Hydrogen treated TiO2 nanoparticles onto FTO glass as photoanode for dye-sensitized solar cells with remarkably enhanced performance

Hydrogen treatment is a facile and efficient approach for the enhancement in the functioning of TiO₂ nanoparticles for dye-sensitized solar cells (DSSC). In this work, TiO₂ nanoparticles have been synthesized in the hydrogen environment followed by the deposition onto FTO glass substrates with various film thickness as photoanodes for DSSC. The synthesized hydrogen treated TiO₂ nanoparticles based photoanodes have showed significantly improved photocurrent in the resulting fabricated devices. SEM and TEM analyses have confirmed the particle size and morphology of TiO₂ nanoparticles at various magnifications. The crystalline structure and phase identification were studied by XRD analysis and Raman spectroscopic measurements. The UV–Vis spectroscopy analysis was carried out to find the response of samples for ultraviolet and visible light. The current-voltage measurements have confirmed the improvement of photocurrent that is principally due to improved photo-activity of hydrogen treated TiO₂ nanoparticles. Moreover, hydrogen treated TiO₂ nanoparticles-based photoanode with the film thickness of 11.65 μm has remarkably enhanced power conversion efficiency of 6.05% in DSSCs. The ability of highly photoactive hydrogen treated TiO₂ nanoparticles will provide the new openings in different fields that include photo-electrochemical water splitting and in many other applications.     

Bimetallic NiCo–NiCoO2 nano-heterostructures embedded on copper foam as a self-supported bifunctional electrode for water oxidation and hydrogen production in alkaline media

Earth-abundant, non-precious metal-based bifunctional electrocatalysts with efficient water splitting activity are of valuable importance in the limitation of energy losses in an alkaline environment. Herein, we report NiCo–NiCoO₂ nano-heterostructures embedded on the oxidized surface of copper foam (NiCo–NiCoO₂@Cu₂O@CF) as an efficient bifunctional electrocatalyst for overall water splitting in 1 M KOH electrolyte solution. In this study, metallic Ni and Co interlinkage with NiCoO₂ nanoparticles (NPs) are suggested to form by thermal decomposition of nickel-cobalt hydroxide precursors embedding on copper foam under a nitrogen environment. Bimetallic thin layered nano-heterostructures of NiCo–NiCoO₂@Cu₂O@CF exhibits a synergic effect of doubly active metals Ni and Co to achieve remarkable small overpotentials of 133 and 327 mV to achieve a current density of 10 mA cm^?2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The influential synergetic and structural effects have been extensively discussed to understand the overall water splitting for designing an efficient electrocatalyst. Hence, this phenomenon for surface modification of conductive substrate (CF) with a suitable combination of metal/metal oxide alloying as catalytic material helps us to design and synthesize low cost, highly efficient, non-precious metal-based electrocatalysts for overall water splitting.     

Synthesis of ternary ceramics (Cr2AlC) by using biochars

In this paper, we report the synthesis of Cr₂AlC by using biochars derived from lignin, Distiller's dried grains with solubles (DDGS), and hemp fibers. Initially, the powders were pyrolyzed at 1350°C for 4 h in Ar atmosphere to form biochars. The ball-milled and sieved biochar powders were then mixed with Cr and Al powders in different stoichiometric ratios according to the C-content of the biochars. The mixed powders were reacted at 1350°C for 4 h in Ar atmosphere. Detailed scanning electron microscopy and X-ray diffraction analysis showed the powders derived from hemp and DDGS biochars were > 90% pure as compared to powders derived from lignin biochar which was 76% pure. It is expected that ternary ceramics derived from biochars can be an addition avenue for carbon-storage.     

Cystic fibrosis transmembrane conductance regulator is an epithelial cell receptor for clearance of Pseudomonas aeruginosa from the lung

The cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride ion channel, but its relationship to the primary clinical manifestation of CF, chronic Pseudomonas aeruginosa pulmonary infection, is unclear. We report that CFTR is a cellular receptor for binding, endocytosing, and clearing P. aeruginosa from the normal lung. Murine cells expressing recombinant human wild-type CFTR ingested 30-100 times as many P. aeruginosa as cells lacking CFTR or expressing mutant DeltaF508 CFTR protein. Purified CFTR inhibited ingestion of P. aeruginosa by human airway epithelial cells. The first extracellular domain of CFTR specifically bound to P. aeruginosa and a synthetic peptide of this region inhibited P. aeruginosa internalization in vivo, leading to increased bacterial lung burdens. CFTR clears P. aeruginosa from the lung, indicating a direct connection between mutations in CFTR and the clinical consequences of CF.     

Three dimensional numerical investigations for the effects of gas diffusion layer on PEM fuel cell performance

Gas diffusion layer (GDL) is an important component of a proton exchange membrane fuel cell (PEMFC) to take part in the interplay of the transport of different species. It has been found that the performance of a PEMFC depends upon the morphology of the GDL. The performance of PEM fuel cell varies with different porosity and thickness of the GDL. Hence, a three dimensional model is simulated to find out the effects of porosity and thickness of GDL on PEMFC performance using a commercial code CFD-ACE+. It was observed that high porosity gave high current density by allowing more reactants to reach the reaction site. Similarly greater thickness of the GDL gives reactant species to increase the consumption rate at the GDL/catalyst layer interface. The simulation results showed that the connection of bipolar plate with the GDL played an important role for reducing the amount of reactants to reach the catalyst layer especially under the land area of the bipolar plate. However, this effect seems to decrease with an increase of overall porosity and the thickness of the GDL.     

