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Compositional disorder is common in crystal compounds. In these compounds, some atoms are randomly distributed at some crystallographic sites. For such compounds, randomness forms many non-identical independent structures. Thus, calculating the energy of all structures using ordinary quantum ab initio methods can be significantly time-consuming. Machine learning can be a reliable alternative to ab initio methods. We calculate the energy of these compounds with an accuracy close to that of density functional theory calculations in a considerably shorter time using machine learning. In this study, we use kernel ridge regression and neural network to predict energy. In the KRR, we employ sine matrix, Ewald sum matrix, SOAP, ACSF, and MBTR. To implement the neural network, we use two important classes of application of the neural network in material science, including high-dimensional neural network and convolutional neural network based on crystal graph representation. We show that kernel ridge regression using MBTR and neural network using ACSF can provide better accuracy than other methods. [Display omitted] [ABSTRACT FROM AUTHOR]

We present ESpinS (Esfahan Spin Simulation) package to evaluate the thermodynamic properties of spin systems described by a spin model Hamiltonian. In addition to the Heisenberg exchange term, the spin Hamiltonian in ESpinS can contain interactions such as bi-quadratic, Dzyaloshinskii–Moriya, and single-ion anisotropy. By applying the classical Monte Carlo simulation, ESpinS simulates the behavior of spin systems with respect to temperature. ESpinS can calculate the specific heat, susceptibility, staggered magnetization, energy histogram, fourth-order Binder cumulants, and neutron scattering structure factor. Further, it can compute the user-defined magnetic order parameter, that is, the summation of the projection of spins on the user-defined directions and the physical quantities based on it. ESpinS works with both a local update algorithm and a parallel tempering algorithm. The latter is an appropriate option for considering frustrated and spin-glass magnetic systems. ESpinS is written in Fortran 90 and can be run in single or parallel mode. The package is freely available under the GPL license (https://github.com/nafiserb/ESpinS). [Display omitted] [ABSTRACT FROM AUTHOR]

First-principles calculations are performed to investigate f magnetism in A 2 Ti 2 O 7 (A=Eu, Gd, Tb, Dy, Ho, Er, Yb) magnetic pyrochlore oxides. The Hubbard U parameter and the relativistic spin orbit correction are applied for a more accurate description of the electronic structure of the systems. It is argued that the main obstacle for the first-principles study of these systems is the multi-minima solutions of their electronic configuration. Among the studied pyrochlores, Gd 2 Ti 2 O 7 shows the least multi-minima problem. The crystal electric field theory is applied for phenomenological comparison of the calculated spin and orbital moments with the experimental data. [ABSTRACT FROM AUTHOR]

We use density functional theory to investigate effects of spin-orbit coupling and single-stripe-type antiferromagnetic (sAFM) ordering on the crystal structure and electronic properties of SmFeAsO. The results indicate that AFM ordering causes the crystal structure transition from tetragonal to orthorhombic, along with increase in the height of As atoms from Fe layer due to magnetostriction. It also leads to the opening of partial band gaps, the emergence of a prominent peak near Fermi energy (E F) in the density of states (DOS) and a reduction in Fermi surface nesting. The study finds a correlation between the calculated area under the DOS curve, spanning from E F to the first peak above it, and the optimal electron-doped concentration required for inducing superconductivity in SmFeAsO. The findings suggest that spin and charge density waves can play important roles in the superconducting mechanism of Fe-based superconductors. Our calculations demonstrate that spin-orbit coupling reduces electronic correlation. [ABSTRACT FROM AUTHOR]

In this work, we present a computational study on 105 selected organic molecules in order to find suitable candidates for using as thermally activated delayed fluorescent (TADF) emitters in organic light emitting diodes (OLEDs), in the emission range of red light. Based on time-dependent density functional theory (TD-DFT) computations, three promising candidates were found, predicted to have low singlet-triplet splittings, lower than 0.06 eV, and TADF rates of 0.124, 0.154 and 0.231 1/ μs. Then, using an experimental-theory calibration approach, the emission wavelength of the molecules were estimated to be 570, 476, and 623 nm, respectively. For the molecule whose emission wavelength (623 nm) is predicted to be in our desired range, we measured the photoluminescence (PL) spectrum and find out that its emission peak is within the predicted accuracy of the employed method. Moreover, we benchmarked the performance of density functional based tight-binding (DFTB) method for future screening works and find out that, this method is an efficient pre-screening tool, useful in searching for molecules with desired emission wavelengths. Unlabelled Image • Finding three efficient molecules for using as thermally activated delayed fluorescent (TADF) emitters in OLEDs. • The predicted emission peak (experimental-theory approach), is in acceptable agreement with the experimental emission peak. • Density functional based tight-binding method is an efficient pre-screening tool, useful in searching for suitable molecules. [ABSTRACT FROM AUTHOR]

The size-dependent properties of small pure copper and silver clusters and their alloys with one and two palladium atoms are studied by using full-potential density functional computations. The stable isomers of these clusters are identified and their magic numbers are determined via the analysis of the second difference of their minimized energy. We discuss that the doped Pd generally prefers the high coordination sites of the pure cluster. It is argued that Pd doping influences the structural cross over of these clusters. The GW correction is applied for more accurate determination of the electronic structure of the systems. [ABSTRACT FROM AUTHOR]