In this study, novel ultrafiltration membranes were prepared via blending cobalt-substituted aluminophosphate (CoAPO-5) plate-like crystal aggregates into polyethersulfone membranes to enhance membrane selectivity for the separation of bovine serum albumin from water. The proposed rejection mechanism is based on size exclusion, formation of hydration layer, and electrostatic interactions exhibited by the composite membranes upon doping with CoAPO-5.
Leonardo da Vinci commented, "water is the driving force of all nature". Freshwater scarcity is increasingly perceived as a global systemic risk. Recently, atmospheric water harvesting (AWH) becomes a promising strategy for decentralized water production. This work aims to design and prepare novel hybrid sorbents to be used for water vapor harvesting under various weather conditions. Synthesis of aluminophosphate (AlPO)-based composites and characterization were carried out to test material properties, stability, and compatibility. Essential benefits are targeted from the developed composites, namely, efficient operation within broad RH% and high capacity. Also, the incorporation of AlPO particles within sodium alginate and polyacrylamide improved the thermal stability of the latter. These properties make these hybrids a promising candidate in future AWH systems.
Vast amount of dye-containing wastewaters from many industries need careful treatment. The adsorption kinetics of methyl orange (MO, an azo dye) on a waste cellulose-derived mesoporous carbon was investigated for application. Simulation results revealed that adsorption kinetics can be well simulated/predicted using the pseudo-second order (PSO) model. Single-staged and two-staged batch adsorbers were designed using experimental data with optimal adsorption times for achieving various removal efficiencies. The results are important in treatment of such wastewaters and can be used in practical design and operations.
Hydrogen is considered the simplest element in existence and one of the most abundant in the earth found as part of another substance, such as water and hydrocarbon. Though of its simple structure, it has the highest energy content of any common fuel by weight. In near future, due to its excessive energy content, it may become one of the most environmentally friendly automobile fuels. Most oil and gas reservoirs in the United Arab Emirates (UAE) are sour, enriched with a high amount of hydrogen sulfide (H2S) and sulfur species. The conversion of H2S into H2 and Sulfur is beneficial from both environmental and energy perspectives. The two-step thermochemical decomposition of H2S is considered as one of the most promising technologies for Hydrogen production. This paper investigates the chemical kinetics of the two-step Thermochemical decomposition of H2S using Nickel Sulfide.
This paper describes the modelling of external corrosion of an underground pipeline. Pitting corrosion and Stress Corrosion Cracking are two of the most common external corrosion types for buried pipeline and they usually happen when corrosion protection methods fail or deteriorate. Pitting corrosion is a localized corrosion that occurs at local sites with no coating or cathodic protection as a results of electrochemical reaction between the pipeline material and the corrosion environment. A finite element model was developed using COMSOL Multiphysics to study the effect of the stress at the corrosion defect on the corrosion growth rate.
In the efforts to combat the increase in the excess emissions of anthropogenic CO2, CCS technologies such as solid sorbents for CO2 capture have been explored. Activated carbon is considered one of the most promising adsorbents due to its many advantages, such as its good thermal stability and excellent adsorption capacity. Activated carbons prepared from date seeds agricultural biomass have already been developed and are used in many industrial applications. However, there is not much research that explored their potential for CO2 capture applications. This study reports the preparation of chemically activated Activated carbon (AC) using KOH. Different impregnation ratios and activation temperatures were studied to find the best preparation combination for high CO2 capture capacity. At the optimized impregnation ratio of 2.5:1 and activation temperature of 600 ?C, the produced AC had the highest adsorption capacity of 2.18 mmol/g and BET surface area of 1033.09 m2/g.
The high theoretical capacity of lithium oxygen batteries (LOBs) made them an attractive target for extensive research over the past two decades. However, major issues related to battery performance need to be addressed before the wide deployment of this technology. One major source of enhancement would be in the air electrode. This research focuses on developing carbon-based air electrodes with optimized textural properties and enhanced catalytic performance. The work will take into consideration the carbon structure design and the catalyst type, loading amount and distribution on the carbon surface. The effect of the interactions of the carbon and the catalyst on the discharge/charge reactions will be studied through galvanostatic discharge-charge measurements, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and other characterization techniques. The proposed electrode is expected to facilitate the electrochemical reactions during the discharge and charge of the battery, reduce overpotential, and increase battery capacity and cyclability.
Since zeolites have been used for cracking for decades, this work aims to produce hierarchical faujasite with the house of cards morphology to be used for FCC through extensive synthesis methods. These zeolites will have better reaction rates, selectivity and a unique adsorption behavior as compared to conventional zeolites used for cracking. Faujasite has only been synthesized in zeolite X with Si/Al ratio less than 1.5, here for the first time the synthesis of zeolite Y with the house of cards morphology will be approached through direct synthesis for catalytic usage. The best Si/Al ratio achieved is 1.36 showing that it is theoretically possible to keep increasing the Si/Al ratio and achieve zeolite Y.
Colorectal Cancer (CRC) is a leading cause of death around the globe, and therefore, the analysis of tumor microenvironment in the CRC WSIs is important for the early detection of CRC. We propose to employ the hypergraph neural network to classify seven different CRC tissue types. Firstly, image deep features are extracted from input patches using the pre-trained VGG19 model. The hypergraph is then constructed whereby patch-level deep features represent the vertices of a hypergraph and hyperedges are assigned using pair-wise euclidean distance. The edges, vertices, and their corresponding patch-level features are passed through a feed-forward neural network to perform tissue classification in a transductive manner. Experiments are performed on an independent CRC tissue classification dataset and compared with existing state-of-the-art methods. Our results reveal that the proposed algorithm outperforms existing methods by achieving an overall accuracy of 95.46% and AvTP of 94.42%.
In recent years, vision-driven robotic grasping has seen widespread use in academia and industry due to its compatibility with contextualized tasks and its sensitivity to object geometries. In this paper, we assume that an event-driven, neuromorphic camera is used and that the mean-shift algorithm is applied to segment the visual field and identify objects. Compared with standard machine vision, the neuromorphic approach has the advantages of low latency, low power consumption, and high dynamic range. In this paper, we address the problem of accelerating meanshift clustering for neuromorphic vision by proposing a novel parallel implementation on an edge computing platform. The platform used is the recently released Jetson Nano GPU from NVIDIA. The proposed GPU parallel implementation is evaluated in comparison to a CPU sequential algorithm running on the same platform, which shows approximately 100 times faster than its sequential counterpart on a set of neuromporphic data sequences.
