Fe-Cr-based steels are broadly considered as important structural materials, e.g., for generation-IV nuclear reactors. In order to address tougher operation conditions in future applications, properties of existing Fe-Cr-based steels must be significantly improved. Multicomponent alloying has been viewed as an efficient tool to achieve this goal. Despite its accepted importance, fundamental knowledge of the effect of the simultaneous alloying of Fe with Cr and other elements, such as Ni, Mo, Al, W, V, and Nb, on the thermodynamic and mechanical properties of the bcc alloys is still quite limited. Here we report results of first-principles simulations of lattice parameters, mixing enthalpies, and magnetic and elastic properties of bcc Fe-Cr-based solid solutions with up to 20% Ni, as well as with small concentrations of other alloying elements, Mo, Al, W, V, and Nb. We predict that alloys with relatively high Ni concentrations containing 2.5%–5% Al demonstrate a simultaneous increase of thermodynamic stability and ductility without significant drop of their elastic moduli with respect to corresponding binary Fe-Cr alloys.

We report a comprehensive study of aqueous halide adsorption on nanoparticles of gold and palladium that addresses several limitations hampering the use of atomistic modeling as a tool for understanding and improving wet-chemical synthesis and related applications. A combination of thermodynamic modeling with density functional theory (DFT) calculations and experimental data is used to predict equilibrium shapes of halide-covered nanoparticles as a function of the chemical environment. To ensure realistic and experimentally relevant results, we account for solvent effects and include a large set of vicinal surfaces, several adsorbate coverages, as well as decahedral particles. While the observed stabilization is not significant enough to result in thermodynamic stability of anisotropic shapes such as nanocubes, nonuniformity in the halide coverage indicates the possibility of obtaining such shapes as kinetic products. With regard to technical challenges, we show that inclusion of surface-solvent interactions leads to qualitative changes in the predicted shape. Furthermore, accounting for nonlocal interactions on the functional level yields a more accurate description of surface systems.

Several studies have recently reported the formation of stacking faults in silicon compressed at low temperatures and high stresses. This observation contradicts the generally accepted framework for the plastic deformation of silicon. We propose here an original plasticity mechanism that could potentially explain stacking fault formation in these conditions: the nucleation and migration of a partial edge dislocation with Burgers vector $\frac{1}{3}\langle 112\rangle$. These results are obtained thanks to a multiscale approach combining three computational methods. Dislocation nucleation is determined by molecular dynamics in both a nanowire and a 2D slab. The latter results are used as inputs for hybrid MD/DFT “learn on the fly” calculations, allowing for studying the dynamical propagation of the dislocation. Selected configurations at different steps are next used for initiating nudged elastic band density functional theory calculations. These calculations revealed that the dislocation displacement mechanism depends on the compression strain. For low values, a dangling bond is temporarily created in the core, resulting in high activation energies. For compression strains larger than about 8%, the reduction of the interlayer distance allows for a more complex displacement mechanism with no dangling bonds in the dislocation core and a significant decrease of the activation energy.

Synthesis of crystallographically well-defined thin films of topological materials is important for unraveling their mesoscale quantum properties and for device applications. ${\mathrm{Mn}}_3\mathrm{Ge}$, an antiferromagnetic Weyl semimetal with a chiral magnetic structure on a kagome lattice, is expected to have enhanced Berry curvature around Weyl nodes near the Fermi energy, leading to large anomalous Hall/Nernst effects and a large spin-Hall effect. Using magnetron sputtering, we have grown epitaxial thin films of hexagonal $\mathrm{D}{0}_{19}{\mathrm{Mn}}_3\mathrm{Ge}$ that are flat and continuous. Large anomalous Nernst and inverse spin-Hall effects are observed in thermoelectric and spin-pumping devices. The anomalous Nernst signal in our ${\mathrm{Mn}}_3\mathrm{Ge}$ films is estimated to be 0.1 μV/K and is comparable to that in ferromagnetic Fe, despite ${\mathrm{Mn}}_3\mathrm{Ge}$ having a weak magnetization of $\sim 3.5\mathrm{m}{\mu }_{\mathrm{B}}/\mathrm{Mn}$ at room temperature. The spin-mixing conductance is $90.5{\mathrm{nm}}^{-2}$ at the $\mathrm{Py}/{\mathrm{Mn}}_3\mathrm{Ge}$ interface, and the spin-Hall angle in ${\mathrm{Mn}}_3\mathrm{Ge}$ is estimated to be about eight times of that in Pt.

