Materials Science (cond-mat.mtrl-sci)

Abstract: The atomic doping of open-shell nanographenes enables the precise tuning of their electronic and magnetic state, which is crucial for their promising potential applications in optoelectronics and spintronics. Among this intriguing class of molecules, triangulenes stand out with their size-dependent electronic properties and spin states, which can also be influenced by the presence of dopant atoms and functional groups. However, the occurrence of Jahn-Teller distortions in such systems can have a crucial impact on their total spin and requires further theoretical and experimental investigation. In this study, we examine the nitrogen-doped aza-triangulene series via a combination of density functional theory and on-surface synthesis. We identify a general trend in the calculated spin states of aza-[n]triangulenes of various sizes, separating them into two symmetry classes, one of which features molecules that are predicted to undergo Jahn-Teller distortions that reduce their symmetry and thus their total spin. We link this behavior to the location of the central nitrogen atom relative to the two underlying carbon sublattices of the molecules. Consequently, our findings reveal that centrally-doped aza-triangulenes have one less radical than their undoped counterparts, irrespective of their predicted symmetry. We follow this by demonstrating the on-surface synthesis of {\pi}-extended aza-[5]triangulene, a large member of the higher symmetry class without Jahn-Teller distortions, via a simple one-step annealing process on Cu(111) and Au(111). Using scanning probe microscopy and spectroscopy combined with theoretical calculations, we prove that the molecule is positively charged on the Au(111) substrate, with a high-spin quintet state of S = 2, the same total spin as undoped neutral [5]triangulene.

Abstract: The traditional display of elements in the periodic table is convenient for the study of chemistry and physics. However, the atomic number alone is insufficient for training statistical machine learning models to describe and extract composition-structure-property relationships. Here, we assess the similarity and correlations contained within high-dimensional local and distributed representations of the chemical elements, as implemented in an open-source Python package ElementEmbeddings. These include element vectors of up to 200 dimensions derived from known physical properties, crystal structure analysis, natural language processing, and deep learning models. A range of distance measures are compared and a clustering of elements into familiar groups is found using dimensionality reduction techniques. The cosine similarity is used to assess the utility of these metrics for crystal structure prediction, showing that they can outperform the traditional radius ratio rules for the structural classification of AB binary solids.

Abstract: LnSbTe (Ln - lanthanide) group of materials, belonging to ZrSiS/PbFCl (P4/nmm) structure type, is a platform to study the phenomena originating from the interplay between the electronic correlations, magnetism, structural instabilities and topological electronic structure. Here we report a systematic study of magnetic properties and magnetic structures of LnSbTe materials. The studied materials undergo antiferromagnetic ordering at TN = 2.1 K (Ln = Er), 6.7 K (Ln = Dy), 3.1 K (Ln = Nd). Neutron powder diffraction reveals ordering with k1 = (1/2 + d 0 0) in ErSbTe, k2 = (1/2 0 1/4) in NdSbTe. DySbTe features two propagation vectors k2 and k4 = (0 0 1/2). No long-range magnetic order is observed in PrSbTe down to 1.8 K. We propose the most probable models of magnetic structures, discuss their symmetry and possible relation between the electronic structure and magnetic ordering.

Abstract: The Li$_2$S-P$_2$S$_5$ pseudo-binary system has been a valuable source of promising superionic conductors, with $\alpha$-Li$_3$PS$_4$, $\beta$-Li$_3$PS$_4$, HT-Li$_7$PS$_6$, and Li$_7$P$_3$S$_{11}$ having excellent room temperature Li-ion conductivity > 0.1 mS/cm. The metastability of these phases at ambient temperature motivates a study to quantify thermodynamic accessibility. Through calculating the electronic, configurational, and vibrational sources of free energy from first principles, a phase diagram of the crystalline Li$_2$S-P$_2$S$_5$ space is constructed. Well-established phase stability trends from experiments are recovered, such as polymorphic phase transitions in Li$_7$PS$_6$ and Li$_3$PS$_4$, and the metastability of Li$_7$P$_3$S$_{11}$ at high temperature. At ambient temperature, it is predicted that all superionic conductors in this space are indeed metastable, but thermodynamically accessible. Vibrational and configurational sources of entropy are shown to be essential towards describing the stability of superionic conductors. New details of the Li sublattices are revealed, and are found to be crucial towards accurately predicting configurational entropy. All superionic conductors contain significant configurational entropy, which suggests an inherent correlation between superionic conductivity and high configurational entropy.

