanotechnology; Adhesion; Carbon fibers; Surface energy; Chemical physics; Density functional theory; Molecular dynamics; Composite number; Nanoscopic scale; Composite material; Molecule; Chemistry; Computational chemistry; Physical chemistry; Organic chemistry; Layer (electronics)","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":[0.00008978904,0.0002529967,0.0002137434,0.0001824108,0.000304104,0.0004175155,0.0004929096,0.0004990225,0.001664274],"category_scores_gemma":[0.0002285319,0.0001709554,0.0001685489,0.0001409726,0.0002745175,0.0003255935,0.0003264131,0.0004578389,0.0003572755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005408062,"about_ca_system_score_gemma":0.0002153305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005353015,"about_ca_topic_score_gemma":0.001113451,"domain_scores_codex":[0.9999062,0.000009234288,0.000003865769,0.00001310156,0.00004256247,0.00002515546],"domain_scores_gemma":[0.999953,0.00001644196,0.000009254753,0.000007635744,0.000007353867,0.000006190741],"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":[0.00006031071,0.0001542265,0.000475972,0.0002807434,0.00003448068,0.0002096526,0.00004469704,0.02956819,0.9355515,0.02605157,0.0004376005,0.007131061],"study_design_scores_gemma":[0.00007461818,0.0003801746,0.00297057,0.00002436543,0.00002916778,0.0001294283,0.0000794699,0.3720369,0.605562,0.0111959,0.007460681,0.00005665706],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9625436,0.0008326898,0.021447,0.0003018418,0.0001019653,0.00005709803,0.0000892647,0.000197033,0.01442955],"genre_scores_gemma":[0.9903033,0.0004042362,0.008023323,0.00004277812,0.000009620483,0.00004241038,0.00005388438,0.00002400633,0.00109646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001664274,"threshold_uncertainty_score":0.005567551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01988252014624577,"score_gpt":0.2315447309132502,"score_spread":0.2116622107670045,"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."}}