Publications related to First-principles investigation of the relation between structural and NMR parameters in vitreous GeO2

Related publications (32)

Automated all-functionals infrared and Raman spectra

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

Nature Portfolio2024

Electronic transport in graphene with out-of-plane disorder

Oleg Yazyev, Yifei Guan

Real-world samples of graphene often exhibit various types of out-of-plane disorder-ripples, wrinkles and folds-introduced at the stage of growth and transfer processes. These complex out-of-plane defects resulting from the interplay between self-adhesion ...

Nature Portfolio2024

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

Paul Joseph Dyson, Farzaneh Fadaei Tirani, Mouna Hadiji

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Amer Chemical Soc2024

Orbital-Resolved DFT plus U for Molecules and Solids

Nicola Marzari, Iurii Timrov

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Amer Chemical Soc2024

Nonempirical semilocal density functionals for correcting the self-interaction of polaronic states

Alfredo Pasquarello, Stefano Falletta

Through the use of the piecewise-linearity condition of the total energy, we correct the self-interaction for the study of polarons by constructing nonempirical functionals at the semilocal level of theory. We consider two functionals, the gamma DFT and mu ...

Aip Publishing2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

Giulia Tagliabue, Alan Richard Bowman, Fateme Kiani Shahvandi, Theodoros Tsoulos

This dataset accompanies the publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films" published in Light: Science & Applications (https://doi.org/10.1038/s41377-024-01408-2). The data can be used to reproduce plots 1-4 ...

Zenodo2024

Murunskite - a new class of functional material

Davor Tolj

The subject of the present work is discovery and in-depth characterization of a new class of functional materials. Tuning of the bond polarity and orbital occupation with a goal of establishing balance between localization and delocalization of electrons - ...

EPFL2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

The convexity condition of density-functional theory

Edward Baxter Linscott

It has long been postulated that within density-functional theory (DFT), the total energy of a finite electronic system is convex with respect to electron count so that 2E(v)[N-0]

Aip Publishing2023

Five-Membered Rings Create Off-Zero Modes in Nanographene

Oleg Yazyev, Kristians Cernevics

The low-energy electronic structure of nanographenes can be tuned through zero-energy pi-electron states, typically referred to as zero-modes. Customizable electronic and magnetic structures have been engineered by coupling zero-modes through exchange and ...

Amer Chemical Soc2023

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

Magnon-phonon interactions enhance the gap at the Dirac point in the spin-wave spectra of CrI3 two-dimensional magnets

Iurii Timrov

Recent neutron-diffraction experiments in honeycomb CrI3 quasi-2D ferromagnets have evinced the existence of a gap at the Dirac point in their spin-wave spectra. The existence of this gap has been attributed to strong in-plane Dzyaloshinskii-Moriya or Kita ...

2023

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Giovanni Pizzi, Antimo Marrazzo, Junfeng Qiao

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations ...

NATURE PORTFOLIO2023

On-Surface Synthesis of Edge-Extended Zigzag Graphene Nanoribbons

Kristjan Eimre

Graphene nanoribbons (GNRs) have gained significant attention in nanoelectronics due to their potential for precise tuning of electronic properties through variations in edge structure and ribbon width. However, the synthesis of GNRs with highly sought-aft ...

Wiley-V C H Verlag Gmbh2023

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

Charge multipole correlations and order in Cs2TaCl6

Henrik Moodysson Rønnow, Ivica Zivkovic, Jian Rui Soh, Jana Pásztorová

We examine the role of charge, structural, and spin degrees of freedom in the previously poorly understood phase transition in the 5d1 transition-metal double perovskite Cs2TaCl6 using a combination of computational and experimental techniques. Our heat ca ...

AMER PHYSICAL SOC2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

Magnetic orderings and electronic structure of complex oxides from advanced Hubbard functionals

Luca Binci

Transition metal oxides represent a class of materials displaying very unusual electronic, structural and magnetic properties. They are extremely interesting, both from a technological and fundamental point of view. The most important characteristic of the ...

EPFL2023