Scientific Highlights

Cover of nature nanotechnology March 2018

MARVEL team wins inaugural PRACE HPC Excellence award

The first ever PRACE (Partnership for Advanced Computing in Europe) HPC Excellence Award has been awarded to 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. The € 20,000 award is given to “an outstanding individual or team for ground-breaking research that leads to significant advances in any research field through the usage of high-performance computing”, and recognizes the team’s effort in the discovery and characterization of novel two-dimensional materials.

Moeckli et al

Two scenarios for superconductivity in CeRh2As2

CeRh2As2, a nonsymmorphic heavy fermion material, was recently reported to host a remarkable temperature versus z-axis magnetic-field phase diagram with two superconducting phases. In this material, the two inequivalent Ce sites per unit cell, related by inversion symmetry, introduce a sublattice structure corresponding to an extra internal degree of freedom. In this work, we propose a classification of the possible superconducting states in CeRh2As2 from the two Ce-sites' perspective.

 

Benefit of random testing

Benefit of random testing

With the imminent relaxation of socio-economic restrictions, it becomes vital to assess its effect on the prevalence of acute infections within the population, as rapidly as possible. Currently available monitoring instruments for the COVID-19 pandemic have an inherent time delay of about 14 days, as they rely on confirmed infections, hospitalizations, and death numbers. These methods give Reff(t) (the number of infections caused by a single infected person), but their delay is a significant disadvantage when restrictions are released. If after relaxation, Reff(t) rises above 1, one will not be able to react adequately before two weeks have passed during which time the prevalence could significantly rise. Here, we propose the use of random testing to shorten this reaction time, by obtaining direct and modeling dependent information on Reff(t). Through random testing of between 2500 and 20000 people per day, we find that over periods significantly shorter than two weeks, it becomes possible to detect a dangerous increase in Reff with reasonable confidence.