Dr. N.G.P. Institute of Technology

In the present work, perovskite LaFeO3 thin films with unique morphology were obtained on silicon substrate using radio frequency magnetron sputtering technique. The effect of thickness and temperature on the morphological and structural properties of LaFeO3 films was systematically studied. The X-ray diffraction pattern explored the highly oriented orthorhombic perovskite phase of the prepared thin films along [121]. Electron micrograph images exposed the network and nanocube surface morphology of LaFeO3 thin films with average sizes of ∼90 and 70 nm, respectively. The developed LaFeO3 thin films not only possess unique morphology, but also influence the gas-sensing performance toward NO2. Among the two morphologies, nanocubes exhibited high sensitivity, good selectivity, fast response-recovery time, and excellent repeatability for 1 ppm level of NO2 gas at room temperature. The response time for nanocubes was 24-11 s with a recovery duration of 35-15 s less than the network structure. The sensitivity toward NO2 detection was found to be in the range 29.60-157.89. The enhancement in gas-sensing properties is attributed to their porous structure, surface morphology, numerous surface active sites, and the oxygen vacancies. The gas-sensing measurements demonstrate that the LaFeO3 sensing material is an outstanding candidate for NO2 detection.

Particle swarm optimization (PSO)-based effective clustering in wireless sensor networks is proposed. In the existing optimized energy efficient routing protocol (OEERP), during cluster formation some of the nodes are left out without being a member of any of the cluster which results in residual node formation. Such residual or individual nodes forward the sensed data either directly to the base station or by finding the next best hop by sending many control messages hence reduces the network lifetime. The proposed enhanced-OEERP (E-OEERP) reduces/eliminates such individual node formation and improves the overall network lifetime when compared with the existing protocols. It can be achieved by applying the concepts of PSO and gravitational search algorithm (GSA) for cluster formation and routing, respectively. For each cluster head (CH), a supportive node called cluster assistant node is elected to reduce the overhead of the CH. With the help of PSO, clustering is performed until all the nodes become a member of any of the cluster. This eliminates the individual node formation which results in comparatively better network lifetime. With the concept of GSA, the term force between the CHs is considered for finding the next best hop during route construction phase. The performance of the proposed work in terms of energy consumption, throughput, packet delivery ratio, and network lifetime are evaluated and compared with the existing OEERP, low energy adaptive clustering hierarchy, data routing for in-network aggregation, base-station controlled dynamic clustering protocols. This paper is simulated using NS-2 simulator. The results prove that, the proposed E-OEERP shows better performance in terms of lifetime.

A facile and cost-effective surfactant assisted hydrothermal technique was used to prepare functional floral-like LaFeO3 nanostructures comprised of nanosheets via a self-assembly process. Scanning electron microscopy images revealed the floral structure of LaFeO3 comprising of nanosheet petals. The petals of ∼15 nm thickness and ∼70–80 nm length observed from transmission electron microscopy self-assembled to form floral structures. X-ray powder diffraction, Fourier-transform infrared spectroscopy and thermal analysis techniques were utilized to determine the structural information and thermal stability. The structural characterization revealed the orthorhombic phase of the prepared LaFeO3 product with high purity even at a high temperature of 800 °C. The growth mechanism of LaFeO3 floral nanostructures has been proposed and the band gap energy was estimated to be 2.10 eV using UV-Vis diffuse reflectance spectroscopy. The Brunauer–Emmett–Teller specific surface area was found to be 90.25 m2 g−1. The visible light photocatalytic activities of LaFeO3 floral nanostructures exhibited higher photocatalytic efficiency compared to the bulk LaFeO3 samples for the degradation of rhodamine B (RhB) and methylene blue (MB). The degradation of MB was higher than RhB. The photocatalytic mechanism for the degradation of organic dye has also been proposed.

In this paper, the coreless photonic crystal fiber (CO-PCF) is investigated using finite element. The absence of core in the PCF structure is achieved by applying the permanent twist on its cladding boundary and hence the light propagation path tends to be circularly polarized. The other modes can also be exerted other than the fundamental modes is known as cladding filled modes or super modes.

