Assessment of Analytical Models of Pure Bending of Sheet Materials Using the Digital Image Correlation Method

Bending of sheet materials is a common forming mode for shaping sheet components. Although many numerical models of bending, both analytical and numerical simulations based, are available in the literature, extensive experimental validations have been rather limited. A new bend test method and complementary three‐dimensional finite element (FE) simulation of the experiments are employed to assess the predictions from an advanced analytical and FE model of pure bending of aluminium sheet materials. The experimental set‐up developed and utilised is an open concept design that allows access to the tensile surface and through‐thickness region in the vicinity of the specimen bend line to continuously record images of the deforming specimen with two cameras. The specimen images are analysed for strains using an online strain mapping system based on digital image correction method. Tangential strain distribution results from the models in terms of material thinning in the bend region are compared with those from the experiments on AA2024 aluminium sheet material by considering the responses from the specimen edges and mid‐width regions at the bend line. Furthermore, the tangential and radial stress distributions on the through‐thickness section of the specimen from the analytical model are compared with those from the FE model. The results from experiments, FE model and analytical model are compared and discussed in the light of the experimental data and the assumptions involved in the development of the models.     

Optimization of Rhizopus niveus Lipase Partitioning by an Aqueous Biphasic System

An unconventional aqueous two‐phase system (ATPS) composed of polyethylene glycol (PEG) and sodium carbonate was developed and optimized by employing response surface methodology for separation of Rhizopus niveus lipase. A five‐level central composite design was applied to evaluate the optimal level of three process variables in order to obtain maximum lipase separation. Experimental data were analyzed by regression and a polynomial model was created which was found significant. The maximum partition coefficient was achieved with the system PEG 4000/sodium carbonate. Validation experiments confirmed the high accordance of predicted and experimental results. The optimized ATPS can be applied as a suitable cost‐effective system for lipase extraction.     

Electrical and electrochemical properties of molten-salt-synthesized 0.05 mol Zr- and Si-doped Li4Ti5O12 microcrystals

This work emphasizes the structural, morphological, electrical, and electrochemical properties of 0.05 mol Zr- and Si-doped Li₄Ti₅O₁₂ synthesized using the molten salt method and applied to negative electrodes in Li-ion batteries. Formation of the spinel phase with face-centered cubic structure in the nominally pure and Zr- and Si-doped samples are revealed from X-ray powder diffraction technique. Lattice parameters refined by full-profile Rietveld method are in accordance with the literature data for the Li₄Ti₅O₁₂ (Li_1.333Ti_1.667O₄) spinel structure. The presence of possible functional groups is identified using Fourier transform infra red spectroscopy. The field emission scanning electron microscopic images indicate the formation of micron-sized (1.5–2 μm) randomly distributed polyhedral-shaped particles. The electrical conductivity studies demonstrate the grain-conducting behavior of the material. The maximum DC conductivity of 2 × 10^?5 S cm^?1 is observed for Zr-doped Li₄Ti₅O₁₂ at room temperature. The galvanostatic charge–discharge studies show that Zr-doped Li₄Ti₅O₁₂ exhibits a high discharge capacity of about 325 mAh g^?1 at 0.01 °C, higher than Si-doped Li₄Ti₅O₁₂ (200 mAh g^?1), and also that the cycling stability of Zr-doped Li₄Ti₅O₁₂ is enhanced.     

Potassium Phosphate‐Catalyzed Chemoselective Reduction of α‐Keto Amides: Route to Synthesize Passerini Adducts and 3‐Phenyloxindoles

A chemoselective reduction of α‐keto amides to biologically important α‐hydroxy amides (mandelamides) by polymethylhydrosiloxane (PMHS) using 5 mol% potassium phosphate (K₃PO₄) as catalyst has been developed. This transition metal‐free protocol discloses excellent chemoselectivity for the ketone reduction of α‐keto amides in the presence of other reducible functionalities like ketone, nitro, halides, nitrile and amide. Also, the chemoselectively reduced α‐hydroxy amide has been derivatized to isocyanide‐free Passerini adducts. The N‐alkyl‐α‐hydroxy amides have been successfully converted to 3‐phenyloxindole derivatives by treatment with methanesulfonyl cholride and triethylamine.

