{"id":"W4307037633","doi":"10.1002/ls.1629","title":"Flow and slip process of Santotrac 50‐based lubricant under high shear by molecular dynamic simulation","year":2022,"lang":"en","type":"article","venue":"Lubrication Science","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Natural Science Foundation of China","keywords":"Slip (aerodynamics); Slip line field; Materials science; Wetting; Shear rate; Lubricant; Shear (geology); Shear stress; Mechanics; Lubrication; Molecular dynamics; Shear flow; Slip ratio; Couette flow; Shear velocity; Composite material; Critical resolved shear stress; Rheology; Thermodynamics; Chemistry; Flow (mathematics); Turbulence; Physics; Computational chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003021706,0.00008881147,0.0001285036,0.0001142972,0.000274518,0.00001112984,0.0002396991,0.00002640685,0.00004042704],"category_scores_gemma":[0.0001051615,0.00009177381,0.00002060388,0.0007382826,0.0003205297,0.0001243686,0.00009541662,0.0001174379,0.000001710865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009881791,"about_ca_system_score_gemma":0.00006017689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002120031,"about_ca_topic_score_gemma":5.03736e-7,"domain_scores_codex":[0.9988971,0.00002501595,0.0002002944,0.0003097526,0.0003820076,0.0001857686],"domain_scores_gemma":[0.9994482,0.0001043242,0.0000945258,0.0001983905,0.000105816,0.00004868882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009261877,0.00003437078,0.0003694831,0.00001263854,0.000004659857,2.992554e-7,0.0001525587,0.7353331,0.2606781,0.002921141,0.0000102337,0.0004741211],"study_design_scores_gemma":[0.0001733026,0.00003048475,0.004340347,0.000003432811,0.000009648303,0.000001609603,0.0001060671,0.9878232,0.006825245,0.0005596234,0.00002341378,0.0001035731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4451573,0.000193649,0.5539014,0.0004202659,0.00005454509,0.00009868159,0.0000155675,0.00003743943,0.0001211675],"genre_scores_gemma":[0.99674,0.000006680516,0.002929296,0.0001516314,0.000003625307,0.00003294108,0.00002166631,0.000008222839,0.0001059829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5515827,"threshold_uncertainty_score":0.3742427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006361159652848799,"score_gpt":0.2625248161445035,"score_spread":0.2561636564916547,"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."}}