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Tag: 2024

Phonons from density-functional perturbation theory using the all-electron full-potential linearized augmented plane-wave method FLEUR

Phonons from density-functional perturbation theory using the all-electron full-potential linearized augmented plane-wave method FLEUR

C.-R. Gerhorst, A. Neukirchen, D. A. Klüppelberg, G. Bihlmayer, M. Betzinger, G. Michalicek, D. Wortmann, and S. Blügel

Electron. Struct. 6, 017001 (2024) DOI:10.1088/2516-1075/ad1614

The NOMAD mini-apps: A suite of kernels from ab initio electronic structure codes enabling co-design in high-performance computing

The NOMAD mini-apps: A suite of kernels from ab initio electronic structure codes enabling co-design in high-performance computing

I. Mas Magre, R. Grima Torres, J. M. Cela Espín, and J. J. Gutiérrez Moreno

Open Res Europe 2024, 4:35 (2024) DOI:10.12688/openreseurope.16920.2

Density functional Bogoliubov-de Gennes theory for superconductors implemented in the SIESTA code

Density functional Bogoliubov-de Gennes theory for superconductors implemented in the SIESTA code

R. Reho, N. Wittemeier, A.H. Kole, O. Ordejon, and Z. Zanolli

Phys. Rev. B 110, 094109 (2024) DOI:10.1103/PhysRevB.110.134505

High-temperature and high-pressure thermoelasticity of hcp metals from ab initio quasiharmonic free energy calculations: The beryllium case

High-temperature and high-pressure thermoelasticity of hcp metals from ab initio quasiharmonic free energy calculations: The beryllium case

X. Gong and A. Dal Corso

Phys. Rev. B 110, 094109 (2024) DOI:10.1103/PhysRevB.110.094109

Thermal transport of glasses via machine learning driven simulations

Thermal transport of glasses via machine learning driven simulations

P. Pegolo and F. Grasselli

Front. Mater., Sec. Ceramics and Glass, 11 (2024) DOI: 10.3389/fmats.2024.1369034

Quantum ESPRESSO towards performance portability: GPU offload with OpenMP

Quantum ESPRESSO towards performance portability: GPU offload with OpenMP

F. Ferrari Ruffino, L. Bellentani, G. Rossi, F. Affinito, S. Baroni, O. Baseggio, P. Delugas, P. Giannozzi, J. Kurzak, Y. Luog, O. O’Reilly, S. Orlandini, and I. Carnimeo

Procedia Computer Science, 240 (2024) DOI: 10.12688/openreseurope.16920.2

Co-designing ab initio electronic structure methods on a RISC-V vector architecture

Co-designing ab initio electronic structure methods on a RISC-V vector architecture

R. Grima Torres, P. Vizcaíno, F. Mantovani, and J. J. Gutiérrez Moreno

Open Res Europe 2024, 4:165 (2024) DOI: 10.12688/openreseurope.18321.1

Ab initio quasi-harmonic thermoelasticity of molybdenum at high temperature and pressure

Ab initio quasi-harmonic thermoelasticity of molybdenum at high temperature and pressure

X. Gong and A. Del Corso

J. Chem. Phys. 160, 244703 (2024) DOI: 10.1063/5.0212162

Pressure and temperature dependent ab-initio quasi-harmonic thermoelastic properties of tungsten

Pressure and temperature dependent ab-initio quasi-harmonic thermoelastic properties of tungsten

X. Gong and A. Del Corso

J. Phys.: Condens. Matter 36, 285702 (2024) DOI: 10.1088/1361-648X/ad3ac3

Evidence of ferroelectric features in low-density supercooled water from ab initio deep neural-network simulations

Evidence of ferroelectric features in low-density supercooled water from ab initio deep neural-network simulations

C. Malosso, N. Manko, M. G. Izzo, S. Baroni, and A. Hassanali

PNAS, 121 (32) e2407295121 (2024) DOI: 10.1073/pnas.2407295121

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MaX – Materials design at the eXascale has received funding from the European High Performance Computing Joint Undertaking and Participating Countries in Project (Czechia, France, Germany, Italy, Slovenia, and Spain) under grant agreement no. 101093374.

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