{"id":"W4300503347","doi":"10.1149/ma2014-02/5/462","title":"Failure Mode Analysis of Li-Ion Batteries Using in-Situ Scanning Electron Microscopy","year":2014,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Scanning electron microscope; Materials science; Battery (electricity); Electrolyte; Electrochemistry; Cathode; Plating (geology); Lithium (medication); Ion; Analytical Chemistry (journal); Lithium-ion battery; Particle (ecology); Electrode; Composite material; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002185198,0.0003834736,0.0002706791,0.0009403501,0.0001913986,0.0002352069,0.0004072292,0.0003659072,0.002924208],"category_scores_gemma":[0.0003217471,0.0001517852,0.0001529164,0.000283518,0.0001495853,0.0002660526,0.0001524937,0.0001835503,0.0003720995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764683,"about_ca_system_score_gemma":0.00004679384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006390845,"about_ca_topic_score_gemma":0.0009709839,"domain_scores_codex":[0.9999067,0.000006872875,0.000006497,0.00001719392,0.00004902643,0.00001369623],"domain_scores_gemma":[0.9996295,0.0001005536,0.00005103616,0.00004624909,0.000152745,0.00001988847],"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":[0.0001164793,0.00006660824,0.010217,0.0002198111,0.00002042846,0.0004878843,0.0003379656,0.002520148,0.9648331,0.0002136574,0.000401196,0.02056568],"study_design_scores_gemma":[0.000009050377,0.0007095266,0.1411388,0.00005428109,0.00005816451,0.001636283,0.0005854075,0.06479071,0.7861843,0.0004345738,0.004354967,0.00004376241],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680607,0.0008304566,0.02693814,0.00004371321,0.0000283351,0.00005491604,0.0009286213,0.0006793988,0.00243564],"genre_scores_gemma":[0.990378,0.0003034023,0.006755891,0.00002153874,0.000009780207,0.00004585813,0.0003805349,0.00003680983,0.002068256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002924208,"threshold_uncertainty_score":0.009782434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052303616985844,"score_gpt":0.2704421479962638,"score_spread":0.2599191118264054,"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."}}