International Journal of Computational Materials Science and Engineering

These days, a massive quantity of data is produced online and is incorporated into a variety of datasets in the form of features, however there are lot of features in these datasets that may not be relevant to the problem. In this perspective, feature selection aids to improve the classification accuracy with lesser number of features, which can be well thought-out as an optimization problem. In this paper, Sine Cosine Algorithm (SCA) hybridized with Ant Lion Optimizer (ALO) to form a hybrid Sine Cosine Ant Lion Optimizer (SCALO) is proposed. The proposed algorithm is mapped to its binary versions by using the concept of transfer functions, with the objective to eliminate the inappropriate features and to enhance the accuracy of the classification algorithm (or in any case remains the same). For the purpose of experimentation, this research considers 18 diverse datasets and moreover, the performance of the binary versions of SCALO is compared with some of the latest metaheuristic algorithms, on the basis of various criterions. It can be observed that the binary versions of SCALO perform better than the other algorithms on various evaluation criterions for solving feature selection problem.

By first-principle study, we propose a possible stable helium-based compound with chemical formula of Na₂HeO. It has a structure of space group $Fm-3m$. Energy calculation indicates that it has a local minimum with a lattice constant $a=4.07$ Å. Electronic band structure suggests that it is a wide gap insulator. Analysis on Hirshfeld charges and charge density distribution shows a chemical bond formed between O and He atoms in this structure. Results from both elastic constants and phonon dispersion indicate that this compound in the proposed structure is both mechanically and dynamically stable.

In this paper, a three-dimensional model of the generalized thermoelasticity with one relaxation time and variable thermal conductivity is constructed. The resulting nondimensional governing equations, together with the Laplace and double Fourier transform techniques have been applied to a three-dimensional half-space subjected to thermal loading with rectangular pulse and traction free surface. The inverses of double Fourier transforms and Laplace transforms have been obtained numerically. Numerical results for the temperature increment, the invariant stress, the invariant strain, and the displacement are represented graphically. The variability of thermal conductivity has significant effects on all the studied fields.

Currently, many new materials including nanomaterials exhibit exotic properties like, mention a few, unconventional superconductivity, reduced magnetism, reduced Pauli repulsion. These exotic properties could not be explained completely with the existing quantum mechanical theories which did not take into account the dimension of angle. Now, there arises a necessity to invoke the forgotten dimension of angle, for explaining these exotic interesting properties. So far angle is considered as a dimensionless quantity even though its all time partner $r$ is endowed with dimension. In materials, where surface plays a dominant role, this new dimension, of angle becomes an important tool for exploring their morphology and exotic properties. This new dimension of angle restores the orbital degrees of freedom to the s electrons whose orbital degrees of freedom are suppressed ($\ell =0$). It compensates for the missed signature of s electron orbital angular momentum.

The main objective of this work is to present a numerical modeling of mixed-mode fracture in isotropic functionally graded materials (FGMs), under mechanical and thermal loading conditions. In this paper, the displacement-based method, termed the generalized displacement correlation (GDC) method, is investigated for estimating stress intensity factor (SIF). Using the ANSYS Parametric Design Language (APDL), the continuous variations of the material properties are incorporated by specified parameters at the centroid of each element. This paper presents various numerical examples in which the accuracy of the present method is verified. Comparisons have been made between the SIFs predicted by the GDC method and the available reference solutions in the current literature. A good agreement is achieved between the results of the GDC method and the reference solutions.

In the current decade, nanomaterials have attracted great attention due to the wide range of applications in various disciplines and nanotechnology. Graphene is the best nanoscale material and one of the thinnest elastic films and has various applications. The thermophoretic motion system describes the diffusion of solitaries into substrate-supported graphene sheets. Lie group transformation of the motion equation is used to reduce the equation into solvable equation which is solved through the Bernoulli approximation method and some properties of the solutions are discussed.