We propose a Bayesian inference methodology to evaluate unobservable parameters involved in multi-phase-field models to accurately predict the observed grain growth, such as in metals and alloys. This approach integrates models and a set of observational image data of grain structures. Because the image data set is not a time series, directly applying conventional inference techniques that require time series as the input data is difficult. The key idea in our methodology to overcome this difficulty is to construct a time series with an appropriate statistic that characterizes static image data of grain structures. Our methodology implements the empirical Bayes method. It can estimate not only a probability density function of the parameters but also an initial phase field, which is generally unobservable in real experiments. After validating the proposed method through numerical tests using synthetic data, we apply it to real experimental images of grain structures in a steel alloy. The proposed method properly estimates unobservable parameters along with their uncertainties and successfully selects the initial phase field that best explains the experimental data from among candidate initial phase fields.

The phase stability of two-dimensional monolayer ${\mathrm{As}}_{1-x}{\mathrm{P}}_x$ solid solutions, exhibiting the puckered ($\alpha$ phase) and buckled ($\beta$ phase) structures are investigated using a first-principles cluster-expansion method. Canonical Monte Carlo simulations, together with harmonic approximation, are performed to capture the influences of thermally induced configurational disorder and lattice vibrations on the phase stability of monolayer ${\mathrm{As}}_{1-x}{\mathrm{P}}_x$. We first demonstrate that, as the temperature approaches 0 K, the monolayer ${\mathrm{As}}_{1-x}{\mathrm{P}}_x$ displays a tendency toward phase separation into its constituent elemental phases, and thus no stable ordered structures of ${\mathrm{As}}_{1-x}{\mathrm{P}}_x$, both $\alpha$ and $\beta$ phases, are predicted to be thermodynamically stable. We further reveal with the inclusion of the lattice vibrational contributions that $\beta -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$ is thermodynamically favored over $\alpha -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$ across the entire composition range even at 0 K and increasingly so at higher temperature, and a continuous series of disordered solid solution of $\beta -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$, where $0⩽x⩽1$, is predicted at the temperature above 550 K. These findings not only indicate that the ordered structures of monolayer $\alpha -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$ and $\beta -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$, frequently studied in the literature, may not exist in nature, but also presumably suggest that monolayer $\alpha -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$ is metastable with respect to monolayer $\beta -{\mathrm{As}}_{1-x}{\mathrm{P}}_x$.

The thermodynamic stability of the coherent shell and Stranski-Krastanov heteroepitaxial growth modes on cylindrical nanowires is analyzed theoretically. In contrast to previous studies, the exact geometrical shape of pyramidal Stranski-Krastanov islands is considered for the calculation of surface- and elastic-energy contributions. In particular, the impact of the pyramid base angle on the relaxation energy is included. Moreover, the dependence of island facet surface-energy density on the distance of the surface to the nanowire substrate is taken into account. Maps of the growth-mode stability are derived for the Si-core/Ge-shell structure, which display the favored mode as a function of deposited volume, wetting-layer thickness, and nanowire radius. We show that for nanowire radii in the range between 15 and 100 nm, the Stranski-Krastanov mode becomes stable only for larger pyramid angles. In addition, it is found that the exact value of the surface-energy density significantly influences the transition between the two growth modes, leading to a stabilization of islands bound by low-energy crystal facets, as observed in experiments.

Irradiation induces significant changes in the microstructure of structural materials, many of which are driven by the preferential capture of point defects at particular sinks, such as dislocations. To quantify the kinetics of defect absorption at sinks, theoretical models of radiation damage generally rely on the concept of sink strength. However, analytical approaches to estimating the sink strength of dislocations rely, in turn, on a series of geometrical assumptions, idealizing the dislocation network as a series of infinite straight dislocations or isolated loops, often with artificial boundary conditions. In this paper, we use a recently developed technique to quantify point defect capture in three-dimensional dislocation networks. We integrate this technique with discrete dislocation dynamics to analyze the sink strengths of realistic dislocation microstructures consisting of a mixture of edge, screw, and junction segments, complete with an accurate description of the strain fields these microstructures produce and the resultant energetic interactions experienced by point defects. We show that the effective kinetics for absorbing point defects can vary significantly with the arrangement of the microstructure with a strong dependence on the structure and character of its dislocation content and introduce a surrogate model for sink strength which incorporates these effects.

