Two-phase Hybrid Thermal Interface Alkali-treated E-Glass Fiber/MWCNT/Graphene/Copper Oxide Nanocomposites for Electronic Gadgets.

INTRODUCTION: Two-phase hybrid mode thermal interface materials were created and characterized for mechanical properties, thermal conductivity, and wear behaviour. Therefore, the ultimate goal of this current research was to use alkali-treated glass fibre and other allotropes to produce high-performance two-phase thermal interface materials. METHOD: Three different polymer composites were prepared to contain 20 vol.% alkalies [NaOH] treated e-glass fibre [E] and epoxy as a matrix with varying proportions of multi-walled carbon nanotube [MWCNT], graphene [G], copper oxide [C]. The one-phase material contained epoxy+20%e-glass+1%MWCNT [EMGC1], the two-phase hybrid composite contained epoxy+20%e-glass+1%MWCNT+1%graphene+1%CuO [EMGC2], and two-phase material contained epoxy+20%e-glass+1%graphene+1%CuO [EMGC3]. Vacuum bagging method was used for fabricating the composites. RESULT: The higher thermal conductivity observed was 0.3466 W/mK for EMGC2, the alkali-treated glass fibre/hybrid mode nanofillers epoxy matrix composite was mechanically tougher than the other two composites [EMGC1 & EMGC3]. Scanning electron microscopy analysis revealed the fine filler dispersion and homogenous interaction with the glass fibre/epoxy resin composite of the upper and lower zone, which also revealed the defective zone, fibre elongation, fibre/filler breakages, and filler leached surfaces. CONCLUSION: Finally, it was concluded that the hybrid mode two-phased structure EMGC2 epoxy matrix composite replicated the maximum thermal conductivity, mechanical properties, and wear properties of the other two specimens.

Investigation of TiO2 Nanoparticles Influence on Tensile Properties and Thermal Stability of Dry and Wet Luffa-Epoxy Nanocomposites.

BACKGROUND: Recently, progress has been made toward understanding the efficiency of polymer composites with natural fibres. With the hope of enhancing the characteristics of polymer composites supplemented with natural fibres in a watery environment, TiO2 nanoparticles have been used to improve their performance in the field. METHOD: These nanoparticles were filled in luffa-epoxy components at 1, 3, and 5 % volume fractions. A combination of x-ray diffraction and Fourier transform infrared spectroscopy was utilized to conduct the structural examinations. The nanoparticle spread was captured by field emission scanning electron microscopy. RESULT: Results show that dry nanocomposite's tensile strength and modulus have increased by 74% and, 13%, 137%, and 50% compared with epoxy and 40 vol% luffa-epoxy [E/L] composites, respectively. In wet nanocomposites, maximum reduction in tensile strength and modulus were observed as 27.4% and 16.54%, respectively. The diminished water absorption and thickness swelling percentage of nanocomposites were recorded as 98% and 91.8%, respectively. The onset temperature of these nanocomposites was scattered in the range of 379-393°C, with a maximum char residue of 38%. CONCLUSION: The increase in the percentage of residue indicates the effectiveness of epoxy's flame retardant, improved thermal stability, diminished water absorption [approximately 2%], and 95% retention of wet composites' tensile properties. These results provided data support for improving the application of nanocomposites in the automobile field.

Optimization of water reuse and modelling by saline composition with nanoparticles based on machine learning architectures.

Water is a necessary resource that enables the existence of all life forms, including humans. Freshwater usage has become increasingly necessary in recent years. Facilities for treating seawater are less dependable and effective. Deep learning methods have the ability to improve salt particle analysis in saltwater's accuracy and efficiency, which will enhance the performance of water treatment plants. This research proposes a novel technique in optimization of water reuse with nanoparticle analysis based on machine learning architecture. Here, the optimization of water reuse is carried out based on nanoparticle solar cell for saline water treatment and the saline composition has been analyzed using a gradient discriminant random field. Experimental analysis is carried out in terms of specificity, computational cost, kappa coefficient, training accuracy, and mean average precision for various tunnelling electron microscope (TEM) image datasets. The bright-field TEM (BF-TEM) dataset attained a specificity of 75%, kappa coefficient of 44%, training accuracy of 81%, and mean average precision of 61%, whereas the annular dark-field scanning TEM (ADF-STEM) dataset produced specificity of 79%, kappa coefficient of 49%, training accuracy of 85%, and mean average precision of 66% as compared with the existing artificial neural network (ANN) approach.