     

An effective cryptanalysis of DES for secure communication using hybrid cryptanalysis and deep neural network

In today's world, information security plays a key role in data storage and communication owing to the modern evolution of digitized data interchange in electronic mode. Cryptography is a widely preferred technique for securing transmitted information by transforming the original text into cipher text. A few cryptographic techniques have the inability to protect the data which are vulnerable to a distinct class of attacks. Therefore, a reliable cryptographic technique is necessitated for enlarging information security. In this paper, a new hybrid cryptanalysis (HCA) model has been proposed to acquire optimal cryptanalysis of data encryption standard (DES). It combines linear cryptanalysis (LCA) and neural cryptanalysis (NCA) for enhancing the performance of the cryptographic system with minimal time complexity. Primarily, the HCA model employs LCA to break cryptographic codes by analyzing linear approximations of the cryptographic algorithm. NCA is then applied with the aid of a deep neural network for identifying patterns in larger datasets. These patterns can be further utilized to break encryption. The efficacy of the proposed HCA model will be assessed through the assessment of three different datasets. The results manifest that the accuracy of the proposed model is increased up to 97.66% and the time needed to break encryption can be reduced.     

A hybrid energy harvesting framework and graphene-based supercapacitor for 6G and smart grid networks

This paper proposes a novel hybrid energy harvesting framework integrated with a graphene-based supercapacitor to address the energy demands of 6G communication systems and smart grid networks. To ensure consistent power generation, the proposed framework combines diverse energy harvesting mechanisms, including acoustic, vibration, and radio frequency (RF) energy sources. These harvested energies are then efficiently managed and stored in a proposed graphene-based supercapacitor compared with existing Li-ion batteries, due to its high energy density and rapid charge-discharge capabilities. Smart grids and 6G networks can utilize the energy that hybrid systems harvest. This paper examines the analysis of RF energy extracted from various antenna configurations. In the acoustic energy harvesting system, energy extraction has been achieved by subjecting it to acoustic pressure and impedance. Notably, the inclusion of acoustic impedance has resulted in a greater amount of harvested energy. The vibration energy harvesting analysis with angular frequencies under various force conditions is employed. The magnitude of force applied to the harvesting system significantly influences the efficiency of the harvested energy. The three-dimensional structure and voltage levels of the graphene-based supercapacitor have been examined for various electrodes. For maximizing the harvested hybrid energy, convex optimization is formulated due to its ability to efficiently navigate complex design spaces while ensuring reliable and globally optimal solutions. CVX tool in MATLAB is used for validation. The results improve the energy harvesting efficiency and enhance the power availability of all the harvesting sources. Furthermore, the compatibility of the proposed framework with existing network infrastructure highlights its potential for seamless integration into real-world communication and energy distribution systems.     

Synthesis of hexagonal mesoporous aluminophosphate using Al dross

Hexagonal mesoporous aluminophosphate (HMA) materials were synthesized using cetyltrimethylammonium bromide as a structure directing agent and industrial aluminum dross powder or Al(OH)₃ extracted from Al dross as an aluminum source at room temperature. XRD confirmed the presence of ordered mesostructures in all of the prepared HMA samples, and textural properties of the prepared samples were close to those of HMA prepared using pure chemicals. Uniform pore structure of the materials prepared using the industrial Al dross was confirmed by TEM, and N₂ adsorption-desorption isotherms of the HMA samples showed type IV isotherms with surface area in the range of 410–560 m²/g. Cr-containing HMA (CrHMA) samples were also prepared using industrial aluminum dross as an aluminum source, which demonstrated virtually identical catalytic performances in liquid phase tetralin oxidation reaction to those obtained over a CrHMA catalyst prepared using pure chemicals.     

Spectral Efficiency in Single-Hop Ad-Hoc Wireless Networks with Interference Using Adaptive Antenna Arrays

Receivers with N antennas in single-hop, ad-hoc wireless networks with nodes randomly distributed on an infinite plane with uniform area density are studied. Transmitting nodes have single antennas and transmit simultaneously in the same frequency band with power P that decays with distance via the commonly-used inverse-polynomial model with path-loss- exponent (PLE) greater than 2. This model applies to shared spectrum systems where multiple links share the same frequency band. In the interference-limited regime, the average spectral efficiency of a representative link E[C] (b/s/Hz/link) is found to grow as log(N) and linearly with PLE, and its variance decays as 1/N. The average signal-to-interference-plus-noise-ratio (SINR) on a representative link is found to grow faster than linearly with N. With multiple-input-multiple-output (MIMO) links where transmit nodes have multiple antennas without Channel- State-Information, it is found that E[C] in the network can be improved if nodes transmit using the optimum number of antennas compared to the optimum selfish strategy of transmitting equal-power streams from every antenna. The results are extended to random code-division-multiple-access systems where the optimum spreading factor for a given link length is found. These results are developed as asymptotic expressions using infinite random matrix theory and are validated by Monte-Carlo simulations.