OrbNet Denali is a neural network potential (NNP) method from Anders S. Christensen and co-workers at Iambic Therapeutics (then Entos) in 2021.
Read the OrbNet Denali preprint. Read the OrbNet Denali paper.
About OrbNet Denali | |
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Architecture | custom |
Dataset | custom |
Dataset Level of Theory | ωB97X-D3/def2-TZVP |
Dataset Size | 2.3M |
GMTKN55 (download) is a high-accuracy molecular benchmark that measures basic properties, reaction energies, and noncovalent interactions. The GMTKN55 benchmark comprises 55 subsets. Each subset contains a number of relative energy measurements computed at the CCSD(T) level of theory. When viewing subset-level results, the mean absolute deviation/error (MAD/MAE) in kcal/mol is shown. Each subset is assigned a difficulty weight (see Section 4). When viewing category-level results, the weighted total mean absolute deviation (using the WTMAD-2 weights) is shown. See all GMTKN55 results.
Name | Incomplete Subsets | Benchmarked By | ||||||
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ωB97M-D3BJ/def2-QZVP | 2.86 | 5.77 | 2.34 | 4.54 | 3.63 | 4.04 | link | |
B3LYP-D3BJ/def2-QZVP | 7.99 | 10.16 | 4.11 | 5.65 | 4.82 | 6.18 | link | |
OrbNet Denali | 11.97 | 4.62 | 10.49 | 8.36 | 14.06 | 9.89 | link | |
B97-3c | 11.99 | 10.51 | 9.17 | 8.62 | 11.89 | 10.16 | link | |
GFN2-xTB | 20.02 | 19.77 | 13.66 | 24.58 | 11.44 | 18.65 | link |