While the metastable $\beta$ (A15) phase of tungsten has one of the largest spin Hall angles measured, the origin of this high spin Hall conductivity is still unclear. Since large concentrations of oxygen and nitrogen are often used to stabilize $\beta$ tungsten, it is not obvious whether the high spin Hall conductivity is due to an intrinsic or extrinsic effect. In this work, we have examined the influence of O and N dopants on the spin Hall conductivity and spin Hall angle of $\beta$-W. Using multiple first-principles approaches, we examine both the intrinsic and extrinsic (skew-scattering) contributions to spin Hall conductivity. We find that intrinsic spin Hall conductivity calculations for pristine $\beta$-W are in excellent agreement with experiment. However, when the effect of high concentrations (11 at.%) of O or N interstitials on the electronic structures is taken into account, the predicted intrinsic spin Hall conductivity is significantly reduced. Skew-scattering calculations for O and N interstitials in $\beta$-W indicate that extrinsic contributions have a limited impact on the total spin Hall conductivity. However, we find that the spin-flip scattering at O and N impurities can well explain the experimentally found spin-diffusion length within the range of 1–5 nm. To explain these findings, we propose that dopants (O and N) help to stabilize $\beta$-W grains during film deposition and afterwards segregate to the grain boundaries. This process leads to films of relatively pristine small $\beta$-W grains and grain boundaries with high concentrations of O or N scattering sites. This combination provides high spin Hall conductivity and large electrical resistance, leading to high spin Hall angles. This work shows that engineering grain-boundary properties in other high spin Hall conductivity materials could provide an effective way to boost the spin Hall angle.

${\mathrm{Fe}}_{3-x}{\mathrm{GeTe}}_2$ is a layered van der Waals magnetic material with a relatively high ordering temperature and large anisotropy. While most studies have concluded the interlayer ordering to be ferromagnetic, there have also been reports of interlayer antiferromagnetism in ${\mathrm{Fe}}_{3-x}{\mathrm{GeTe}}_2$. Here, we investigate the interlayer magnetic ordering by neutron diffraction experiments, scanning tunneling microscopy (STM) and spin-polarized STM measurements, density functional theory plus U calculations, and STM simulations. We conclude that the layers of ${\mathrm{Fe}}_{3-x}{\mathrm{GeTe}}_2$ are coupled ferromagnetically and that in order to capture the magnetic and electronic properties of ${\mathrm{Fe}}_{3-x}{\mathrm{GeTe}}_2$ within density functional theory, Hubbard U corrections need to be taken into account.

