Executive Summary : | Understanding theory and modeling is crucial in modern science, as it helps monitor quantum transport phenomena, design electronics and spintronics devices, develop mechanistic tools for catalytic science, and demonstrate sensor applications. Density Functional (DFT) Theory plays a significant role in exploring these processes, such as in catalytic reactions by identifying key intermediates and producing mechanistic energy profiles. Experimentalists can use theoretical prediction to obtain qualitative information about catalytic activity and trends, enabling them to scale down or tune reaction costs before conducting experiments. This study designs a nanohybrid made of graphitic carbon nitride (gC3N4) and cobalt-nitrogen (CoN4) doped carbon matrix. The composite has been reported for spin crossover and electrocatalytic activity in the presence of an electric field. gC3N4 has higher catalytic activity than pure carbon and is well-known for biosensors. To overcome limitations of using a pure non-metallic catalyst and reduce the use of costly metal catalysts, the nanohybrid is composed with one metallic part (CoN4) and one non-metallic part (gC3N4). The spin analog of electron is used to validate the potential application of the nanohybrid for quantum computing. The spin/charge distribution of different spin states of gC3N4/CoN4 will be used to check its catalytic activity towards oxygen reduction, oxygen evaluation, hydrogen evaluation, and carbon dioxide reduction reactions. The different electron affinity and conductivity of high and low spin states in the presence of an electric field will be used to develop a biosensor for lung cancer diagnosis. |