Nanocrystalline diamond film for biosensor applications

In this study, we have developed a novel capacitive biosensor based on interdigitated gold nanodiamond (GID-NCD) electrode for detection of C-reactive protein (CRP) antigen. CRP is one of the plasma proteins known as acute-phase proteins and its levels rise dramatically during inflammatory processes occurring in the body. It has been reported that CRP in serum can be used for risk assessment of cardiovascular diseases. The antibodies immobilization were confirmed by fourier transform spectroscopy (FTIR) and contact angle measurements. In this capacitive biosensor, nanocrystalline diamond acting as a dielectric layer between the electrodes. The CRP antigen detection was performed by capacitive/dielectric-constant measurements. Our results showed that the response of NCD-based capacitive-based biosensor for CRP antigen was dependent on both concentration (25–800 ng/ml) as well as frequency (50–350 MHz). Furthermore, using optimized conditions, the biosensors developed in this study can be potentially used for detection of elevated level of risk markers protein in suspected subjects for early diagnosis of disease.     

Development and physicochemical characterization of modified polymeric surfaces for bacterial adhesion

Radiation‐induced graft polymerization was used to modify the surfaces of polypropylene (PP) sheets for bacterial adhesion. For the experiments, two monomers were mixed: the quaternary ammonium salt (QAS) [2‐(methacryloyloxy)ethyl]trimethylammonium chloride and acrylic acid (AAc). The PP sheets were activated by electron‐beam radiation before the grafting reaction. Different AAc/QAS comonomer mixture ratios (50 : 10, 40 : 20, 30 : 30, 20 : 40, and 10 : 50) were used to determine the degree of grafting and to make the PP surfaces hydrophilic. The graft level increased with an increase in the percentage of AAc in the comonomer mixtures. Synergism was investigated during graft polymerization to quantify the poly(acrylic acid) and poly{[2‐(methacryloyloxy)ethyl]trimethylammonium chloride} graft fractions in the resulting graft copolymers. An approximation of the graft fractions was made with an analytical technique based on acid–base volumetric titration. The wettability of the modified surfaces was determined by the measurement of the water contact angles. The surfaces prepared with higher percentages of QAS in the comonomer mixtures had lower contact angles than those prepared with lower percentages of QAS. The presence of oxygen and nitrogen on the modified PP surfaces was investigated with X‐ray photoelectron spectroscopy. Structural changes in unmodified and modified PP were characterized with differential scanning calorimetry. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Development of membranes by radiation grafting of acrylamide into polyethylene films: Characterization and thermal investigations

Polyethylene-g-polyacrylamide membranes were prepared by graft polymerization of acrylamide into polyethylene films by preirradiation technique. The characterization and thermal behavior of membranes with different degrees of grafting were evaluated by density, X-ray diffraction, thermogravimetric analysis, and differential scanning calorimetry measurements. Grafting led to considerable changes in the structure of polyethylene membranes. The density of the polyethylene film increased wtih the increase in the degree of grafting, although the increase beyond 100% grafting was less pronounced than at lower graft levels. The heat of fusion and the crystallinity of polyethylene decreased with the increase in the degree of grafting. The decrease in crystallinity is because of the cumulative effect of the dilution of inherent crystallinity by the incorporation of amorphous polyacrylamide grafts within the noncrystalline region of polyethylene (dilution effect) and partial disruption of the crystallites (crystal defects). X-ray diffraction measurements also revealed a decrease in the crystallinity in grafted films. Membranes behaved as a two-component system where polyethylene and polyacrylamide components underwent independent degradation irrespective of the graft levels. In general, the thermal stability of polyethylene in membranes was markedly improved by the grafting of acrylamide monomer as evident from the initial decomposition temperature increasing from 311°C for virgin PE to 390°C in grafted membranes. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 2629–2635, 2001     

Removal of SiC from Silicon After Electron Beam Melting Technique on Industrial Scale

Silicon - Carbon and their compounds were removed successfully through electron beam melting (EBM), so that those areas (contaminated with carbon) of ingot were recycled and reused. During EBM...     

