Computing

Researchers Win PRACE HPC Excellence Award for Work on 2D Materials

Researchers Win PRACE HPC Excellence Award for Their Revolutionary Work on 2D Materials.
Written by admin

A team led by Professor Nicola Marzari, head of Theory and Simulation of Materials at EPFL’s School of Engineering and Materials Simulations at PSI, and director of NCCR MARVEL, has received the first-ever PRACE (Partnership for Advanced Computing in Europe) HPC Excellence Award .

Image Credit: National Center of Competence in Research.

The team’s work in the identification and characterization of novel two-dimensional materials has been recognized with a € 20,000 prize that is given to “an outstanding individual or team for ground-breaking research that leads to significant advances in any research field through the use of high-performance computing.”

The team led by Nicola Marzari earned the first PRACE (Partnership for Advanced Computing in Europe) HPC Excellence Award for their research on an intriguing class of new materials that could support quantum computing and next-generation electrical and optoelectronic applications.

The award was intended to recognize “the most outstanding initiatives and researchers in the field of high-performance computing.”

While Nobel-prize-winning work producing and characterizing graphene had shifted 2D materials from a concept to actuality around 15 years prior, improvement in defining novel 2D materials was slow—only a few had been recognized.

The award-winning research was initially described in the 2018 Nature Nanotechnology article “Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds.”

Fundamental problems persisted although it was obvious that a computational strategy might aid in determining which of the hundreds of thousands of known chemicals could exfoliate or be durable as 2D monolayers.

How could they establish whether or not a crystal structure could be exfoliated? How should they treat and eventually perform simulations over an extensive set of candidate materials? How could they streamline predictions so that they would more reliably and automatically go from structure to property?

Marzari and his colleagues used data- and computing-intensive methodology to address all of these problems, managing to reduce a field of 108,423 distinct, empirically known inorganic compounds to less than 2000 that could be exfoliated into innovative 2D materials.

After that, they looked at a selection of the most intriguing 258 compounds’ vibrational, electrical, magnetic, and topological characteristics, discovering novel magnetic materials as well as half-metals and half-semiconductors.

The depth of this portfolio was then investigated in more than a dozen further studies, which focused on screening for the best performance across a range of applications, including band topology, superconductivity, and electrical transport.

As a result, the first Kane-Mele topological insulator, the material with the highest superconducting temperature in 2D, and the most effective spin-FET transistor were discovered.

Without a cutting-edge method of computation and data, none of this would have been feasible. The researchers had to run half a million computations on tens of thousands of different materials for the initial high-throughput analysis, frequently mixing numerous algorithms to target complicated features.

Doing this by hand would have been very labor-intensive and power-intensive, prone to mistakes, and impossible to duplicate.

To cope with these calculations automatically, reliably, and efficiently while maintaining a fully reproducible record of the whole calculation procedures and processes, the team had to approach HPC in a completely new way.

AiiDA (https://www.aiida.net) was developed as the infrastructure to automate, manage, persist, share, and reproduce all of the intricate workflows and data, and the Materials Cloud (https://www.materialscloud.org /discover/mc2d) was developed to disseminate those to the general public.

AiiDA can manage thousands of computations at once, automating the submission and control procedure as well as the retrieval and storage of the results. After that, the complete workflow, as well as the unprocessed and curated data, can be exposed on the Materials Cloud.

The team that will split the award—who were all at EPFL when the study was completed—has now left to pursue independent careers throughout the world.

Andrius Merkys (researcher at the Vilnius University), Antimo Marrazzo, (junior assistant professor at the University of Trieste), Thibault Sohier (researcher at CNRS), Laboratoire Charles Coulomb, Marco Gibertini (assistant professor at the University of Modena) and Reggio Emilia , Philippe Schwaller (assistant professor at EPFL), Davide Campi (assistant professor at the University of Milano-Bicocca), Ivano E. Castelli (associate professor at the Technical University of Denmark), Andrea Cepellotti (research scientist at the Harvard University) Nicolas Mounet (research scientist at CERN), Giovanni Pizzi (senior scientist at EPFL and group leader at PSI), and Nicola Marzari at EPFL.

They are all extremely appreciative of PRACE and the Swiss National Supercomputing Center for providing the assistance and computing resources that enabled all of the studies.

The award will be given during PASC22, which will take place from June 27th–29th2022, in Basel, Switzerland.

Journal Reference:

Mounet, N. et al. (2018) Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds. Nature Nanotechnology. doi:10.1038/s41565-017-0035-5.

Source: https://nccr-marvel.ch/

About the author

admin

Leave a Comment