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Computer physics communications, ISSN 0010-4655, 11/2015, Volume 196, Issue C, pp. 36 - 44
Journal Article
Physical review. B, ISSN 2469-9950, 06/2017, Volume 95, Issue 23
Journal Article
Computational materials science, ISSN 0927-0256, 01/2014, Volume 81, pp. 446 - 452
•We present design criteria for high-throughput pseudopotentials.•We present and test the GBRV pseudopotential library.•We draw conclusions about the accuracy... 
High-throughput | Pseudopotentials | Density functional theory | Materials Science | Technology | Materials Science, Multidisciplinary | Science & Technology | Availability | Freeware | Accuracy | Computation | Mathematical analysis | Benchmarking | Optimization | Physics - Materials Science
Journal Article
Computational materials science, ISSN 0927-0256, 12/2014, Volume 95, pp. 337 - 350
[Display omitted] •A new PAW data-set and US pseudopotential library is described.•All elements from H to Pu are considered.•Scalar relativistic and fully... 
Pseudopotentials | Electronic structure | Plane-waves | Elements | Materials Science | Technology | Materials Science, Multidisciplinary | Science & Technology
Journal Article
Computational materials science, ISSN 0927-0256, 02/2015, Volume 98, pp. 372 - 389
[Display omitted] •New method to create and validate pseudopotentials from reference eigenvalue sets.•Improved SIESTA pseudopotentials for Ge, Pd, Ag, Sn, Ta,... 
C. SIESTA | B. Density-functional theory | A. Pseudopotentials | Materials Science | Technology | Materials Science, Multidisciplinary | Science & Technology | Computation | Mathematical analysis | Eigenvalues | Tin | Electronics | Pseudopotentials | Benchmarking | Palladium
Journal Article
Journal of physics. D, Applied physics, ISSN 0022-3727, 01/2016, Volume 49, Issue 8, pp. 85104 - 85112
Journal Article
Physical chemistry chemical physics : PCCP, ISSN 1463-9084, 2019, Volume 21, Issue 1, pp. 378 - 395
We study the performance of fourth-order gradient expansions of the kinetic energy density (KED) in semi-local kinetic energy functionals depending on the... 
Physical Sciences | Chemistry | Physics, Atomic, Molecular & Chemical | Chemistry, Physical | Physics | Science & Technology | Thermal expansion | Flux density | Energy | Neural networks | Reproducibility | Dependent variables | Machine learning | Pseudopotentials | Kinetic energy | Tuning
Journal Article