For a given set of parameters, we initially optimise the different bulk phases of the system and compute the respective equation of states (EOS). From these calculations, the minimum volume V 0 , the lattice parameters (a 0 , b 0 , c 0 , α 0 , β 0 , γ 0 ), the cohesive energy E coh , energy differences ∆E and the bulk modulus B 0 are obtained. Next, the different surface structures are generated based on the minimum lattice parameters of the given parameter set. Apart from the surface energies γ hkl of the different facets, the energetics (adsorption energies E ad , dimer interaction energies E int,dimer ) of the characteristic adsorption sites and the coveragedependent adsorption are analysed. Due to the newly implemented force-based optimiser, it is possible to fix some degrees of freedom in the system, enabling simple integration of metastable and unstable surface structures into the training. Following the terrace-step-kink model , we use well-chosen diffusion processes to train the surface kinetics. Their minimum energy paths and activation energies (E for a (forward), E rev a (reversed)) are computed utilising NEB calculations. Finally, the vibrational frequencies ν i are determined for the initial, transition, and final state to derive the pre-exponential factors k for 0 and k rev 0 . All obtained quantities are referenced against the training set data to calculate the error value for the given parameter set using the error function defined in Eq. (11). We repeat this procedure for each new parameter set until an appropriate termination criterion is reached.