{"id":"W2949599446","doi":"10.1039/c9ta04025k","title":"A 3D ordered hierarchically porous non-carbon electrode for highly effective and efficient capacitive deionization","year":2019,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Membrane-based Ion Separation Techniques","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; University of Ottawa; National Institute for Nanotechnology; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; University of Ottawa","keywords":"Capacitive deionization; Electrode; Materials science; Capacitive sensing; Adsorption; Porosity; Carbon fibers; Nanotechnology; Chemical engineering; Salt (chemistry); Titanium; Electrochemistry; Composite material; Chemistry; Computer science; Metallurgy","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":[],"consensus_categories":[],"category_scores_codex":[0.0003506333,0.0001445663,0.0003015163,0.00005224844,0.00002392489,0.00005246395,0.00008230146,0.0001167721,0.00005685433],"category_scores_gemma":[0.00008943426,0.0001326578,0.00003611653,0.00006784684,0.00002067078,0.00005954901,0.0000107596,0.000110426,0.000001625312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000979042,"about_ca_system_score_gemma":0.00003977404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000156894,"about_ca_topic_score_gemma":1.213009e-7,"domain_scores_codex":[0.9991478,0.00002895397,0.0003974967,0.000116343,0.0001532541,0.0001561494],"domain_scores_gemma":[0.99933,0.0001027376,0.0002038575,0.0001017993,0.0001974933,0.00006406723],"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":[0.0002344825,0.00002154963,0.0000082093,0.0003643873,0.00004255606,0.00000314035,0.0001214995,0.0028172,0.9961092,0.000008554774,0.00008083108,0.0001884165],"study_design_scores_gemma":[0.00089518,0.0001531914,0.000105834,0.0001206996,0.00002632897,0.00008109082,0.00001331358,0.004158411,0.9940934,0.00009715974,0.0001222981,0.0001330514],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880087,0.00005352714,0.01073742,0.00004353925,0.000170796,0.0004160456,0.00002108973,0.00005952928,0.0004893373],"genre_scores_gemma":[0.9971151,0.00002633434,0.002543592,0.00001954032,0.0001697452,0.00003285685,0.00001203184,0.00002903437,0.00005170829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009106447,"threshold_uncertainty_score":0.5409628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002954461161517264,"score_gpt":0.2039818101085739,"score_spread":0.2010273489470566,"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."}}