We propose a framework for optimization of the chemical composition of multinary compounds with the aid of machine learning. The scheme is based on first-principles calculation using the Korringa-Kohn-Rostoker method and the coherent potential approximation (KKR-CPA). We introduce a method for integrating datasets to reduce systematic errors in a dataset, where the data are corrected using a smaller and more accurate dataset. We apply this method to values of the formation energy calculated by KKR-CPA for nonstoichiometric systems to improve them using a small dataset for stoichiometric systems obtained by the projector-augmented-wave method. We apply our framework to optimization of $R{\mathrm{Fe}}_{12}$-type magnet compounds $(R_{1-\alpha }{Z}_{\alpha }){\left({\mathrm{Fe}}_{1-\beta }{\mathrm{Co}}_{\beta }\right)}_{12-\gamma }{\mathrm{Ti}}_{\gamma }$, and benchmark the efficiency in determination of the optimal choice of elements ($R$ and $Z$) and ratio ($\alpha$, $\beta$, and $\gamma$) with respect to magnetization, Curie temperature, and formation energy. We find that the optimization efficiency depends on descriptors significantly. The variables $\beta$, $\gamma$, and the number of electrons from the $R$ and $Z$ elements per cell are important in improving the efficiency. When the descriptor is appropriately chosen, the Bayesian optimization becomes much more efficient than random sampling.

Evidence of flat-band magnetism and half-metallicity in compressed twisted bilayer graphene is provided with first-principles calculations. We show that dynamic band-structure engineering in twisted bilayer graphene is possible by controlling the chemical composition with extrinsic doping, the interlayer coupling strength with pressure, and the magnetic ordering with external electric field. By varying the rotational order and reducing the interlayer separation, an unbalanced distribution of charge density results in the spontaneous apparition of localized magnetic moments without disrupting the structural integrity of the bilayer. Weak exchange correlation between magnetic moments is estimated in large unit cells. External electric field switches the local magnetic ordering from ferromagnetic to antiferromagnetic. Substitutional doping shifts the chemical potential of one spin distribution and leads to half-metallicity. Flakes of compressed twisted bilayer graphene exhibit spontaneous magnetization, demonstrating that correlation between magnetic moments is not a necessary condition for their formation.

Grain boundary (GB) and surface segregation have been studied by computer simulations in the so-called Cantor alloy: $\mathrm{C}{\mathrm{o}}_{20}\mathrm{N}{\mathrm{i}}_{20}\mathrm{C}{\mathrm{r}}_{20}\mathrm{F}{\mathrm{e}}_{20}\mathrm{M}{\mathrm{n}}_{20}$. Monte Carlo, molecular dynamics, as well as lattice statics methods, using second nearest-neighbor modified embedded atom method potentials, have been applied sequentially in order to equilibrate the alloy. Simulations of GB segregation showed that Cr segregates most strongly, and is accompanied by weak Mn segregation. In contrast, in the case of surface segregation, Mn segregates most strongly to the outermost surface atom plane. However, when adsorption is measured as the integrated excess of the components over a 4-atom-layer region adjacent to the surface, Cr again emerges as the dominant segregant. A mass balance model has also been applied to the results of the segregation behavior, in order to estimate the potential for depletion of the bulk alloy composition due to segregation at GBs. It is found that significant depletion of bulk composition can occur if the alloy grain size falls below about 100 nm.

We study the influence of sample termination on the electronic properties of the novel quantum spin Hall insulator monolayer $1T^{\prime }\text{−}{\mathrm{WTe}}_2$. For this purpose, we construct an accurate, minimal four-orbital tight-binding model with spin-orbit coupling by employing a combination of density-functional theory calculations, symmetry considerations, and fitting to experimental data. Based on this model, we compute energy bands and two-terminal conductance spectra for various ribbon geometries with different terminations, with and without a magnetic field. Because of the strong electron-hole asymmetry, we find that the edge Dirac point is buried in the bulk bands for most edge terminations. In the presence of a magnetic field, an in-gap edge Dirac point leads to exponential suppression of conductance as an edge Zeeman gap opens, whereas the conductance stays at the quantized value when the Dirac point is buried in the bulk bands. Finally, we find that disorder in the edge termination drastically changes this picture: the conductance of a sufficiently rough edge is uniformly suppressed for all energies in the bulk gap regardless of the orientation of the edge.

We report the observation of the crossover between the extrinsic and intrinsic spin Hall effect induced by alloying. We found that the spin Hall angle, the ratio of the spin Hall conductivity to the electric conductivity, changes drastically by tuning the composition of the Au-Cu alloy. The spin Hall angle changes sign only in a limited range of the Cu concentration due to the extrinsic skew scattering, while the intrinsic contribution becomes dominant with increasing Cu concentration. This observation provides essential information for a fundamental understanding of spin-orbit physics.