Abstract: The TiSiCO-family monolayers have recently been attracting significant attention due to their unique valley-layer coupling (VLC). In this work, we present a minimal, four-band tight-binding (TB) model to capture the low-energy physics of the TiSiCO-family monolayers $X_{2}Y$CO$_{2}$ ($X=$ Ti, Zr, Hf; $Y=$ Si, Ge) with strong VLC. These monolayers comprise two $X$ atom layers separated by approximately $4$ \AA ~in the out-of-plane direction. Around each valley ($X$ or $X'$), the conduction and valence bands are mainly dominated by the $A_{1}\{d_{z^{2}(x^{2}-y^{2})}\}$ and $B_{2}\{d_{yz}\}$ orbitals of the top $X$ atoms,and the $A_{1}\{d_{z^{2}(x^{2}-y^{2})}\}$ and $B_{1}\{d_{xz}\}$ orbitals of the bottom $X$ atoms. Using these four states as a basis, we construct a symmetry-allowed TB model. Through parameter fitting from first-principles calculations, the four-band TB model not only reproduces the electronic band structure, but also captures the strong VLC, high-order topology, and valley-contrasting linear dichroism of the monolayers. Furthermore, the TB model reveals that these monolayers may exhibit various intriguing topological phases under electric fields and biaxial strains. Hence, the TB model established here can serve as the starting point for future research exploring the physics related to VLC and the $X_{2}Y$CO$_{2}$ monolayers.

Abstract: Long-distance strong coupling between short-wavelength magnons remains an outstanding challenge in quantum magnonics, an emerging interdiscipline between magnonics and quantum information science. Recently, altermagnets are identified as the third elementary class of magnets that break the time-reversal symmetry without magnetization and thus combine characteristics of conventional collinear ferromagnets and antiferromagnets. In this work, we show that cavity photons can mediate the long-distance strong coupling of exchange magnons with opposite chiralities in altermagnets, manifesting as an anticrossing of the magnon-polariton spectrum in the extremely dispersive regime. The predicted effective magnon-magnon coupling strongly depends on the magnon propagation direction, and is thus highly anisotropic. Our findings are intimately connected to the intrinsic nature of altermagnetic magnons, i.e., chirality-splitting-induced crossing of exchange magnons, which has no counterpart in conventional ferromagnets or antiferromagnets, and may open a new path way for magnon-based quantum information processing in altermagnets.

Abstract: Under operating conditions, the dynamics of water and ions confined within protonic aluminosilicate zeolite (H-AS) micropores are responsible for many of their properties, including hydrothermal stability, acidity and catalytic activity. However, due to high computational cost, operando studies of H-AS are currently rare and limited to specific cases and simplified models. In this work, we have developed a general potential energy surface interpolator with consistent accuracy for the entire class of H-AS, including the full range of experimentally relevant water concentrations and Si/Al ratios, via a reactive neural network potential (NNP). This NNP combines dramatic sampling acceleration at the metaGGA reference level with the capacity for discovery of new chemistry, such as collective defect formation mechanisms at the zeolite surface. Furthermore, we show that the baseline model allows for data-efficient adoption of higher-level (hybrid) references via $\Delta$-learning and the acceleration of rare event sampling via automatic construction of collective variables. This framework allows for operando simulations of realistic catalysts at quantitative accuracy.

Abstract: So far, the efficiency of thermoelectric energy conversion remains low compared to traditional technologies, such as coal or nuclear. This low efficiency can be explained by connecting the thermoelastic properties of the electronic working fluid to its transport properties. Such connection also shows that operating close to electronic phase transitions can be an efficient way to boost the thermoelectric energy conversion. In this paper, we analyze themoelectric efficiency close to the metal-insulator Anderson transition. Our results reveal the direct link between the thermoelectric and thermoelastic properties of Anderson-type systems. Moreover, the role of the conductivity critical exponent in the thermoelectric energy conversion is analysed. Finally, we show that relatively large values of the thermolectric figure of merit may be obtained in the vicinity of the Anderson transition.

Abstract: Recently, Chuanying Li, Tao Fu, Xule Li, Hao Hu, and Xianghe Peng in [Phys. Rev. B 107, 224106] investigated the mechanical behavior of cubic HfC and TaC under simple shear (SS) and pure shear (PS) using first-principles calculations. Unfortunately, the paper contains some serious and fundamental flaws in the field of continuum mechanics and nanomechanics. The results presented appear to be qualitatively and quantitatively incorrect, they would be correct if we were in the small/linear deformation/strain regime, which we are not. A correct description therefore requires a finite/nonlinear deformation/strain apparatus.

