Materials Science (cond-mat.mtrl-sci)

Abstract: Two-dimensional band dispersion of (2$\times$2) superstructure with Bi grown on Ag(111), which has been urged as an ultraflat hexagonal bismuthene, is investigated using angle-resolved photoemission spectroscopy (ARPES). The (2$\times$2)-Bi superstructure can be grown on the Ag(111) surface at low temperatures; it transforms into a surface alloy with a ($\sqrt{3}\times\sqrt{3}$) superstructure at 300 K. ARPES measurements reveal the consistency with the band structure of ultraflat bismuthene in previous reports. The band structure of (2$\times$2)-Bi surface remains unchanged with decreasing Ag layer thickness, indicating the limited penetration of Bi p-orbitals into the Ag layer.

Abstract: The role played by electronic and phononic excitations in the femtosecond laser induced desorption and oxidation of CO coadsorbed with O on Ru(0001) is investigated using ab initio molecular dynamics with electronic friction. To this aim, simulations that account for both kind of excitations and that only consider electronic excitations are performed. Results for three different surface coverages are obtained. We unequivocally demonstrate that CO desorption is governed by phononic excitations. In the case of oxidation the low statistics does not allow to give a categorical answer. However, the analysis of the adsorbates kinetic energy gain and displacements strongly suggest that phononic excitations and surface distortion also play an important role in the oxidation process.

Abstract: The increased time- and length-scale of classical molecular dynamics simulations have led to raw data flows surpassing storage capacities, necessitating on-the-fly integration of structural analysis algorithms. As a result, algorithms must be computationally efficient, accurate, and stable at finite temperature to reliably extract the relevant features of the data at simulation time. In this work, we leverage spectral descriptors to encode local atomic environments and build crystal structure classification models. In addition to the classical way spectral descriptors are computed, i.e. over a fixed radius neighborhood sphere around a central atom, we propose an extension to make them independent from the material's density. Models are trained on defect-free crystal structures with moderate thermal noise and elastic deformation, using the linear discriminant analysis (LDA) method for dimensionality reduction and logistic regression (LR) for subsequent classification. The proposed classification model is intentionally designed to be simple, incorporating only a limited number of parameters. This deliberate simplicity enables the model to be trained effectively even when working with small databases. Despite the limited training data, the model still demonstrates inherent transferability, making it applicable to a broader range of scenarios and datasets. The accuracy of our models in extreme conditions is compared to traditional algorithms from the literature, namely adaptive common neighbor analysis (a-CNA), polyhedral template matching (PTM) and diamond structure identification (IDS). Finally, we showcase two applications of our method: tracking a solid-solid BCC-to-HCP phase transformation in Zirconium at high pressure up to high temperature, and visualizing stress-induced dislocation loop expansion in single crystal FCC Aluminum containing a Frank-Read source, at high temperature.

Abstract: Here we describe an efficient numerical implementation of the Bethe-Salpeter equation to obtain the excitonic spectrum of semiconductors. This is done on the electronic structure calculated either at the simplest tight-binding level or through density funcional theory calculations based on local orbitals. We use a simplified model for the electron-electron interactions which considers atomic orbitals as point-like orbitals and a phenomenological screening. The optical conductivity can then be optionally computed within the Kubo formalism. Our results for paradigmatic two-dimensional materials such as hBN and MoS2, when compared with those of more sophisticated first-principles methods, are excellent and envision a practical use of our implementation beyond the computational limitations of such methods.

Abstract: Thin Ge layers deposited on Si(105) form a stable single-domain film structure with large terraces and rebonded-step surface termination, thus realizing an extended and ordered Ge/Si planar hetero-junction. At the coverage of four Ge monolayers angle-resolved photoemission spectroscopy reveals the presence of two-dimensional surface and film bands displaying energy-momentum dispersion compatible with the 5x4 periodicity of the system. The good agreement between experiment and first-principles electronic structure calculations confirms the validity of the rebonded-step structural model. The direct observation of surface features within 1 eV below the valence band maximum corroborates previously reported analysis of the electronic and optical behavior of the Ge/Si hetero-interface.

