Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent struc
tural motifs and their dynamical evolution has been of longstanding interest. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. Here, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with ~500 total reference calculations. Our NN predictions are within 30 meV/atom and 40 meV/AA of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments.
In this work, we expand the set of known layered compounds to include ionic layered materials, which are well known for superconducting, thermoelectric, and battery applications. Focusing on known ternary compounds from the ICSD, we screen for ionic
layered structures by expanding upon our previously developed algorithm for identification of van der Waals (vdW) layered structures, thus identifying over 1,500 ionic layered compounds. Since vdW layered structures can be chemically mutated to form ionic layered structures, we have developed a methodology to structurally link binary vdW to ternary ionic layered materials. We perform an in-depth analysis of similarities and differences between these two classes of layered systems and assess the interplay between layer geometry and bond strength with a study of the elastic anisotropy. We observe a rich variety of anisotropic behavior in which the layering direction alone is not a simple predictor of elastic anisotropy. Our results enable discovery of new layered materials through intercalation or de- intercalation of vdW or ionic layered systems, respectively, as well as lay the groundwork for studies of anisotropic transport phenomena such as sound propagation or lattice thermal conductivity.
A novel phase field model has been developed to study the effect of coherent precipitate on the Zener pinning of matrix grain boundaries. The model accounts for misfit strain between precipitate and matrix as well as the elastic inhomogeneity and ani
sotropy between them. The results show that increase in elastic misfit, elastic inhomogeneity, and elastic anisotropy increases the coarsening rate of the precipitates. Increased coarsening of precipitates in turn decreases the pinning of grain boundaries. Therefore, increase in misfit strain, elastic inhomogeneity and anisotropy negatively affect the Zener pinning through coherent precipitate. This study shows elastic anisotropy gives rise to the needle shape precipitate. It has also been shown that these needle shaped precipitates are not very effective in Zener pinning. This study provides an understanding into the effect of coherent precipitate on the Zener pinning of matrix grain boundaries.
The bulk piezoelectric response, as measured by the piezoelectric modulus tensor (textbf{d}), is determined by a combination of charge redistribution due to strain and the amount of strain produced by the application of stress (stiffness). Motivated
by the notion that less stiff materials could exhibit large piezoelectric responses, herein we investigate the piezoelectric modulus of van der Waals-bonded quasi-2D ionic compounds using first-principles calculations. From a pool of 869 known binary and ternary quasi-2D materials, we have identified 135 non-centrosymmetric crystals of which 48 systems are found to have textbf{d} components larger than the longitudinal piezoelectric modulus of AlN (a common piezoelectric for resonators), and three systems with the response greater than that of PbTiO$_3$, which is among the materials with largest known piezoelectric modulus. None of the identified materials have previously been considered for piezoelectric applications. Furthermore, we find that large textbf{d} components always couple to the deformations (shearing or axial) of van der Waals gaps between the layers and are indeed enabled by the weak intra-layer interactions.
Certain alumino-silicates display exotic properties enabled by their framework structure made of corner-sharing tetrahedral rigid units. Using textit{in situ} diamond-anvil cell x-ray diffraction (XRD), we study the pressure-induced transformation of
$beta$ eucryptite, a prototypical alumino-silicate. $beta$ eucryptite undergoes a phase transformation at moderate pressures, but the atomic structure of the new phase has not yet been reported. Based on density functional theory stability studies and Rietveld analysis of XRD patterns, we find that the pressure-stabilized phase belongs to the Pna2$_1$ space group. Furthermore, we discover two other possible pressure-stabilized polymorphs, P1c1 and Pca2$_1$.