Abstract: Accurate structural analysis is essential to gain physical knowledge and understanding of atomic-scale processes in materials from atomistic simulations. However, traditional analysis methods often reach their limits when applied to crystalline systems with thermal fluctuations, defect-induced distortions, partial vitrification, etc. In order to enhance the means of structural analysis, we present a novel descriptor for encoding atomic environments into 2D images, based on a pixelated representation of graph-like architecture with weighted edge connections of neighboring atoms. This descriptor is well adapted for Convolutional Neural Networks and enables accurate structural analysis at a low computational cost. In this paper, we showcase a series of applications, including the classification of crystalline structures in distorted systems, tracking phase transformations up to the melting temperature, and analyzing liquid-to-amorphous transitions in pure metals and alloys. This work provides the foundation for robust and efficient structural analysis in materials science, opening up new possibilities for studying complex structural processes, which can not be described with traditional approaches.

Abstract: The phase-field crystal model (PFC) describes crystal structures at diffusive timescales through a periodic order parameter representing the atomic density. One of its main features is that it naturally incorporates elastic and plastic deformation. To correctly interpret numerical simulation results or devise extensions related to the elasticity description, it is important to have direct access to the elastic field. In this work, we discuss its evaluation in classical PFC models based on the Swift-Hohenberg energy functional. We consider approaches where the stress field can be derived from the microscopic density field (i.e., the order parameter), and a simple novel numerical routine is proposed. By numerical simulations, we demonstrate that it overcomes some limitations of currently used methods. Moreover, we shed light on the elasticity description conveyed by classical PFC models, characterizing a residual stress effect present at equilibrium. We show explicitly and discuss the evaluation of the elastic fields in prototypical representative cases involving an elastic inclusion, a grain boundary, and dislocations.

Abstract: The solid-state electrolyte is critical for achieving next-generation high energy density and high-safety batteries. Solid polymer electrolytes (SPEs) possess great potential for commercial application owing to their compatibility with the existing manufacturing systems. However, unsatisfactory room-temperature ionic conductivity severely limits its application. Herein, an ultra-high room-temperature ionic conductivity composite solid-state electrolyte (CSE) is prepared by introducing an appropriate amount of SiO2 nanosphere to the PVDF-HFP matrix. By doing this, the polymer particles are divided and surrounded by SiO2. And the interface amount is maximized resulting in the high ionic conductivity of 1.35 mS cm-1 under room temperature. In addition, the CSE shows a wide electrochemical window of 4.95 V and a moderate Li+ transference number of 0.44. The CSE demonstrates good stability with Li anode, with Li symmetric cells that could cycle 1000 h at a current density of 0.2 mA cm-2. The full cell assembled with LiFePO4 (LFP) and Li metal displays a high reversible specific capacity of 157.8 mAh g-1 at 0.1C, and it could maintain 92.9% of initial capacity after 300 cycles at 3C. Moreover, the strategy is applied in solid-state sodium/potassium batteries and displays excellent performance.

Abstract: Thin films based on silicon and transition-metal elements dominate the semiconducting industry and are ubiquitous in all modern devices. Films have also been produced in the rare-earth series of elements for both research and specialized applications. Thin films of uranium and uranium dioxide were fabricated in the 1960s and 1970s, but there was little sustained effort until the early 2000s. Significant programmes started at Oxford University (transferring to Bristol University in 2011), and Los Alamos National Laboratory (LANL) in New Mexico, USA. In this review we cover the work that has been published over the last ~20 years with these materials. Important breakthroughs occurred with the fabrication of epitaxial thin films of initially uranium metal and UO2, but more recently of many other uranium compounds and alloys. These have led to a number of different experiments that are reviewed, as well as some important trends. The interaction with the substrate leads to differing strain and hence changes in properties. An important advantage is that epitaxial films can often be made of materials that are impossible to produce as bulk single crystals. Examples are U3O8, U2N3 and alloys of U-Mo, which form in a modified bcc structure. Epitaxial films may also be used in applied research. They represent excellent surfaces, and it is at the surfaces that most of the important reactions occur in the nuclear fuel cycle. For example, the fuel-cladding interactions, and the dissolution of fuel by water in the long-term storage of spent fuel. To conclude, we discuss possible future prospects, examples include bilayers containing uranium for spintronics, and superlattices that could be used in heterostructures. Such applications will require a more detailed knowledge of the interface interactions in these systems, and this is an important direction for future research.

