Highlights

MARVEL scientists at the Paul Scherrer Institute and the University of Zurich have used a machine learning model to calculate the screening parameters for Koopmans functionals, a promising approach to expand the power of density-functional theory so that it can be used to predict the spectral properties of materials . The study, published in npj Computational Materials, focussed on two model systems: liquid water and the halide perovskite CsSnI3. Even with a relatively simple network and learning model, the scientists were able to significantly reduce the computational cost of the algorithm, paving the way to a more efficient calculation of the temperature-dependent spectral properties of interesting materials. 

In a new article published in Computer Physics Communications, the team of the Open Software Services for Classrooms and Research project (OSSCAR) describes how to create custom widgets and extensions that can be used in interactive notebooks to teach computational materials science. The article also introduces two new entries in OSSCAR: a widget to display an interactive periodic table that allows users to group elements into different states, and one to plot and visualize electronic band structures and density of states.

Can theory and computation methods help the search for the best divertor material and thus contribute to making fusion a reality? Scientists in Nicola Marzari’s MARVEL laboratory at EPFL decided to answer the question, and in a new article they present a method for a large-scale screening of potential materials to be used in a nuclear fusion divertor, a component that has to withstand extreme heat and a bombardment of particles. The shortlist of the most promising materials contains tungsten, that has been chosen for the ITER reactor, together with other options that may be considered for future reactors.

Orbital angular momentum monopoles have been the subject of great theoretical interest as they offer major practical advantages for the emerging field of orbitronics, a potential energy-efficient alternative to traditional electronics. Now, through a combination of robust theory and experiments at the Swiss Light Source SLS at Paul Scherrer Institute PSI, their existence has been demonstrated. The discovery is published in the journal Nature Physics.

A large collaboration led by MARVEL's Giuseppe Carleo has  introduced a method to compare the performance of different algorithms, both classical and quantum ones, when simulating complex phenomena in condensed matter physics. The new benchmark, called V-score, is described in an article just published in Science and has been validated on several examples of quantum many-body problems, pointing to the ones where future quantum computing algorithms may really make a difference. 

The first article of a series about MARVEL's success stories from its 10 years of research. In this story, we revisit how a close collaboration between theorists and experimentalists led to identify, synthesize and test a unique exotic material that until then had only appeared in some samples from a Brazilian mine. The material, called jacutingaite and with the composition Pt2HgSe3, was eventually confirmed to be the first ever material showing the so-called Kane-Mele physics, a quantum phenomenon that had been predicted but never seen in action before. Research is still ongoing on the original jacutingaite and on other materials of its family, and could lead to several technological applications. 

A group of MARVEL researchers from the Paul Scherrer Institute has conducted a "hero run" on the new Swiss supercomputer, occupying it entirely for about 20 hours with calculations managed remotely by the AiiDA software tools. The run demonstrated the efficiency and stability of AiiDA, that could seamlessly fill the entire capacity of an exascale machine, as well as the performance of the Alps supercomputer, that has been just inaugurated. All the results will soon be published on the Materials Cloud.

A new mathematical framework developed by MARVEL scientists at EPFL allows to calculate the spectrum of a material and its thermodynamics behavior at the same time, including the total energy and the band structure, and it does this even for complex, correlated materials. The method, published in an article in Physical Review Research, combines thermodynamics from DFT+U and spectra from GW, and was validated on transition metal oxides.

In a new article just published in Physical Review Research, Nicola Colonna from PSI and MARVEL and Antimo Marrazzo from Scuola Internazionale Superiore di Studi Avanzati (International School of Advanced Studies) in Trieste, Italy, introduce a new approach that allows calculating band structures of semiconductors in a simple way and at low computational cost, even in presence of spin-orbit coupling or complex magnetic configurations. The new method was validated on some well-studied materials and the results of the calculations proved in very good agreements with other well-established but more costly and unwieldy theories, such as many-body perturbation theory, and with experiments. This development will allow efficient and accurate computational screenings of materials databases and enable simulating complex materials under more realistic conditions, such as in presence of defects or at finite temperature.

A new computational method allows to perform a thorough exploration of the energy landscape of magnetic materials, which often have many possible solutions to the electronic structure problem. It allows to access many different starting points in terms of which orbitals are occupied by the electrons, and uses a global  algorithm to search systematically for all possible local minima of the energy in a material. The method, as well as its validation on many magnetic systems, has just been published in npj computational materials by scientists from Nicola Marzari's lab at EPFL. 

MARVEL scientists at the University of Fribourg have devised new mathematical techniques and applied them to an experimental method called angle-resolved photoemission spectroscopy (ARPES) to measure the Berry curvature, a particular way by which the laws of quantum mechanics interact with the electronic structure of a material and dictate the possible behavior of its electrons. So far this fundamental quantum geometrical property can only be measured indirectly. The study, published in Science Advances, could pave the way to a better understanding of topological materials. 

Artificial intelligence (AI) is accelerating the development of new materials. A prerequisite for AI in materials research is large-scale use and exchange of data on materials, which is facilitated by a broad international standard. A major international collaboration including MARVEL and CECAM now presents an extended version of the OPTIMADE standard.