The use of chemical warfare agents (CWAs) remains a real threat to public life, in order to safeguard and protect lives. Continues research and investment need to make into early warning systems. Within the scientific literature several sensors have been produced for the detection of CWAs and organophosphorus compounds with varying sensitivities and selectivity. Most sensors developed are unable to detect below the minimum risk level, rendering them ineffective for early warning systems. The use of molecularly imprinted polymers (MIPs) to increase the sensitivity of the sensor is a possible solution to this problem. For an MIP to be successful, the correct monomer must be selected that is complementary to the chosen template molecule. This study utilises computational chemistry for the identification of potential monomers complementary to the chosen template, for the fabrication of an MIP. Dimethyl methylphosphonate (DMMP) was used as the template for the MIP as the compound is a mimic for Sarin and is used heavily within the literature for the design of chemical warfare sensors. By investigating the polymerisation capabilities and interactions with the template, a suitable candidate can be selected without wasting time and resources. The chemical structures of the monomers and template were imported into Spartan and converted into a 3D model. Density functional theory (DFT) with the B3LYP/6-31G level was used to calculate the electronic binding energies with a 1 to 3 ratio of Chitosan to DMMP proving to be the most efficient option.
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