Developing the Chemist’s Inner Coder: A MATLAB Tutorial on the Stochastic Simulation of a Pseudo-First-Order Reaction

Abstract

The drive in computational methods and more intuitive software has seen a rise in the number of publications in this area in recent years. Computational simulations can be found in many areas of science from computational biology and chemistry to fundamental physics. These may help synthetic chemists in their drug discovery endeavors and cosmologists predicting astronomical events. This paper is designed to equip chemists with a basic understanding of how loops and conditional statements can be used within both the MATLAB syntax and Excel spreadsheets to simulate dynamic processes. Many commercial software packages require little to no programming and often do not explicitly display the underlying calculations. While these programs are often very efficient for solving a specific problem, they are somewhat limited. Principally, this practical uses a stochastic simulation algorithm to generate the kinetic data of a reversible association reaction. The kinetic data is analyzed using the standard rate laws to highlight to students the effectiveness of this method. Ultimately, the skills developed in this practical will help students in future computational projects, where bespoke coding is necessary.

Experience-Based Learning Approach to Chemical Kinetics: Learning from the COVID-19 Pandemic

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Revisiting Distance Learning Resources for Undergraduate Research and Lab Activities during COVID-19 Pandemic

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Integrating Python into a Physical Chemistry Lab

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