Alloying structurally similar perovskites to form mixed-cation lead iodide perovskites, e.g., ${\mathrm{Cs}}_x\mathrm{F}{\mathrm{A}}_{(1-x)}\mathrm{Pb}{\mathrm{I}}_3, \mathrm{M}{\mathrm{A}}_x\mathrm{F}{\mathrm{A}}_{(1-x)}\mathrm{Pb}{\mathrm{I}}_3$, and ${\mathrm{Cs}}_x\mathrm{M}{\mathrm{A}}_y\mathrm{F}{\mathrm{A}}_{(1-x-y)}\mathrm{Pb}{\mathrm{I}}_3$, could improve the performance of perovskite-based solar cells and light-emitting diodes. However, a phase diagram of them and a clear understanding of the underlying atomic-scale mechanism are still lacking. Using ab initio calculations combined with high-throughput experimentation, we demonstrate the phase diagram of mixed-cation lead iodide perovskites. Only a small proportion of monovalent cations (${\mathrm{Cs}}^{+}/{\mathrm{Rb}}^{+}/{\mathrm{MA}}^{+}$) could be incorporated into the ${\mathrm{FAPbI}}_3/{\mathrm{MAPbI}}_3$ matrix; otherwise it will be separated into δ-${\mathrm{CsPbI}}_3$, δ-${\mathrm{RbPbI}}_3$, MAI, etc. The smaller the radius of doping cations, the harder it is to incorporate them into a perovskite lattice and the easier it is to stabilize the perovskite phase. In ${\mathrm{FAPbI}}_3$-based multication perovskites, moreover, over 10 mol % alloying is needed to convert δ phase to α phase at room temperature. The combined upper and lower limits for doping concentration restrict the appropriate alloying ratio to a narrow window. We further plot the relative energy diagram for triple-cation perovskite ${\mathrm{Cs}}_x\mathrm{M}{\mathrm{A}}_y\mathrm{F}{\mathrm{A}}_{(1-x-y)}\mathrm{Pb}{\mathrm{I}}_3$, which reveals the ideal doping ratio for uniform stable alloying. This theory-experiment-combined study provides a clear microscopic picture of phase stability and segregation for mixed-cation perovskite solids.

Material representations that are compatible with machine learning models play a key role in developing models that exhibit high accuracy for property prediction. Atomic orbital interactions are one of the important factors that govern the properties of crystalline materials from which the local chemical environments of atoms is inferred. Therefore, to develop robust machine learning models for material properties prediction, it is imperative to include features representing such chemical attributes. Here, we propose the orbital graph convolutional neural network (OGCNN), a crystal graph convolutional neural network framework that includes atomic orbital interaction features that learns material properties in a robust way. In addition, we embedded an encoder-decoder network into the OGCNN enabling it to learn important features among basic atomic (elemental features), orbital-orbital interactions, and topological features. We examined the performance of this model on a broad range of crystalline materials data to predict different properties. We benchmarked the performance of the OGCNN model with that of: (1) the crystal graph convolutional neural network, (2) other state-of-the-art descriptors for material representations including many-body tensor representation and the smooth overlap of atomic positions, and (3) other conventional regression machine learning algorithms where different crystal featurization methods have been used. We find that the OGCNN significantly outperforms them. The OGCNN model with high predictive accuracy can be used to discover new materials among the immense phase and compound spaces of materials.

Ferrimagnets in the vicinity of the magnetic compensation point are of particular interest for spin-torque-based spintronics applications, because they require lower switching currents and thus smaller switching energies. Room-temperature compensation is rather uncommon, but can be obtained by tuning the chemical concentrations of compounds such as ${\mathrm{Co}}_{0.79}{\mathrm{Tb}}_{0.21}$ or ${\mathrm{Co}}_{0.56}{\mathrm{Gd}}_{0.44}$, in order to find the single concentration at which one sublattice compensates the other. Here we study the ferrimagnetic ${\mathrm{Mn}}_{4\text{−}x}{\mathrm{Co}}_x\mathrm{N}$ films, showing that they presumably possess at room temperature not only one but two different Co concentrations at which the magnetic compensation occurs. Using x-ray absorption spectroscopy and x-ray magnetic circular dichroism measurements, we show that this startling behavior can be explained by the existence of two nonequivalent sites for the Co, when it is inserted in the antiperovskite structure of epitaxial ${\mathrm{Mn}}_{4\text{−}x}{\mathrm{Co}}_x\mathrm{N}$ films.

