Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/111305
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dc.contributor.authorHoffmann, Noah-
dc.contributor.authorCerqueira, Tiago F.T.-
dc.contributor.authorBorlido, Pedro-
dc.contributor.authorSanna, Antonio-
dc.contributor.authorSchmidt, Jonathan-
dc.contributor.authorMarques, Miguel-
dc.date.accessioned2023-10-20T11:35:30Z-
dc.date.available2023-10-20T11:35:30Z-
dc.date.issued2023-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/113259-
dc.identifier.urihttp://dx.doi.org/10.25673/111305-
dc.description.abstractHeusler compounds attract a great deal of attention from researchers thanks to a wealth of interesting properties, among which is superconductivity. Here we perform an extensive study of the superconducting and elastic properties of the cubic (full-)Heusler family using a mixture of ab initio methods, as well as interpretable and predictive machine-learning models. By analyzing the statistical distributions of these properties and comparing them to anti-perovskites, we recognize universal behaviors that should be common to all conventional superconductors while others turn out to be specific to the material family. In total, we discover a total of eight hypothetical materials with critical temperatures above 10 K to be compared with the current record of Tc = 4.7 K in this family. Furthermore, we expect most of these materials to be highly ductile, making them potential candidates for the manufacture of wires and tapes for superconducting magnets.eng
dc.language.isoeng-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subject.ddc530-
dc.titleSearching for ductile superconducting Heusler X2YZ compoundseng
dc.typeArticle-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitlenpj computational materials-
local.bibliographicCitation.volume9-
local.bibliographicCitation.publishernameNature Publ. Group-
local.bibliographicCitation.publisherplaceLondon-
local.bibliographicCitation.doi10.1038/s41524-023-01084-7-
local.openaccesstrue-
dc.identifier.ppn1866732617-
cbs.publication.displayform2023-
local.bibliographicCitation.year2023-
cbs.sru.importDate2023-10-20T11:35:01Z-
local.bibliographicCitationEnthalten in npj computational materials - London : Nature Publ. Group, 2015-
local.accessrights.dnbfree-
Appears in Collections:Open Access Publikationen der MLU

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