{"id":"W4412480166","doi":"10.1016/j.cjche.2025.06.011","title":"Nickel and iron impregnated alkali-modified fly ash nanoparticle for improved CO2 capture performance in MDEA aqueous solutions","year":2025,"lang":"en","type":"article","venue":"Chinese Journal of Chemical Engineering","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"123 Certification (Canada)","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Hebei Province; National Natural Science Foundation of China","keywords":"Fly ash; Aqueous solution; Nickel; Alkali metal; Nanoparticle; Materials science; Chemical engineering; Chemistry; Metallurgy; Nanotechnology; Organic chemistry; Composite material; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000164195,0.0002372417,0.0004001345,0.000266117,0.00001244248,0.00002931105,0.0002183358,0.0002121846,0.00000117988],"category_scores_gemma":[0.0003670136,0.0002040692,0.00009989065,0.0003983109,0.00003958754,0.0001778075,0.00006878314,0.0005093446,2.556962e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888426,"about_ca_system_score_gemma":0.00003041308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002963151,"about_ca_topic_score_gemma":0.000002545845,"domain_scores_codex":[0.9989706,0.000003900794,0.000464827,0.0001332218,0.00007839843,0.0003490102],"domain_scores_gemma":[0.9994894,0.00012756,0.00005911348,0.0001695084,0.00007643401,0.00007793718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003349031,0.00001715521,0.0001336383,0.0002394284,0.0000403667,0.000004034559,0.00006270647,0.0814617,0.9164641,0.00009478984,0.0001120039,0.00133651],"study_design_scores_gemma":[0.001562321,0.00003470474,0.0007880675,0.0002578626,0.00003803777,0.00007615723,0.00002130758,0.7191347,0.2773742,0.0002825292,0.0001807542,0.0002493608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896237,0.005224977,0.004093586,0.0002794025,0.0003081808,0.0001773749,0.000006764263,0.0002241811,0.00006178974],"genre_scores_gemma":[0.9980249,0.0001208723,0.001710041,0.00002126449,0.00005139715,0.00002093734,0.000002642225,0.00003162125,0.00001634511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6390899,"threshold_uncertainty_score":0.83217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004280097340009115,"score_gpt":0.1977947189906936,"score_spread":0.1935146216506845,"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."}}