As first-order saddle points, TSs represent an unstable, high-energy state that is transient in nature, often existing on the order of femtoseconds. Hence, TSs are difficult to isolate experimentally. As an alternative, computational methods grounded in quantum mechanics offer a strategy to model chemical reactions. Quantum mechanical (QM) methods can calculate the energies of chemical species and be paired with optimisation algorithms that iteratively adjust atomic positions to systematically explore the PES. This allows for the identification of energy minima and saddle points, enabling the computation of the reactant, product and TS geometries. One of the most widely employed QM approaches is density functional theory (DFT), which approximates the electron density of a chemical system to calculate the system's energy. While DFT has proven highly effective for problems involving small molecules, its QM foundations result in the method scaling with 𝑂(𝑛 ! ), where n is the number of Kohn-Sham orbitals. The computational expense becomes prohibitive at approximately 200 atoms -individual calculations typically take hours or days, depending on the size of the system, with mechanistic studies therefore taking weeks or months to complete. Consequently, QM methods, including DFT, are not able to provide a universal, affordable solution to mechanistic problems.