Related papers: Structure prediction based on ab initio simulated …
Ab initio molecular dynamics simulation is used to study the structure and electronic properties of the liquid Ga-Se system at the three compositions Ga$_2$Se, GaSe and Ga$_2$Se$_3$, and of the GaSe and Ga$_2$Se$_3$ crystals. The calculated…
We have used soft x-ray photoemission electron microscopy to image the magnetization of single domain La$_{0.7}$Sr$_{0.3}$MnO$_{3}$ nano-islands arranged in geometrically frustrated configurations such as square ice and kagome ice…
The phase diagram of binary mixtures of particles interacting via a pair potential of parallel dipoles is computed at zero temperature as a function of composition and the ratio of their magnetic susceptibilities. Using lattice sums, a rich…
We explore the possibility of performing nuclear structure studies using low energy neutrino beams. In particular, low energy beta-beams and conventional sources (muon decay-at-rest) are considered. We present results on the total…
This article introduces a modified simulated annealing optimization approach for automatically determining optimal energy management strategies in grid-connected, storage-augmented, photovoltaics-supplied prosumer buildings and…
In recent years, artificial neural networks and their applications for large data sets have became a crucial part of scientific research. In this work, we implement the Multilayer Perceptron (MLP), which is a class of feedforward artificial…
Structure prediction has become a key task of the modern atomistic sciences, and depends on the rapid and reliable computation of the energy landscape. First principles density functional based calculations are highly reliable, faithfully…
We present a scheme to categorize the structure of different layered phosphorene allotropes by mapping their non-planar atomic structure onto a two-color 2D triangular tiling pattern. In the buckled structure of a phosphorene monolayer, we…
Inspired by the recent success of machine-learned interatomic potentials for crystal structure prediction of the inorganic crystals, we present a methodology that exploits Moment Tensor Potentials and active learning (based on maxvol…
In the present paper, we introduce a new neural network-based tool for the prediction of formation energies of atomic structures based on elemental and structural features of Voronoi-tessellated materials. We provide a concise overview of…
We present a universal method for the large-scale prediction of the atomic structure of clusters. Our algorithm performs the joint evolutionary search for all clusters in a given area of the compositional space and takes advantage of…
The planar hexagonal phase of ZnO, known as h-ZnO, g-ZnO, {\alpha}-ZnO, the Bk structure, the 5-5 phase, the {\alpha}-BN phase, etc., has P63/mmc symmetry and is implicated in ferroelectric switching mechanisms for wurtzite-ZnO. It is…
According to previous interpretations of experimental data, sodium-scandium double-cation borohydride NaSc(BH$_4$)$_4$ crystallizes in the crystallographic space group $Cmcm$ where each sodium (scandium) atom is surrounded by six scandium…
Determining crystal structures from powder X-ray diffraction (PXRD) has been a significant challenge in materials science, particularly when experimental data contain noise or the target structure has a high complexity. While recent AI…
We have studied boron nitride monolayer and bilayer band structures. For bilayers, the ground state energies of the different five stackings are computed using DFT in order to determine the most stable configuration. Also, the interlayer…
Ab-initio calculations for the structural properties of Zr-Nb alloys at different values of the niobium concentration are done at zero temperature. Different cases for Zr-Nb alloys with unit cells having BCC and HCP structures are…
In this work we used $\textit{ab-initio}$ random structure searching (AIRSS) to carry out a systematic search for crystalline Na-Ge materials at both 0 and 10 GPa. The high-throughput structural relaxations were accelerated using a…
Sintering of alumina nanoparticles is of interest both from the view of fundamental research as well as for industrial applications. Atomistic simulations are tailor-made for understanding and predicting the time- and temperature-dependent…
We present a proof of concept that machine learning techniques can be used to predict the properties of CNOHF energetic molecules from their molecular structures. We focus on a small but diverse dataset consisting of 109 molecular…
In this paper, we study the construction of structural models for the description of substitutional defects in crystalline materials. Predicting and designing the atomic structures in such systems is highly challenging due to the…