To mitigate the laborious process of synthesizing an extensive array of materials, researchers perform computational screenings to find the most promising materials for their application . These computational screenings usually rely on Monte Carlo simulations, such as configurational-bias Monte Carlo (CBMC) and Grand Canonical Monte Carlo (GCMC) or, more recently, machine learning (ML) models trained on GCMC data .