{"id":"W4404540514","doi":"10.1021/acsami.4c15939","title":"Efficient Lithium Recovery from Water Using Polyamide Thin-Film Nanocomposite (TFN) Membrane Modified with Positively Charged Silica Nanoparticles","year":2024,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; National Institute for Nanotechnology; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada's Oil Sands Innovation Alliance; Alberta Innovates","keywords":"Materials science; Polyamide; Nanocomposite; Nanoparticle; Membrane; Lithium (medication); Chemical engineering; Composite material; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000188086,0.0003538566,0.0003691221,0.000130013,0.0001377784,0.0006658277,0.0001859199,0.0001351866,0.0004869083],"category_scores_gemma":[0.000003983704,0.0002560872,0.00002261598,0.0001320173,0.00006063979,0.0002332236,0.00005831784,0.0001508831,0.0004425783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007828904,"about_ca_system_score_gemma":0.00002578362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009292594,"about_ca_topic_score_gemma":0.00001134617,"domain_scores_codex":[0.9984124,0.00003948847,0.0004760555,0.0004384941,0.0002414434,0.0003921099],"domain_scores_gemma":[0.9995189,0.00008148287,0.00005144757,0.0002234255,0.00005009142,0.00007464654],"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":[0.000300293,0.00003314445,6.657863e-7,0.0001585221,0.0001657317,0.000008966828,0.001368785,0.1351863,0.8623193,0.0002731477,0.00009788602,0.00008728272],"study_design_scores_gemma":[0.0002848947,0.00004431815,0.00001767651,0.0001784635,0.00007927386,0.00001620549,0.0001855847,0.005654503,0.992739,0.0001245766,0.0002998039,0.00037573],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946176,0.0004778398,0.0006529083,0.0001142866,0.0008836701,0.000356747,0.0001491734,0.0008410843,0.001906645],"genre_scores_gemma":[0.9986679,0.00004914095,0.0004792015,0.000109682,0.0001461788,0.00007560064,0.00007398138,0.00008813441,0.0003101782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1304197,"threshold_uncertainty_score":0.9999892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187871004657077,"score_gpt":0.2247798024905712,"score_spread":0.2129010924440004,"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."}}