The development of green and efficient electrocatalysis, which targets the generation and storage of renewable energy by transforming electrical energy to chemical energy, is strongly driven by the challenges we face in increasing energy demand. Consequently, great efforts have been made in exploring efficient electrocatalysts. The conventional trial-and-error approach for electrocatalysts is timeconsuming due to the lack of direct information regarding the atomic-scale properties of electrocatalysts and the underlying elementary reaction mechanisms. To date, the rational molecular design of high-performance electrocatalysts has been extensively used. However, most of these computational studies are still in their infancy and more reliable modelling of electrochemical processes is needed to bridge the gap between experiments and theory. This thesis aims to utilize structural engineering at the atomic scale to develop high-performance electrocatalysts for hydrogen evolution reaction (HER) and chlorine evolution reaction (CER), and model the external factors of the operating environment to provide a better description of electrocatalytic processes. The general background and objectives of this PhD project are presented in Chapter 1. The recent progress in numerical modelling of electrochemical reactions and processes is discussed in Chapter 2. The importance of theoretical identification and understanding of catalytic active sites is highlighted in this chapter. The computational method employed in this project is the density functional theory (DFT), which has been demonstrated to achieve increasing success in the description and understanding of the II complexity of electrocatalysis. Chapter 3 provides a short introduction of the DFT method, including its origin, development, and implementation. Chapters 4-7 present all the research work completed for this project. As metalorganic frameworks (MOFs) are considered a large family of low-dimensional materials, a comprehensive computational study was conducted to investigate the structural properties and electronic properties of one-dimensional (1D) transition metalbased dithiolene MOFs. Their high electrical conductivities offer the potential for electrocatalytic hydrogen evolution, which is examined with the consideration of electrolyte effects in Chapter 4. As the one of main industrial reactions, CER electrolysis is challenging due to the selectivity of Cl2. This can be ascribed to the unavoidable oxygen evolution from the noble metal-based dimensionally stable anodes (DSAs) used in industry. To this end, six TMN4 complex embedded graphene (TMN4@G) single-atom catalysts (SACs) were systematically investigated in Chapter 5. The DFT results predicted that NiN4@G is a promising candidate for efficiently and selectively catalyzing chlorine evolution in acidic solution. Chapter 6 theoretically studied the performance of CER for eight two-dimensional (2D) semiconducting group- VA monolayers with α and β phases. It is suggested that β-arsenene monolayer exhibits high activity and selectivity of gaseous Cl2 generation by virtue of the expected Cl* precursor. In Chapter 7, three low-dimensional Fe/Co/Ni−dithiolene MOFs were purposely selected due to their acid resistance and comprehensively investigated for electrocatalytic CER. The calculated results demonstrate that Ni-based dithiolene MOF can efficiently catalyze the CER via the Cl* pathway. This thesis makes significant contributions to the theoretical understanding of electrochemical processes, materials science, and electrochemical energy conversion and storage through: (i) demonstrating the importance of electronic configurations of metal cations in the electrical conductivities of transition metal-dithiolene MOFs; (ii) proposing a novel strategy for optimizing the electronic structure of materials on the basis of the resonant charge transfer mechanism; (iii) predicting efficient lowdimensional electrocatalysts for Cl2 evolution with the Cl* intermediate rather than the ClO* intermediate; and (iv) investigating the interactions between adsorbates and catalysts to provide a new descriptor for the discovery of high-performance CER electrocatalysts. It is worth noting that the studies on the electrocatalytic properties of low-dimensional materials are still in the early stage. As such, more accurate models and approaches combined with multiscale simulation are needed in future studies, such as the modelling of the electrode-electrolyte interface, dynamic solvent, and electrical double layer.