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Computational screening of materials with extreme gap deformation potentials

npj Computational Materials 2022年第1期8卷 1482-1491页

作者： pedro borlido Jonathan Schmidt Hai-Chen Wang Silvana Botti Miguel A.L.Marques Institut für Festkörpertheorie und-optik Friedrich-Schiller-Universität Jena and European Theoretical Spectroscopy FacilityMax-Wien-Platz 107743JenaGermany CFisUC Department of PhysicsUniversity of CoimbraRua Larga3004-516CoimbraPortugal Institut für Physik Martin-Luther-Universität Halle-WittenbergD-06099HalleGermany

In this work,we present a large-scale study of gap deformation potentials based on density-functional theory calculations for over 5000 *** expected,in most cases the band gap decreases for increasing volume with deformation potentials that can reach values of almost−15 *** find,however,also a sizeable number of materials with positive deformation *** members of this group are halide perovskites,known for their applications in *** then focus on understanding the physical reasons for so different values of the deformation potentials by investigating the correlations between this property and a large number of other material and compositional *** also train explainable machine learning models as well as graph convolutional networks to predict deformation potentials and establish simple rules to understand predicted ***,we analyze in more detail a series of materials that have record positive and negative deformation potentials.

关键词： deformation properties. extreme

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Searching for ductile superconducting Heusler X_(2)YZ compounds

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npj Computational Materials 2023年第1期9卷 919-927页

作者： Noah Hoffmann Tiago F.T.Cerqueira pedro borlido Antonio Sanna Jonathan Schmidt Miguel A.L.Marques Institut für Physik Martin-Luther-Universität Halle-WittenbergD-06099 HalleGermany CFisUC Department of PhysicsUniversity of CoimbraRua Larga 3004-516 CoimbraPortugal Max-Planck-Institut für Mikrostrukturphysik Weinberg 2D-06120 HalleGermany

Heusler compounds attract a great deal of attention from researchers thanks to a wealth of interesting properties,among which is *** 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 *** 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 *** total,we discover a total of eight hypothetical materials with critical temperatures above 10 K to be compared with the current record of T_(c)=4.7 K in this ***,we expect most of these materials to be highly ductile,making them potential candidates for the manufacture of wires and tapes for superconducting magnets.

关键词： ductile compounds superconducting

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Exchange-correlation functionals for band gaps of solids:benchmark,reparametrization and machine learning

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npj Computational Materials 2020年第1期6卷 869-885页

作者： pedro borlido Jonathan Schmidt Ahmad W.Huran Fabien Tran Miguel A.L.Marques Silvana Botti Institut für Festkörpertheorie und-optik Friedrich-Schiller-Universität Jena and European Theoretical Spectroscopy FacilityMax-Wien-Platz 107743 JenaGermany Institut für Physik Martin-Luther-Universität Halle-Wittenberg06099 HalleGermany Institute of Materials Chemistry Vienna University of TechnologyGetreidemarkt 9/165-TC1060 ViennaAustria

We conducted a large-scale density-functional theory study on the influence of the exchange-correlation functional in the calculation of electronic band gaps of ***,we use the large materials data set that we have recently proposed to benchmark 21 different functionals,with a particular focus on approximations of the meta-generalized-gradient *** these data with the results for 12 functionals in our previous work,we can analyze in detail the characteristics of each approximation and identify its strong and/or weak *** confirming that mBJ,HLE16 and HSE06 are the most accurate functionals for band gap calculations,we reveal several other interesting functionals,chief among which are the local Slater potential approximation,the GGA AK13LDA,and the meta-GGAs HLE17 and *** also compare the computational efficiency of these different *** on these data,we investigate the potential for improvement of a promising subset of functionals by varying their internal *** identified optimal parameters yield a family of functionals fitted for the calculation of band ***,we demonstrate how to train machine learning models for accurate band gap prediction,using as input structural and composition data,as well as approximate band gaps obtained from density-functional theory.

关键词： theory functionals solids

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