Aerosol particles undergo physical and chemical changes during cloud processes. In this work, we quantified the changes in aerosol mixing state using a particle-resolved model. To this end, we coupled the particle-resolved aerosol model PartMC-MOSAIC with the aqueous chemistry module CAPRAM 2.4 and designed cloud parcel simulations that mimicked several cloud cycles that a particle population may be exposed to in an urban environment. Aqueous-phase chemistry during these cloud cycles affected aerosol mixing state and the particles’ potential to act as cloud condensation nuclei (CCN) significantly, with the largest differences after the first cloud cycle. The mean size and total dry mass of the population increased by 24% and 219%, respectively, after the first cycle, while the increments were only 5% and 38% after the fourth cycle. The formation of ammonium sulfate and nitrate were responsible for those changes. Cloud processing increased the internally mixed state of all particle populations, with the mixing state index increasing from 50 to 83 percentage points after four cloud cycles. The CCN concentrations for supersaturations lower than 0.23% increased. For example, for supersaturation levels of 0.02%, the CCN concentration increased from 25 to 547 cm^-3. Brownian coagulation led to an increase of the CCN/CN ratio for supersaturation levels higher than 0.2%. The ratio increased by 4.1% at the supersaturation level 0.5%. Total number concentration and CCN concentration decreased by 5.9% and 1.7%, respectively, when Brownian coagulation is considered. These findings highlight the complex influence of cloud processing on particle properties.