This article investigates the stability and lifetime of diffusion-trapped oxygen in oxide-derived copper (OD-Cu) catalysts used for electrochemical CO₂ reduction. Using large-scale molecular dynamics simulations with a neural network potential trained on first-principles data, the study reveals that oxygen concentration in OD-Cu increases with pH, potential, or specific surface area. While the catalyst can be fully reduced to Cu, removing all trapped oxygen takes considerable time. The highly reconstructed Cu surface provides multiple oxygen adsorption sites, but surface oxygen atoms are not stable under common experimental conditions. The study provides insights into the evolution of OD-Cu catalysts and residual oxygen during reaction, as well as the nature of active sites. OD-Cu catalysts are promising for CO₂ reduction due to their ability to produce C₂+ products at high reaction rates and faradaic efficiency. However, their dynamic behavior under experimental conditions leads to controversy regarding their real structure. Experimental and computational studies show that OD-Cu can be reduced in the bulk, but residual oxygen can be trapped, enhancing the electrocatalytic process. The morphology of OD-Cu evolves rapidly under CO₂ reduction conditions, with initial formation of Cu aggregates that change into Cu₂O nanocubes under air exposure. Oxygen species under reductive conditions were investigated using grazing incidence hard X-ray photoelectron spectroscopy, revealing oxygen depth distribution profiles. The study uses a neural network potential (NNP) to simulate the dynamic behavior of OD-Cu under various conditions. The results show that the oxygen concentration in OD-Cu depends on pH, potential, and specific surface area. The most stable configuration of OD-Cu has a higher oxygen concentration under higher pH, potential, or specific surface area. Oxygen tends to aggregate to form Cu₂O on the surface and inside the bulk to reduce energy. In long electrochemical experiments, OD-Cu reduces to Cu, but removing all trapped oxygen takes considerable time. The highly reconstructed Cu surface provides sites with widely distributed oxygen adsorption energy values, although residual oxygen will be reduced under common experimental conditions. The study also examines the reoxidation of reduced OD-Cu under air exposure or pulsed potential. The results show that oxygen diffuses into the interior of the material, forming an oxide layer. The composition of the oxide layer changes with temperature and time, and the thickness of the oxide layer is comparable to experimental findings. The study also identifies active sites on the surface of OD-Cu using graph theory, revealing different types of active sites with varying oxygen desorption energies. The results show that the oxygen desorption energy varies depending on the type of active site and the pH and electric potential. The study provides a systematic approach for understanding the material changes from bulk to surface during operando conditions, not only from a thermodynamic perspective but also from a kinetic standpoint. The results show that the oxygen content of OD-Cu is highly dependent on the pH and electric potential, with Cu₂O reduced toThis article investigates the stability and lifetime of diffusion-trapped oxygen in oxide-derived copper (OD-Cu) catalysts used for electrochemical CO₂ reduction. Using large-scale molecular dynamics simulations with a neural network potential trained on first-principles data, the study reveals that oxygen concentration in OD-Cu increases with pH, potential, or specific surface area. While the catalyst can be fully reduced to Cu, removing all trapped oxygen takes considerable time. The highly reconstructed Cu surface provides multiple oxygen adsorption sites, but surface oxygen atoms are not stable under common experimental conditions. The study provides insights into the evolution of OD-Cu catalysts and residual oxygen during reaction, as well as the nature of active sites. OD-Cu catalysts are promising for CO₂ reduction due to their ability to produce C₂+ products at high reaction rates and faradaic efficiency. However, their dynamic behavior under experimental conditions leads to controversy regarding their real structure. Experimental and computational studies show that OD-Cu can be reduced in the bulk, but residual oxygen can be trapped, enhancing the electrocatalytic process. The morphology of OD-Cu evolves rapidly under CO₂ reduction conditions, with initial formation of Cu aggregates that change into Cu₂O nanocubes under air exposure. Oxygen species under reductive conditions were investigated using grazing incidence hard X-ray photoelectron spectroscopy, revealing oxygen depth distribution profiles. The study uses a neural network potential (NNP) to simulate the dynamic behavior of OD-Cu under various conditions. The results show that the oxygen concentration in OD-Cu depends on pH, potential, and specific surface area. The most stable configuration of OD-Cu has a higher oxygen concentration under higher pH, potential, or specific surface area. Oxygen tends to aggregate to form Cu₂O on the surface and inside the bulk to reduce energy. In long electrochemical experiments, OD-Cu reduces to Cu, but removing all trapped oxygen takes considerable time. The highly reconstructed Cu surface provides sites with widely distributed oxygen adsorption energy values, although residual oxygen will be reduced under common experimental conditions. The study also examines the reoxidation of reduced OD-Cu under air exposure or pulsed potential. The results show that oxygen diffuses into the interior of the material, forming an oxide layer. The composition of the oxide layer changes with temperature and time, and the thickness of the oxide layer is comparable to experimental findings. The study also identifies active sites on the surface of OD-Cu using graph theory, revealing different types of active sites with varying oxygen desorption energies. The results show that the oxygen desorption energy varies depending on the type of active site and the pH and electric potential. The study provides a systematic approach for understanding the material changes from bulk to surface during operando conditions, not only from a thermodynamic perspective but also from a kinetic standpoint. The results show that the oxygen content of OD-Cu is highly dependent on the pH and electric potential, with Cu₂O reduced to