structural:reformatting, information:classification
Numerical methods

In some cases, equations are unsolvable analytically, but can be solved using numerical methods if data values are given. There are two different ways to do this, by either using software programmes or mathematical methods such as the Euler method. Examples of software for chemical kinetics are i) Tenua, a Java app which simulates chemical reactions numerically and allows comparison of the simulation to real data, ii) Python coding for calculations and estimates and iii) the Kintecus software compiler to model, regress, fit and optimize reactions.

-Numerical integration: for a 1st order reaction A → B

The differential equation of the reactant A is: d d t = − k {\displaystyle {\frac {d{\ce {}}}{dt}}=-k{\ce {}}}

It can also be expressed as d d t = f (t,) {\displaystyle {\frac {d{\ce {}}}{dt}}=f(t,{\ce {}})} which is the same as y ′ = f (x, y) {\displaystyle y'=f(x,y)}

To solve the differential equations with Euler and Runge-Kutta methods we need to have the initial values.