Regression analysis on forward modeling of diffuse optical tomography system for carcinoma cell detection.

The forward model design was employed in the Diffuse Optical Tomography (DOT) system to determine the optimal photonic flux in soft tissues like the brain and breast. Absorption coefficient (mua), reduced scattering coefficient (mus), and photonic flux (phi) were the parameters subjected to optimization. The Box-Behnken Design (BBD) method of the Response Surface Methodology (RSM) was applied to enhance the Diffuse Optical Tomography experimental system. The DC modulation voltages applied to different laser diodes of 850 nm and 780 nm wavelengths and spacing between the source and detector are the two factors operating on three optimization parameters that predicted the result through two-dimensional tissue image contours. The analysis of the Variance (ANOVA) model developed was substantial (R2 = > 0.954). The experimental results indicate that spacing and wavelength were more influential factors for rebuilding image contour. The position of the tumor in soft tissues is inspired by parameters like absorption coefficient and scattering coefficient, which depend on DC voltages applied to the Laser diode. This regression method predicted the values throughout the studied parameter space and was suitable for enhancement learning of diffuse optical tomography systems. The range of residual error percentage evaluated between experimental and predicted values for mua, mus, and phi was 0.301%, 0.287%, and 0.1%, respectively.

Improving energy consumption prediction for residential buildings using Modified Wild Horse Optimization with Deep Learning model.

The consumption of a significant quantity of energy in buildings has been linked to the emergence of environmental problems that can have unfavourable effects on people. The prediction of energy consumption is widely regarded as an effective method for the conservation of energy and the improvement of decision-making processes for the purpose of lowering energy use. When it comes to the generation of positive results in prediction tasks, the Machine Learning (ML) technique can be considered the most appropriate and applicable strategy. This article presents a Modified Wild Horse Optimization with Deep Learning approach for Energy Consumption Prediction (MWHODL-ECP) model in residential buildings. The MWHODL-ECP method that has been provided places an emphasis on providing an up-to-date and precise forecast of the amount of energy that residential buildings consume. The MWHODL-ECP algorithm goes through several phases of data preprocessing in order to achieve this goal. These steps include merging and cleaning the data, converting and normalising the data, and converting the data. A model known as deep belief network (DBN) is used here for the purpose of predicting energy consumption. In the end, the MWHO algorithm is utilised for the hyperparameter tuning procedure. The results of the experiments demonstrated that the MWHODL-ECP approach is superior to other existing DL models in terms of its performance. The MWHODL-ECP model has improved its performance, with effective prediction results of MSE-1.10, RMSE-1.05, MAE-0.41, R-squared-96.28, and Training time-1.23.

Remediation of heavy metal polluted waters using activated carbon from lignocellulosic biomass: An update of recent trends.

The use of a cheap and effective adsorption approach based on biomass-activated carbon (AC) to remediate heavy metal contamination is clearly desirable for developing countries that are economically disadvantaged yet have abundant biomass. Therefore, this review provides an update of recent works utilizing biomass waste-AC to adsorb commonly-encountered adsorbates like Cr, Pb, Cu, Cd, Hg, and As. Various biomass wastes were employed in synthesizing AC via two-steps processing; oxygen-free carbonization followed by activation. In recent works related to the activation step, the microwave technique is growing in popularity compared to the more conventional physical/chemical activation method because the microwave technique can ensure a more uniform energy distribution in the solid adsorbent, resulting in enhanced surface area. Nonetheless, chemical activation is still generally preferred for its ease of operation, lower cost, and shorter preparation time. Several mechanisms related to heavy metal adsorption on biomass wastes-AC were also discussed in detail, such as (i) - physical adsorption/deposition of metals, (ii) - ion-exchange between protonated oxygen-containing functional groups (-OH, -COOH) and divalent metal cations (M2+), (iii) - electrostatic interaction between oppositely-charged ions, (iv) - surface complexation between functional groups (-OH, O2-, -CO-NH-, and -COOH) and heavy metal ions/complexes, and (v) - precipitation/co-precipitation technique. Additionally, key parameters affecting the adsorption performance were scrutinized. In general, this review offers a comprehensive insight into the production of AC from lignocellulosic biomass and its application in treating heavy metals-polluted water, showing that biomass-originated AC could bring great benefits to the environment, economy, and sustainability.

