fig3

Figure 3. Evaluation of MLFF accuracy. (A) Scatter plot of the energy predictions, demonstrating the MLFF’s high accuracy, with an RMSE for energy within 1 meV/atom, as validated against DFT calculations; (B) Corresponding force predictions plot, where the MLFF achieves an RMSE of less than 0.03 eV/Å, indicating the model’s precision in capturing the forces in the Cu-CO system across a vast configuration space; (C) Comparing the initial CO adsorption configuration with those optimized by DFT and MLFF, showing the MLFF’s ability to replicate DFT-level structural accuracy on Cu surfaces; (D) Histogram of Cu–C bond lengths from stable-state configurations, highlighting the close match between MLFF and DFT results, with bond length discrepancies averaging less than 0.01 Å. MLFF: Machine-learning force field; DFT: density functional theory; RMSE: root mean square error.