To advance our understanding of corrosion mechanisms at the atomic level and to develop corrosion mitigation strategies, computational approaches, particularly density functional theory (DFT), have become valuable tools. DFT enables researchers to probe atomicscale interactions, providing insight into the energetics, adsorption behaviour, reaction mechanisms, and electronic properties of materials in corrosive environments. In the last two decades, numerous DFT studies have been conducted to investigate iron oxidation processes at the atomic scale. Since water and oxygen are the main corrosive agents, most studies have focused on how these agents interact with the crystallographic surface planes of iron. For example, Eder et al. investigated the water dissociation energies on Fe(100) and Fe(110) surfaces using spin-polarized DFT calculations and found that the Fe(100) surface is more reactive than Fe(110). In another study, it was revealed that water adsorption on the Fe(100) surface is relatively weak, leading to physisorption. Several studies have also investigated the influence of pre-adsorbed oxygen on water dissociation and demonstrated that when the surface is partially covered with oxygen, water can easily dissociate. However, when the surface is fully covered with oxygen, water-surface interactions become weaker. These DFT simulations have provided valuable insights into oxygen and water adsorption locations, energetics, coverages, and interaction mechanisms on the metal surface, which provided important information to understand the initial metal oxidation process. Despite these efforts, traditional DFT simulations are often limited to gas/solid interfaces with fixed electronic states, which do not accurately reflect the dynamic nature of realistic electrochemical environments. The varying electrochemical potential at the surface-electrolyte interface significantly impacts the corrosion mechanism, where electron transfer plays a pivotal role. Recent computational advancements have tackled these challenges by incorporating constant potential simulations, such as grand canonical DFT (GC-DFT), combined with explicit or implicit solvation models to more accurately simulate electrochemical environments. GC-DFT offers a more realistic interpretation of the electrochemical interface by dynamically adjusting the Fermi level to maintain a constant electrode potential. For instance, several researchers have used this method to study the water/Pt interface under varying electrode potentials and observed that applied potentials can significantly alter the properties of near-surface water layers, the hydrogen bonding network, and the adsorption characteristics of different surface species. In this study, we employed grand canonical DFT simulations along with a hybrid explicit/implicit solvation method to examine the Fe(100)-water interface under varying electrode potentials. First, we present the behaviour of the inner Helmholtz water layer under different potentials. Subsequently, we systematically investigate the role of dissolved oxygen in the initial stages of oxidation and explore the mechanism of water dissociation on the metal surface. Through this approach, we aim to better insights into how electrochemical conditions influence the early stages of iron oxidation.