Download Applied AI Techniques in the Process Industry: From Molecular Design to Process Design and Optimization 2025
Applied AI Techniques in the Process Industry: From Molecular Design to Process Design and Optimization book pdf download. identifies and categorizes the various hybrid models available that integrate data-driven models for energy-relevant systems and processes with different forms of process knowledge and domain expertise. State-of-the-art techniques such as reduced-order modeling, sparse identification, and physics-informed neural networks are comprehensively summarized, along with their benefits, such as improved interpretability and predictive power.
Numerous in-depth case studies regarding the covered models and methods for data-driven modeling, process optimization, and machine learning are presented, from screening high-performance ionic liquids and AI-assisted drug design to designing heat exchangers with physics-informed deep learning.
- Integration of observed data and reaction mechanisms in deep learning for designing sustainable glycolic acid
- Machine learning-aided rational screening of task-specific ionic liquids and AI for property modeling and solvent tailoring
- Integration of incomplete prior knowledge into data-driven inferential sensor models under the variational Bayesian framework
- AI-aided high-throughput screening, optimistic design of MOF materials for adsorptive gas separation, and reduced-order modeling and optimization of cooling tower systems
- Surrogate modeling for accelerating optimization of complex systems in chemical engineering
- Author (s): Chang He, Jingzheng Ren
- Year of publication: 2025
- Publisher: Wiley-VCH
- Language: English
- ISBN: 9783527353392, 3527353399, 9783527353392, 9783527845477, 9783527845484, 9783527845491
- Number of pages: 336 pages
- Book format: PDF
- File size: 8 MB