The poor wear performance of copper is improved by reinforcing hard ceramic particles. The present work reports the fabrication of Cu/TiB2 (0, 6, 12, 18 vol.%) copper matrix composites (CMCs) using friction stir processing (FSP). TiB2 particles were initially packed together into a machined groove and were subjected to FSP under a constant set of process parameters. The microstructure was observed using optical, scanning and transmission electron microscopy. The wear behavior was examined using a pin-on-disc apparatus. The micrographs showed a homogeneous distribution of TiB2 particles without aggregation and segregation. The distribution of TiB2 particles was closely persistent across the stir zone. TiB2 particles were well bonded with the copper matrix without any interfacial reaction. Many TiB2 particles fractured during FSP. The grains in the composite were extensively refined because of dynamic recrystallization and pinning effect of TiB2 particles. The wear behavior under dry sliding condition was presented in detail.

< 1, the phenomenon is reversed. Other industrial applications of this work are wire coating, plastic coverings, paper fabrication, fiber whirling, etc. In all of those processes, the fluid flow is manipulated by thermal conditions.

Abstract This paper provides a thorough analysis of recent developments in radio frequency identification (RFID)-based biosensors and their uses in the medical industry. The most recent and cutting-edge technologies used in RFID sensors, as well as their operational procedures in the medical industry, are the main focus of this article. The most effective design methodology for RFID biosensors is determined by evaluating various design methodologies. The present state of the art technologies in this domain are also analyzed and discussed. This paper aims to support researchers in the development of inexpensive and widely available RFID-based biosensors that can improve medical and healthcare outcomes. The use of RFID biosensors in contemporary medical applications has demonstrated significant promise for enhancing patient care and facilitating the early diagnosis of a number of diseases. It is anticipated that RFID biosensor technology will maintain to play a significant role in the development of the medical field as it undergoes further development.

In the present investigation, we employ a dual approach consisting of experimental and computational techniques to synthesise and characterise the Schiff-base including the moieties of nitrophenyl (3), nitrothiazole (5) and nitrobenzothiazole (7). The synthesised Schiff bases are confirmed by FT-IR, 1H-NMR and UV-visible spectroscopic techniques. The experimental UV-visible spectroscopic results are compared to the theoretically calculated TD-DFT results. There is a reasonably good agreement between the experimental and the theoretically calculated spectroscopic results. We also calculate the third-order nonlinear optical (NLO) polarizability (γ) of above entitled derivatives using finite field (FF) approach and DFT methods. The compound 7 shows an amplitude of γ as large as 124.15×104 a. u., which is found to be several times larger than that of para-nitroaniline. Moreover, the partial and total density of states (PDOS and TDOS) along with electrostatic potential maps are calculated to get more physical insights into the structure-property relationship and electronic communications between terminal donor and central core acceptor moieties in the synthesised compounds. The present investigation highlights the significance of indigenously synthesised nitrothiazole and nitrobenzothiazole compounds as efficient NLO materials, which may evoke the interest of scientific community in such efficient NLO materials for their potential utilization in device applications.

Morphology controlled synthesis of β-Ga₂O₃ microspheres comprised of nanospheres exhibit excellent ultraviolet light photocatalytic performance towards RhB and MB organic dyes.

The present investigation signifies the Second grade nanofluid stream with porous media, viscous dissipation, joule heating and thermal radiation effects over a moving flat horizontal surface with entropy analysis. This study presents a novel idea regarding the implementation of single phase (Tiwari and Das) model on Second grade fluid model by considering Engine Oil (EO) as a base fluid. Single phase model considers nanoparticles volume fraction for heat transfer enhancement instead of the Buongiorno model which heavily relies on thermophoresis and Brownian diffusion effects for heat transfer analysis. The velocity slip and convective slip boundary conditions have been employed at the surface of the sheet. By utilizing the suitable transformations, the modeled PDEs (partial-differential equations) are renewed in ODEs (ordinary-differential equations) and treated these equations analytically with the help of Variation Iteration Method (VIM). Two different classes of nanofluids, Copper-engine oil (Cu−EO) and Titanium oxide-engine oil (TiO2−EO) have been taken into considering for our analysis. The behavior of surface drag coefficient and Nusselt number for the varied values of various sundry parameters is designed via tables. Our findings show that an increase in the Reynolds and Brinkman numbers increased the overall entropy of the system. Moreover, the stricking outcome of the current study is that due to the heavier density of the Cu nanoparticle the inclusion of nanoparticle volume fraction retards the flow profile and though Cu is a good conductor of heat it boosts up the fluid temperature throughout the domain.

