{"id":"W4410113966","doi":"10.1039/d5ta02317c","title":"Au atom tailoring of palladium nanocatalysts to boost cathodic coupling of carbon dioxide and methanol into dimethyl carbonate","year":2025,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Carbon dioxide utilization in catalysis","field":"Chemical Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Palladium; Nanomaterial-based catalyst; Methanol; Carbon dioxide; Dimethyl carbonate; Carbonate; Atom (system on chip); Coupling (piping); Materials science; Inorganic chemistry; Carbon atom; Chemistry; Catalysis; Metallurgy; Organic chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006062157,0.0002829269,0.0001769309,0.0001394594,0.0001147994,0.0002973495,0.0003550793,0.0003143088,0.001366206],"category_scores_gemma":[0.0001860451,0.0001780038,0.0001508727,0.0001511595,0.0002076885,0.0002132481,0.0001921033,0.0004256734,0.0003598142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004853223,"about_ca_system_score_gemma":0.0001562157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001184025,"about_ca_topic_score_gemma":0.002914072,"domain_scores_codex":[0.9998863,0.000006322579,0.000007159434,0.00003662288,0.00003530738,0.00002832524],"domain_scores_gemma":[0.9999478,0.00001034757,0.00001221957,0.000006825103,0.00001233595,0.00001050641],"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":[0.00008994157,0.00002282536,0.0000677409,0.00006191985,0.000007147809,0.00004790607,0.00002023935,0.0002384566,0.994534,0.0003689699,0.0002921027,0.004248746],"study_design_scores_gemma":[0.000006301724,0.00004651084,0.00017365,0.000001425215,0.000003781909,0.00002077637,0.000007267274,0.00169219,0.9970017,0.00002596477,0.001017252,0.000003124224],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762931,0.001558156,0.009016167,0.0002929182,0.000152056,0.0000443271,0.0002430066,0.0005123547,0.01188783],"genre_scores_gemma":[0.9954667,0.0003047179,0.002126688,0.00005874983,0.00000751473,0.00001474726,0.00006836549,0.00002902803,0.001923461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001366206,"threshold_uncertainty_score":0.004570365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008597975055087357,"score_gpt":0.2492747451038657,"score_spread":0.2406767700487784,"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."}}