Synthesis and characterization of novel Pr6O11/Mn3O4 nanocomposites for electrochemical supercapacitors

This study presents the successful synthesis of praseodymium oxide, Pr₆O₁₁ and hausmannite manganese oxide, Mn₃O₄ nanoparticles, along with a novel synthesis of (Pr₆O₁₁/Mn₃O₄) nanocomposites by employing the hydrothermal route followed by post thermal annealing. X-ray Diffraction, Field Emission Scanning Electron Microscopy and Energy Dispersive X-ray characterization techniques are being adapted to analyze the physical characteristics of all the synthesized materials. XRD results reveal the crystalline nature of the synthesized materials. FE-SEM results display the irregular nanograins of Mn₃O₄ and a regular network of interconnected Pr₆O₁₁ nanoparticles. Nitrogen adsorption/desorption tests confirm the mesoporous nature of all the synthesized electrode materials. The Pr₆O₁₁/Mn₃O₄ ??2 electrode material exhibits an outstanding specific capacitance of 794.58?F/g at a current density of 0.5?A/g, as compared to the 521.24?F/g for the Pr₆O₁₁ electrode material. These investigations provide an easy and efficient method to develop nanocomposites (Pr₆O₁₁/Mn₃O₄) with better electrochemical characteristics, as electrode materials for supercapacitor applications.     

Monitoring Assisted Robust Routing in Wireless Mesh Networks

In this paper, we present a monitoring assisted robust routing scheme for wireless mesh networks which exploits the broadcast nature of wireless transmissions at special routers with added monitoring functionalities. These routers passively listen to the transmissions in their neighborhood and compare the routing behavior against the routing state collectively maintained by them. If any inconsistency is found, as a result of software/hardware malfunction, these routers try to determine the node causing it and recover from it in a timely fashion. The scheme is developed for wireless mesh networks where the communication overhead is a critical issue. The performance evaluation of our scheme shows considerable improvement in reliability (i.e., delivery ratio achieved by standard routing protocols) with minimal overhead under situations of malfunctions.     

Effect of helium xenon as working fluid on centrifugal compressor of power conversion unit of closed Brayton cycle power plant

Closed Brayton cycle (CBC) having single-shaft, centrifugal type compressor is considered as an efficient energy-conversion option associated for gas-cooled reactor (GCR) heat source. In terrestrial power plants and space power systems noble gases are considered as an efficient working fluid for most of the GCR's and CBC engines. The effectiveness of various noble gases as working fluid in closed cycle power plants for the power conversion units is of imperative concern. Although pure helium is relatively difficult to compress nonetheless it is measured as the best coolants for closed Brayton cycle power plants due to its better transport properties. Due to compression properties, its use resulted in the requirement of more mass, bigger size, higher cost and relatively more dynamic problems of rotatory machines in energy conversion system. The mixture of xenon with helium up to a molecular weight of <40 g/mol resulted in an increase of the coefficient of heat transfer as well as the significant increase in the loading of the compressor. Therefore, performance analysis is conducted for a novel design of helium xenon centrifugal compressor. The performance analysis is conducted with different molecular weight mixtures of helium xenon using similarity criteria. It is concluded that the use of helium xenon 40 g/mol is the optimum choice for space applications and 15 g/mol for closed Brayton cycle terrestrial power plants.     

Real-time mobility tracking algorithms for cellular networks based on Kalman filtering

We propose two algorithms for real-time tracking of the location and dynamic motion of a mobile station in a cellular network using the pilot signal strengths from neighboring base stations. The underlying mobility model is based on a dynamic linear system driven by a discrete command process that determines the mobile station's acceleration. The command process is modeled as a semi-Markov process over a finite set of acceleration levels. The first algorithm consists of an averaging filter for processing pilot signal, strength measurements and two Kalman filters, one to estimate the discrete command process and the other to estimate the mobility state. The second algorithm employs a single Kalman filter without prefiltering and is able to track a mobile station even when a limited set of pilot signal measurements is available. Both of the proposed tracking algorithms can be used to predict future mobility behavior, which can be, useful in resource allocation applications. Our numerical results show that the proposed tracking algorithms perform accurately over a wide range of mobility parameter values.     

A Novel Action Transformer Network for Hybrid Multimodal Sign Language Recognition

Sign language fills the communication gap for people with hearing and speaking ailments. It includes both visual modalities, manual gestures consisting of movements of hands, and non-manual gestures incorporating body movements including head, facial expressions, eyes, shoulder shrugging, etc. Previously both gestures have been detected; identifying separately may have better accuracy, but much communicational information is lost. A proper sign language mechanism is needed to detect manual and non-manual gestures to convey the appropriate detailed message to others. Our novel proposed system contributes as Sign Language Action Transformer Network (SLATN), localizing hand, body, and facial gestures in video sequences. Here we are expending a Transformer-style structural design as a “base network” to extract features from a spatiotemporal domain. The model impulsively learns to track individual persons and their action context in multiple frames. Furthermore, a “head network” emphasizes hand movement and facial expression simultaneously, which is often crucial to understanding sign language, using its attention mechanism for creating tight bounding boxes around classified gestures. The model’s work is later compared with the traditional identification methods of activity recognition. It not only works faster but achieves better accuracy as well. The model achieves overall 82.66% testing accuracy with a very considerable performance of computation with 94.13 Giga-Floating Point Operations per Second (G-FLOPS). Another contribution is a newly created dataset of Pakistan Sign Language for Manual and Non-Manual (PkSLMNM) gestures.