One of the primary challenges is the substantial computational cost. Quantum mechanical calculations are resource-intensive, especially for large systems or long simulation times. Additionally, accurate modeling of catalytic processes often requires considering the effects of temperature, pressure, and solvent, further increasing the complexity. Despite these challenges, advancements in computational power and algorithms are continually expanding the applicability of AIMD in catalysis.
