Artificial Intelligence in Chemistry and Chemical Engineering
Artificial Intelligence in Chemistry and Chemical Engineering
Integrate AI into chemical research through structured tutorials and exercises
Chemists adopting AI methods need discipline-specific training beyond generic introductions. Artificial Intelligence in Chemistry and Chemical Engineering: From Basics to Practical Exercises provides a step-by-step tutorial guiding researchers through AI, automation, data science, and cheminformatics. Progressing from foundational concepts to advanced applications, hands-on exercises and real-world case studies enable direct application to ongoing research programs.
Coverage spans AI reaction prediction models, automated high-throughput synthesis platforms, and chemical reaction big data systems. The book addresses ethical implications and regulatory considerations for AI deployment in chemistry. A companion website and a specialized large language model deliver continuous interactive support, providing updated resources and ongoing learning opportunities beyond the printed text.
Readers will also find:
- Foundational machine learning concepts tailored specifically for practitioners working in chemistry and chemical engineering research disciplines
- Detailed tutorials on building and utilizing chemical reaction big data systems for accelerating discovery and optimizing workflows
- Real-world case studies demonstrating how AI-driven approaches solve specific challenges in organic synthesis and molecular science
- Discussion of potential misuse scenarios and regulatory frameworks to navigate responsible AI integration in laboratory settings
- Practical guidance on constructing next-generation automated high-throughput synthesis platforms for efficient experimental design and execution
Designed for organic, physical, theoretical, medicinal, analytical, pharmaceutical, and environmental chemists, as well as materials scientists, chemical engineers, and computer scientists, this book delivers the structured training required to apply AI methods directly to chemical research and industrial practice.
Preface
Chapter 1: Introduction to AI in Chemistry: Landscape, Motivation, and Scientific Workflow
Lin Tan
Chapter 2: Fundamentals of AI and Machine Learning
Chonghuan Zhang
Chapter 3: Data Science for Chemists
Chonghuan Zhang
Chapter 4: Cheminformatics
Chonghuan Zhang
Chapter 5: Integrating Automation Tools in Chemical Research
Kai Xue
Chapter 6: Foundations of Predictive Modeling in Chemistry
Chonghuan Zhang
Chapter 7: AI in Chemical Synthesis, Process Optimization, and Automation
Chonghuan Zhang
Chapter 8: Molecular Modeling and Design
Chonghuan Zhang
Chapter 9: Materials Discovery and Design
Chonghuan Zhang
Chapter 10: Analytical Chemistry
Qianghua Lin
Chapter 11: Environmental Chemistry
Qianghua Lin
Chapter 12: AI in Chemical Engineering
Chonghuan Zhang
Chapter 13: AI in Chemical Education and Training
Chan Zhu
Chapter 14: Practical Exercises and Projects
Chonghuan Zhang
Chapter 15: Ethical Considerations and Best Practices in AI for Chemistry
Chonghuan Zhang
Index
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Liao, Kuangbiao
| ISBN | 9783527355112 |
|---|---|
| Media type | Book |
| Copyright year | 2026 |
| Publisher | Wiley-VCH |
| Language | English |