In this current study, five types of strong, stiff, and lightweight composites were developed utilizing hand lay-up and cold press methods by the hybridization of JUCO and carbon fabrics. Before the fabrication of the composites, the surfaces of the JUCO fabrics were treated with a 5% NaOH aqueous solution. To evaluate and compare the mechanical characteristics of the fabricated composites, tensile, flexural, impact, and hardness tests were conducted. Specimens were also aged in artificial seawater (pH 8) for 150 days to explore the effects of seawater aging on the mechanical characteristics of the composites. Numerical analysis of the tensile and flexural properties was also done by the finite element method (FEM). The findings from the current study showed that hybridization with carbon fibers considerably enhanced the mechanical properties of the natural fiber-reinforced composites. On the other hand, a decrement in tensile strength, flexural strength, and hardness, and an improvement in impact strength were noticed due to fiber degradation as a result of aging in seawater. Results obtained from the numerical analysis also displayed good alignment with the experimental findings

Surface plasmon resonance (SPR) sensors have made significant progress in detecting biomolecules such as DNA, viruses, bacteria, and proteins in real-time. These improvements have established SPR as a major biosensing technology. This work investigates the efficacy of SPR sensors using different combinations of plasmonic metals such as gold (Au), silver (Ag), and copper (Cu) with graphene (C) in multi-layer topologies. The study utilizes a single D-shape optical fiber-based SPR sensor due to its fabrication simplicity, cost-effectiveness, and robust nature. Our investigation shows how the SPR sensor is affected by single, dual, tri, quad, and penta layers of metals and graphene with different configurations. In addition, we considered two different fiber designs, namely, design-1 and design-2, respectively, for internal and external sensing environments, and interestingly, both show the same responses. This study found a maximum wavelength sensitivity of 70,000 nm/RIU for Ag-Au, Ag-C-Au, Cu-C-Cu, C-Cu-Ag-Au, and Au-C-Cu-C-Au-based models. Furthermore, the Ag-Au-Cu-Au and Ag-Au-Cu-Au models have the most significant sensitivity in terms of amplitude, found at 116.788 RIU −1. The highest figure of merit (FOM) value of 466.67 is found in the Ag-C-Au, Au-C-Cu-C-Au, and Au-C-Ag-C-Au models. The preferred models for chemical stability due to the Au use at the outer layer are Au-C-Cu-C-Au and Au-C-Ag-Au, which have substantial amplitude sensitivities of 109.483 RIU −1 and 75.345 RIU −1, respectively.

ABSTRACTDesigning an optimized performance elliptic curve cryptography (ECC) processor capable of rapid point multiplication while saving hardware resources is an essential part of system security. This study introduces the implementation of a field‐programmable gate array (FPGA) design of the ECC processor (ECCP), prioritizing speed, compactness, maximum operating frequency, and resultant throughput rate in the prime field of 256‐bit. The processor enables efficient point multiplication for 256 bits in the twisted Edwards25519 curve, which is vital for the strength of the Edwards curve digital signature algorithm (EdDSA). Unique architectures of hardware for different modular and group operations in the twisted Edwards curve are proposed in this work. The processor achieves modular multiplication, point addition, and doubling in only 257, 1286, and 518 clock cycles, respectively. For 256‐bit keys, a point multiplication takes 0.51 ms, which operates at the highest frequency of 226.7 MHz with a cycle count of 115.2 k and a throughput of 501.9 Kbps. The implementation, executed on the Kintex‐7 platform for FPGA implementation in projective coordinates, utilizes 14.7 k slices. This design demonstrates time‐ and throughput‐efficient design by providing fast scalar multiplication while using minimum hardware resources without compromising security. The proposed ECCP on the Edwards curve's performance is improved in such a way that the device uses optimized area, time, frequency, and throughput rate. To generate a key for the ECCP and EdDSA, we simulate various operations like modular arithmetic operations, group operations, and point operations required for correct ECPM implementation on Xilinx ISE and ModelSim. Then we verify these results using the Maple tool.

ABSTRACTPolyvinyl alcohol (PVA) nanofibers have potential importance in industrial applications. In this study, three‐dimensional (3D) net‐structured PVA nanofibers are successfully fabricated using the spray‐freeze‐drying (SFD) technique for the first time. At first, different concentrations of PVA solutions from 0.001 to 5 wt% are applied to prepare PVA nanofibers using liquid nitrogen at −196°C by the SFD method. These nanofibers are characterized by scanning electron microscopy for morphological analysis, photo ruler software for diameter measurement, thermogravimetric analysis and differential scanning calorimetry for thermal stability and crystallinity, as well as nitrogen adsorption isotherms and pore size distribution curves for specific surface area and porous surface quality. Prepared SFD nanofibers with finer nano diameters, fewer beads, more regular 3D net‐structures and without any massive blocks are obtained from 0.05 to 1 wt%. These are compared with the nanofibers prepared by the freeze‐drying (FD) technique. The SFD method shows better results than the FD method in respect to fiber morphology, finer nanoscale diameter, crystallinity, specific surface area, and surface porous property. The best results are obtained from the nanofibers fabricated by the SFD method at 0.1 wt% concentration. Finally, the findings of this work open the opportunities for potential industrial applications and further development of PVA nanofibers.

Pristine and arsenic-doped tetragonal boron nitride nanosheets (BNNS and As-BNNS) have been reported as potential candidates for toxic gas sensing applications. We have investigated the adsorption behavior of BNNS and As-BNNS for CO2, H2S, and SO3 gas molecules using first-principles density functional theory (DFT). Both BNNS and As-BNNS possess negative cohesive energies of -8.47 and -8.22 eV, respectively, which indicates that both sheets are energetically stable. Successful adsorption is inferred from the negative adsorption energy and structural deformation in the vicinity of the adsorbent and adsorbate. As-doping results in a significant increase in adsorption energies from -0.094, -0.175, and -0.462 eV to -2.748, -2.637, and 3.057 eV for CO2, H2S and SO3 gases, respectively. Due to gas adsorption, the electronic bandgap in As-BNNS varies by approximately 32% compared to a maximum of 24% in BNNS. A notable fluctuation in the energy gap and electrical conductivity is seen, with ambient temperature being the point of maximal sensitivity. For SO3, the maximum charge transfer during adsorption in BNNS and As-BNNS is determined to be 0.08|e| and 0.25|e|, respectively. Due to the interaction with gases, all structures exhibit an extremely high absorption coefficient on the order of 104 cm-1 with minimal peak shifting. Additionally, doping an As atom on BNNS' surface remarkably improved its ability to sense CO2, H2S, and SO3 gasses.