An effective Hamiltonian scheme is developed to study finite-temperature properties of multiferroic BiFeO3. This approach reproduces very well (i) the symmetry of the ground state, (ii) the Néel and Curie temperatures, and (iii) the intrinsic magnetoelectric coefficients (that are very weak). This scheme also predicts (a) an overlooked phase above Tc approximately 1100 K that is associated with antiferrodistortive motions, as consistent with our additional x-ray diffractions, (b) improperlike dielectric features above Tc, and (c) that the ferroelectric transition is of first order with no group-subgroup relation between the paraelectric and polar phases.
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http://dx.doi.org/10.1103/PhysRevLett.99.227602 | DOI Listing |
Dalton Trans
January 2025
Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork, T12 R5CP, Ireland.
Layered materials, such as tungsten dichalcogenides (TMDs), are being studied for a wide range of applications, due to their unique and varied properties. Specifically, their use as either a support for low dimensional catalysts or as an ultrathin diffusion barrier in semiconductor devices interconnect structures are particularly relevant. In order to fully realise these possible applications for TMDs, understanding the interaction between metals and the monolayer they are deposited on is of utmost importance.
View Article and Find Full Text PDFJ Comput Chem
January 2025
School of Chemical Sciences, Indian Association for the Cultivation of Science, Kolkata, India.
The ensemble properties of a system are obtained by averaging over the properties calculated for the various configurations it can have at a finite temperature and thus cannot be captured by a single molecular structure. Such ensemble properties are often important in material discovery. In designing new materials, the goal is to predict those ensemble structures that display a tailored property.
View Article and Find Full Text PDFEntropy (Basel)
January 2025
CeBio-Departamento de Ciencias Básicas, Universidad Nacional del Noroeste Provincia de Buenos Aires (UNNOBA), CONICET, Junin 6000, Argentina.
In this study, we utilize information theory tools to investigate notable features of the quantum degree of mixedness (Cf) in a finite model of interacting fermions. This model serves as a simplified proxy for an atomic nucleus, capturing its essential features in a more manageable form compared to a realistic nuclear model, which would require the diagonalization of matrices with millions of elements, making the extraction of qualitative features a significant challenge. Specifically, we aim to correlate Cf with particle number fluctuations and temperature, using the paradigmatic Lipkin model.
View Article and Find Full Text PDFInd Eng Chem Res
January 2025
Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, U.K.
Efficiently obtaining atomic-scale thermodynamic parameters characterizing crystallization from solution is key to developing the modeling strategies needed in the quest for digital design strategies for industrial crystallization processes. Based on the thermodynamics of crystal nucleation in confined solutions, we develop a simulation framework to efficiently estimate the solubility and surface tension of organic crystals in solution from a few unbiased molecular dynamics simulations at a reference temperature. We then show that such a result can be extended with minimal computational overhead to capture the solubility curve.
View Article and Find Full Text PDFChem Sci
December 2024
VASP Software GmbH Berggasse 21 A-1090 Vienna Austria.
Constructing a self-consistent first-principles framework that accurately predicts the properties of electron transfer reactions through finite-temperature molecular dynamics simulations is a dream of theoretical electrochemists and physical chemists. Yet, predicting even the absolute standard hydrogen electrode potential, the most fundamental reference for electrode potentials, proves to be extremely challenging. Here, we show that a hybrid functional incorporating 25% exact exchange enables quantitative predictions when statistically accurate phase-space sampling is achieved thermodynamic integrations and thermodynamic perturbation theory calculations, utilizing machine-learned force fields and Δ-machine learning models.
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