Both the content and the depth profile of the oxygen distribution is highly contentious since OD-Cu is easily re-oxidized when it is characterized by ex-situ methods limiting experimental capability to assess active and selective ensembles during operation. To gain an insight on the OD-Cu structures in eCO2RR we trained an accurate neural network potential to address the highly dynamic nature of the catalysts strongly coupled to the history of the sample and to the reaction conditions. Based on the OD-Cu structure, the structure under different conditions and distributions of active sites were obtained paving the way for their control.