Apply computational analysis methods to predict organic reactivity and mechanisms

Theoretical calculations have become one of the most powerful tools for exploring organic reaction mechanisms, yet extracting meaningful conclusions from computational data requires systematic analytical methods. Computational Analysis in Organic Chemistry provides practical guidance on implementing these methods to understand observed reaction mechanisms and selectivity, presenting the principle, purpose, and implementation of each approach alongside specific research cases demonstrating real-world application.

Organized across six parts, the book categorizes analysis methods into five domains: energy, structure, electronic properties, electrons, and dynamics. Each chapter walks through how to analyze data results obtained from theoretical calculations and extract actionable conclusions. The text draws on current computational organic chemistry research cases, equipping readers with the tools to predict and rationalize structures and reactivity of organic molecules.

The book also covers:

• Practical implementation of software and computational tools used to analyze bonding and reactivity across diverse organic systems
• Methods for studying selectivity in organic reactions through systematic computational approaches grounded in current theoretical frameworks
• Techniques for analyzing electronic properties of organic molecules, including charge distribution, orbital interactions, and related descriptors
• Dynamics-based analysis methods that capture time-dependent behavior and trajectory information relevant to organic reaction pathways
• Research cases from recent computational organic chemistry literature illustrating how to move from raw calculation data to mechanistic insight

Designed for theoretical chemists, organic chemists, physical chemists, structural chemists, and chemists in industry, this book provides the analytical framework needed to apply computational methods to mechanistic problems. Researchers seeking to rationalize experimental observations or predict molecular reactivity will find direct, practical guidance for their work.

Yu Lan is a Professor of organic chemistry at Chongqing University, China, and a former postdoctoral fellow with Kendall N. Houk at the University of California, Los Angeles. A Scopus highly cited researcher since 2022, he has authored over 300 scientific publications and received the Chinese Chemical Society Award for Outstanding Young Chemist and First Prize of Chongqing Natural Science Award.

Shihan Liu is an Associate Research Fellow at Henan University. He obtained his Master's degree in Chemical Engineering and Ph.D. in Chemistry at Chongqing University under the supervision of Prof. Yu Lan. His research focuses on the interdisciplinary field of computational organic chemistry and artificial intelligence chemistry.