arXiv subjects

Pau Torruella

Publications and source records attributed to Pau Torruella.

2 recordsLinked to original sources

arXiv2026

Paramagnetically driven superconducting re-entrance in Eu-doped infinite layer nickelates

The breakthrough discovery of superconductivity in infinite-layer nickelates, and subsequently in several superconducting nickelates with more complex layered structures, capped a search spanning more than two decades and opened an entirely new field of research. Significant efforts aim to increase the critical temperature, to determine the electronic structure of the system, the underlying pairing mechanism, and the similarities between this system and cuprates - Ni1+ in infinite-layer nickelates being isoelectronic to Cu2+ in high-Tc cuprates. Here, we explore the unique role of magnetic rare earth ions in superconducting Eu-doped NdNiO2. We show that the field-induced re-entrant superconductivity which we evidence in this compound is the result of a delicate balance between the competing effects of the Eu2+ and Nd3+ ions. Our analyses of the extraordinary Hall effect and modeling of the superconducting critical fields demonstrate that the influence of these ions on magneto-transport is only felt when they are polarized by a magnetic field.

cond-mat.supr-con↗

arXiv2025

A multiscale Bayesian approach to quantification and denoising of energy-dispersive x-ray data

Energy dispersive X-ray (EDX) spectrum imaging yields compositional information with a spatial resolution down to the atomic level. However, experimental limitations often produce extremely sparse and noisy EDX spectra. Under such conditions, every detected X-ray must be leveraged to obtain the maximum possible amount of information about the sample. To this end, we introduce a robust multiscale Bayesian approach that accounts for the Poisson statistics in the EDX data and leverages their underlying spatial correlations. This is combined with EDX spectral simulation (elemental contributions and Bremsstrahlung background) into a Bayesian estimation strategy. When tested using simulated datasets, the chemical maps obtained with this approach are more accurate and preserve a higher spatial resolution than those obtained by standard methods. These properties translate to experimental datasets, where the method enhances the atomic resolution chemical maps of a canonical tetragonal ferroelectric PbTiO3 sample, such that ferroelectric domains are mapped with unit-cell resolution.

cond-mat.mtrl-sci↗