Abstract: EuTiO3 (ETO) is a well-known complex oxide mainly investigated for its magnetic properties and its incipient ferro-electricity. In this work, we demonstrate the realization of suspended micro-mechanical structures, such as cantilevers and micro-bridges, from 100 nm-thick single-crystal epitaxial ETO films deposited on top of SrTiO3(100) substrates. By combining profile analysis and resonance frequency measurements of these devices, we obtain the Young's modulus, strain, and strain gradients of the ETO thin films. Moreover, we investigate the ETO anti-ferro-distorsive transition by temperature-dependent characterizations, which show a non-monotonic and hysteretic mechanical response. Comparison between experimental and literature data allows us to weight the contribution from thermal expansion and softening to the tuning slope, while a full understanding of the origin of the hysteresis is still missing. We also discuss the influence of oxygen vacancies on the reported mechanical properties by comparing stoichiometric and oxygen-deficient samples.

Abstract: Scanning precession electron diffraction (SPED) is a powerful technique for investigating strain. While extensive literature exists analysing strain under high convergence angle conditions there are few systematic studies describing work based around the use of smaller convergence angles despite this being a common set-up. We fill in some of this gap in the literature by providing a workflow for both the experimental and analysis components of such experiments. Our case study investigates strained Gallium Arsenide nanowires with a modern direct electron detector and common microscope alignments. Three peak finding routines are compared and we provide both source code and raw data to allow others to reproduce our findings.

Abstract: Extracting reliable information on certain physical properties of materials, like thermal behavior, such as thermal transport, which can be very computationally demanding. Aiming to overcome such difficulties in the particular case of lattice thermal conductivity (LTC) of 2D nanomaterials, we propose a simple, fast, and accurate semi-empirical approach for its calculation.The approach is based on parameterized thermochemical equations and Arrhenius-like fitting procedures, thus avoiding molecular dynamics or \textit{ab initio} protocols, which frequently demand computationally expensive simulations. As proof of concept, we obtain the LTC of some prototypical physical systems, such as graphene (and other 2D carbon allotropes), hexagonal boron nitride (hBN), silicene, germanene, binary, and ternary BNC latices and two examples of the fullerene network family. Our values are in good agreement with other theoretical and experimental estimations, nonetheless being derived in a rather straightforward way, at a fraction of the computational cost.

Abstract: Efficiently simulating real materials under the application of a time-dependent field and computing reliably the evolution over time of relevant response functions, such as the TR-ARPES signal or differential transient optical properties, has become one of the main concerns of modern condensed matter theory in response to the recent developments in all areas of experimental out-of-equilibrium physics. In this manuscript, we propose a novel model-Hamiltonian method, the dynamical projective operatorial approach (DPOA), designed and developed to overcome some of the limitations and drawbacks of currently available methods. Relying on (i) many-body second-quantization formalism and composite operators, DPOA is in principle capable of handling both weakly and strongly correlated systems, (ii) tight-binding approach and wannierization of DFT band structures, DPOA naturally deals with the complexity and the very many degrees of freedom of real materials, (iii) dipole gauge and Peierls substitution, DPOA is built to address pumped systems and, in particular, pump-probe spectroscopies, (iv) a Peierls expansion we have devised ad hoc, DPOA is numerically extremely efficient and fast. The latter expansion clarifies how single- and multi-photon resonances, rigid shifts, band dressings, and different types of sidebands emerge and allows understanding the related phenomenologies. Comparing DPOA to the single-particle density-matrix approach and the Houston method (this latter is generalized to second-quantization formalism), we show how it can compute multi-particle multi-time correlation functions and go well beyond these approaches for real materials. We also propose protocols for evaluating the strength of single- and multi-photon resonances and for assigning the residual excited electronic population at each crystal momentum and band to a specific excitation process. The expression for ...

Abstract: The discovery of magnetism in van der Waals (vdW) materials has established unique building blocks for the research of emergent spintronic phenomena. In particular, owing to their intrinsically clean surface without dangling bonds, the vdW magnets hold the potential to construct a superior interface that allows for efficient electrical manipulation of magnetism. Despite several attempts in this direction, it usually requires a cryogenic condition and the assistance of external magnetic fields, which is detrimental to the real application. Here, we fabricate heterostructures based on Fe3GaTe2 flakes that possess room-temperature ferromagnetism with excellent perpendicular magnetic anisotropy. The current-driven non-reciprocal modulation of coercive fields reveals a high spin-torque efficiency in the Fe3GaTe2/Pt heterostructures, which further leads to a full magnetization switching by current. Moreover, we demonstrate the field-free magnetization switching resulting from out-of-plane polarized spin currents by asymmetric geometry design. Our work could expedite the development of efficient vdW spintronic logic, memory and neuromorphic computing devices.

