Stochastic Chemical Kinetics for Chemical Engineers

In traditional chemical engineering, reactions are often modeled as deterministic systems. However, at small scales or low molecule counts, random fluctuations dictate the true behavior of chemical processes. This course introduces you to stochastic chemical kinetics, providing the mathematical and numerical foundation needed to model these probabilistic systems with confidence. You will transition from deterministic modeling to simulating molecular-level randomness using structured, step-by-step algorithms. Learn the core principles of probability in chemical systems, understand the master equation, and implement simulation algorithms like the Gillespie algorithm. Build a strong foundational knowledge of stochastic modeling, apply modern numerical techniques to simulate biological and chemical networks, and practice analyzing fluctuation phenomena in reaction rates. This text-only course begins with essential probability theory and kinetics terminology before guiding you through algorithm design and modern computational workflows. It is designed specifically for beginners in stochastic modeling, requiring only basic knowledge of calculus and general chemistry. Start exploring the probabilistic nature of chemical reactions today.