{"id":"W4327559586","doi":"10.1016/j.micromeso.2023.112554","title":"Improved adsorption desalination performance of DUT-67 by incorporating Graphene Oxide (GO)","year":2023,"lang":"en","type":"article","venue":"Microporous and Mesoporous Materials","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Postal Museum; Djavad Mowafaghian Foundation; Huazhong University of Science and Technology","keywords":"Adsorption; Desalination; Materials science; Graphene; Mass transfer; Oxide; Composite number; Composite material; Coefficient of performance; Chemical engineering; Nanotechnology; Chemistry; Chromatography; Mechanical engineering; Engineering; Metallurgy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008091731,0.0003309254,0.0002051811,0.000201984,0.0001501873,0.0001944271,0.0001962169,0.0002897114,0.0008215972],"category_scores_gemma":[0.0000803111,0.0001390085,0.000195754,0.0001720806,0.00008558897,0.0003057294,0.0001923078,0.0003500369,0.0003415141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002092301,"about_ca_system_score_gemma":0.0002067502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002600525,"about_ca_topic_score_gemma":0.005660933,"domain_scores_codex":[0.9999243,0.000004347857,0.000003969308,0.00001021937,0.00002464035,0.00003255058],"domain_scores_gemma":[0.9999754,0.000004408653,0.000004246716,0.000002126893,0.000008985052,0.000004819572],"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":[0.00003323401,0.000006542123,0.00007892259,0.00002510863,0.000002730051,0.00002221618,0.00001039039,0.00005627845,0.998311,0.00003197885,0.00002680278,0.001394719],"study_design_scores_gemma":[7.662679e-7,0.00001783575,0.0002848462,9.751332e-7,0.000003694348,0.00001073311,0.000006830616,0.0003009592,0.9990799,0.00000290502,0.0002885793,0.000001973337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969893,0.0005977441,0.001284919,0.00004445945,0.00001839744,0.000005929527,0.00009200387,0.00005630776,0.0009110177],"genre_scores_gemma":[0.9961743,0.0004611709,0.0009966721,0.00002342926,0.000003463371,0.000003724907,0.0001501373,0.00001236928,0.002174755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002600525,"threshold_uncertainty_score":0.005170822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008400794338146599,"score_gpt":0.2180775148123864,"score_spread":0.2096767204742398,"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."}}