Highlights

  • In search of new alloys for aerospace applications

    A study by MARVEL researchers in Raju Natarajan's laboratory at EPFL has used computational methods to accurately describe the properties of a 6-component alloy made of aluminum , niobium, titanium, vanadium, zirconium and tantalum. This alloy has promising properties that could be applied to aircraft engines or nuclear applications, due to its microstructure comprised of a disordered solid solution matrix and embedded precipitates of an ordered phase. Predictions from ab-initio calculations are in excellent agreement with experiments, and the study also allowed to derive some design rules for experimentalists on how to improve the performance of the alloy.

  • AiiDA used to drive experiments for the first time, matched with Empa’s Aurora robotic platform

    A new study shows how MARVEL's computational workflow engine AiiDA can be used not only to run computer simulations, but also actual experiments. Researchers from PSI, Empa, EPFL, ETH Zurich, and Technische Universität Berlin interfaced AiiDA with a robotic platform that automates battery experiments. AiiDA takes case of controlling the experimental devices, archiving and analyzing the resulting data, a first step toward fully autonomous self-driving labs. 

  • Materials follow the 'Rule of Four', but scientists don’t know why yet

    A new study by MARVEL researchers describes an unexpected "rule" followed by about 60 per cent of structures included in large databases of computational and experimental materials: their primitive unit cells are made out of multiples of four atoms. The scientists tried many different explanations, considering the role of specific chemical elements as well as formation energy and symmetry, but a convincing explanation is yet to be found. Still, the scientists could use an algorithm to predict with high accuracy whether a given compound will follow the Rule of Four or not.

  • Computational study points to a promising Weyl semimetal

    EPFL scientists have studied in detail the electronic structure and magnetic properties of InMnTi2, a compound they had first identified as a candidate Weyl semimetal during a high-throughput study. Weyl semimetals have unusual electrical conductivity that make them interesting for several applications in quantum technologies, lasers, or advanced optics. Interestingly, this material was initially described as non-magnetic, but DFT + U calculations showed it is actually antiferromagnetic, a property that could be exploited for memory devices, sensors, or quantum computing.

  • Using machine learning to study the microscopic behavior of a solid-state electrolyte

    Scientists in Michele Ceriotti's lab at EPFL have used machine learning to paint a more precise picture of how charge transport happens in lithium thiophosphate,  a promising material for solid-state batteries. The group is now perfecting the study of this material by adding an analysis of thermal transport, which will be the topic of a new publication.

  • GPT-3 transforms chemical research

    A study by MARVEL researchers in Berend Smit's laboratory at EPFL shows that large language models such as GPT-3 can be used to simplify the application of artificial intelligence to chemical analysis, improving accuracy while drastically reducing the amount of data needed for training.  The model, trained with relatively few Q&As, correctly answered over 95% of very diverse chemical problems. The method is as easy as conducting a literature search, and is applicable to various chemical problems.

  • In search of muons: why they switch sites in antiferromagnetic oxides

    A study involving MARVEL scientists and just published in Physical Review Letters has found that in manganese oxide, a textbook antiferromagnetic material,  the site of an implanted spin-polarized muon is not well identified, but can change due to a previously neglected effect: magnetostriction.

  • An in-depth look at a high-temperature superconducting nickelate

    A new study by Philipp Werner's group at the University of Fribourg makes advancements in the theoretical description of the correlated electron state of La3Ni2O7,  which has recently been described as a superconductor with a critical temperature around 80 K. The use of  GW+EDMFT, a method developed within MARVEL over the last ten years, was crucial for the study.

  • A “gold standard” for computational materials science codes

    Scientists from NCCR MARVEL led the most comprehensive verification effort so far on computer codes for materials simulations, providing their colleagues with a reference dataset and a set of guidelines for assessing and improving existing and future codes.

  • Automated, bespoke Wannier functions for all materials

    Two newly-released articles by MARVEL members Junfeng Qiao, Giovanni Pizzi and Nicola Marzari provide scientists with very robust and reliable algorithms that standardize and automatize the process of obtaining  Wannier functions for a given material, a much used tool for computational condensed matter physics and materials science.  To validate their algorithms, the scientists first chose four or five typical materials to explain how the methods work and reproduce what chemists would already guess about the materials. Then they stress-tested these algorithms on a larger set of materials to collect statistics and compare to previous approaches.

  • The semi-metal that wasn’t there

    Scientists have been looking for real-world examples of Weyl semi-metals, that are topological materials with unique transport, optical and thermoelectric behavior. Many computational and experimental papers had described a compound of europium, cadmium and arsenic, EuCd2As2, as a Weyl semi-metal. But a new study just published by an international research team led by MARVEL’s Ana Akrap has found that it is instead a magnetic semiconductor.

  • Tackling excited states: Koopmans functionals now available as an open-source software package

    A 10-year effort has led to a theoretical framework and a software package, called koopmans, that allows to obtain reliable spectral properties of molecules and materials with density functional theory. The framework is described in a new article by MARVEL researchers at EPFL, and last month a week-long school co-organised by MARVEL in Pavia saw students learning about Koopmans functionals and trying out the code.