Highlights

Research from NCCR MARVEL scientists and colleagues resulted in not one but two Editors' Suggestions in Physical Review Materials in November.  

MARVEL researchers were part of a group that used ultrafast X-ray diffraction to show how photodoping triggers a purely structural phase transition in a perovskite. The research was published in Physical Review Letters.

Researchers from the lab of NCCR MARVEL's deputy director Berend Smit and colleagues have developed a photocatalytic system that is based on a material in the class of metal-organic frameworks. The system can be used to degrade pollutants present in water while simultaneously producing hydrogen that can be captured and used further. The research was published in Advanced Functional Materials.

Considering how it can unexpectedly screw up almost anything, from Napoleon’s military campaign to your medical treatment, it would be nice to be able to control polymorphism: to have a way to predict whether a substance has polymorphs, and if so, which polymorphs form under which conditions. In a recent paper, MARVEL researchers Pablo Piaggi and Michele Parrinello set out to understand the phenomenon.

EPFL scientists including NCCR MARVEL's Michele Ceriotti have developed a machine learning method to predict chemical shifts of molecular solids with an accuracy comparable to that derived from electronic-structure calculations—but at a much faster speed and lower computational cost. The research was published in Nature Communications.

EPFL Professor and NCCR MARVEL researcher Michele Ceriotti and colleagues at the University of Cambridge in the U.K. have developed a computational method to more efficiently identify materials candidates that are likely synthesizable.  

There’s a lot of mystique around quantum mechanics, but it’s actually very simple, says Nicola Marzari, director of the Swiss National Centre of Competence in Research (NCCR) MARVEL, a center for the computational design and discovery of novel materials.

Catalysts are essential to an endless number of chemical reactions. The right catalyst can make the difference between a process that is industrially viable and one that is not. Identifying new and better catalysts is therefore an important focus of chemical research. In a series of papers, Prof. Clemence Corminboeuf (EPFL) and her colleagues have explored the possibility of extending the use of volcano plots to identify ideal catalysts from heterogeneous and electro-catalysis to homogeneous catalysis. Teaming up with the group of Prof. Anatole von Lilienfeld (University of Basel), the latest paper in the series moreover shows how using quantum machine learning models in combination with volcano plots could considerably speed up discovery.  

With internet use ever expanding, there is an urgent need for more energy efficient data storage. Current technology records data in the magnetic state of a material using a magnetic field generated by an electric current. Energy efficiency would be enormously improved if we could replace the magnetic field by an electric field. Manipulating a material’s magnetisation by an electric field is not straightforward, however. Multiferroic magnetic spirals are one of very few ways this might be achieved, but these tend to be stable only at temperatures way below normal device operating conditions. In a series of papers, MARVEL groups led by Nicola Spaldin at ETHZ and Marisa Medarde at PSI show that magnetic spirals can be tuned and stabilised beyond room temperature by manipulating chemical disorder. This new mechanism may be exploited in the design of energy efficient data storage devices where the magnetisation is controlled by an electric field.

Close collaboration between two NCCR MARVEL labs may soon result in a fundamental change to the traditional simulation approaches in computational metallurgy and a deeper understanding of how processing and composition affect the properties of metals and their alloys.

Materials Cloud (www.materialscloud.org), a new web platform developed to help computational materials scientists share their work and promote open science, may also offer advantages to industrial partners more concerned with IP.

Quantum spin Hall insulators are part of a new class of materials, the so-called topological materials. Topological materials host exotic phases of matter that are protected by topological properties of the quantum state. They are of great interest for reasons both fundamental and applied. Notably, they would open a window into the quantum world through condensed matter physics. For all their theoretical promise however, there is a scarcity of experimentally known materials that exhibit a robust topologically non-trivial phase. In their paper Prediction of a Large-Gap and Switchable Kane-Mele Quantum Spin Hall Insulator, Antimo Marrazzo, Marco Gibertini, Davide Campi, Nicolas Mounet and Nicola Marzari identify one such material, showing that a monolayer of the mineral Jacutingaite realises the Kane-Mele model for a quantum spin Hall Insulator.