These approaches initially employ low-accuracy and less computationally demanding quantum mechanics (QM) methods combined with sampling algorithms to explore the potential energy surface (PES). Subsequently, more accurate and computationally expensive quantum chemistry methods are applied to obtain precise configurations. In such approaches, it is essential to establish correlations between the methods used at each step. The aforementioned difficulties present a bottleneck in the application of quantum chemistry to large clusters.