Running universal machine-learned force fields: Revision history

17 June 2026

• curprev 08:1608:16, 17 June 2026 Liebetreu talk contribs 9,173 bytes +12 No edit summary
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16 June 2026

• curprev 13:0013:00, 16 June 2026 Liebetreu talk contribs m 9,338 bytes 0 Liebetreu moved page Construction:Running universal machine-learned force fields in VASP to Running universal machine-learned force fields: Publish and align title with naming convention
• curprev 12:5912:59, 16 June 2026 Liebetreu talk contribs 9,338 bytes +339 No edit summary

11 June 2026

• curprev 15:1215:12, 11 June 2026 Liebetreu talk contribs 8,999 bytes +13 →Example A: Model inference with the tensorpotential package (GRACE)
• curprev 12:1812:18, 11 June 2026 Liebetreu talk contribs 8,986 bytes +352 →Example A: Model inference with the tensorpotential package (GRACE)
• curprev 12:0912:09, 11 June 2026 Liebetreu talk contribs 8,634 bytes 0 →Example A: Model inference with the tensorpotential package (GRACE)
• curprev 12:0912:09, 11 June 2026 Liebetreu talk contribs 8,634 bytes −1 No edit summary
• curprev 12:0712:07, 11 June 2026 Liebetreu talk contribs 8,635 bytes −19 No edit summary
• curprev 12:0112:01, 11 June 2026 Liebetreu talk contribs 8,654 bytes +1,818 No edit summary

10 June 2026

• curprev 08:5708:57, 10 June 2026 Liebetreu talk contribs 6,836 bytes +4 →Example B: Model inference with the DeePMD-Kit
• curprev 08:1908:19, 10 June 2026 Liebetreu talk contribs 6,832 bytes −16 No edit summary
• curprev 08:1608:16, 10 June 2026 Liebetreu talk contribs 6,848 bytes 0 No edit summary
• curprev 08:1508:15, 10 June 2026 Liebetreu talk contribs 6,848 bytes +334 No edit summary
• curprev 07:4507:45, 10 June 2026 Liebetreu talk contribs 6,514 bytes +58 No edit summary
• curprev 07:4307:43, 10 June 2026 Liebetreu talk contribs 6,456 bytes +32 →Example B:

9 June 2026

• curprev 14:0014:00, 9 June 2026 Liebetreu talk contribs 6,424 bytes +21 No edit summary
• curprev 13:5613:56, 9 June 2026 Liebetreu talk contribs 6,403 bytes +4,241 No edit summary

8 June 2026

• curprev 13:5413:54, 8 June 2026 Liebetreu talk contribs 2,162 bytes +2,162 Created page with "Universal machine-learned force fields (uMLFF, or alternatively: uMLIP for "universal machine-learned interatomic potentials") offer a fast alternative to the computational demands of DFT. Pre-trained uMLFFs can be used as an alternative to {{VASP}}-native force fields to drive essentially every {{VASP}} simulation which uses the the prediction-only mode {{TAG|ML_MODE|run}}. This includes :Category:Molecular_dynamics|molecular..."