Development of an optimized fitting routine for comparing theoretical data with experiments on moisture sensitive beads for carbon dioxide capture

Carbon dioxide (CO2) is one of the most dangerous greenhouse gas. Its concentration in the atmosphere has increased to very high levels since the industrial revolution. This continues to be a threat due to increasing energy demands. 60% of the worlds global emissions come from automobiles and other such moving sources. Hence, to stay within safe limits, it is extremely important to curb current emissions and remove those which have already been emitted. Out of many available technologies, one such technology is the moisture swing based air capture technology that makes use of resin material that absorbs CO2 when it is dry and releases it when it is wet. A mathematical model was developed to better understand the mechanism of this process. In order to validate this model, numerical simulation and experimentation was done. Once the mechanism was proved, it was seen that there are many factors and parameters that govern this process. Some of these do not have definite value. To find the best fit value for these parameters, an optimized fitting routine needs to be developed that can minimize the standard deviation of the error. This thesis looks into ways in which the optimization of parameters can be done and the possible future work by using substantial data.