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001020057 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-05858
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001020057 1001_ $$0P:(DE-Juel1)186072$$aWasmer, Johannes$$b0$$eCorresponding author$$ufzj
001020057 1112_ $$aDPG SKM 2023$$cDresden$$d2023-03-26 - 2023-03-31$$gSKM23$$wGermany
001020057 245__ $$aBenchmark study of symmetry-adapted ML-DFT models for magnetically doped topological insulators
001020057 260__ $$c2022
001020057 3367_ $$033$$2EndNote$$aConference Paper
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001020057 500__ $$ahttps://www.dpg-verhandlungen.de/year/2023/conference/skm/part/ma/session/10/contribution/1
001020057 502__ $$cRWTH Aachen University
001020057 520__ $$aWe present a benchmark study of surrogate models for impurities embedded into crystalline solids. Using the Korringa-Kohn-Rostoker Green Function method [1], we have built databases of several thousand calculations of single impurities (monomers) embedded into different elemental crystals, as well as magnetic transition metal impurity dimers embedded in the topological insulator Bi2Te3. We predict the converged monomer impurity electron potential and the isotropic exchange interaction of the impurity dimer in the classical Heisenberg model. From these surrogates, we intend to build transferable models for larger systems in the future, which will accelerate the convergence of our DFT codes. The study compares various recent E(3)-equivariant models such as ACE and MACE [2] in terms of performance and reproducible end-to-end workflows.[1] P. Rüßmann et al., npj Comput Mater 7, 13 (2021)[2] I. Batatia et al., arXiv:2206.07697 (2022)
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001020057 536__ $$0G:(DE-Juel1)HDS-LEE-20190612$$aHDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612)$$cHDS-LEE-20190612$$x3
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001020057 7001_ $$0P:(DE-Juel1)185917$$aMozumder, Rubel$$b1$$eContributor
001020057 7001_ $$0P:(DE-Juel1)157882$$aRüssmann, Philipp$$b2$$ufzj
001020057 7001_ $$0P:(DE-Juel1)188313$$aAssent, Ira$$b3$$ufzj
001020057 7001_ $$0P:(DE-Juel1)130548$$aBlügel, Stefan$$b4$$ufzj
001020057 8564_ $$uhttps://iffgit.fz-juelich.de/phd-project-wasmer/presentations/2023-03-26-talk-skm23
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001020057 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x1
001020057 9141_ $$y2023
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