Integrate MATLAB computation with rigorous reactor design and kinetics theory
Chemical reaction engineering problems increasingly demand computational approaches that traditional textbooks treat as supplementary. Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB integrates tested MATLAB scripts throughout every chapter, enabling students and practitioners to solve reactor design, kinetics, and optimization problems using both classical methods and modern computational techniques side by side.
The text develops reactor design principles across batch, CSTR, PFR, PBR, and FBR systems with verified MATLAB codes for reactor sizing, conversion calculations, and performance analysis including yield and selectivity. Coverage includes chemical equilibrium, thermodynamics, and operating condition impacts with programs for calculating equilibrium constants and coupled equilibria. AI-assisted problem-solving strategies using LLM platforms as computational co-pilots are also introduced.
You'll also discover:
- Step-by-step annotated MATLAB examples demonstrating both manual and computational approaches so readers understand when computation adds analytical value
- Verified, tested MATLAB scripts for students with a comprehensive solutions manual available separately for course instructors adopting this text
- Chemical identity fundamentals including reaction kinetics, rate laws, Arrhenius behavior, and reaction orders for homogeneous and heterogeneous systems
- Prompt-engineering strategies, verification techniques, and error diagnostics for collaborating responsibly with AI tools in CRE problem solving
- Multiple reactor configurations with MATLAB codes illustrating sizing, conversion, and performance (e.g., yield and selectivity) across single and combined reactor arrangements
Written for third- and fourth-year chemical engineering students in reactor design courses, this textbook also serves practicing engineers seeking reproducible MATLAB templates for designing, troubleshooting, and optimizing chemical processes. Instructors will find a fully integrated computational framework ready for classroom adoption.
