Applied AI Techniques in the Process Industry
From Molecular Design to Process Design and Optimization
Edited by Chang He Edited by Jingzheng Ren
Hardback (Published)
(January 2025)
ISBN: 9783527353392
6.69 x 9.61 inches
Price: $153.00
Out of stock
Data-driven and first principles models for energy-relevant systems and processes approached through various in-depth case studies.
Chapter 1: Integrating Data-Driven Modeling with First-Principles Knowledge
Chapter 2: Advanced algorithms for Hybrid Data-driven Modelling
Chapter 3: A computational Framework for Model-based Design and Optimization of Dynamic and Cyclic Membrane Processes
Chapter 4: AI-Aided Optimization and Design of MOF Materials for Gas Separation
Chapter 5: Machine Learning Aided Materials and Process Integration Design for High-Efficiency Gas Separation
Chapter 6: Data-driven Screening of High-performance Ionic Liquids
Chapter 7: Hunting for Aromatic Chemicals with AI Techniques
Chapter 8: AI-assisted Drug Design and Production
Chapter 9: Designing a Heat Exchanger by Combining Physics-Informed Deep Learning and Transfer Learning
Chapter 10: Catalyst Design Based on Machine Learning
Chapter 11: Surrogate Models for Sustainability Optimization of Complex Industrial System
Chapter 12: Advanced Machine Learning and Deep Learning Models for Chemical Process Control and Process Data Analytics
- Edited by Chang He
- Edited by Jingzheng Ren