{"id":"W4318953606","doi":"10.1016/j.jpowsour.2023.232745","title":"3D microscale modeling of NMC cathodes using multi-resolution FIB-SEM tomography","year":2023,"lang":"en","type":"article","venue":"Journal of Power Sources","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Energy; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tortuosity; Conductivity; Materials science; Microstructure; Microscale chemistry; Cathode; Scanning electron microscope; Focused ion beam; Electrical resistivity and conductivity; Composite material; Analytical Chemistry (journal); Ion; Porosity; Chemistry; Chromatography","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":[0.0002430822,0.0005119357,0.000327792,0.0004139235,0.0004177858,0.001769135,0.0007464304,0.001144133,0.003549918],"category_scores_gemma":[0.0005079602,0.0004636238,0.000495785,0.0004598206,0.0003319432,0.0005761673,0.0004284888,0.0004007593,0.0007669302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104047,"about_ca_system_score_gemma":0.001455039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008825839,"about_ca_topic_score_gemma":0.01111551,"domain_scores_codex":[0.9998481,0.000007955984,0.000007904271,0.00002416473,0.00009180529,0.00002003175],"domain_scores_gemma":[0.9998035,0.00005297715,0.00002929663,0.00003277974,0.00006948431,0.00001203377],"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":[0.0001151856,0.00008723134,0.004758856,0.0003599547,0.00006611322,0.0007971043,0.0004182415,0.8100764,0.1491152,0.008302826,0.00238931,0.02351356],"study_design_scores_gemma":[0.00001020431,0.00002956024,0.003903346,0.00002628445,0.00001407901,0.0002169499,0.0001027879,0.9589108,0.03107547,0.0008841475,0.004791267,0.00003505056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4424155,0.00124682,0.5164678,0.0005783825,0.0001026336,0.0002612108,0.004413784,0.004699318,0.02981448],"genre_scores_gemma":[0.8657512,0.0006193738,0.124937,0.00005913573,0.00001356947,0.0001888192,0.001123879,0.0003675139,0.006939589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008825839,"threshold_uncertainty_score":0.01754892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988380170151482,"score_gpt":0.3101958972596906,"score_spread":0.2803120955581758,"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."}}