Ab initio quantum chemistry methods

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Related publications (31)

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Rubén Laplaza Solanas, Anne-Clémence Corminboeuf, Frédéric Célerse, Veronika Juraskova

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

cell2mol: encoding chemistry to interpret crystallographic data

Rubén Laplaza Solanas, Anne-Clémence Corminboeuf, Sergio Vela Llausi, Yuri Cho

The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules ...

NATURE PORTFOLIO2022

Structures of the (Imidazole)(n)H+ ... Ar (n=1,2,3) complexes determined from IR spectroscopy and quantum chemical calculations

Valeriu Scutelnic

Here, we present new cryogenic infrared spectra of the (Imidazole) H-n(+) (n=1,2,3) ions. The data was obtained using helium tagging infrared predissociation spectroscopy. The new results were compared with the data obtained by Gerardi et al. (Chem. Phys. ...

SPRINGER/PLENUM PUBLISHERS2023

Modeling non-covalent interactions in condensed phase

Veronika Juraskova

The modeling of non-covalent interactions, solvation effects, and chemical reactions in complex molecular environment is a challenging task. Current state-of-the-art approaches often rely on static computations using implicit solvent models and harmonic ap ...

EPFL2022

Real space and reciprocal space investigations of the spin dynamics in skyrmion-hosting materials

Le Yu

Magnetic skyrmions are whirl-like spin configurations with particle-like properties protected by non-trivial topology. Due to their unique spin structures and dynamical properties, they have attracted tremendous interests over the past decade, from fundame ...

EPFL2022

Ab initio theory of magnetism in two-dimensional 1T-TaS2

Oleg Yazyev, Diego José Pasquier

We investigate, using a first-principles density functional methodology, the nature of magnetism in monolayer 1T phase of tantalum disulfide (1T-TaS2). Magnetism in the insulating phase of TaS2 is a longstanding puzzle and has led to a variety of theoretic ...

AMER PHYSICAL SOC2022

Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries

Annalisa Buffa, Pablo Antolin Sanchez, Margarita Chasapi

This contribution explores the combined capabilities of reduced basis methods and IsoGeometric Analysis (IGA) in the context of parameterized partial differential equations. The introduction of IGA enables a unified simulation framework based on a single g ...

2022

Intercalant-mediated Kitaev exchange in Ag3LiIr2O6

Oleg Yazyev, Ravi Yadav

The recently synthesized Ag3LiIr2O6 has been proposed as a Kitaev magnet in proximity to the quantum spin liquid phase. We explore its microscopic Hamiltonian and magnetic ground state using many-body quantum chemistry methods and exact diagonalization tec ...

AMER PHYSICAL SOC2022

Microscopic picture of paraelectric perovskites from structural prototypes

Nicola Marzari, Giovanni Pizzi, Michele Kotiuga, Boris Kozinsky

We highlight with first-principles molecular dynamics the persistence of intrinsic < 111 > Ti off-centerings for BaTiO3 in its cubic paraelectric phase. Intriguingly, these are inconsistent with the Pm (3) over barm space group often used to atomistically ...

AMER PHYSICAL SOC2022

Influence of static correlation on the magnon dynamics of an itinerant ferromagnet with competing exchange interactions: First-principles study of MnBi

Henrik Moodysson Rønnow, Thorbjørn Skovhus

We present first-principles calculations of the dynamic susceptibility in strained and doped ferromagnetic MnBi using time-dependent density functional theory. In spite of being a metal, MnBi exhibits signatures of strong correlation and a proper descripti ...

AMER PHYSICAL SOC2022

Beyond potentials: Integrated machine learning models for materials

Michele Ceriotti

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

SPRINGER HEIDELBERG2022

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