Collaborative Search Engine for Enhancing Personalized User Search Based on Domain Knowledge.

In the fast moving world, users cross over large amount of data for their daily life. Due to the misinterpretation of the context, user cannot retrieve the proper context or failure to retrieve the information. The main aim of this paper is to design and implement a personalized search engine which works based on the domain of the user with the specific constraints suggested by the user. In this paper, the proposed system, build a search engine with web content which get information from the document corpus for the domain through the cloud databases. Web search engine re-ranks the generic results based on a ranking of a context linked with the domain. In this system, collaborative search service helps to improve the relevancy of the search results and to reduce the overtime on bad links and hence caters to customized needs with collaborative feedback using fuzzy decision tree based on fuzzy rules.

Green synthesis of magnetic Fe3O4 nanoparticles using Couroupita guianensis Aubl. fruit extract for their antibacterial and cytotoxicity activities.

In the present study, a sustainable green chemistry approach was established to fabricate magnetic Fe3O4 nanoparticles (Fe3O4NPs) using the aqueous fruit extract of edible C. guianensis (CGFE). Synthesized NPs were further confirmed with different high-throughput characterization techniques such as UV-visible spectroscopy, FT-IR, XPS, DLS and zeta potential analysis. Additionally, XRD, AFM, HRTEM and SQUID VSM demonstrate the generation of crystalline CGFe3O4NPs with mean diameter of 17 ± 10 nm. Interestingly, CGFe3O4NPs exhibit a stupendous bactericidal action against different human pathogens which depicts its antimicrobial value. A significant dose-dependent cytotoxic effect of CGFe3O4NPs was noticed against treated human hepatocellular carcinoma cells (HepG2).

New Molecular Design Concurrently Providing Superior Pure Blue, Thermally Activated Delayed Fluorescence and Optical Out-Coupling Efficiencies.

Simultaneous enhancement of out-coupling efficiency, internal quantum efficiency, and color purity in thermally activated delayed fluorescence (TADF) emitters is highly desired for the practical application of these materials. We designed and synthesized two isomeric TADF emitters, 2DPyM-mDTC and 3DPyM-pDTC, based on di(pyridinyl)methanone (DPyM) cores as the new electron-accepting units and di(tert-butyl)carbazole (DTC) as the electron-donating units. 3DPyM-pDTC, which is structurally nearly planar with a very small ΔEST, shows higher color purity, horizontal ratio, and quantum yield than 2DPyM-mDTC, which has a more flexible structure. An electroluminescence device based on 3DPyM-pDTC as the dopant emitter can reach an extremely high external quantum efficiency of 31.9% with a pure blue emission. This work also demonstrates a way to design materials with a high portion of horizontal molecular orientation to realize a highly efficient pure-blue device based on TADF emitters.

The Photovoltaic Performances of PVdF-HFP Electrospun Membranes Employed Quasi-Solid-State Dye Sensitized Solar Cells.

The PVdF-HFP nanofiber membranes with different molecular weight were prepared by electrospinning technique and were investigated as solid state electrolyte membranes in quasi solid state dye sensitized solar cells (QS-DSSC). The homogeneously distributed and fully interconnected nanofibers were obtained for all of the prepared PVdF-HFP electrospun membranes and the average fiber diameters of fabricated membranes were dependent upon the molecular weight of polymer. The thermal stability of electrospun PVdF-HFP membrane was decreased with a decrement of molecular weight, specifying the high heat transfer area of small diameter nanofibers. The QS-DSSC fabricated with the lower molecular weight PVdF-HFP electrospun nanofiber membrane exhibited the power conversion efficiency of 1 = 5.38%, which is superior over the high molecular weight membranes and is comparable with the liquid electrolyte. Furthermore, the electrospun PVdF-HFP membrane exhibited long-term durability over the liquid electrolyte, owing to the higher adsorption and retention efficiencies of liquid electrolyte in its highly porous and interconnected nanofibers. Thus the proposed electrospun PVdF-HFP membrane effectively tackled the volatilization and leakage of liquid electrolyte and provided good photoconversion efficiency associated with an excellent stability, which constructs the prepared electrospun membranes as credible solid state candidates for the application of QS-DSSCs.

