• New approach for a unified formalism for spectral and thermodynamic properties of interacting-electron systems 

    Addressing increased need for more accurate predictions of materials spectra and thermodynamics, NCCR MARVEL researchers Tommaso Chiarotti and Nicola Marzari, and colleague Andrea Ferretti, introduce a treatment of frequency dependence allowing for the algorithmic inversion method on sum over poles (AIM-SOP) for solving Dyson-like equations and handling frequency-dependent quantities in dynamical theories. Specializing to the case of many-body perturbation theory applied to the homogeneous electron gas, they show that the AIM-SOP approach provides a unified formalism for generating the spectral and thermodynamic properties of an interacting-electron system. The authors are now working on generalizing the AIM-SOP method to non-homogeneous crystalline systems.  

  • Electronic structure study of AV3Sb5 kagome metals bolsters understanding of correlated phenomena

    The recently discovered layered kagome metals AV3Sb5 (A=K, Rb, Cs) exhibit diverse correlated phenomena, thought to be linked to so-called Van Hove singularities (VHSs) in the material. Using a combination of polarization-dependent angle-resolved photoemission spectroscopy (ARPES) and density-functional theory, researchers led by NCCR MARVEL’s Professor Ming Shi at the Paul Scherrer Institute directly revealed the sublattice properties of 3d-orbital VHSs in CsV3Sb5. The research reveals important insights into the material’s electronic structure and provides a basis for understanding correlation phenomena in the metals.

  • Predicting the optical read-out of a qubit from first principles

    Phonon-assisted luminescence is a key property of defect centers in semiconductors. It can be measured to perform the readout of the information stored in a quantum bit or used to detect temperature variations. The investigation of phonon-assisted luminescence is now generally carried out through models that incorporate restrictive assumptions and so fail to be predictive. The paper “Phonon-assisted luminescence in defect centers from many-body perturbation theory,” recently published in Physical Review Letters by researchers led by NCCR MARVEL’s Prof. Nicola Marzari and PhD student Francesco Libbi of EPFL’s Theory and Simulation of Materials laboratory, outlines a novel approach to predicting luminescence and studying exciton-phonon couplings with a many-body perturbation theory framework, an analysis that has never been performed for defect centers.

  • Scientists propose open platform for managing data from chemical research

    EPFL scientists including NCCR MARVEL's deputy director Berend Smit have proposed an open platform for managing the vast amounts of diverse data produced in chemical research. They presented their vision in a paper recently published in Nature Chemistry. The article below was written by EPFL journalist Nik Papageorgiou. 

  • Researchers identify new paraelectric phase prototypes for use in computational engineering of functional materials

    A deeper investigation into the microscopic picture of the BaTiO3 perovskite revealed the persistence of intrinsic off-centerings in its cubic paraelectric phase. Interestingly, this feature is inconsistent with the space group often used to atomistically model this phase using density-functional theory (DFT) or similar methods. This prompted researchers, led by NCCR MARVEL’s Giovanni Pizzi and Michele Kotiuga at Professor Nicola Marzari’s Theory and simulation of materials laboratory at EPFL, to use a systematic symmetry analysis to construct representative structural models, supercells that satisfy a desired point symmetry but are built from a combination of lower-symmetry primitive cells. In this way, they identified two 40-atom structural prototypes—the smallest of the representative models that are both energetically and dynamically stable—for paraelectric BaTiO3. These prototypes, which are also common to many other ABO3 perovskites, offer structural models of paraelectric phases for use in the computational engineering of functional materials. The paper was recently published in Physical Review Research.

  • New paper describes on-surface synthesis and characterization of nitrogen-substituted undecacenes

    Heteroatom substitution—the replacement of carbon atoms with others such as sulfur and nitrogen—can be used to tailor the electronic, magnetic, and physico-chemical properties of acenes, a class of organic compounds and polycyclic aromatic hydrocarbons made up of linearly fused benzene rings. With potential applications in organic electronics, this fine-tuning could allow for precise engineering and property optimization. Synthesizing and characterizing larger acenes has, however, remained a challenge for solution chemistry because they feature low solubility and high reactivity. In the paper On-surface synthesis and characterization of nitrogen-substituted undecacenes, recently published in Nature Communications, NCCR MARVEL affiliated scientists and colleagues addressed this by demonstrating first on-surface synthesis of three undecacene analogs substituted with four nitrogen atoms on an Au(111) substrate and then characterizing the materials using various techniques. The work paves the way towards the precise fabrication of nitrogen-substituted acenes and their analogs, potential building-blocks of organic electronics and spintronics. 

