{"id":"W3035152845","doi":"10.1016/j.addma.2020.101378","title":"Simultaneous enhancement of strength, ductility, and hardness of TiN/AlSi10Mg nanocomposites via selective laser melting","year":2020,"lang":"en","type":"article","venue":"Additive manufacturing","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":209,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Materials science; Selective laser melting; Tin; Microstructure; Nanocomposite; Composite material; Ductility (Earth science); Recrystallization (geology); Nanoparticle; Nucleation; Ultimate tensile strength; Indentation hardness; Accumulative roll bonding; Grain boundary; Alloy; Metallurgy; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000910005,0.0003257991,0.0005259482,0.00007357805,0.00007984012,0.00002771856,0.0001654447,0.00008102661,0.0003792872],"category_scores_gemma":[0.0001108337,0.0003195112,0.00006995138,0.00008862233,0.0001265208,0.000181485,0.0001456145,0.0001715595,0.000009047096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003478498,"about_ca_system_score_gemma":0.00001319578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002870359,"about_ca_topic_score_gemma":0.000005988655,"domain_scores_codex":[0.9985999,0.00005024439,0.0004630734,0.0003568965,0.0002199499,0.0003099368],"domain_scores_gemma":[0.9990172,0.0004345654,0.0001881055,0.0001372638,0.0001060007,0.0001168257],"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":[0.0004471432,0.0001960085,0.0004064912,0.004943752,0.001101007,0.00007719939,0.008897819,0.01688898,0.8530536,0.00006372435,0.0006799764,0.1132443],"study_design_scores_gemma":[0.0003341521,0.0001528434,0.0008237817,0.0001283928,0.00005160087,0.000007064971,0.0002537067,0.001454644,0.995388,0.0001820611,0.000928306,0.0002954638],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938775,0.0001869948,0.003674762,0.00002705703,0.0001749641,0.0002820623,0.0003608566,0.0001412259,0.001274618],"genre_scores_gemma":[0.9985748,0.0001051267,0.0009885234,0.00003198074,0.0001528648,0.00002188983,0.00005561674,0.00004828546,0.00002094376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1423344,"threshold_uncertainty_score":0.9999257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008162744807875294,"score_gpt":0.2053071708831512,"score_spread":0.1971444260752759,"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."}}