Improvement in end-use quality of spring wheat varieties grown in different eras

Evaluation of wheat cultivars from different eras allows scientists to determine changes in agronomic and end-use quality characteristics associated with grain yield and end-use quality improvement over time. Forty-four spring wheat cultivars introduced or released since 1933 were evaluated for quality improvement using canonical variant analysis. It was observed that there was a considerable improvement in protein content from 1933 to 1964 whereas the genetic potential for straight grade flour protein from 11.34% in 1933–1964 to 12.13% in 1991–1996. Crude protein increased by 6.95% from 1933 to 1996. Ash content and flour yield declined by 9.55% and 5.51%, respectively. Total chapati scores of modern cultivars were 8.97% higher than those of cultivars grown earlier. The average spread ratio and overall cookie scores increased almost 5.53% and 4.44%, respectively from 1933 to 1996. It was also observed that overall cookie scores were highest during the period 1981–1990. The average dry gluten and total chapati scores of varieties grown since 1991 were approximately 10.20% and 74.72% respectively, which were 4.72% and 8.97% higher than those of cultivars grown since 1933. Average spread ratio and overall cookie scores increased almost 5.53% and 4.44% from 1933 to 1996, respectively. The era (1991–1996) containing the modern varieties showed a substantial improvement in lysine content than the era containing the oldest wheat varieties. Similarly amino acid score was also found to be 4.26% higher than the varieties released during the period 1933–1964.     

Investigation of the Observed Localized Corrosion in an Industrial Steel Cation Exchanger Vessel

Cation exchanger (steel vessel), containing polymeric beads as exchange resin, in a process industry is found to be affected from localized “pitting” corrosion during the turnaround. There are two main cycles of such exchanger’s operation, i.e., normal and regeneration cycles, differentiated by passing canal/well water and sulfuric acid solution, respectively. Corrosion rates by Tafel techniques are measured for both these cycles. The different corrosion rates for canal and well water are explained as per reduction reaction equilibrium. During regeneration cycle, certain other tests like cyclic polarization and potentiostatic polarization are also conducted to understand the cause of the localized corrosion. Potentiostatic tests' observations revealed an interesting phenomenon probably explaining the failure not elucidated by the conventional corrosion measurement techniques.     

Impact of Artificial Compressibility on the Numerical Solution of Incompressible Nanofluid Flow

The numerical solution of compressible flows has become more prevalent than that of incompressible flows. With the help of the artificial compressibility approach, incompressible flows can be solved numerically using the same methods as compressible ones. The artificial compressibility scheme is thus widely used to numerically solve incompressible Navier-Stokes equations. Any numerical method highly depends on its accuracy and speed of convergence. Although the artificial compressibility approach is utilized in several numerical simulations, the effect of the compressibility factor on the accuracy of results and convergence speed has not been investigated for nanofluid flows in previous studies. Therefore, this paper assesses the effect of this factor on the convergence speed and accuracy of results for various types of thermo-flow. To improve the stability and convergence speed of time discretizations, the fifth-order Runge-Kutta method is applied. A computer program has been written in FORTRAN to solve the discretized equations in different Reynolds and Grashof numbers for various grids. The results demonstrate that the artificial compressibility factor has a noticeable effect on the accuracy and convergence rate of the simulation. The optimum artificial compressibility is found to be between 1 and 5. These findings can be utilized to enhance the performance of commercial numerical simulation tools, including ANSYS and COMSOL.     

Fruits and Vegetable Diseases Recognition Using Convolutional Neural Networks

As they have nutritional, therapeutic, so values, plants were regarded as important and they’re the main source of humankind’s energy supply. Plant pathogens will affect its leaves at a certain time during crop cultivation, leading to substantial harm to crop productivity & economic selling price. In the agriculture industry, the identification of fungal diseases plays a vital role. However, it requires immense labor, greater planning time, and extensive knowledge of plant pathogens. Computerized approaches are developed and tested by different researchers to classify plant disease identification, and that in many cases they have also had important results several times. Therefore, the proposed study presents a new framework for the recognition of fruits and vegetable diseases. This work comprises of the two phases wherein the phase-I improved localization model is presented that comprises of the two different types of the deep learning models such as You Only Look Once (YOLO)v2 and Open Exchange Neural (ONNX) model. The localization model is constructed by the combination of the deep features that are extracted from the ONNX model and features learning has been done through the convolutional-05 layer and transferred as input to the YOLOv2 model. The localized images passed as input to classify the different types of plant diseases. The classification model is constructed by ensembling the deep features learning, where features are extracted dimension of from pre-trained Efficientnetb0 model and supplied to next 07 layers of the convolutional neural network such as 01 features input, 01 ReLU, 01 Batch-normalization, 02 fully-connected. The proposed model classifies the plant input images into associated labels with approximately 95% prediction scores that are far better as compared to current published work in this domain.