In conclusion, the structures of OD-Cu during the reduction process under different conditions were systematically studied via large-scale molecular dynamics at first-principles accuracy with a neural network potential (error 4.58 meV/atom w.r.t. PBE-D2). The oxygen concentration of the OD-Cu materials is strongly dependent on the history of the sample and the reaction conditions, the higher the pH/potential/specific surface area, the higher the oxygen concentration in the most stable OD-Cu configuration. The oxygen atoms tend to aggregate to form Cu2O on the surface and inside the bulk to reduce the energy by lowering the formation energy and surface energy instead of being distributed uniformly. For long electrochemical experiments OD-Cu materials reduce to Cu but requires a considerable time to remove all the trapped oxygen. In addition, the highly reconstructed Cu surface leads to a wide distribution of oxygen adsorption energy sites, increasing the probability of stable residual oxygen at strong reduction potentials. These results not only reveal the dynamics of the stable structure of OD-Cu under different experimental conditions but also give an insight into the formation mechanism of the reduction of OD-Cu and the limits for fine-tuning by controlling experimental conditions.