Deep Convolutional neural networks (CNN) have been among the utmost competitive neural network architectures and have set the state-of-the-art in various fields of computer vision. In this paper, we present OCR-Nets, variants of (AlexNet & GoogleNet) for recognition of handwritten Urdu characters through transfer learning. Our proposed networks are experimented using an integrated dataset. To compare the recognition rate with traditional character recognition methods and to confirm the fairness of the experiment an additional Urdu character dataset is manually generated with different fonts and size. The experimental result shows that OCR-AlexNet and OCR-GoogleNet produce significant performance gains of 96.3% and 94.7% averaged success rate respectively.

Abstract MHD Natural convection, which is one of the principal types of convective heat transfer in numerous research of heat exchangers and geothermal energy systems, as well as nanofluids and hybrid nanofluids. This work focuses on the investigation of Natural convective heat transfer evaluation inside a porous triangular cavity filled with silver-magnesium oxide/water hybrid nanofluid [H 2 O/Ag-MgO] hnf under a consistent magnetic field. The laminar and incompressible nanofluid flow is taken to account while Darcy–Forchheimer model takes account of the advection inertia effect in the porous sheet. Controlled equations of the work have been approached nondimensional and resolved by Galerkin finite element technique. The numerical analyses were carried out by varying the Darcy, Hartmann, and Rayleigh numbers, porosity, and characteristics of solid volume fraction and flow fields. Further, the findings are reported in streamlines, isotherms and Nusselt numbers. For this work, the parametric impact may be categorized into two groups. One of them has an effect on the structural factors such as triangular form and scale on the physical characteristics of the important outputs such as fluidity and thermal transfer rates. The significant findings are the parameters like Rayleigh and slightly supported by Hartmann along with Darcy number, minimally assists by solid-particle size and rotating factor as clockwise assists the cooler flow at the center and anticlockwise direction assists the warmer flow. Clear raise in heat transporting rate can be obtained for increasing solid-particle size.

Friction stir processing (FSP) is used as a secondary processing technique that has been employed to enhance the microstructure and other attributes of aluminum matrix composites (AMCs). AA6061/(0–15 wt.%) Al3Ni AMCs were created using pure nickel powder, which was added to molten aluminum. The composite was then subjected to FSP. The AMC microstructures were studied prior to and after FSP using TEM, SEM, OM, and EBSD. The cast composite showed coarse grains, segregation, pores, aggression, as well as polygonal-shaped particles. FSP made the particle distribution homogeneous. Additionally, the coarse Al3Ni particles were broken down into fine particles, and the process eliminated casting defects, for example pores. The size of the grain was significantly reduced because of the severe deformation of plastic and a pinning effect induced by the particles, which were reinforced. FSP also considerably increased the density of dislocations. The resulting microstructural changes improved ductility and tensile strength.

Objective of the present work is to explore the fluidity and thermal performance of Silver and Magnesium oxide mixed water based hybrid nanofluid over the penetrable hollow ampoule under the magnetic influence. Effective thermophysical modelling has been adopted along with the Darcy Forchheimer model engaged exclusively for the inertia of the porosity layer. Governing model equations were solved with the efficient Galerkin Finite Element Analysis (GFEM) and the outcomes were scrutinized towards the error tolerance of 10−6. Parametrical study has been performed with crucial and influencing constraints to traces the behaviors of streamlines and isotherms. Added to the flow influencing constraints the meandering structure of the enclosure itself creates a significant impact on the fluidity which can be evident through the contours developed in the streamline plots. Initial values of the Rayleigh number (Ra) and the Darcy number (Da) make the thermal dissemination stays away from the walls particularly in the hooter wall side with two cliff bar structures. Thermal transference rates get notable assistance from most of the constraints except from the accumulative Hartmann number (Ha) and for the lower Rayleigh number (Ra).

Glassy carbon electrode modified with LaFeO₃ microspheres made up of nanospheres and having high electrocatalytic ability to detect the neurotransmitter dopamine.