We successfully synthesized and characterized the triangular lattice antiferromagnet ${\mathrm{Ba}}_8{\mathrm{MnNb}}_6{\mathrm{O}}_{24}$, which comprises equilateral spin-$\frac{5}{2}{\mathrm{Mn}}^{2+}$ triangular layers separated by six nonmagnetic ${\mathrm{Nb}}^{5+}$ layers. The detailed susceptibility, specific heat, elastic and inelastic neutron scattering measurements, and spin-wave theory simulation on this system reveal that it has a ${120}^{\circ }$ ordering ground state below $T_{\text{N}}=1.45\mathrm{K}$ with in-plane nearest-neighbor exchange interaction $\approx 0.11\mathrm{meV}$. While the large separation 18.9 Å between magnetic layers makes the interlayer exchange interaction virtually zero, our results suggest that a weak easy-plane anisotropy is the driving force for the ${\mathbf{k}}_{\mathrm{m}}=(1/3,1/3,0)$ magnetic ordering. The magnetic properties of ${\mathrm{Ba}}_8{\mathrm{MnNb}}_6{\mathrm{O}}_{24}$, along with its classical excitation spectra, contrast with the related triple perovskite ${\mathrm{Ba}}_3{\mathrm{MnNb}}_2{\mathrm{O}}_9$, which shows easy-axis anisotropy, and the isostructural compound ${\mathrm{Ba}}_8{\mathrm{CoNb}}_6{\mathrm{O}}_{24}$, in which the effective spin-$\frac{1}{2}{\mathrm{Co}}^{2+}$ spins do not order down to 60 mK and in which the spin dynamics shows signs of strong quantum effects.

The dissociation of excitons into a liquid of holes and electrons in photoexcited semiconductors, despite being one of the first recognized examples of a Mott transition, still defies a complete understanding, especially regarding the nature of the transition, which is found to be continuous in some cases and discontinuous in others. Here we consider an idealized model of photoexcited semiconductors that can be mapped onto a spin-polarized half-filled Hubbard model, whose phase diagram reproduces most of the phenomenology of those systems and uncovers the key role of the exciton binding energy in determining the nature of the exciton Mott transition. We find indeed that the transition changes from discontinuous to continuous as the binding energy increases. Moreover, we uncover a rather anomalous electron-hole liquid phase next to the transition, which still sustains excitonic excitations despite being a degenerate Fermi liquid of heavy mass quasiparticles.

Creating carrier reservoirs in layered compounds can effectively tune the carrier density, which often induces a variety of emergent properties. Based on solid-ion-conductor gating technique, we successfully induce superconductivity of 4.8 K in ultrathin Li-intercalated ${\mathrm{SnSe}}_2$ samples. The ${\mathrm{Li}}^{+}$ ions are driven in between interspacing of ${\mathrm{SnSe}}_2$ layers and form a single reservoir layer to provide electrons. In addition, a domelike $T_c$ is found through substituting S for Se, where the optimal $T_c$ is 6.2 K for ${\mathrm{SnSe}}_{1.8}{\mathrm{S}}_{0.2}$. Density-functional theory calculations confirm that the intercalated ${\mathrm{LiSnSe}}_2$ is thermodynamically favorable, where the intercalation of Li expands the interlayer spacing by 10% and increases the carrier density by two orders of magnitude. Meanwhile, the calculated results reveal that the enhanced electron-phonon interaction due to softened phonons determines the occurrence of superconductivity. Our results demonstrate that this strategy is very effective to explore superconductors in layered materials with narrow band gaps.

Previously, auxetic materials were realized by designing building blocks with specific geometries or tuning topology of spring networks. Here, we propose a new approach by properly manipulating the disorder, especially the bond stiffness disorder, of an unstressed spring network. When randomly distorting a spring network initially with a close-packed lattice structure, we find that the resultant unstressed network becomes auxetic. Resulted from the distortion, longer bonds are likely to contribute more to the shear modulus but less to the bulk modulus. Inspired by this correlation, we realize isotropic auxeticity in the unstressed triangular lattice, by distributing each bond a spring constant according to a virtual lattice distortion. In the perspective of previous approaches, however, it is not straightforward to figure out how the close-packed lattices can be turned into auxetic independent of directions. The key of our approach is the correlated disorder induced by the (virtual) lattice distortion, which leads to a sufficiently large nonaffine contribution responsible to the auxeticity.

We report on the study of magnetophotogalvanic and magnetotransport phenomena in 200 nm partially strained HgTe films. This thickness is slightly larger than the estimated critical thickness of lattice relaxation leaving the film partially relaxed with the value of the energy gap close to zero. We show that illumination of HgTe films with monochromatic terahertz laser radiation results in a giant resonant photocurrent caused by the cyclotron resonance in the surface states. The resonant photocurrent is also detected in the reference fully strained 80 nm HgTe films previously shown to be fully gapped 3D topological insulators. We show that the resonance positions in both types of films almost coincide demonstrating the existence of topologically protected surface states in thick HgTe films. The conclusion is supported by magnetotransport experiments.

