A micromechanical characterization of angular bidirectional fibrous composites

A micromechanical numerical algorithm to efficiently determine the homogenized elastic properties of bidirectional fibrous composites is presented. A repeating unit cell (RUC) based on a pre-determined bidirectional fiber packing is assumed to represent the microstructure of the composite. For angular bidirectional fiber distribution, the symmetry lines define a parallelepiped unit cell, representing the periodic microstructure of an angular bidirectional fiber composite. The lines of symmetry extrude a volume to capture a three dimensional unit cell. Finite element analysis of this unit cell under six possible independent loading conditions is carried out to study and quantify the homogenized mechanical property of the cell. A volume averaging scheme is implemented to determine the average response as a function of loading in terms of stresses and strains. The individual elastic properties of the constituents’ materials, as well as, the composite can be assumed to be completely isotropic to completely anisotropic. The output of the analysis can determine this degree. The logic behind the selection of the unit cell and the implementation of the periodic boundary conditions as well as the constraints are presented. To verify this micromechanics algorithm, the results for four composites are presented. The results in this paper are mainly focused on the impact of the fiber cross angles on the stiffness properties of the composites chosen. The accuracy of the results from this micromechanics modeling procedure has been compared with the stiffness/compliance solutions from lamination theory. The methodology is to be accurate and efficient to the extent that periodicity of the composite material is maintained. In addition, the results will show the impact of fiber volume fraction on the material properties of the composite. This micromechanics tool could make a powerful viable algorithm for determination of many linear as well as nonlinear properties in continuum mechanics material characterization and analysis.     

Expanding the Molecular Spectrum of ANKRD11 Gene Defects in 33 Patients with a Clinical Presentation of KBG Syndrome

KBG syndrome (KBGS) is a neurodevelopmental disorder caused by the Ankyrin Repeat Domain 11 (ANKRD11) haploinsufficiency. Here, we report the molecular investigations performed on a cohort of 33 individuals with KBGS clinical suspicion. By using a multi-testing genomic approach, including gene sequencing, Chromosome Microarray Analysis (CMA), and RT-qPCR gene expression assay, we searched for pathogenic alterations in ANKRD11. A molecular diagnosis was obtained in 22 out of 33 patients (67%). ANKRD11 sequencing disclosed pathogenic or likely pathogenic variants in 18 out of 33 patients. CMA identified one full and one terminal ANKRD11 pathogenic deletions, and one partial duplication and one intronic microdeletion, with both possibly being pathogenic. The pathogenic effect was established by RT-qPCR, which confirmed ANKRD11 haploinsufficiency only for the three deletions. Moreover, RT-qPCR applied to six molecularly unsolved KBGS patients identified gene downregulation in a clinically typical patient with previous negative tests, and further molecular investigations revealed a cryptic deletion involving the gene promoter. In conclusion, ANKRD11 pathogenic variants could also involve the regulatory regions of the gene. Moreover, the application of a multi-test approach along with the innovative use of RT-qPCR improved the diagnostic yield in KBGS suspected patients.     

Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures

In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm. VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC). In the current work a modified version of VEABC algorithm for discrete variables has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria: failure mechanism based failure criteria, maximum stress failure criteria and the tsai-wu failure criteria. The optimization method is validated for a number of different loading configurations—uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Finally the performance is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA). The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations.     

Crosstalk noise analysis of coupled on-chip interconnects using a multiresolution time domain (MRTD) technique

Journal of Computational Electronics - In this paper, crosstalk noise analysis of coupled on-chip interconnects is presented. The multiresolution time domain (MRTD) method is used to analyze the...     

Path loss model based on exponential water cycle algorithm for wireless sensor network

Wireless sensor networks (WSNs) are frequently employed in the agriculture field to improve the quality and crop yield. The WSN might reduce the quality of the communication link because of the absorption, dispersion, and attenuation through the leaves of plants. Therefore, estimating the path loss due to signal attenuation before WSN deployment is crucial for the smooth operation of the network. In this research paper, three innovative path loss models are defined based on the MATLAB curve fitting tool: polynomial water cycle (PWC), exponential water cycle (EWC), and Gaussian water cycle (GWC) algorithm. Here, the path loss between the router node and the coordinator node is modeled on the basis of the received signal strength indicator (RSSI) and time of arrival (TOA) measurements in a sugarcane field. The correlation coefficient between the RSSI measurement and the distance must be increased to create a precise path loss model. This paper integrates the exponential, polynomial, and Gaussian functions with the water cycle algorithm (WCA) to evaluate the optimal coefficients that would lead to precise path loss models. The performance of the proposed models that determines the optimum linear fit between RSSI and distance is validated using the correction coefficient $R^2$. The results show that the proposed path loss model is superior to existing path loss models. The correlation coefficient $R^2$ of the proposed EWC model is 0.9993, whereas the existing PE-PSO, LNSM, and PSO-Exponential models yield 0.98, 0.87, and 0.93, respectively. Also, the proposed models attain the best mean absolute error (MAE) of 0.2187, 0.2951, and 0.3457 dBm for EWC, PWC, and GWC algorithms, respectively.     

