Dynamics of Brownian motion and flux conditions on naturally unsteady thermophoretic flow with variable fluid properties

This work examines the boundary flow difficulties of the past and the heat transfer properties of Blasius and Sakiadis flows under prescribed concentration flux and prescribed heat flux. The nanofluid is also taken into account in this model, along with impacts from Brownian motion and thermophoresis. The modified system governing partial differential equations is numerically solved by using the R-K method along with the shooting technique. Various values of physical quantities like thermophoresis parameter, Brownian motion parameter, Eckert number, thermal radiation parameter, heat source parameter, and magnetic field parameter along with the $C_f,N{u}_x,\text{and}S{h}_x$ were calculated using the temperature, concentration, and velocity profiles. Finally, we demonstrated how the Brownian motion, radiation, and thermophoresis parameters can significantly increase the temperature distributions. The concentration distributions were decelerated with an increase in Brownian motion parameters for both Blasius and Sakiadis cases.     

Sub-Picosecond Carrier Dynamics Explored using Automated High-Throughput Studies of Doping Inhomogeneity within a Bayesian Framework

Bottom–up production of semiconductor nanomaterials is often accompanied by inhomogeneity resulting in a spread in electronic properties which may be influenced by the nanoparticle geometry, crystal quality, stoichiometry, or doping. Using photoluminescence spectroscopy of a population of more than 11 000 individual zinc-doped gallium arsenide nanowires, inhomogeneity is revealed in, and correlation between doping and nanowire diameter by use of a Bayesian statistical approach. Recombination of hot-carriers is shown to be responsible for the photoluminescence lineshape; by exploiting lifetime variation across the population, hot-carrier dynamics is revealed at the sub-picosecond timescale showing interband electronic dynamics. High-throughput spectroscopy together with a Bayesian approach are shown to provide unique insight in an inhomogeneous nanomaterial population, and can reveal electronic dynamics otherwise requiring complex pump-probe experiments in highly non-equilibrium conditions.     

Mechanical and Microstructure Characterization of Alccofine Based High Strength Concrete

Silicon - This study presents the influence of alccofine-1203 (alccofine) on mechanical and microstructure characteristics of High Strength Concrete (HSC). A total of 7 binder proportions were...     

Comparative Assessment of Crystallographic Phase Stability of Anatase and Rutile TiO2 at Dynamic Shock Wave Loaded Conditions

In the present research article, authors have experimentally evaluated the shock wave resistant properties of technologically potential materials of the anatase and the rutile phase TiO₂ nanoparticles at the dynamic shock wave loaded conditions. The shock wave resistant behavior has been quantitatively drawn utilizing the crystallographic phase stability of the test samples for which the required crystallographic information has been extracted from the powder XRD patterns. Based on our observed experimental results as well as the respective interpretations, it is strongly authenticated that Rutile TiO₂ NPs are suitable candidates for aerospace and defense industrial applications of materials fabrications because of the outstanding shock resistant properties than that of Anatase TiO₂ NPs which undergo the crystallographic phase transition of rutile-TiO₂ at shocked conditions.

     

Cu(II) ions removal from wastewater using starch nanoparticles (SNPs): An eco-sustainable approach