Using the superconducting proximity effect for engineering a topological superconducting state in a topological insulator (TI) is a promising route to realize Majorana fermions. However, epitaxial growth of a superconductor on the TI surface to achieve a good proximity effect has been a challenge. We discovered that simply depositing Pd on thin films of the TI material ${\left({\mathrm{Bi}}_{1-x}{\mathrm{Sb}}_x\right)}_2{\mathrm{Te}}_3$ leads to an epitaxial self-formation of $\mathrm{Pd}{\mathrm{Te}}_2$ superconductor having the superconducting transition temperature of $\sim 1$ K. This self-formed superconductor proximitizes the TI, which is confirmed by the appearance of a supercurrent in Josephson-junction devices made on ${\left({\mathrm{Bi}}_{1-x}{\mathrm{Sb}}_x\right)}_2{\mathrm{Te}}_3$. This self-epitaxy phenomenon can be conveniently used for fabricating TI-based superconducting nanodevices to address the superconducting proximity effect in TIs.

The mesoscale morphologies of organic small molecular films fabricated via vacuum deposition processes are critical to the performance of small-molecule solar cells and organic light-emitting diodes. In the present study, the morphological evolution of the active layer of DPDCPB:${\mathrm{C}}_{70}$ small-molecule solar cells during vacuum codeposition processes was revealed by a series of GPU-accelerated coarse-grained molecular-dynamics simulations. The ${\mathrm{C}}_{70}$ and DPDCPB molecules were coarsened into ellipsoids and bonded ellipsoids, respectively. The interactions between ellipsoids were described by the Gay-Berne formulation and were parametrized to reproduce potential energy surfaces from all-atom atomistic simulations using a genetic algorithm. Due to the significantly reduced overall degrees of freedom, this coarse-grained scheme allowed us to simulate the vacuum codeposition processes and monitor the morphological evolution of systems with system length scales compatible with those of the experiments (∼30 nm). Our simulations indicate that the film morphologies are closely correlated with the DPDCPB:${\mathrm{C}}_{70}$ blending ratio. High ${\mathrm{C}}_{70}$ concentration leads to a rough film surface, which is in accordance with experimental observations and can be attributed to the strong self-aggregation behavior of ${\mathrm{C}}_{70}$ molecules. The morphological property analysis indicates that the rough film surface has an almost negligible impact on the DPDCPB/${\mathrm{C}}_{70}$ domain percolations, and the device with the optimal deposition ratio should give the most balanced hole/electron transfer in respective DPDCPB/${\mathrm{C}}_{70}$ domains. The present study demonstrates that by using the ellipsoid-based coarse-grained model, it is possible to study the morphological evolution of small-molecule organic thin film during vacuum deposition processes with molecular scale details, which can provide valuable insights for experimental teams to further optimize device fabrication protocols for the next generation of organic optoelectronic devices.

Multiphasic intermetallic materials are attractive candidates for functional applications where the constituent phases alone do not meet the property targets. The interfaces at the phase boundaries in these materials are central to their macroscopic properties, with the details of the atomic structure underpinning local thermomechanical, electrical, and magnetic behavior. Here, we characterize the interface structure in the biphasic Nb-Co-Sn system consisting of $\mathrm{Nb}{\mathrm{Co}}_2\mathrm{Sn}$ full Heusler (FH) precipitates embedded in a NbCoSn half Heusler (HH) matrix, which exhibits semicoherent interfaces with a 3.3% lattice parameter misfit that determines the constitution of the FH/HH interface on the nanometer scale. We use detailed transmission electron microscopy (TEM) and atomistic calculations to precisely determine the dislocation content and structure at the semicoherent interface, which modulates the strain fields in a semiregular pattern. We find that the interface forms regularly spaced paired partial dislocations with a joint Burgers vector of $a/2\langle 110\rangle$, favored by misfit energy relief and chemical ordering. The interface exhibits numerous interface steps (disconnections) which in turn determine the precipitate morphology. Overall, the two phases show full coherency except in the vicinity of the misfit dislocation cores located every 11 nm, leading to a modulated strain field parallel to the interface, and no long-range strain fields as the interfacial dislocations accommodate the misfit strain.

