{"id":1184953,"date":"2026-08-27T12:35:06","date_gmt":"2026-08-27T19:35:06","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/molecular-implementation-of-the-machine-learned-skala-exchange-correlation-functional-in-cp2k-through-gauxc\/"},"modified":"2026-09-02T17:43:31","modified_gmt":"2026-09-03T00:43:31","slug":"molecular-implementation-of-the-machine-learned-skala-exchange-correlation-functional-in-cp2k-through-gauxc","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/molecular-implementation-of-the-machine-learned-skala-exchange-correlation-functional-in-cp2k-through-gauxc\/","title":{"rendered":"Molecular Implementation of the Machine-Learned Skala Exchange-Correlation Functional in CP2K through GauXC"},"content":{"rendered":"\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Machine-learned exchange&#8211;correlation (XC) functionals offer a route to improve Kohn&#8211;Sham density-functional theory without incurring the cost of explicitly correlated electronic-structure methods. Their use in production simulation codes, however, requires a well-defined mapping between the learned model and the host-code density representation. We formulate and implement a Skala-1.1 interface in CP2K through the external GauXC library. CP2K supplies the geometry, Gaussian basis, spin-resolved atomic-orbital density matrix, and communicator, while GauXC evaluates the XC energy, atomic-orbital potential matrix, and available nuclear derivatives. The interface accepts both all-electron and valence-only density matrices. The latter may arise from separable dual-space pseudopotentials or molecular effective-core potentials. Implementation errors are isolated from functional differences by comparing the Perdew&#8211;Burke&#8211;Ernzerhof (PBE) functional evaluated through GauXC with native CP2K PBE. The resulting interface gives consistent energies, forces validated against finite-difference total-energy checks, and force-based molecular-virial diagnostics for representative molecular cases. The dietGMTKN55 benchmark suite is evaluated with an all-electron Gaussian augmented plane-wave treatment for elements up to bromine and def2 effective-core potentials for the heavier elements. The resulting aggregate mean absolute deviation of 1.255 kcal\/mol is within 0.020 kcal\/mol of the corresponding Skala reference value of 1.235 kcal\/mol. This work establishes a validated molecular implementation of Skala in CP2K through GauXC.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine-learned exchange&#8211;correlation (XC) functionals offer a route to improve Kohn&#8211;Sham density-functional theory without incurring the cost of explicitly correlated electronic-structure methods. Their use in production simulation codes, however, requires a well-defined mapping between the learned model and the host-code density representation. We formulate and implement a Skala-1.1 interface in CP2K through the external GauXC library. [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"text","value":"Franz P&ouml;schel","user_id":0},{"type":"text","value":"Johann Pototschnig","user_id":0},{"type":"text","value":"Frederick Stein","user_id":0},{"type":"text","value":"A. 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