April 21, 2020
Nicola Marzari
Prof. Nicola Marzari holds the Chair of Theory and Simulation of Materials at EPFL . He is the...
April 21, 2020
Andrea Ferretti
Andrea Ferretti is senior researcher at CNR-NANO, Modena, Italy. He works in the field of condensed...
April 21, 2020
Pietro Bonfá
Pietro Bonfà received his BSc in Engineering Physics from Politecnico di Milano and MSc in Physics...
April 21, 2020
Mariella Ippolito
Mariella Ippolito got a Bachelor Degree cum laude in Physics at University Tor Vergata of Rome. She...
April 21, 2020
Pietro Delugas
Pietro Delugas works as a Code Developer in SISSA. He worked at the development of Quantum Espresso...
April 21, 2020
How to use Quantum ESPRESSO on new GPU based HPC systems
Did you miss the MAX webinar on "How to use Quantum ESPRESSO on new GPU based HPC systems"? The...
April 21, 2020
Quantum ESPRESSO towards the exascale
P. Giannozzi, O. Baseggio, P. Bonfà, D. Brunato, R. Car, I. Carnimeo, C. Cavazzoni, S. de...
April 15, 2020
MaX Newsletter - April 2020
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April 14, 2020
Performance Limit of Monolayer WSe2 Transistors; Significantly Outperform Their MoS2 Counterpart
X.T. Sun, L. Xu, Y. Zhang, W.Z. Wang, S.Q. Liu, C. Yang, Z.Y. Zhang, and J. Lu
April 13, 2020
Strongly correlated electrons and hybrid excitons in a moire heterostructure
Y. Shimazaki, I. Schwartz, K.Watanabe, T. Taniguchi, M. Kroner, and A. Imamoglu
April 13, 2020
Engineering Edge States of Graphene Nanoribbons for Narrow-Band Photoluminescence
C.X. Ma, Z.C. Xiao, A.A. Puretzky, H. Wang, A. Mohsin, J.S. Huang, L.B. Liang, Y.D. Luo, B.J...
April 10, 2020
Sub-Angstrom Characterization of the Structural Origin for High In-Plane Anisotropy in 2D GeS2
Materials with layered crystal structures and high in-plane anisotropy, such as black phosphorus,...
April 10, 2020
Sub-Angstrom Characterization of the Structural Origin for High In-Plane Anisotropy in 2D GeS2
X.D. Wang, J.L. Tan, C.Q. Han, J.J. Wang, L. Lu, H.C. Du, C.L. Jia, V.L. Deringer, J. Zhou, and W...
April 10, 2020
Electronic Transport through DNA Nucleotides in BC3 Nanogap for Rapid DNA Sequencing
R.L. Kumawat, P. Garg, G. Bhattacharyya, and B. Pathak
April 9, 2020
All-Atom Simulations Decrypt the Molecular Terms of RNA Catalysis in the Exon-Ligation Step of the Spliceosome
The spliceosome, a protein-directed metallo-ribozyme, catalyzes premature mRNA splicing via two...
April 9, 2020
All-Atom Simulations Decrypt the Molecular Terms of RNA Catalysis in the Exon-Ligation Step of the Spliceosome
J. Borisek and A. Magistrato
April 8, 2020
Fireside chats for lockdown times: A gentle introduction to density-functional theory April 15-17, 2020
3 public live webinars " Fireside chats for lockdown times: A gentle introduction to density-...
April 6, 2020
Antimicrobial Metal Nanomaterials: From Passive to Stimuli-Activated Applications
S. Cheeseman, A.J. Christofferson, R. Kariuki, D. Cozzolino, T. Daeneke, R.J. Crawford, V.K. Truong...
April 5, 2020
Computational School on Electronic Excitations in Novel Materials using Yambo Code
The school "Electronic Excitations in Novel Materials using the Yambo code" was held at the International Center of Theoretical Physics (ICTP) campus in Trieste from 27th to 31st January 2020. The school was sponsored by the MaX Centre of Excellence and the Psi-K network and was part of the ICTP 2020 scientific calendar.
April 5, 2020
Machine Learning: Improved predictions for time-to-solution of materials science simulations
The accurate prediction of the time-to-solution required by massively parallel scientific codes is a key goal in HPC. It allows scientists to better program and allocate their computational tasks, and benefits environmental sustainability since energy waste due to sub-optimal execution parameters could be easily detected. Such prediction is however especially challenging for hybrid and complex architectures. An important step in this direction has been obtained with machine learning techniques for DFT-based material science codes. The results by Pittino et al, presented at PASC 19, show how accurate predictions obtained with machine learning approaches can outperform parametrized analytical performance models made by domain experts.
April 3, 2020
DFT and GW towards the exascale: porting MaX codes on to GPUs
MaX developers are working to support the European HPC community. As of today, a number of MaX...
April 3, 2020
Direct evidence of spatial stability of Bose-Einstein condensate of magnons
I.V. Borisenko, B. Divinskiy, V.E. Demidov, G. Li, T. Nattermann, V.L. Pokrovsky, and S.O...