Figure3

FT<sup>2</sup>DP: large atomic model fine-tuned machine learning potential for accelerating atomistic simulation of iron-based Fischer-Tropsch synthesis

Figure 3. Validation results of the FT$$ ^2 $$DP model after fine-tuning on the entire dataset. Figures on the left are the parity plots comparing formation energies (A) and forces (B) from FT$$ ^2 $$DP against those from DFT on the dataset, with R$$ ^2 $$ equal to 1.000 and 0.9570, respectively. Figures on the right illustrate the violin plots of (C) distribution of DFT formation energies and atomic forces of the FT$$ ^2 $$DP dataset and (D) distribution of difference in energies and atomic forces between FT$$ ^2 $$DP predictions and DFT results on this dataset, and a box-plot without outlier is used to show the detailed distribution inside the peak region. FT$$ ^2 $$DP: Fine-tuned Fischer-Tropsch deep potential; DFT: density-functional theory.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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