C-Phycocyanin from Oscillatoria tenuis exhibited an antioxidant and in vitro antiproliferative activity through induction of apoptosis and G0/G1 cell cycle arrest.

This study was undertaken to develop an efficient single step chromatographic method for purification of C-phycocyanin (CPC) from species of Oscillatoria tenuis. Purification of CPC involves a multistep treatment of the crude extract by precipitation with ammonium sulphate, followed by gel filtration chromatography. Pure CPC was finally obtained from O. tenuis with purity ratio (A620/A280) 4.88. SDS-PAGE of pure CPC yielded two bands corresponding to α and ß subunits; the molecular weight of α subunit is 17.0 kDa, whereas the molecular weight of ß subunit is 19.5 kDa. Fluorescence and phase contrast microscopy revealed characteristic apoptotic features like cell shrinkage, membrane blebbing, nuclear condensation and DNA fragmentation. CPC exhibited antioxidant and antiproliferative activity against human cancer cells through apoptosis; nuclear apoptosis induction was accompanied by G0/G1 phase arrest and DNA fragmentation. CPC is a natural pigment with potential as an anticancer agent.

Larvicidal and adulticidal activities of some medicinal plants against the malarial vector, Anopheles stephensi (Liston).

The present study was undertaken to test the efficacy of 11 commonly available medicinal plants and compare its efficacy in relation to larvicidal and mosquitocidal activities against larvae and adults of Anopheles stephensi (Liston). All the medicinal plants and the mixture were effective against larvae of A. stephensi as evidenced by low lethal concentration and lethal time. The lethality varied in adults and plant extracts of mixture; Eucalyptus globulus, Cymbopogan citratus, Artemisia annua, Justicia gendarussa, Myristica fragrans, Annona squamosa, and Centella asiatica were found to be most effective. Larval mortality between 80% and 100% was observed in mixture treatment, C. asiatica and E. globulus. The adults that emerged from all the treatments were malformed. Further, the treated larvae showed significant decrement in the levels of protein, carbohydrate, and lipids and affect negatively the presence of certain amino acids. The present findings have important implications in the practical control of mosquito larvae and adults in the aquatic ecosystem as the medicinal plants studied are commonly available in large quantities. These plant extracts are easy to prepare, inexpensive, and safe for mosquito control which might be used directly as larvicidal and mosquitocidal agents in small volume aquatic habitats or breeding sites of around human dwellings.

Electro-analysis of energetic materials.

Cyclic voltammetric studies of triaminoguanidine nitrate (TAGN), 3,3'-hydrazino bis(bis[6,6'-(3,5-dimethylpyrazol-lyl])-1,2,4,5-tetrazine (HBPT), 4,6-dinitrobenzofuroxan (DNBF) and 3,3'-diamino-4,4'-azoxyfurazan (DAAF) were carried out at different pH conditions in 50% aqueous acetonitrile using glassy carbon electrode. Optimum pH was selected for individual compounds. Influence of scan rate and concentration on the voltammetric response were studied in optimum pH. The number of electron transferred was determined by controlled potential coulometry. All compounds undergo diffusion controlled electrochemical reaction. Based on cyclic voltammetric results, differential pulse and square wave voltammetric methods have been developed for the analytical determination. Instrumental parameters such as initial scan potential, amplitude, pulse increment, pulse period, pulse width and frequency were studied. Optimum experimental conditions for each compound were obtained. After fixing optimum conditions, the effect of concentration was studied and calibration plot was arrived. These plots can be used to determine the traces of the above said four energetic materials.

Voltammetric determination of nitroaromatic and nitramine explosives contamination in soil.

