To generate low-level SQM activation energies, we optimized all reactions from the high-level dataset using AM1, PM3, and GFN2-xTB methods. Reactions that did not converge successfully were excluded from further analysis. For each reaction, the zeropoint energy was calculated by performing harmonic vibrational analysis and added to the electronic energies of the reactant, product, and transition state. To ensure accuracy, a scaling factor was applied to the computed harmonic frequencies when calculating the zero-point vibrational energy. The scaling factors used were 0.948 for AM1, 0.940 for PM3, and 0.990 for GFN2-xTB. Additionally, the extra features utilized in our study, as listed in Table , were calculated using GFN2-xTB. All SQM calculations were conducted using the ORCA software package. For the Chemprop predictions, we employed an ensemble approach, using five models trained with different initial weights to minimize model bias. ). After hyperparameter optimization, the MAE and RMSE were reduced slightly to 6.16 and 8.86 kcal/mol, respectively. A detailed comparison with other GNN models is available in the Supporting Information (Table ).