Since AlN has emerged as an important piezoelectric material for a wide variety of applications, efforts have been made to increase its piezoelectric response via alloying with transition metals that can substitute for Al in the wurtzite lattice. Her
ein, we report density functional theory calculations of structure and properties of the Cr-AlN system for Cr concentrations ranging past the wurtzite-rocksalt transition point. By studying the different contributions to the longitudinal piezoelectric coefficient, we propose that the physical origin of the enhanced piezoelectricity in Cr$_x$Al$_{1-x}$N alloys is the increase of the internal parameter $u$ of the wurtzite structure upon substitution of Al with the larger Cr ions. Among a set of wurtzite-structured materials, we have found that Cr-AlN has the most sensitive piezoelectric coefficient with respect to alloying concentration. Based on these results, we propose that Cr-AlN is a viable piezoelectric material whose properties can be tuned via Cr composition; we support this proposal by combinatorial synthesis experiments, which show that Cr can be incorporated in the AlN lattice up to 30% before a detectable transition to rocksalt occurs. At this Cr content, the piezoelectric modulus $d_{33}$ is approximately four times larger than that of pure AlN. This finding, combined with the relative ease of synthesis, may propel Cr-AlN as the prime piezoelectric material for applications such as resonators and acoustic wave generators.
Recent advances in microelectromechanical systems often require multifunctional materials, which are designed so as to optimize more than one property. Using density functional theory calculations for alloyed nitride systems, we illustrate how co-all
oying a piezoelectric material (AlN) with different nitrides helps tune both its piezoelectric and mechanical properties simultaneously. Wurtzite AlN-YN alloys display increased piezoelectric response with YN concentration, accompanied by mechanical softening along the crystallographic c direction. Both effects increase the electromechanical coupling coefficients relevant for transducers and actuators. Resonator applications, however, require superior stiffness, thus leading to the need to decouple the increased piezoelectric response from a softened lattice. We show that co-alloying of AlN with YN and BN results in improved elastic properties while retaining most of the piezoelectric enhancements from YN alloying. This finding may lead to new avenues for tuning the design properties of piezoelectrics through composition-property maps. Keywords: piezoelectricity, electromechanical coupling, density functional theory, co-alloying
While it is well established that ionic conduction in lithium aluminosilicates proceeds via hopping of Li ions, the nature of the various hoping-based mechanisms in different temperature regimes has not been fully elucidated. The difficulties associa
ted with investigating the conduction have to do with the presence of grains and grain boundaries of different orientations in these usually polycrystalline materials. Herein, we use electrochemical impedance spectroscopy (EIS) to investigate the ion conduction mechanisms in -eucryptite, which is a prototypical lithium aluminosilicate. In the absence of significant structural transitions in grain boundaries, we have found that there are three conduction regimes for the one-dimensional ionic motion along the c axis channels in the grains, and determined the activation energies for each of these temperature regimes. Activation energies computed from molecular statics calculations of the potential energy landscape encountered by Li ions suggest that at temperatures below 440 {deg}C conduction proceeds via cooperative or correlated motion, in agreement with established literature. Between 440 {deg}C and 500{deg}C, the activation barriers extracted from EIS measurements are large and consistent with those from atomistic calculations for uncorrelated Li ion hopping. Above 500 {deg}C the activation barriers decrease significantly, which indicates that after the transition to the Li-disordered phase of -eucryptite, the Li ion motion largely regains the correlated character.
Thermal stability of nanocrystalline multilayer thin film is of paramount importance as the applications often involve high temperature. Here we report on the layer instability phenomenon in binary polycrystalline thin film initiating from the grain
boundary migrations at higher temperatures using phase-field simulations. Effect of layer thickness, bilayer spacing and the absence of grain boundary are also investigated along with the grain boundary mobility of individual phases on the layer stability. Layer instability in the polycrystalline film is shown to arise from the grain boundary grooving which originates spontaneously from the presence of grain boundaries. Our results show that the growth of the perturbation generated from the differential curvature follows Plateau-Rayleigh instability criterion. Increase in layer thickness, lower bilayer thickness as well as lower grain boundary mobility improve layer stability. Phase-field simulations show similar microstructural evolution as has been observed in our Zirconium (Zr)/Zirconium Nitride (ZrN) system experimentally. Detail analysis performed in this work to understand the mechanisms of layer instability leads us to predict measures which will improve the thermal stability of multilayer nanocrystalline thin film.
