Network Mechanism Analysis

Contents

Overview and Motivation

During discussions with the experimental team it became clear to us that the exact reaction mechanism in place was not clearly understood. By modelling a range of different potential mechanisms and comparing the outputs to experimental data we could draw conclusions about the accuracy of the mechanisms and hence refine the model in an effort to produce more accurate predictions and improve our understanding of the system.

The combinations of different rate laws used to model our reactions are as below:

Methodology

For each of the combinations of potential rate equations for each step the following was undertaken:

The model was run with many iterations.
The concentration at steady state for each iteration was recorded and plotted in a histogram.
Experimental steady state data was then compared to these histograms.

For each combination of different rate laws used to model our network, the following steps were taken: 1) Generate probability distributions for each kinetic parameter required. 2) Simulate the model with different sets of kinetic values that are sampled from probability distributions. In our study, 1000 samples for each reaction were modelled, i.e. the model was simulated with 1000 different sets of kinetic values. 3) Analysed the model by retrieving concentrations at reaction completion for each sample and plotted in a histogram. 4) Compared experimental data with our model predictions.

Results

PLACEHOLDER FOR GRAPHS

Conclusions

From the graphs you can see that...