Highlights

  • MOF co-catalyst allows selectivity of branched aldehydes of up to 90%

    Heterogeneous catalysts are often preferred in industrial settings because of their robustness and lower operating costs, but homogenous catalysts still dominate when high selectivity is needed—finding superior heterogeneous catalysts has been a challenge. A recent collaboration between the Paul Scherrer Institute's experimental Syncat Group, led by Marco Ranocchiari, and EPFL’s Laboratory of Molecular Simulation, a computational group led by Berend Smit, has shown how micropores in metal-organic frameworks (MOFs) can enhance selectivity to levels that cannot be achieved with existing catalysts. Though the findings have significant potential in the production of aldehydes, the easy experimental protocol and the chemical and structural flexibility of MOFs means that the approach represents a powerful tool for designing selective catalytic heterogeneous processes in the fine chemical industry overall. A paper on the research has just been published in Nature Communications.

  • New artificial neural network model bests MaxEnt in inverse problem example

    NCCR MARVEL researchers at EPFL’s Chair of Computational Condensed Matter Physics (C3MP) and colleagues have developed an artificial neural network (ANN) model that may serve as a basis for solving inverse problems. Their approach reaches the same level of accuracy as the now commonly used maximum entropy (MaxEnt) method for low-noise data, performs significantly better than this standard technique when the noise strength increases, and features a reduction in computational cost by orders of magnitude. The research has just been published in Physical Review Letters.

  • Researchers generalize Fourier’s 200-year-old heat equation, explaining hydrodynamic heat propagation

    Michele Simoncelli, a PhD student here at EPFL, together with Andrea Cepellotti, a former EPFL student now at Harvard, and Nicola Marzari, head of EPFL's Theory and Simulation of Materials laboratory as well as director of NCCR MARVEL, have developed a novel set of equations for heat propagation that goes beyond Fourier’s law and explains why and under which conditions heat propagation can become fluid-like, rather than diffusive. These "viscous heat equations'' show how heat conduction is not only governed by thermal conductivity, which was introduced by Fourier in his well-known macroscopic law of heat conduction, but also by another quantity, thermal viscosity. The theory is in striking agreement with pioneering experimental results in graphite published last year and may pave the way for the design of the next generation of more efficient electronic devices. The paper, Generalization of Fourier's law into viscous heat equations, has been published in Physical Review X.  

  • Wannier90 program becomes community code in major new release

    Wannier90—a computer program for generating maximally-localized Wannier functions and using them in the computation of advanced electronic properties of materials—has become a community code with a wide base of contributors over the last few years. This has resulted in a major new release with novel features described in the paper Wannier90 as a community code: new features and applications, published in Journal of Physics: Condensed Matter.

  • New computational screening approach identifies potential solid-state electrolytes

    Though researchers have been looking for solid-state electrolytes that could enhance both the safety and performance of lithium-ion batteries for decades, no thoroughly suitable candidate has yet been found. Computational screening may offer better chances of success than previous methods of investigation, largely led by chemical intuition and experiment, but such methods must also meet certain criteria. In a recent paper published in the journal Energy & Environmental Science, NCCR MARVEL researchers Leonid Kahle, Aris Marcolongo and Nicola Marzari present a suitable computational framework for predicting the diffusion of Li-ions in solid-state materials, show how to employ it in large-scale computational screening and use it to identify new ceramic compounds for further experimental investigation. 

  • New algorithm allows for the rapid identification of entire reaction pathways in complex systems

    Researchers led by Stefan Goedecker at the University of Basel have developed an algorithm allowing for the rapid identification of entire reaction pathways in complex systems. Applying it to C60 and C20H20, they show that the reaction pathways found contain valuable information on how these molecules can be synthesized. The paper was recently published in Physical Review Letters. 

  • Computationally designed material shows improved carbon capture in wet flue gases

    Chemical engineers led by Berend Smit, MARVEL deputy director and head of the Laboratory of Molecular Simulation at EPFL have designed a material that can capture carbon dioxide from wet flue gases better than some commercial materials. The work has been published in Nature.

  • Researchers identify 13 monolayers as potentially promising quantum spin Hall insulator candidates

    In a recently published paper, Relative Abundance of Z2 Topological Order in Exfoliable Two-Dimensional Insulators, researchers from MARVEL director Nicola Marzari’s Laboratory of theory and simulation of materials (THEOS) screened a comprehensive database and identified 13 monolayers that are dynamically stable and potentially exfoliable quantum spin Hall insulators. This highlights a relative abundance of such topological order of around 1%. The paper was published in Nano Letters.

  • MARVEL researchers, partners present work on materials for energy at Materials Science Day

    NCCR MARVEL and CCMX, the Competence Centre for Materials Science and Technology, hosted their third annual Materials Science Day on October 8 to present both experimental and modeling approaches to the development of innovative new materials. The event, meant to highlight cutting-edge research and give people a chance to network, drew more than 60 people from industry and academia.

  • MARVEL Sector Days give industry a chance to help shape research

    Research should be driven by societal issues—we need to pursue what is urgent and needed for the community at large. Just as the NCCR MARVEL seeks the guidance and expertise of a scientific advisory board in developing lines of research, we also seek insight from industry. 

  • Machine learning approach predicts electron densities with DFT accuracy

    Clémence Corminboeuf, Michele Ceriotti and colleagues at EPFL have developed a machine learning model that can predict the electron density from atomic coordinates. The approach may facilitate the characterization of non-covalent interactions, helping researchers  understand complex interactions between biomolecules and potentially assist in the design of self-assembled materials and drugs. The research was recently published in the journal Chemical Science.

  • Science paper proposes non-Abelian band topology

    A paper published in the journal Science by NCCR MARVEL's QuanSheng Wu, postdoc in the group of Oleg Yazyev at EPFL, Alexey Soluyanov, professor at the Physics Institute of the University of Zurich as well as group leader in Design & Discovery Project 6, and colleague Tomáš Bzdušek at Stanford University  introduces non-Abelian topological charges that characterize line nodes inside the momentum space of certain symmetric crystalline metals with weak spin-orbit coupling. The analysis goes beyond the standard approach to band topology, and implies the existence of 1D topological phases not present in existing classifications.