Big-Data Analytics for the Thermal and Electrical Conductivity of Materials from First Principles

Pubblicazioni

Beyond Scaling Relations for the Description of Catalytic Materials

Autori: Mie Andersen, Sergey V. Levchenko, Matthias Scheffler, Karsten Reuter
Pubblicato in: ACS Catalysis, Numero 9/4, 2019, Pagina/e 2752-2759, ISSN 2155-5435
Editore: American Chemical Society
DOI: 10.1021/acscatal.8b04478

NOMAD: The FAIR concept for big data-driven materials science

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: MRS Bulletin, Numero 43/9, 2018, Pagina/e 676-682, ISSN 0883-7694
Editore: Materials Research Society
DOI: 10.1557/mrs.2018.208

SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

Autori: Runhai Ouyang, Stefano Curtarolo, Emre Ahmetcik, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review Materials, Numero 2/8, 2018, ISSN 2475-9953
Editore: American Physical Society
DOI: 10.1103/physrevmaterials.2.083802

Two-to-three dimensional transition in neutral gold clusters: The crucial role of van der Waals interactions and temperature

Autori: Bryan R. Goldsmith, Jacob Florian, Jin-Xun Liu, Philipp Gruene, Jonathan T. Lyon, David M. Rayner, André Fielicke, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review Materials, Numero 3/1, 2019, ISSN 2475-9953
Editore: APS
DOI: 10.1103/physrevmaterials.3.016002

Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO

Autori: Runhai Ouyang, Emre Ahmetcik, Christian Carbogno, Matthias Scheffler, Luca M Ghiringhelli
Pubblicato in: Journal of Physics: Materials, Numero 2/2, 2019, Pagina/e 024002, ISSN 2515-7639
Editore: IOP Publishing
DOI: 10.1088/2515-7639/ab077b

Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition

Autori: Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto, Yury Lysogorskiy, Lars Blumenthal, Thomas Hammerschmidt, Jacek R. Golebiowski, Xiangyue Liu, Angelo Ziletti, Matthias Scheffler
Pubblicato in: npj Computational Materials, Numero 5/1, 2019, ISSN 2057-3960
Editore: Nature Research, Springer Nature
DOI: 10.1038/s41524-019-0239-3

Main-group test set for materials science and engineering with user-friendly graphical tools for error analysis: systematic benchmark of the numerical and intrinsic errors in state-of-the-art electronic-structure approximations

Autori: Igor Ying Zhang, Andrew J Logsdail, Xinguo Ren, Sergey V Levchenko, Luca Ghiringhelli, Matthias Scheffler
Pubblicato in: New Journal of Physics, Numero 21/1, 2019, Pagina/e 013025, ISSN 1367-2630
Editore: Institute of Physics Publishing
DOI: 10.1088/1367-2630/aaf751

New tolerance factor to predict the stability of perovskite oxides and halides

Autori: Christopher J. Bartel, Christopher Sutton, Bryan R. Goldsmith, Runhai Ouyang, Charles B. Musgrave, Luca M. Ghiringhelli, Matthias Scheffler
Pubblicato in: Science Advances, Numero 5/2, 2019, Pagina/e eaav0693, ISSN 2375-2548
Editore: American Association for the Advancement of Science
DOI: 10.1126/sciadv.aav0693

(Meta-)stability and Core–Shell Dynamics of Gold Nanoclusters at Finite Temperature

Autori: Diego Guedes-Sobrinho, Weiqi Wang, Ian P. Hamilton, Juarez L. F. Da Silva, Luca M. Ghiringhelli
Pubblicato in: The Journal of Physical Chemistry Letters, Numero 10/3, 2019, Pagina/e 685-692, ISSN 1948-7185
Editore: American Chemical Society
DOI: 10.1021/acs.jpclett.8b03397

Artificial intelligence for high-throughput discovery of topological insulators: The example of alloyed tetradymites

Autori: Guohua Cao, Runhai Ouyang, Luca M. Ghiringhelli, Matthias Scheffler, Huijun Liu, Christian Carbogno, Zhenyu Zhang
Pubblicato in: Physical Review Materials, Numero 4/3, 2020, ISSN 2475-9953
Editore: APS
DOI: 10.1103/physrevmaterials.4.034204

Determining surface phase diagrams including anharmonic effects

Autori: Yuanyuan Zhou, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review B, Numero 100/17, 2019, ISSN 2469-9950
Editore: APS
DOI: 10.1103/physrevb.100.174106

Electron-phonon coupling in d -electron solids: A temperature-dependent study of rutile Ti O 2 by first-principles theory and two-photon photoemission

Autori: Honghui Shang, Adam Argondizzo, Shijing Tan, Jin Zhao, Patrick Rinke, Christian Carbogno, Matthias Scheffler, Hrvoje Petek
Pubblicato in: Physical Review Research, Numero 1/3, 2019, ISSN 2643-1564
Editore: APS
DOI: 10.1103/physrevresearch.1.033153

Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects

Autori: Andreas Alvermann, Achim Basermann, Hans-Joachim Bungartz, Christian Carbogno, Dominik Ernst, Holger Fehske, Yasunori Futamura, Martin Galgon, Georg Hager, Sarah Huber, Thomas Huckle, Akihiro Ida, Akira Imakura, Masatoshi Kawai, Simone Köcher, Moritz Kreutzer, Pavel Kus, Bruno Lang, Hermann Lederer, Valeriy Manin, Andreas Marek, Kengo Nakajima, Lydia Nemec, Karsten Reuter, Michael Rippl, Melven R
Pubblicato in: Japan Journal of Industrial and Applied Mathematics, Numero 36/2, 2019, Pagina/e 699-717, ISSN 0916-7005
Editore: Kinokuniya Co., Ltd.
DOI: 10.1007/s13160-019-00360-8

Step-flow growth in homoepitaxy of β -Ga 2 O 3 (100)—The influence of the miscut direction and faceting

Autori: R. Schewski, K. Lion, A. Fiedler, C. Wouters, A. Popp, S. V. Levchenko, T. Schulz, M. Schmidbauer, S. Bin Anooz, R. Grüneberg, Z. Galazka, G. Wagner, K. Irmscher, M. Scheffler, C. Draxl, M. Albrecht
Pubblicato in: APL Materials, Numero 7/2, 2019, Pagina/e 022515, ISSN 2166-532X
Editore: American Institute of Physics
DOI: 10.1063/1.5054943

Parametrically constrained geometry relaxations for high-throughput materials science

Autori: Maja-Olivia Lenz, Thomas A. R. Purcell, David Hicks, Stefano Curtarolo, Matthias Scheffler, Christian Carbogno
Pubblicato in: npj Computational Materials, Numero 5/1, 2019, ISSN 2057-3960
Editore: Elsevier
DOI: 10.1038/s41524-019-0254-4

The NOMAD laboratory: from data sharing to artificial intelligence

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: Journal of Physics: Materials, Numero 2/3, 2019, Pagina/e 036001, ISSN 2515-7639
Editore: IOP Publishing
DOI: 10.1088/2515-7639/ab13bb

Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications

Autori: Florian Belviso, Victor E. P. Claerbout, Aleix Comas-Vives, Naresh S. Dalal, Feng-Ren Fan, Alessio Filippetti, Vincenzo Fiorentini, Lucas Foppa, Cesare Franchini, Benjamin Geisler, Luca M. Ghiringhelli, Axel Groß, Shunbo Hu, Jorge Íñiguez, Steven Kaai Kauwe, Janice L. Musfeldt, Paolo Nicolini, Rossitza Pentcheva, Tomas Polcar, Wei Ren, Fabio Ricci, Francesco Ricci, Huseyin Sener Sen, Jonathan M
Pubblicato in: Inorganic Chemistry, Numero 58/22, 2019, Pagina/e 14939-14980, ISSN 0020-1669
Editore: American Chemical Society
DOI: 10.1021/acs.inorgchem.9b01785

AFLOW-CHULL: Cloud-Oriented Platform for Autonomous Phase Stability Analysis

Autori: Corey Oses, Eric Gossett, David Hicks, Frisco Rose, Michael J. Mehl, Eric Perim, Ichiro Takeuchi, Stefano Sanvito, Matthias Scheffler, Yoav Lederer, Ohad Levy, Cormac Toher, Stefano Curtarolo
Pubblicato in: Journal of Chemical Information and Modeling, Numero 58/12, 2018, Pagina/e 2477-2490, ISSN 1549-9596
Editore: American Chemical Society
DOI: 10.1021/acs.jcim.8b00393

Insightful classification of crystal structures using deep learning

Autori: Angelo Ziletti, Devinder Kumar, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Nature Communications, Numero 9/1, 2018, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-018-05169-6

Optimizations of the eigensolvers in the ELPA library

Autori: P. Kůs, A. Marek, S.S. Köcher, H.-H. Kowalski, C. Carbogno, Ch. Scheurer, K. Reuter, M. Scheffler, H. Lederer
Pubblicato in: Parallel Computing, Numero 85, 2019, Pagina/e 167-177, ISSN 0167-8191
Editore: Elsevier BV
DOI: 10.1016/j.parco.2019.04.003

Big Data-Driven Materials Science and Its FAIR Data Infrastructure

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: Handbook of Materials Modeling - Methods: Theory and Modeling, 2020, Pagina/e 49-73, ISBN 978-3-319-44676-9
Editore: Springer International Publishing
DOI: 10.1007/978-3-319-44677-6_104

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