Advanced integration strategies and machine learning-based superstructure optimization for Power-to-Methanol

• Main Authors: Vo, Dat-Nguyen, Qi, Meng, Lee, Chang-Ha, Yin, Xunyuan
• Other Authors: School of Chemistry, Chemical Engineering and Biotechnology
• Format: Article
• Language: English
• Published: 2025
• Subjects: Chemistry; Power-to-Methanol; Electrolyzer
• Online Access: https://hdl.handle.net/10356/181957
• Institution: Nanyang Technological University

The Power-to-methanol (PtMe) process faces significant challenges, including high production costs, low energy efficiency, and a lack of systematic and applicable integrated design and superstructure optimization methods. This study proposes advanced integration and machine learning (ML)-based super...