Density functional theory (DFT) simulations, Metropolis Monte Carlo (MMC), and kinetic Monte Carlo (kMC) simulations were performed to understand the mechanisms of mass diffusion in a group IVB transition metal carbide, TiC, and a group VB transition metal carbide, TaC. The DFT calculations were used to obtain the vacancy formation energy and migration energy of a variety of microstates for off-stoichiometric TiC and TaC. MMC simulations, based on our DFT results, were used to determine the ensemble average of the metal vacancy formation energy and determine the average size metal-vacancy clusters present in these materials. kMC simulations were used to determine the ensemble average of the migration energy barrier as well as understand how the vacancies in these materials, on average, migrate. These collective results show that metal vacancy migration in TiC and TaC are quite different, where Ti vacancies should be surrounded by four to five carbon vacancies whereas, on average, tantalum vacancies are surrounded by one or zero carbon vacancies. However, the carbon vacancies substantially contribute to metal vacancy diffusion in both these materials, as the metal vacancy statistically will have a carbon vacancy near it before and after migration. From these results, we find that the activation energy of metal vacancy diffusion is 7.66 eV in ${\mathrm{Ti}}_{0.995}{\mathrm{C}}_{0.97}$ and 6.41 eV in ${\mathrm{Ta}}_{0.995}{\mathrm{C}}_{0.97}$, which agrees reasonably well with experimentally reported activation energies. These results give further insights into the mechanisms associated with mass diffusion within the transition metal carbide families, an important insight needed to better elucidate high temperature diffusional creep responses which is often difficult to assess experimentally.

Halide perovskite (HP) semiconductors exhibit unique strong coupling between the electronic and structural dynamics. We use Raman polarization-orientation (PO) measurements and ab initio molecular dynamics (AIMD) to investigate the origin and temperature evolution of the strong structural anharmonicity throughout the tetragonal phase of $\mathrm{C}{\mathrm{H}}_3\mathrm{N}{\mathrm{H}}_3\mathrm{Pb}{\mathrm{I}}_3$. Raman PO measurements reveal a soft modelike spectral feature. This mode shows an unusual continuous increase in damping with temperature which is indicative of an anharmonic potential surface. The analysis of AIMD trajectories identifies two major sources of anharmonicity: the orientational unlocking of the ${\left[\mathrm{C}{\mathrm{H}}_3\mathrm{N}{\mathrm{H}}_3\right]}^{+}$ ions and large-amplitude octahedral tilting that continuously increases with temperature. Our work suggests that the standard phonon picture cannot describe the structural dynamics of tetragonal $\mathrm{C}{\mathrm{H}}_3\mathrm{N}{\mathrm{H}}_3\mathrm{Pb}{\mathrm{I}}_3$.

We perform first-principles calculations to investigate a two-dimensional 1T phase of $\mathrm{Ti}{\mathrm{O}}_2$. Our results indicate that electronic band gap, electron and hole effective mass, and structural stability of an 1T phase are comparable to those of bulk and the other two-dimensional phases. 1T-$\mathrm{Ti}{\mathrm{O}}_2$ is predicted to be easily achieved by exfoliation from bulk hexagonal ${\mathrm{NaTiO}}_2$, and the obtained phase is dynamically stable. In addition, we find that mechanical strain significantly influences the electronic structure of 1T-$\mathrm{Ti}{\mathrm{O}}_2$, and even it causes a transition from indirect to direct band gap.

We report investigations of the structural, magnetic, electrical transport, and thermal properties of five compositions of the metallic perovskite ${\mathrm{Gd}\mathrm{Rh}}_3{\mathrm{C}}_{1-x}{\mathrm{B}}_x$ ($0.00\le x\le 1.00$). Our results show that all five compositions undergo magnetic ordering at low temperatures, but the nature of the ordered state is significantly different in the carbon- and the boron-rich compositions, where the former shows signatures of an amplitude-modulated magnetic structure and the latter exhibits evidence of an equal-moment incommensurate antiferromagnetic ordering. We also observe a remarkable field-dependent evolution of conduction carrier polarization in the compositionally disordered compounds. The outcomes indicate that this system is energetically situated in proximity to a magnetic instability where small variations in the control parameter(s), such as the lattice constant and/or electron density, lead to considerably different ground states.