In this work, a modified square photonic crystal fiber (MS-PCF) architecture is exposed with ultra-high negative dispersion for communication window. The validation of the model is successfully performed by applying an efficient full-vector finite element method (FV-FEM) with anisotropic perfectly matched layers (PMLs) for precise simulation of PCFs. Additionally, waveguide dispersion engineering is accomplished by tuning the structural parameters of the MS-PCF. From the numerical investigation, negative dispersion behavior permits remarkable suppression rather than positive dispersion. It offers the high negative dispersion of −2357.54 ps/nm/km and Kerr nonlinearity (γ) of 74.68 W−1 km−1 simultaneously at the operating wavelength, λ = 1550 nm. Nevertheless, the designed fiber ensures the mono mode operation in the entire band of interest from λ = 1340 nm to λ = 1580 nm. MS-PCF with these outstanding optical performances has distinguished potency to be practiced as a dispersion compensating fiber in optical communication systems.

According to the World Health Organization, out of 7.4 billion population around 285 million people are estimated to be visually impaired worldwide. It is observed that they are still finding it difficult to roll their day today life and it is important to take necessary measure with the emerging technologies to help them to live the current world irrespective of their impairments. In the motive of supporting them We have proposed a smart spec for the blind persons which can perform text detection thereby produce a voice output. This can help the visually impaired persons to read any printed text in vocal form. A specs inbuilt camera is used to capture the text image from the printed text and the captured image is analyzed using Tesseract-Optical Character recognition (OCR). The detected text is then converted into speech using a compact open source software speech synthesizer, eSpeak. Finally, the synthesized speech is produced by the headphone by TTS method. In this project Raspberry Pi is the main target for the implementation, as it provides an interface between camera, sensors, and image processing results, while also performing functions to manipulate peripheral units (Keyboard, USB etc.,).

A bacterial or bone infection in the feet causes diabetic foot infection (DFI), which results in reddish skin in the wound and surrounding area. DFI is the most prevalent and dangerous type of diabetic mellitus. It will mainly occur in people with heart disease, renal illness, or eye disease. The clinical signs and symptoms of local inflammation are used to diagnose diabetic foot infection. In assessing diabetic foot ulcers, the infection has significant clinical implications in predicting the likelihood of amputation. In this work, a diabetic foot infection network (DFINET) is proposed to assess infection and no infection from diabetic foot ulcer images. A DFINET consists of 22 layers with a unique parallel convolution layer with ReLU, a normalization layer, and a fully connected layer with a dropout connection. Experiments have shown that the DFINET, when combined with this technique and improved image augmentation, should yield promising results in infection recognition, with an accuracy of 91.98%, and a Matthews correlation coefficient of 0.84 on binary classification. Such enhancements to existing methods shows that the suggested approach can assist medical experts in automated detection of DFI.

Internet of Things node authentication via blockchain is discussed in this study (loST). Each node's credentials are verified as part of network security. Cluster leaders receive this data from sensor nodes and process it using loST. CHs gather information. They are exhausted by the additional workload. DDR-LEACHE was suggested as a solution to this issue. DDR-LEACH can replace CHs with conventional nodes if distance from the BS, residual energy and degree are taken into account. The cost of adding additional data to the blockchain is prohibitive. This problem can be solved by utilising IPFS, an external data store. Because AES 128-bit encryption is superior to other approaches, IPFS employs it to safeguard data. For transactions, proof-of-work requires too much computational resources. Consensus proof of authority is used as a basis for this solution (PoA). The model's efficiency and efficacy are demonstrated by the simulation results. According to a comparison, DDR-LEACH improves network lifetime while consuming less energy than LEACH. IPFS storage and service provisioning transaction costs can be reduced by using PoA. We can forecast how long it will take by comparing AES 128-bit encryption to the existing method. Smart contract security is examined. MITM and Sybil were used to test our system's resilience.

Abstract The ability of green micro algae Chlorella vulgaris for biosorption of Cu(II) ions from an aqueous solution was studied. The biosorption process was affected by the solution pH, contact time, temperature and initial Cu(II) concentration. Experimental data were analyzed in terms of pseudo-first order, pseudo-second order and intra particle diffusion models. Results showed that the sorption process of Cu(II) ions followed pseudo-second order kinetics. The sorption data of Cu(II) ions are fitted to Langmuir, Freundlich, and Redlich–Peterson isotherms, and the Temkin isotherm. The thermodynamic study shows the Cu(II) biosorption was exothermic in nature. The Cu(II) ions were recovered effectively from Chlorella vulgaris biomass using 0.1 M H 2 SO 4 with up to 90.3% recovery, allowing for recycling of the Cu. Green algae from freshwater bodies showed significant potential for Cu(II) removal and recovery from industrial wastewater.