000893317 001__ 893317 000893317 005__ 20230111074310.0 000893317 037__ $$aFZJ-2021-02691 000893317 1001_ $$0P:(DE-Juel1)130545$$aBihlmayer, Gustav$$b0$$eCorresponding author$$ufzj 000893317 1112_ $$aSPIE Optics & Phtotonics Conference, Spintronics XIII$$conline$$d2020-08-25 - 2020-08-28$$wUSA 000893317 245__ $$aDeriving spin-models from DFT: Challanges and Limitations 000893317 260__ $$c2020 000893317 3367_ $$033$$2EndNote$$aConference Paper 000893317 3367_ $$2DataCite$$aOther 000893317 3367_ $$2BibTeX$$aINPROCEEDINGS 000893317 3367_ $$2DRIVER$$aconferenceObject 000893317 3367_ $$2ORCID$$aLECTURE_SPEECH 000893317 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1625843031_1328$$xInvited 000893317 520__ $$aWe examine the mapping of density functional theory (DFT) calculations to spin models for the determination of magnetic properties on larger length scales, e.g. for chiral domain walls, skyrmions, or spin-spiral ground states. While careful tests, using different DFT methods and magnetic sampling configurations allow getting converged results for the exchange parameters [1], it is not so clear that they give a reliable account of the material properties. This can be due to a methodologically enforced truncation of the expansion (e.g. finite sampling in real / reciprocal space) or a neglect of terms in the spin model Hamiltonian. E.g. for the B20 compound FeGe some properties like the period of the spin-spiral in the ground state are at variance with experimental findings, while others like the Curie temperature agree reasonably [2]. We argue that in many cases the underlying spin model is too simplified to capture the full complexity embedded in the electronic structure and the recent discovery of new magnetic interactions in these compounds supports this view [3]. [1] B. Zimmermann et al., Phys. Rev. B 99, 214426 (2019)[2] S. Grytsiuk et al., Phys. Rev. B 100, 214406 (2019)[3] S. Grytsiuk et al., Nature Commun. 11, 511 (2020) 000893317 536__ $$0G:(DE-HGF)POF4-5211$$a5211 - Topological Matter (POF4-521)$$cPOF4-521$$fPOF IV$$x0 000893317 7001_ $$0P:(DE-Juel1)131065$$aZimmermann, Bernd$$b1 000893317 7001_ $$0P:(DE-Juel1)169958$$aGrytsiuk, Sergii$$b2$$ufzj 000893317 7001_ $$0P:(DE-Juel1)162311$$aHoffmann, Markus$$b3$$ufzj 000893317 7001_ $$0P:(DE-Juel1)130548$$aBlügel, Stefan$$b4$$ufzj 000893317 909CO $$ooai:juser.fz-juelich.de:893317$$pVDB 000893317 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130545$$aForschungszentrum Jülich$$b0$$kFZJ 000893317 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169958$$aForschungszentrum Jülich$$b2$$kFZJ 000893317 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162311$$aForschungszentrum Jülich$$b3$$kFZJ 000893317 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)130548$$aForschungszentrum Jülich$$b4$$kFZJ 000893317 9131_ $$0G:(DE-HGF)POF4-521$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5211$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vQuantum Materials$$x0 000893317 9141_ $$y2021 000893317 920__ $$lyes 000893317 9201_ $$0I:(DE-Juel1)IAS-1-20090406$$kIAS-1$$lQuanten-Theorie der Materialien$$x0 000893317 9201_ $$0I:(DE-Juel1)PGI-1-20110106$$kPGI-1$$lQuanten-Theorie der Materialien$$x1 000893317 9201_ $$0I:(DE-82)080009_20140620$$kJARA-FIT$$lJARA-FIT$$x2 000893317 9201_ $$0I:(DE-82)080012_20140620$$kJARA-HPC$$lJARA - HPC$$x3 000893317 980__ $$aconf 000893317 980__ $$aVDB 000893317 980__ $$aI:(DE-Juel1)IAS-1-20090406 000893317 980__ $$aI:(DE-Juel1)PGI-1-20110106 000893317 980__ $$aI:(DE-82)080009_20140620 000893317 980__ $$aI:(DE-82)080012_20140620 000893317 980__ $$aUNRESTRICTED