Abstract: By applying auxiliary-field quantum Monte Carlo, we calculate the equation of state (EOS) and B1-B2 phase transition of magnesium oxide (MgO) up to 1 TPa. The results agree with available experimental data at low pressures and are used to benchmark the performance of various exchange-correlation functionals in density functional theory calculations. We determine PBEsol is an optimal choice for the exchange-correlation functional and perform extensive phonon and quantum molecular-dynamics calculations to obtain the thermal EOS. Our results provide a preliminary reference for the EOS and B1-B2 phase boundary of MgO from zero up to 10,500 K.

Abstract: To describe the charge-polarization coupling in the nanostructure formed by a thin Hf$_x$Zr$_{1-x}$O$_2$ film with a single-layer graphene as a top electrode, we develop the phenomenological effective Landau-Ginzburg-Devonshire model. This approach is based on the parametrization of the Landau expansion coefficients for the polar and antipolar orderings in thin Hf$_x$Zr$_{1-x}$O$_2$ films from a limited number of polarization-field curves and hysteresis loops. The Landau expansion coefficients are nonlinearly dependent on the film thickness $h$ and Zr/[Hf+Zr] ratio $x$, in contrast to h-independent and linearly $x$-dependent expansion coefficients of a classical Landau energy. We explain the dependence of the Landau expansion coefficients by the strong nonmonotonic dependence of the Hf$_x$Zr$_{1-x}$O$_2$ film polar properties on the film thickness, grain size and surface energy. The proposed Landau free energy with five "effective" expansion coefficients, which are interpolation functions of $x$ and $h$, describes the continuous transformation of polarization dependences on applied electric field and hysteresis loop shapes induced by the changes of $x$ and $h$ in the range $0 < x < 1$ and 5 nm < $h$ < 35 nm. Using this effective free energy, we demonstrated that the polarization of Hf$_x$Zr$_{1-x}$O$_2$ film influences strongly on the graphene conductivity, and the full correlation between the distribution of polarization and charge carriers in graphene is revealed. In accordance with our modeling, the polarization of the (5 - 25) nm thick Hf$_x$Zr$_{1-x}$O$_2$ films, which are in the ferroelectric-like or antiferroelectric-like states for the chemical compositions $0.35 < x < 0.95$, determine the concentration of carriers in graphene and can control its field dependence. The result can be promising for creation of next generation Si-compatible nonvolatile memories and graphene-ferroelectric FETs.

Abstract: Two-dimensional (2D) antiferromagnets have garnered considerable interest for the next generation of functional spintronics. However, many available bulk materials from which 2D antiferromagnets are isolated are limited by their sensitivity to air, low ordering temperatures, and insulating transport properties. TaFe$_{1+y}$Te$_3$ offers unique opportunities to address these challenges with increased air stability, metallic transport properties, and robust antiferromagnetic order. Here, we synthesize TaFe$_{1+y}$Te$_3$ ($y$ = 0.14), identify its structural, magnetic, and electronic properties, and elucidate the relationships between them. Axial-dependent high-field magnetization measurements on TaFe$_{1.14}$Te$_3$ reveal saturation magnetic fields ranging between 27-30 T with a saturation magnetic moment of 2.05-2.12 $\mu_B$. Magnetotransport measurements confirm TaFe$_{1.14}$Te$_3$ is metallic with strong coupling between magnetic order and electronic transport. Angle-resolved photoemission spectroscopy measurements across the magnetic transition uncover a complex interplay between itinerant electrons and local magnetic moments that drives the magnetic transition. We further demonstrate the ability to isolate few-layer sheets of TaFe$_{1.14}$Te$_3$ through mechanical exfoliation, establishing TaFe$_{1.14}$Te$_3$ as a potential platform for 2D spintronics based on metallic layered antiferromagnets.

Abstract: Saddle point search schemes are widely used to identify the transition state of different processes, like chemical reactions, surface and bulk diffusion, surface adsorption, and many more. In solid-state materials with relatively large numbers of atoms, the minimum mode following schemes such as dimer are commonly used because they alleviate the calculation of the Hessian on the high-dimensional potential energy surface. Here, we show that the dimer search can be further accelerated by leveraging Gaussian process regression (GPR). The GPR serves as a surrogate model to feed the dimer with the required energy and force input. We test the GPR- accelerated dimer method for predicting the diffusion coefficient of vacancy-mediated self-diffusion in bcc molybdenum and sulfur diffusion in hexagonal molybdenum disulfide. We use a multi-task learning approach that utilizes a shared covariance function between energy and force input, and we show that the multi-task learning significantly improves the performance of the GPR surrogate model compared to previously used learning approaches. Additionally, we demonstrate that a translation-hop sampling approach is necessary to avoid over-fitting the GPR surrogate model to the minimum-mode-following pathway and thus succeeding in locating the saddle point. We show that our method reduces the number of evaluations to a fraction of what a conventional dimer requires.