New and simple synthetic strategy for two-dimensional ultra-microporous aromatic framework for selective uranium capture in liquid

Uranium is a key element to improve nuclear energy demands, and thereby the extraction of uranium from seawater is a strategic way to address uranium sustainability. Herein, a novel two-dimensional porous aromatic framework (AO-PAF), which possesses an ultra-microporous architecture with an ordered structure, excellent stability and selectivity of uranium extraction from a liquid phase. AO-PAF shows excellent uranium adsorption capacities of 637 (mg/g) and 3.22 (mg/g) in simulated and natural seawater attributable to the selective uranium coordinating groups on highly accessible pores on the walls of open channels. In addition, benefiting from the super-hydrophilicity due to the presence of amidoxime groups attributes high selectivity and ultrafast kinetics with an uptake rate of 0.43 ± 0.03 (mg/g·day) and allowing half-saturation within 1.35 ± 0.09 days. This strategy demonstrates the potential of PAF not only recovery of uranium and can be extended for other applications by sensible planning of target ligands.     

Physical effects of nanoaluminum oxide and nanographene on kenaf epoxy composite; vacuum bagging process

In this study, the effect of secondary filler nanographene and primary filler nanoaluminum oxide with kenaf epoxy was investigated. The vacuum bagging process was performed, and a magnetic stirrer was used for blending additives. Water absorption (borewell, distilled, normal, and seawater) and chemical absorption (acid, base, and neutral solution) tests were carried out to evaluate the water absorption, chemical absorption, thickness swelling, and diffusivity of the composite with varying percentages of fillers. The result demonstrates that the addition of 6% primary and 3% secondary filler together, increases the density of the sample by 13.5% and decreases void content by 77%. The addition of secondary filler lowers water absorption in normal water by 1.3% compared to other types of water, as the addition of secondary filler increases the water absorption decreases by 70% in borewell water, 75% in distilled water, 76% in normal water, and 69% in seawater. Thickness swelling of the samples decreases upon the addition of secondary fillers. In acid, the primary and secondary fillers increase the resistance to dissolution. The diffusivity rate of the sample with a combination of fillers 1.3 × 10⁻⁵.     

One-pot hydrothermal synthesis of Cu2Te/NiTe nanocomposite materials: A structural,morphological, and optical study

Due to various structural and optical properties, metal chalcogenide nanomaterials are favorable candidates for different optoelectronic applications. In the current report, Cu₂Te/NiTe nanocomposites were synthesized via the facile hydrothermal method. With the variation of concentration of Cu and Ni, various materials had been prepared along with pure Cu₂Te and NiTe. The observed several vibrational modes in the material through the Raman spectroscopy are well agreed with the appearing phases. The morphological study confirmed the nanostructures are combination of nanoparticles with sheets. The size of nanoparticles varied in the range of 66–34 nm. The absorbance spectra of the nanocomposite exhibit a blueshift and support the enhancement in the optical bandgap. The value of bandgap energy of the composite samples has been noted in the range of 1.8–2.2 eV. This bandgap range enables the material for various optoelectronic applications such as solar cell and other photovoltaic devices. Thermal analysis of the material demonstrates the presences of several endothermic and exothermic peaks. Thus, several studies on the material prevail its various applicability as optoelectronics as well as other thermal application.     

Kinetic study of Hg(II)-promoted substitution of cyanide from hexacyanoferrate(II) in an anionic surfactant medium by 2,2′-bipyridine

The kinetic investigation of Hg(II)-promoted reaction between [Fe(CN)₆]⁴⁻ and 2,2′-bipyridine (Bipy) has been performed in anionic sodium dodecyl sulfate (SDS) micellar medium by recording the surge in absorbance at 400 nm, corresponding to ultimate reaction product [Fe(CN)₄ Bipy]²⁻ using UV–visible spectrophotometer. Pseudo-first-order condition has been used to examine the progress of reaction as a function of temperature, [Fe(CN)₆⁴⁻], ionic strength, [SDS], pH, [Hg²⁺], and [Bipy] by changing one parameter at a time. The results exhibit that [Hg²⁺], [SDS], and pH are the decisive parameter showing maximum reaction rate at 1.5 × 10⁻⁴ mol dm⁻³, 6.0 × 10⁻³ mol dm⁻³, and 3.8, respectively. [Fe(CN)₆]⁴⁻ does not show any appreciable effect on the critical micellar concentration (CMC) of SDS as the polar head of SDS and [Fe(CN)₆]⁴⁻ both are negatively charged. Variable order kinetics was observed for [Fe(CN)₆]⁴⁻ and Bipy in their examined concentration range. The reverse response observed in the reaction rate with [KNO₃] shows a negative salt effect. The K⁺ provided by K₄[Fe(CN)₆] and KNO₃ decreases the repulsion between the negatively charged heads of the surfactant molecules thereby decreasing the CMC of SDS. The negative value for the entropy of activation also supports the interchange dissociative (I_d) mechanism recommended by us.