  • ARPES gives first observation of dispersive excitons in a low-dimensional metallic system

    Already used in some solar cells, excitons, with their charge neutrality and expected mobility, have also been proposed as potential transmitters of quantum information. In either use, it’s essential to understand how and why these quasiparticles move. Investigations into exciton mobility have been inaccessible to traditional optical experiments though because they only create and detect excitons with negligible momentum. Now, using angle-resolved photoemission spectroscopy (ARPES), scientists led by NCCR MARVEL’s Professor Ming Shi at the Paul Scherrer Institute have detected several types of mobile excitons in the quasi-one-dimensional metallic trichalcogenide, TaSe3. They’ve also shown that certain exciton properties can be tuned by surface doping. The paper was recently published in Nature Materials. 

  • Manifolds in commonly used atomic fingerprints lead to failure in machine-learning four-body interactions

    The existence of manifolds in two atomic environment fingerprints commonly used to characterize the local environments of atoms in machine learning and other contexts causes a failure to machine learn four-body interactions such as torsional energies, which are an important part of standard force fields. No such manifolds can be found for the Overlap Matrix (OM) fingerprint due to its intrinsic many-body character, making it an appealing alternative, NCCR MARVEL researchers at the University of Basel found in a paper recently published in the Journal of Chemical Physics.

  • Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties

    Considerations of symmetry underpin the mathematical representations of the atomic configurations that are used by machine learning models to predict properties of various molecular structures. Though these models generally rely on a description of atom-centered environments, many of the quantities that are relevant for quantum mechanical calculations – notably the single-particle Hamiltonian Ĥ matrix when written in an atomic-orbital basis – aren’t associated with a single center, but rather with two or more atoms in the structure. In the paper “Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties,” recently published in the Journal of Chemical Physics, researchers discuss a family of structural descriptors that generalize atom-centered density correlation features to the N-centers case and show how it can be applied to efficiently learn the matrix elements of Ĥ. These N-centers features are fully equivariant in terms of both translations and rotations as well as in terms of permutations of the indices associated with the atoms and are therefore suitable for use in constructing symmetry-adapted machine-learning models of new classes of properties of molecules and materials.

  • Quantum physics across dimensions: unidirectional Kondo scattering

    NCCR MARVEL researchers Ana Akrap and Oleg Yazyev formed part of an international team led by EPFL scientists who unveiled a unique quantum-mechanical interaction between electrons and topological defects in layered materials. Only observed in engineered atomic thin layers, the phenomenon can be reproduced by the native defects of lab-grown large crystals, making future investigation of Kondo systems and quantum electronic devices more accessible. EPFL journalists report on the phenomenon below.

  • Ab initio model of Ca2RuO4 perovskite in remarkably good agreement with available experimental data

    NCCR MARVEL researchers at the University of Fribourg have tested the GW + EDMFT ab initio approach for correlated materials modelling. Using the insulator-metal transition in the perovskite Ca2RuO4 as a benchmark, they found that their parameter-free simulation was in close agreement with the available experimental data and that the extension to the nonlocal polarization and self-energy provided by GW are essential to attaining such accuracy. The calculations represent an important test and an encouraging result for the further application and development of the GW + EDMFT framework, the authors said.

  • Machine learning solves the who’s who problem in NMR spectra of organic crystals

    A team of EPFL researchers has combined a large database of 3D structures with a machine learning model of chemical shifts and topological representations of molecular environments to allow for the probabilistic assignment of NMR spectra of organic crystals directly from their 2D chemical structures. They demonstrated the approach on seven molecular solids with experimental shifts and benchmarked it on 100 crystals using predicted shifts. The correct assignment was found among the two most probable assignments in more than 80% of cases. The paper, Bayesian Probabilistic Assignment of Chemical Shifts in Organic Solids, was published today in Science Advances.