October 24, 2022 article Predicting PC-SAFT pure-component parameters by machine learning using a molecular fingerprint as key input Fluid Phase Equilibria DOI: 10.1016/j.fluid.2022.113657 OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 41 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 Molecular machine learning in chemical process design 2026 Current Opinion in Chemical Engineering review Materials Science Machine Learning in Materials Science Open access 5 citations ML-SAFT: A machine learning framework for PCP-SAFT parameter prediction 2024 Chemical Engineering Journal article Engineering Phase Equilibria and Thermodynamics Open access 33 citations ML-SAFT: A machine learning framework for PCP-SAFT parameter prediction 2023 ChemRxiv preprint Engineering Phase Equilibria and Thermodynamics Open access 6 citations 3 results References 0