{"id":"W2599613225","doi":"10.1149/ma2017-01/1/42","title":"LiPF<sub>6 </sub>as Effective Etching Agent of LiMnPO<sub>4 </sub>colloidal Nanocrystals for High Rate Li-Ion Battery Cathodes","year":2017,"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":"Materials science; Chemical engineering; Aqueous solution; Cathode; Carbon fibers; Etching (microfabrication); Coating; Nanocrystal; Nanoparticle; Lithium (medication); Colloid; Conductivity; Battery (electricity); Nanotechnology; Layer (electronics); Composite material; Composite number; Chemistry; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001397334,0.0003518573,0.0002175083,0.0001490963,0.0001383182,0.0002214343,0.0002657624,0.0004134428,0.0007001014],"category_scores_gemma":[0.000207331,0.0001568537,0.0002446519,0.0000833774,0.0002011729,0.0002992429,0.0002394057,0.0003690958,0.0003246571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002954846,"about_ca_system_score_gemma":0.0001529008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000694508,"about_ca_topic_score_gemma":0.0008886864,"domain_scores_codex":[0.999908,0.00001001052,0.000009399245,0.00002543806,0.00003172621,0.00001543317],"domain_scores_gemma":[0.9999272,0.00001573946,0.00002086392,0.000005365063,0.00002189771,0.000008939295],"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":[0.00001663801,0.000005316148,0.00002957774,0.00003852529,0.000002570797,0.00003375189,0.000008716873,0.00007903685,0.998731,0.00004976792,0.0000260038,0.0009790424],"study_design_scores_gemma":[0.000004156114,0.00003694017,0.0001902705,0.000003011332,0.000006903699,0.00005226767,0.000006702638,0.0008703311,0.9982033,0.00001341999,0.0006082943,0.0000044658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827916,0.001645569,0.01325896,0.0001441238,0.00006187344,0.00005529504,0.0001372454,0.0001741193,0.001731244],"genre_scores_gemma":[0.9792381,0.0009836388,0.01690413,0.00008075828,0.00001886588,0.00007492412,0.0001301838,0.00006088257,0.002508433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007001014,"threshold_uncertainty_score":0.002342105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309601387770036,"score_gpt":0.253365382641376,"score_spread":0.2402693687636756,"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."}}