April 02, 2026 article Open access Knowledge-driven machine learning models for prediction of critical outputs in atmospheric and pressurized trickle-bed reactors for ex-situ biomethanation Chemical Engineering Journal DOI: 10.1016/j.cej.2026.175664 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 1 References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Machine Learning in Chemical Engineering: A Perspective 2021 Chemie Ingenieur Technik article Materials Science Machine Learning in Materials Science Open access 290 citations Optimization of the Ex Situ Biomethanation of Hydrogen and Carbon Dioxide in a Novel Meandering Plug Flow Reactor: Start-Up Phase and Flexible Operation 2024 Bioengineering article Engineering Anaerobic Digestion and Biogas Production Open access cited by 1 patent 8 citations 2 results