In dynamic systems such as chemical systems, reactions occur between a number of chemicals. Here reaction rates rarely stay constant and the rate of each reaction is intricately tied to both temperature and the concentration of reactants. As these variables change, for instance with a rise or fall of temperature or the reactants levels decreasing, the increase in concentration of the products with time will vary constantly, so the rate at which products form continuously changes.  Understanding and predicting this behaviour is critical, particularly when dealing with complex reactions or processing environments.

This is where Reaction Kinetics comes into play and how modelling can help.

Reaction Kinetics, also called chemical kinetics, is the study of the rates of the chemical reactions, meaning how fast reactants get converted into products, as well as the factors affecting those rates. So, with Reaction Kinetics we can understand how fast a reaction happens, what influences its speed and what steps and mechanisms are involved in the reaction transformation. 

In industries such as food processing, reaction kinetics help predict how long to cook, mix or store a product to achieve the desired result such as colour, flavour, shelf-life as well as to help avoid unwanted changes such as the loss of nutrients or flavours which are off. 

This is where reaction rate equations come into play. These mathematical formulations allow scientists and engineers to describe how fast a reaction proceeds under given conditions. For simple reactions, these equations are relatively straightforward, but in reality, many important chemical transformations are anything but simple.

For instance, let's take one of the most common reactions, the Maillard reaction. This is a staple in food chemistry and this type of reaction is responsible for the browning and the flavour of cooked foods. The Maillard reaction is not one single reaction but a cascade of coupled reactions involving sugars, amino acids and heat. The pathways of the reaction can branch, loop back and create a wide variety of end products depending on how conditions evolve over time. The end product can influence not only the colour and aroma but also the sensory perception and hence consumer acceptability of the final product. 

To model such a Reaction Kinetics system properly, one must take into consideration multiple and often interdependent variables that change simultaneously. In food processing, for instance, the roasting of coffee beans or cocoa involves spatial and temporal temperature gradients, moisture migration and the evolution of volatile compounds, all of which shape the final sensory profile. And when these reactions occur in environments where other than the chemical reactions taking place there are also physical processes, such as mixing, the challenge increases further and that is where tools such as Computational Fluid Dynamics (CFD) get extremely valuable if not essential. CFD allows us to simulate how fluids move and mix over time and by coupling CFD with Kinetic Models of chemical reactions one can begin to understand how physical mixing influences reaction rates, and possibly vice versa. 

Let's imagine that we are developing a new beverage formulation. In the production process, during mixing, not only it is very important to achieve homogeneity but also to control reaction pathways and the latter is done to stabilise colour, to manage flavour development or avoid unwanted browning. Another example would be the production of thermally processed soups or sauces, where you would need to model the interplay between mixing, heating and chemical transformations, such as for instance acid-base reactions, degradation of aroma compounds, to help optimise the product quality while reducing energy input.

When you combine and integrate Chemical Kinetics with Computational Fluid Dynamics (CFD) a powerful avenue opens up that allows you to predict and optimise processes in fields ranging from food science, to pharmaceuticals, to combustion and materials engineering. It enables a more realistic and detailed view of how complex reactions unfold in dynamic, real-world settings which goes beyond the simplicity of a well-mixed beaker in a lab.