{"id":"W2465894348","doi":"10.1021/acs.cgd.6b00470","title":"Formation of Lithium Titanate Hydrate Nanosheets: Insight into a Two-Dimension Growth Mechanism by in Situ Raman","year":2016,"lang":"en","type":"article","venue":"Crystal Growth & Design","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Université de Montréal; McGill University","funders":"Hydro-Québec; Natural Sciences and Engineering Research Council of Canada; Faculty of Engineering, McGill University","keywords":"Materials science; Nanosheet; Nucleation; Crystallization; Lithium titanate; Raman spectroscopy; Chemical engineering; Amorphous solid; Titanate; Crystal growth; Context (archaeology); Nanotechnology; Crystallography; Thermodynamics; Ceramic; Chemistry; Composite material; Lithium-ion battery; Battery (electricity); Physics; Optics","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":[0.0001169812,0.0001857484,0.0001133208,0.0001596557,0.0001309997,0.0002790999,0.0002979244,0.0002946055,0.0004810283],"category_scores_gemma":[0.0001521192,0.0002196964,0.0001835807,0.00009517855,0.0002793878,0.0005019928,0.0001551882,0.0002818835,0.00009418702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000233077,"about_ca_system_score_gemma":0.0001286785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006049339,"about_ca_topic_score_gemma":0.0009591678,"domain_scores_codex":[0.9999425,0.000006420461,0.000002909128,0.00001677839,0.0000222843,0.000009134214],"domain_scores_gemma":[0.9999397,0.00002712031,0.00001122199,0.000008307377,0.000009674251,0.000003972531],"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":[0.00002473612,0.00001476118,0.0006484403,0.00006006364,0.000005034729,0.00008391216,0.00006907036,0.001380697,0.9947879,0.001355134,0.00005643797,0.001513868],"study_design_scores_gemma":[0.00001279134,0.0000787309,0.002664551,0.000005517065,0.000008591983,0.0001587005,0.00009778672,0.1028364,0.892436,0.0007066822,0.0009787073,0.00001546169],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878654,0.0004310363,0.009506021,0.00009345412,0.00001375256,0.00001798192,0.0001076607,0.00007047428,0.001894161],"genre_scores_gemma":[0.9948282,0.000234998,0.004403683,0.00001207135,0.000004382046,0.000009491343,0.00004915746,0.000009550153,0.0004484869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006049339,"threshold_uncertainty_score":0.001691163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090659690442273,"score_gpt":0.2336318477467354,"score_spread":0.2227252508423127,"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."}}