{"id":"W3111605349","doi":"10.1016/j.isci.2020.101920","title":"Nitrogen-doped nanoporous graphene induced by a multiple confinement strategy for membrane separation of rare earth","year":2020,"lang":"en","type":"article","venue":"iScience","topic":"Graphene research and applications","field":"Materials Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; National Key Research and Development Program of China; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Graphene; Nanoporous; Materials science; Hydrotalcite; Selectivity; Membrane; Oxide; Nanoreactor; Nanotechnology; Chemical engineering; Nanopore; Nanoparticle; Doping; Nanomaterials; Polyetherimide; Inorganic chemistry; Chemistry; Organic chemistry; Catalysis; Composite material; Optoelectronics","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":[0.00008147464,0.0003584853,0.0001803938,0.0001860405,0.0001823819,0.0001518977,0.00031439,0.0003572454,0.0003930672],"category_scores_gemma":[0.00007859235,0.0001238373,0.0002795604,0.0001252547,0.000212608,0.0003408801,0.0003186153,0.0003237067,0.0001542486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004190589,"about_ca_system_score_gemma":0.0002169146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041383,"about_ca_topic_score_gemma":0.002841158,"domain_scores_codex":[0.9999309,0.000005915289,0.000003858855,0.00001625986,0.00002544017,0.00001773887],"domain_scores_gemma":[0.9999541,0.000007523458,0.00001245546,0.000007211969,0.000007996079,0.00001079007],"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":[0.00001245695,0.00001030644,0.00003771568,0.00004159219,0.000004756911,0.00004650514,0.00001087615,0.0001624343,0.998099,0.0002600464,0.00004961024,0.001264686],"study_design_scores_gemma":[0.000005154601,0.00004338815,0.0003109985,0.000002932749,0.000006772365,0.00006823369,0.000009295668,0.00240377,0.9954502,0.00005101985,0.001639894,0.000008434199],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764317,0.001723747,0.01722078,0.0002264066,0.00008890458,0.000054518,0.000180782,0.0002628856,0.003810252],"genre_scores_gemma":[0.987039,0.0007579876,0.01057303,0.00004929453,0.000009115806,0.00002574741,0.0001085314,0.00001540168,0.00142183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001041383,"threshold_uncertainty_score":0.003040552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05491185781833868,"score_gpt":0.3179797725423311,"score_spread":0.2630679147239924,"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."}}