Given the success of our Diffusion Model on our metrics, we attempted to validate some of the CIFs generated by our Diffusion Model. M3GNet is a materials graph neural network that incorporates threebody interactions. M3GNet can be used as an additional predictor of formation energy for all of the CIFs generated by the Diffusion Model . Among the top 35 CIFs with the lowest M3GNet-predicted formation energy, we selected 6 of them to be rigorously analyzed using Vienna Ab Initio Simulation Package (VASP). To prepare the 6 CIFs, slight manual tuning was applied after post-processing to maximize the likelihood that the structure would be realistic and stable. The manual tuning consisted of rounding fractional coordinates to more probable locations such as (0.011, 0.502, 0.009) → (0.0, 0.5, 0.0), and correcting potentially erroneous atomic number assignments as a result of the post-processing (36:Kr → 37:Rb). We calculated the free energy of the 6 selected CIFs, and then performed 4 consecutive structure relaxations to allow the atomic positions to be slightly adjusted each time. The resulting free energy and external pressure values after each relaxation are used to evaluate their stability. The calculated free energy for the pre-relaxed structures (E 0 ) , after the 4th relaxation (E 4 ) and the external pressure on the unit cell in kb after the 1st (P 1 ) and 4th (P 4 ) relaxation are shown below: As expected, all the free energy are lower and the external pressure values are closer to zero for the 4th relaxation, which indicates the VASP optmized the CIFs into even more stable structures. However, it is observed that the 6 CIFs exhibited low free energy and external pressure on the unit cell even from the pre-relaxation and 1st optimization. This is especially apparent for the NaF and SnYF 3 structures, which E 0 and E 4 are very close and the external pressure values after the 1st optimization are very close to 0kb. These are strong indications of the stability of the produced CIFs.