We report a fully ab initio calculation of the temperature dependence of the electronic band structure of PbTe. We address two main features relevant for the thermoelectric figure of merit: the temperature variations of the direct gap and the difference in energies of the two topmost valence band maxima located at L and $\mathrm{\Sigma }$. We account for the energy shift of the electronic states due to thermal expansion, as well as electron-phonon interaction computed using the nonadiabatic Allen-Heine-Cardona formalism within density functional perturbation theory and the local density approximation. We capture the increase of the direct gap with temperature in very good agreement with experiment. We also predict that the valence band maxima at L and $\mathrm{\Sigma }$ become aligned at $\sim 600–700\mathrm{K}$. We find that both thermal expansion and electron-phonon interaction have a considerable effect on these temperature variations. The Fan-Migdal and Debye-Waller terms are of almost equal magnitude but have an opposite sign, and the delicate balance of these terms gives the correct band shifts. The electron-phonon induced renormalization of the direct gap is produced mostly by high-frequency optical phonons, while acoustic phonons are also responsible for the alignment of the valence band maxima at L and $\mathrm{\Sigma }$.

The experimental observation of quantum anomalous Hall effect (QAHE) in magnetic topological insulators has stimulated enormous interest in condensed-matter physics and materials science. For the purpose of realizing high-temperature QAHE, several material candidates have been proposed, among which the interface states in the CdO/ferromagnetic insulator heterostructures are particularly interesting and favorable for technological applications. Here, we report the experimental observation of the interfacial ferromagnetism and anomalous Hall effect in the $\mathrm{F}{\mathrm{e}}_3{\mathrm{O}}_4/\mathrm{CdO}/\mathrm{F}{\mathrm{e}}_3{\mathrm{O}}_4$ heterostructures grown via oxide molecular-beam epitaxy. Systematical variation of the CdO thickness reveals the interface ferromagnetism as the major cause for the observed planar magnetoresistance and anomalous Hall effect. Our results might pave the way to engineer oxide interface states for the exploration of QAHE towards exotic quantum-physical phenomena and potential applications.

The experimentally verified negative Poisson's ratio of black phosphorus allows the extension of the medical and defense applications to the nanoscale regime without any artificial engineering. With a structure analogous to monolayer black phosphorus, monolayer SiS, SiSe, SnTe, and W-phase antimonene are predicted to show auxetic behavior, while a W-phase antimonene does not by using first-principles calculations. By putting these systems into a collective perspective with other puckered two-dimensional (2D) materials, we further formulate a uniform mechanism that could explain the different types of out-of-plane Poisson's ratio in the puckered 2D materials including monolayer group V-enes (BP, As, and Sb) and group IV monochalcogenides (SiS, SiSe, GeS, GeSe, SnS, SnSe, and SnTe). We found that both the structure and composition of the puckered monolayers play important roles in the out-of-plane Poisson's ratio.

Here we study the magnetic proximity effect in amorphous layered magnets of alternating high- and low-$T_{\text{c}}$ materials using magnetometry and polarized neutron reflectivity. By altering the thickness of either the high- or low-$T_{\text{c}}$ layer we are able to extract the induced magnetic moment in the low-$T_{\text{c}}$ layer directly and study how it scales with thickness. We observe that the ordering temperature of the low-$T_{\text{c}}$ layer is enhanced and above which a second magnetically ordered state with a very large extension is observed. This induced magnetic state survives to a temperature at least three times that of the ordering temperature of the low-$T_{\text{c}}$ layer and the induced magnetization is approximately constant throughout at least a 10-nm-thick layer. The induced magnetic region within the low-$T_{\text{c}}$ layer does not depend on the thickness of the adjacent high-$T_{\text{c}}$ layer.

Molecular dynamics is a versatile and powerful method to study diffusion in solid-state ionic conductors, requiring minimal prior knowledge of equilibrium or transition states of the system's free energy surface. However, the analysis of trajectories for relevant but rare events, such as a jump of the diffusing mobile ion, is still rather cumbersome, requiring prior knowledge of the diffusive process in order to get meaningful results. In this work, we present a novel approach to detect the relevant events in a diffusive system without assuming prior information regarding the underlying process. We start from a projection of the atomic coordinates into a landmark basis to identify the dominant features in a mobile ion's environment. Subsequent clustering in landmark space enables a discretization of any trajectory into a sequence of distinct states. As a final step, the use of the smooth overlap of atomic positions descriptor allows distinguishing between different environments in a straightforward way. We apply this algorithm to ten Li-ionic systems and perform in-depth analyses of cubic ${\mathrm{Li}}_7{\mathrm{La}}_3{\mathrm{Zr}}_2{\mathrm{O}}_{12}$, tetragonal ${\mathrm{Li}}_{10}{\mathrm{GeP}}_2{\mathrm{S}}_{12}$, and the $\beta$-eucryptite ${\mathrm{LiAlSiO}}_4$. We compare our results to existing methods, underscoring strong points, weaknesses, and insights into the diffusive behavior of the ionic conduction in the materials investigated.