Title Titel
npj Computational Materials
 
e-ISSN
2057-3960
 
ISSN
2057-3960
 
Publisher Herausgeber
NATURE PORTFOLIO
 
Publisher's Address Herausgeber Adresse
HEIDELBERGER PLATZ 3, BERLIN, Germany, 14197
 
Listed in SCI Aufgelistet im SCI
 
Peer reviewed Begutachtet
 
Listed in DOAJ Aufgelisted im DOAJ
 

Publications Publikationen

Results 1-14 of 14 (Search time: 0.008 seconds).

PreviewAuthor(s)TitleTypeIssue Date
1Liao, Ke ; Li, Xin-Zheng ; Alavi, Ali ; Grüneis, Andreas A comparative study using state-of-the-art electronic structure theories on solid hydrogen phases under high pressuresArtikel Article 2019
2Herzog, Basile ; Gallo, Alejandro ; Hummel, Felix ; Badawi, Michael ; Bučko, Tomáš ; Lebègue, Sébastien ; Grüneis, Andreas ; Rocca, Dario Coupled cluster finite temperature simulations of periodic materials via machine learningArticle Artikel 4-Apr-2024
3Arrigoni, Marco ; Madsen, Georg K. H. Evolutionary computing and machine learning for discovering of low-energy defect configurationsArtikel Article 2021
4Borlido, Pedro ; Schmidt, Jonathan ; Huran, Ahmad W. ; Tran, Fabien ; Marques, Miguel A. L. ; Botti, Silvana Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learningArtikel Article 2020
5Oezelt, Harald ; Qu, Luman ; Kovacs, Alexander ; Fischbacher, Johann ; Gusenbauer, Markus ; Beigelbeck, Roman ; Praetorius, Dirk ; Masao, Yano ; Shoji, Tetsuya ; Kato, Akira ; Chantrell, Roy ; Winklhofer, Michael ; Zimanyi, Gergely ; Schrefl, Thomas Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversalArtikel Article 2022
6Legenstein, Lukas ; Reicht, Lukas ; Wieser, Sandro ; Simoncelli, Michele ; Zojer, Egbert Heat transport in crystalline organic semiconductors: coexistence of phonon propagation and tunnelingArticle Artikel 14-Feb-2025
7Fava, Mauro ; Protik, Nakib Haider ; Li, Chunhua ; Ravichandran, Navaneetha Krishnan ; Carrete, Jesus ; Roekeghem, Ambroise v. ; Madsen, Georg ; Mingo, Natalio ; Broido, David How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles studyArtikel Article 2021
8Chen, Siyu ; Wei, Yao ; Monserrat, Bartomeu ; Tomczak, Jan M. ; Poncé, Samuel Impact of electronic correlations on the superconductivity of high-pressure CeH₉Article Artikel 14-Jan-2026
9Fried, Henry Phillip ; Barragan-Yani, Daniel ; Libisch, Florian ; Wirtz, Ludger A machine learning approach to predict tight-binding parameters for point defects via the projected density of statesArticle Artikel 11-Jun-2025
10Birschitzky, Viktor ; Ellinger, F ; Diebold, Ulrike ; Reticcioli, Michele ; Franchini, Cesare Machine learning for exploring small polaron configurational spaceArticle Artikel 2022
11Schattauer, Christoph ; Todorović, Milica ; Ghosh, Kunal ; Rinke, Patrick ; Libisch, Florian Machine learning sparse tight-binding parameters for defectsArticle Artikel 20-May-2022
12Birschitzky-2024-npj Computational Materials-vor.pdf.jpgBirschitzky, Viktor ; Sokolovic, Igor ; Prezzi, Michael ; Palotás, Krisztián ; Setvin, Martin ; Diebold, Ulrike ; Reticcioli, Michele ; Franchini, Cesare Machine learning-based prediction of polaron-vacancy patterns on the TiO₂(110) surfaceArticle Artikel 2024
13Lin, Shuyao ; Casillas-Trujillo, Luis ; Tasnádi, Ferenc ; Hultman, Lars ; Mayrhofer, Paul H. ; Sangiovanni, Davide G. ; Koutná, Nikola Machine-learning potentials for nanoscale simulations of tensile deformation and fracture in ceramicsArticle Artikel 2-Apr-2024
14Parzer, Michael ; Riss, Alexander ; Garmroudi, Fabian ; de Boor, Johannes ; Mori, Takao ; Bauer, Ernst SeeBand: a highly efficient, interactive tool for analyzing electronic transport dataArticle Artikel 2025