We conducted a benchmarking exercise to evaluate the performance of the trained DP. The accuracy of the DP in predicting energies and atomic forces was tested on a dataset consisting of charged and uncharged configurations of DSG not included in the training dataset. The uncharged dataset was based on the u24C system, while the charged dataset comprised of the 1c24C and 2c24C systems. The test dataset consisted of 500 randomly selected configurations from high temperature DFT-MD simulations that were not part of the initial training data. We created parity plots, as shown in Figure , by comparing the energy per atom predictions from the DP and the corresponding DFT results. We calculated the root mean squared errors (RMSE) as a metric to validate the accuracy of the DP. The energies per atom for both the uncharged and the charged datasets were accurately predicted by the DP, with RMSE values of 2.8 × 10 -3 and 2.0 × 10 -3 eV/atom, respectively. These levels of accuracy are similar to those of the DP developed for SSG . In addition to energies, it is critical that a DP predict accurate forces. We have therefore computed the RMSE of the predicted forces. We found that the DP achieved a low RMSE of 0.088 eV/ Å for the charged system and 0.117 eV/ Å for the uncharged one. Describing the lattice dynamics of DSG accurately is an essential requirement for the DP. In our previous work, we tested for structural instabilities in SSG by computing the phonon density of states (PDOS) from the phonon dispersion spectrum . Our DP for SSG, along with the corresponding DFT results, did not show any instabilities for SSG in the form of imaginary frequency modes . We followed similar methods to compute the PDOS for DSG. These phonon calculations were performed within the quasi-harmonic approximation at 0 K using the phonopy and phonolammps packages. We used the primitive cell of DSG (blue monoclinic box in Figure ) to generate the phonon results. Figure shows plots comparing the phonon density of states computed from DP and DFT. We see that DSG does not suffer from instabilities, since there are no modes below 0 THz. We also observe that our DP accurately captures the densities of phonon modes throughout the frequency range. The phonon dispersion curves in Figure indicate that the dispersion behavior of each of the bands is accurately predicted by the DP. This accuracy is consistent across all of the sampled regions of the Brillouin zone. Furthermore, many other thermodynamic properties of DSG were obtained from these dispersion relations via the calculation of the phonon number (n), harmonic phonon energy (E ph ) and the partition function (Z). We report predictions of Helmholtz free energy (A), entropy (S) and constant volume heat capacity (C V ) as plotted in Figure and, respectively. These results were calculated over the temperature range T = 0 to 1000 K. We report the mean absolute error (MAE) and mean absolute percentage error (MAPE) of predictions from DP referenced to DFT in Table , showing that the errors are consistently low for all three properties. The scale at which we perform PT calculations does not account for the effects of thermal-based flexural modes on structural changes. We hypothesized that the thermal fluctuation in DSG is considerably lower than SSG or graphane. We used the DP for DSG to verify our hypothesis by running multiple N V T DP-MD simulations at a fixed temperature T = 300 K in freestanding graphanol as a function of system size. Thermal fluctuation was quantified by measuring the squares of the out-of-plane displacements, w 2 i , which is computed using the z-coordinate of each atom i. DP-MD simulations spanning 50 ps (0.5 fs time steps) were used for system sizes of 648 to 28800 atoms to calculate w 2 i . The ensemble average, ⟨w 2 i ⟩, is calculated for each system size and plotted in Figure . We made use of uncharged DSG to measure thermal fluctuation. This procedure was first implemented for graphene by Ahmadpor et al. . and then by Achar et al. for graphane and SSG . We compared the effects of having a fully functionalized system like DSG by plotting the results for SSG and graphane. Results for SSG and graphane were calculated for similar system sizes and DP-MD temperatures. The fits to the log transform of the scaling law, ln(⟨w 2 i ⟩) = η ln(L) + δ ln(T ), are also plotted in Figure . The slope η of the fitting parameter indicates the sensitivity of the material to the system size for a given temperature, with lower values of η indicating smaller thermal fluctuations. We found that DSG has an η value of 0.20, more than five times lower than SSG or grahane, with 1.10 and 1.07, respectively . This suggests that DSG is less susceptible to thermal fluctuation. The reason for such a low η in DSG is the large H-bonding network on both sides of the graphane layer, which is absent in both SSG and graphane. This implies that PT results for smaller system sizes can be reliably scaled to larger system sizes, which would have been challenging if the thermal fluctuations were large. The final configurations from molecular simulations for DSG and SSG are shown in Figure and, respectively. These configurations were taken from DP-MD simulations of the largest system size, with characteristic length L of 20 nm. These visualizations demonstrate that SSG has much larger thermal fluctuations compared to DSG.