Abstract: The properties of porous glasses and their field of application strongly depend on the characteristics of the void space. Understanding the relationship between their porous structure and failure behaviour can contribute to the development of porous glasses with long-term reliability optimized for specific applications. In the present work, we used X-ray computed tomography with nanometric resolution (nano-CT) to image a controlled pore glass (CPG) with 400 nm-sized pores whilst undergoing uniaxial compression in-situ to emulate a stress process. Our results show that in-situ nano-CT provides an ideal platform for identifying the mechanisms of damage within glass with pores of 400 nm, as it allowed the tracking of the pores and struts change of shape during compression until specimen failure. We have also applied computational tools to quantify the microstructural changes within the CPG sample by mapping the displacements and strain fields, and to numerically simulate the behaviour of the CPG using a Fast Fourier Transform/phase-field method. Both experimental and numerical data show local shear deformation, organized along bands, consistent with the appearance and propagation of +/- 45 degrees cracks.

Abstract: Cu-based argyrodites have gained much attention as a new class of thermoelectric materials for energy harvesting. However, the phase transition occurring in these materials and low energy conversion performance limited their broad application in thermoelectric converters. In this work, we disclose a newly discovered highly efficient Cu8SiSxSe6-x argyrodite with stabilized high-symmetry cubic phase at above 282 K opening the practical potential of this material for the mid-temperature region applications. The temperature range broadening of the high-symmetry phase existence was possible due to the successful substitution of Se with S in Cu8SiSxSe6-x, which enhances the configurational entropy. The developed argyrodites show excellent thermoelectric performance thanks to the increased density of states effective mass and ultralow lattice thermal conductivity. Further tuning of the carrier concentration through the Cu-deviation improves the thermoelectric performance significantly. The dimensionless thermoelectric figure of merit ZT and estimated energy conversion efficiency {\eta} for Cu7.95SiS3Se3 achieve outstanding values of the 1.45 and 13 %, respectively, offering this argyrodite as a low-cost and Te-free alternative for the thermoelectric energy conversion applications.

Abstract: The reactivity of silicates in an aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of chemical reactions can provide insight at the molecular level, balancing accuracy and scale in reactive simulations in the condensed phase is a challenge. Here, we demonstrate how a machine-learning reactive interatomic potential can accurately capture silicate-water reactivity. The model was trained on a new dataset comprising 400,000 energies and forces of molecular clusters at the $\omega$-B97XD def2-TVZP level. To ensure the robustness of the model, we introduce a new and general active learning strategy based on the attribution of the model uncertainty, that automatically isolates uncertain regions of bulk simulations to be calculated as small-sized clusters. Our trained potential is found to reproduce static and dynamic properties of liquid water and solid crystalline silicates, despite having been trained exclusively on cluster data. Furthermore, we utilize enhanced sampling simulations to recover the self-ionization reactivity of water accurately, and the acidity of silicate oligomers, and lastly study the silicate dimerization reaction in a water solution at neutral conditions and find that the reaction occurs through a flanking mechanism.

Abstract: Chiral symmetry plays an indispensable role in topological classifications as well as in the understanding of the origin of bulk or boundary flat bands. The conventional definition of chiral symmetry refers to the existence of a constant unitary matrix anticommuting with the Hamiltonian. As a constant unitary matrix has constant eigenvectors, boundary flat bands enforced by chiral symmetry, which share the same eigenvectors with the chiral symmetry operator, are known to carry fixed (pseudo)spin polarizations and be featureless in quantum geometry. In this work, we generalize the chiral symmetry and introduce a concept termed sub-chiral symmetry. Unlike the conventional chiral symmetry operator defined as constant, the sub-chiral symmetry operator depends on partial components of the momentum vector, so as its eigenvectors. We show that topological gapped or gapless systems without the chiral symmetry but with the sub-chiral symmetry can support boundary flat bands, which exhibit topological spin textures and quantized Berry phases. We expect that such intriguing boundary flat bands could give rise to a variety of exotic physics in the presence of interactions or disorders.

Abstract: The developing field of strain-induced magnetization dynamics offers a promising path toward efficiently controlling spins and phase transitions. Understanding the underlying mechanisms is crucial in finding the optimal parameters supporting the phononic switching of magnetization. Here, we present an experimental and numerical study of time-resolved magnetization dynamics driven by the resonant excitation of an optical phonon mode in iron garnets. Upon pumping the latter with an infrared pulse obtained from a free-electron laser, we observe spatially-varying magnetization precession, with its phase depending on the direction of an external magnetic field. Our micromagnetic simulations effectively describe the magnetization precession and switching in terms of laser-induced changes in the crystal's magneto-elastic energy.