Deformation behaviors and fracture strength of β$\ubeta$-Si3N4 single crystals

In this study, the yield stress and fracture strength of $\beta$-Si₃N₄ single crystals were directly measured by bending tests of microcantilever beam specimens that were prepared by a focused ion beam method. The $\beta$-Si₃N₄ single crystals were plastically deformed at room temperature under high bending stress, and the yield stress depended on the crystal orientation. Transmission electron microscopy observation of the specimens after bending tests indicates that the plastic deformation resulted from dislocations in the primary slip system $\{10\overline{1}0\}$<0001>, and the critical resolved shear stress of this slip system determined from the yield stress was 1.34 GPa. The fracture strength of $\beta$-Si₃N₄ single crystals ranged approximately up to 20 GPa, depending on the crystal orientation as with the yield stress. The fracture behavior of $\beta$-Si₃N₄ single crystals was discussed in terms of the accumulation of dislocations.     

Smart and Multifunctional Fiber-Reinforced Composites of 2D Heterostructure-Based Textiles

Smart and multifunctional fiber reinforced polymer (FRP) composites with energy storage, sensing, and heating capabilities have gained significant interest for automotive, civil, and aerospace applications. However, achieving smart and multifunctional capabilities in an FRP composite while maintaining desired mechanical properties remains challenging. Here, a novel approach for layer-by-layer (LBL) deposition of 2D material (graphene and molybdenum disulfide, MoS₂)-based heterostructure onto glass fiber fabric using a highly scalable manufacturing technique at a remarkable speed of ≈150 m min⁻¹ is reported. This process enables the creation of smart textiles with integrated energy storage, sensing, and heating functionalities. This methodology combines gel-based electrolyte with a vacuum resin infusion technique, resulting in an efficient and stable smart FRP composite with an areal capacitance of up to ≈182 µF cm⁻² at 10 mV s⁻¹. The composite exhibits exceptional cyclic stability, maintaining ≈90% capacitance after 1000 cycles. Moreover, the smart composite demonstrates joule heating, reaching from ≈24 to ≈27 °C within 120 s at 25 V. Additionally, the smart composite displays strain sensitivity by altering electrical resistance with longitudinal strain, enabling structural health monitoring. These findings highlight the potential of smart composites for multifunctional applications and provide an important step toward realizing their actual real-world applications.     

Double diffusive Buoyancy-driven flow in a fluid-saturated elliptical annulus with a neural network-based prediction of heat and mass transfer

This paper presents a numerical study of buoyancy-driven double-diffusive convection within an elliptical annulus enclosure filled with a saturated porous medium. An in-house built FORTRAN code has been developed, and computations are carried out in a range of values of Darcy–Rayleigh number Ra_m (10 ≤ Ra_m ≤ 500), Lewis number Le (0.1 ≤ Le ≤ 10), and the ratio of buoyancy forces N (−5 ≤ N ≤ 5). In addition, three methods are used, namely the multi-variable polynomial regression, the group method of data handling (GMDH), and the artificial neural network (ANN) for the predictions of heat and mass transfer rates. First, results are successfully validated with existing numerical and experimental data. Then, the results indicated that temperature and concentration distributions are sensitive to the Lewis number and thermal and mass plumes are developing in proportion to the Lewis number. Two particular values of Lewis number Le = 2.735 and Le = 2.75 captured the flow's transition toward an asymmetric structure with a bifurcation of convective cells. The average Nusselt number tends to have an almost asymptotic value for Le » 5. For the case of aiding buoyancies N > 1, the average Nusselt Number $\overline{\mathit{Nu}}$ decreased by 33% when the Lewis number increased to its maximum value. Then, it increased by 10% when the Lewis number increased to Le = 1 for the case of opposing buoyancies N < 1 and then decreased by 33% when the Lewis number increased to its maximum value., contrary to the behavior of the average Sherwood number $\overline{\mathit{Sh}}$ that increased by 700% for both cases N > 1 and N < 1. New correlations of $\overline{\mathit{Nu}}$, and $\overline{\mathit{Sh}}$ as a function of Ra_m, Le, and N are derived and compared with GMDH and ANN methods, and the ANN method showed higher performance for the prediction of $\overline{\mathit{Nu}}$ and $\overline{\mathit{Sh}}$ with R² exceeding 0.99.     

Synthesis,Characterization and Adsorption of Bisphenol A Using Novel Hybrid Materiel Produced from PANI Matrix Reinforced by Kieselguhr

Journal of Inorganic and Organometallic Polymers and Materials - This study investigated the preparation of new adsorbent based PANI and Kieselguhr (KG). The produced materials were characterized...     

CADS-ML/DL: efficient cloud-based multi-attack detection system

International Journal of Information Security - With the increasing adoption of cloud computing, securing cloud-based systems and applications has become a critical concern for almost every...