{"id":"W4416185356","doi":"10.1016/j.cej.2025.170755","title":"Enhancing CO2 hydrogenation to methanol in fixed and fluidized bed reactors by selective in-situ adsorption of water","year":2025,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; Bundesamt für Energie; Board of the Swiss Federal Institutes of Technology; Eidgenössische Technische Hochschule Zürich; European Commission; Horizon 2020 Framework Programme; Physicians' Services Incorporated Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Methanol; Sorbent; Fluidized bed; Steam reforming; Carbon dioxide; Sorption; Adsorption; Hydrogen; Continuous reactor; Carbon monoxide","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":[0.0001483584,0.000385829,0.0003340119,0.0001699855,0.0001510309,0.0002997818,0.0003982503,0.0002736442,0.000482189],"category_scores_gemma":[0.000150507,0.0001821692,0.0003854963,0.0001772694,0.0002477503,0.0003005573,0.0002002171,0.0003016675,0.0001700904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003689419,"about_ca_system_score_gemma":0.0001599961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794464,"about_ca_topic_score_gemma":0.002149599,"domain_scores_codex":[0.9998996,0.00001490038,0.000005224036,0.00002381865,0.00003348585,0.00002295467],"domain_scores_gemma":[0.9999553,0.00001670898,0.00001024832,0.000004388412,0.000007515787,0.000005870172],"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":[0.000081477,0.00002340736,0.0001655439,0.00006811206,0.000008108274,0.00004009963,0.00001429614,0.001358354,0.9958223,0.0001557583,0.00001975527,0.00224292],"study_design_scores_gemma":[0.00001166252,0.0001424059,0.0008181247,0.000002219941,0.0000082496,0.00002519791,0.00001345656,0.01244598,0.9858526,0.00005863362,0.0006129463,0.000008611367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902174,0.0004462473,0.008453218,0.0000349246,0.00001787758,0.00001173032,0.00008313057,0.0001038034,0.0006315911],"genre_scores_gemma":[0.9964484,0.0002620369,0.00279149,0.000005177347,0.00000315083,0.00001110486,0.00006075339,0.000009757518,0.0004080831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001794464,"threshold_uncertainty_score":0.003568053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003180148188568091,"score_gpt":0.1928007921322065,"score_spread":0.1896206439436384,"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."}}