The complex structured starch particles were reduced to the nanoscale size range through hydrolysis utilizing low concentration acid assisted by ultrasound irradiation. The synthesized starch nanoparticles (SNPs) were characterized by transmission electron microscopy (TEM), Fourier-transform infrared (FTIR), and X-ray diffraction (XRD) techniques. The synthesized SNPs possessed surface activated entities, as many cationic functional groups were confirmed through the FTIR spectrum. Also, these SNPs were effectively utilized to separate heavy Cu metal ions from the synthetic ion solution. The SNPs were characterized using field emission scanning electron microscope (FESEM), X-ray photoelectron spectroscopy (XPS), and Brunauer–Emmett–Teller (BET) analysis for the surface modification after the adsorption process. The weak electrostatic interaction between the SNP surface and Cu ion was confirmed by the XPS spectrum and energy-dispersive X-ray spectroscopy. The maximum efficiency of Cu ions removal was about 93% at an optimal pH 5 and 25 mg/ml dosage. The adsorption equilibrium was obtained in 60 min. The nitrogen isotherm BET analysis of SNPs after adsorption shows a higher specific surface area of 18.552 m²/g, attributed to the interaction and presence of Cu ions on the SNP surface. The process feasibility was validated by the Langmuir isotherm model. The process exhibits pseudo-second-order adsorption kinetics and follows the Langmuir isotherm. The R_L predicted by the Langmuir isotherm mechanism is 0.017, implying favourable adsorption. The process is reproducible and allows for the separation of heavy metal ions from the wastewater through biosorption effectively.     

Optimized channel prediction and auction-based channel allocation for personal cognitive networks

Cognitive networks are stands out as intelligent technology which evolved to enhance spectrum utilization. Secondary users are allowed to utilize the primary user's frequency bands on idling times. Identifying the idle licensed spectrum is achieved through spectrum sensing. The spectrum holes should be explored such that a suitable spectrum can be selected and allocated to the secondary users. Existing spectrum sensing and selection schemes have limitations due to interferences. Thus, an optimization algorithm based on bio-inspired improved weed optimization was presented in this research work for enhanced channel utilization. The optimization model explores the channel characteristics and reduces the primary network interferences through its optimal solution. Further, Markov greedy-based auction scheme was presented for channel allocation. Considering the channel capacity, delay, and switching rates the allocation is performed to enhance the overall system performance. Simulation analysis demonstrates the superior performance of the proposed model over existing techniques like particle swarm optimization and genetic algorithm.     

Extraction and Analysis of Recovered Silver and Silicon from Laboratory Grade Waste Solar Cells

Silicon - In the present work, a new process is reported to recover metallic contacts and wafer from the crystalline silicon solar cell through chemical etching. 2 M KOH was used as an...     

Tribological and Mechanical Properties of Hybrid nHAp/ SiO2/chitosan Composites Fabricated from Snail Shell Using Grey Rational Grade (GRG) Analysis

Silicon - The inorganic nanomaterial plays a crucial role in bone defect repair. Nano hydroxyapatite (nHAp) is the most important inorganic substance that closely resembles the mineral component of...     

Habitat suitability of golden mahseer young ones (Tor putitora,Hamilton 1822) in Himalayan waters,India

Habitat suitability refers to the mechanism that enables organisms to choose suitable habitats to survive. In the present study, we studied the habitat suitability of young golden mahseer (fingerlings and juveniles) in the streams of the Ramganga River, one of the prominent rivers of the western Himalaya. Different habitat types and microhabitat features were documented. Habitat suitability was evaluated by generating habitat suitability criteria curves in response to varying habitat availability and use by young golden mahseer during different seasons. Generalised linear modelling (GLM) was used to analyse environmental characteristics responsible for selecting golden mahseer habitats. We studied mahseer based on body size into two main classes, that is, fingerlings (1.5–10 cm) and juveniles (10–30 cm). Golden mahseer fingerlings preferred mean depth (0.1–0.6 m) and mean stream velocity (0–0.2 m/s) at stream reach dominated by diverse substrate compositions such as sand, gravel, and small cobbles. Similarly, juveniles preferred mean depth (0.1–1.5 m) and mean water velocity (0.1–0.5 m/s), with cobbles, bedrock, and sand dominating their habitats. The GLM results indicated that dissolved oxygen, temperature, and water velocity were the significant factors influencing habitat suitability. High dissolved oxygen positively influenced fingerlings, whereas moderate to high water velocity affected juveniles the most. Therefore, to understand the flow requirement for threatened species like golden mahseer, it is essential to characterise critical habitats and develop criteria based on habitat suitability curves.