The contamination of soil by nitroaromatic and nitramine explosives is widespread during the manufacture, testing and disposal of explosives and ammunitions. The analysis for the presence of trace explosive contaminants in soil becomes important in the light of their effect on the growth of different varieties of plants and crops. 2,4,6-Trinitrotoluene (TNT), cyclotrimethylene trinitramine (Research Department explosive, RDX) and cyclotetramethylene tetranitramine (high melting point explosive, HMX), other related explosive compounds and their by-products must be monitored in soil and surrounding waterways since these are mutagenic, toxic and persistent pollutants that can leach from the contaminated soil to accumulate in the food chain. In this study, a voltammetric method has been developed for the determination of explosive such as RDX, HMX and TNT. The electrochemical redox behavior of RDX, HMX and TNT was studied through cyclic voltammetry and quantitative determination was carried out by using square wave voltammetry technique. Calibration curves were drawn and were linear in the range of 63-129ppm for RDX with a detection limit of 10ppm, 49-182ppm for HMX with a detection limit of 1ppm and 38-139ppm for TNT with a detection limit of 1ppm. This method was applied to determine the contaminations in several soil samples that yielded a relative error of 1% in the concentrations.

Association of fowl adenovirus serotype 12 with hydropericardium syndrome of poultry in India.

Eight fowl adenovirus (FAdV) isolates obtained from different geographical regions of India were typed by a virus-neutralization test (VNT) using rabbit antisera against all the 12 serotypes of FAdV and by PCR for the hyper-variable region of hexon gene combined with restriction fragment length polymorphism (RFLP) analysis using AluI and MboI restriction enzymes. It was found that six isolates belonged to FAdV-4, one to FAdV-12 and one to both of them. This study revealed the involvement of FAdV-12 alone or in association with FAdV-4 in precipitating inclusion body hepatitis--hydropericardium syndrome (IBH-HPS) among poultry flocks in the country.

Restriction enzyme analysis of Indian isolates of egg drop syndrome 1976 virus recovered from chicken, duck and quail.

Egg drop syndrome 1976 (EDS-76) is caused by a haemagglutinating adenovirus belonging to group III of the genus Aviadenovirus in the family Adenoviridae. All isolates are serologically identical, but have been divided into three groups based on restriction endonuclease (RE) analysis. In this study the viral DNA of various Indian EDS-76 viral isolates (CEDS-A, CEDS-B, EDS-M, EDS-ML, EDS-1/AD/86, EDS-KC and QEDS) obtained from different avian species and different geographical regions were digested with restriction endonucleases viz., EcoRI, BamHI, HindIII and PstI. The results showed that one Indian isolate obtained from duck (DEDS-KC) was different from all other chicken and quail counterparts. All other isolates were identical to the reference viral strain BC-14, which belong to group I of EDS-76 viruses. The duck isolate EDS-KC could not be placed in any of the three groups reported earlier.

Synthesis, characterization and thermal studies on furazan- and tetrazine-based high energy materials.

This paper reports the synthesis of high energy materials (HEMs) viz. 3,3'-diamino-4,4'-azoxyfurazan (DAAF), 3,3s'-azobis(6-amino-1,2,4,5-tetrazine) [DAAT] and 1,4-dihydrazino tetrazine (DHTz). The products obtained were characterized by IR, 1H NMR, 13C NMR and mass spectra. Thermolysis of these compounds carried out by applying TG-DTA and DSC techniques indicated that the thermal stability of DAAF and DAAT was in the temperature range of 230-250 degrees C, whereas that of DHTz was up to approximately 140 degrees C. TG-FTIR of gaseous products of these compounds suggests the evolution of NH2CN/NH3 and HCN as major decomposition products. The impact and friction sensitivity data revealed that DAAF is insensitive to mechanical stimuli whereas DAAT and DHTz are vulnerable to impact stimuli. The cyclic voltammetric studies brought out that, DAAF, DAAT and DHTz are electroactive compounds and thereby can be detected at even low concentration at pH 7 and 13. The theoretical predictions of explosive power of DAAF, DAAT and DHTz alone and their combinations with well-known insensitive high explosives using Becker-Kistiakowsky Wilson (BKW) code as well as that of propellants based on them by NASA-CEC-71 suggest their potential in specific systems.