Environmental applications of inorganic-organic clays for recalcitrant organic pollutants removal: Bisphenol A

Bisphenol-A (BPA) adsorption onto inorganic-organic clays (IOCs) was investigated. For this purpose, IOCs synthesised using octadecyltrimethylammonium bromide (ODTMA, organic modifier) and hydroxy aluminium (Al13, inorganic modifier) were used. Three intercalation methods were employed with varying ODTMA concentration in the synthesis of IOCs. Molecular interactions of clay surfaces with ODTMA and Al13 and their arrangements within the interlayers were determined using Fourier transform infrared spectroscopy (FTIR). Surface area and porous structure of IOCs were determined by applying Brunauer, Emmett, and Teller (BET) method to N2 adsorption-desorption isotherms. Surface area decreased upon ODTMA intercalation while it increased with Al13 pillaring. As a result, BET specific surface area of IOCs was considerably higher than those of organoclays. Initial concentration of BPA, contact time and adsorbent dose significantly affected BPA adsorption into IOCs. Pseudo-second order kinetics model is the best fit for BPA adsorption into IOCs. Both Langmuir and Freundlich adsorption isotherms were applicable for BPA adsorption (R2 > 0.91) for IOCs. Langmuir maximum adsorption capacity for IOCs was as high as 109.89 mg g‒1 and it was closely related to the loaded ODTMA amount into the clay. Hydrophobic interactions between long alkyl chains of ODTMA and BPA are responsible for BPA adsorption into IOCs.

The Systems Theory Framework of career development: Applications to career counselling and career assessment

Since its inception, the Systems Theory Framework of career development has afforded ready translation into practice, especially into career counselling and qualitative career assessment. Through its clearly articulated constructs and the clarity of its diagrammatic representation, the Systems Theory Framework has facilitated the development of qualitative career assessment instruments as well as a quantitative measure. This article briefly overviews these practical applications of the Systems Theory Framework as well as its application in career counselling through a story telling approach. The article concludes by offering a synthesis of and considering future directions for the Systems Theory Framework’s practical applications.

Predicting single-layer technetium dichalcogenides (TcX2, X = S, Se) with promising applications in photovoltaics and photocatalysis

One of the least known compounds among transition metal dichalcogenides (TMDCs) is the layered triclinic technetium dichalcogenides (TcX2, X = S, Se). In this work, we systematically study the structural, mechanical, electronic, and optical properties of TcS2 and TcSe2 monolayers based on density functional theory (DFT). We find that TcS2 and TcSe2 can be easily exfoliated in a monolayer form because their formation and cleavage energy are analogous to those of other experimentally realized TMDCs monolayer. By using a hybrid DFT functional, the TcS2 and TcSe2 monolayers are calculated to be indirect semiconductors with band gaps of 1.91 and 1.69 eV, respectively. However, bilayer TcS2 exhibits direct-bandgap character, and both TcS2 and TcSe2 monolayers can be tuned from semiconductor to metal under effective tensile/compressive strains. Calculations of visible light absorption indicate that 2D TcS2 and TcSe2 generally possess better capability of harvesting sunlight compared to single-layer MoS2 and ReSe2, implying their potential as excellent light-absorbers. Most interestingly, we have discovered that the TcSe2 monolayer is an excellent photocatalyst for splitting water into hydrogen due to the perfect fit of band edge positions with respect to the water reduction and oxidation potentials. Our predictions expand the two-dimensional (2D) family of TMDCs, and the remarkable electronic/optical properties of monolayer TcS2 and TcSe2 will place them among the most promising 2D TMDCs for renewable energy application in the future.

An investigation into the thermophysical and rheological properties of nanofluids for solar thermal applications

Considered to be the next generation of heat transfer fluids, nanofluids have been receiving a growing amount of attention in the past decade despite the controversy and inconsistencies that have been reported. Nanofluids have great potential in a wide range of fields, particularly for solar thermal applications. This paper presents a comprehensive review of the literature on the enhancements in thermophysical and rheological properties resulting from experimental works conducted on molten salt nanofluids that are used in solar thermal energy systems. It was found that an increase in specific heat of 10–30% was achieved for most nanofluids and appeared independent of particle size and to an extent mass concentration. The specific heat increase was attributed to the formation of nanostructures at the solid–liquid interface and it was also noted that the aggregation of nanoparticles has detrimental effects on the specific heat increase. Thermal conductivity was also found to increase, though less consistently, ranging from 3% to 35%. Viscosity was seen to increase with the addition of nanoparticles and is dependent on the amount of aggregation of the particles. An in-depth micro level analysis of the mechanisms behind the thermophysical property changes is presented in this paper. In addition, possible trends are discussed relating to current theorised mechanisms in an attempt to explain the behaviour of molten salt nanofluids.

Performance estimation of streaming applications for hierarchical MPSoCs

Parallel programming and effective partitioning of applications for embedded many-core architectures requires optimization algorithms. However, these algorithms have to quickly evaluate thousands of different partitions. We present a fast performance estimator embedded in a parallelizing compiler for streaming applications. The estimator combines a single execution-based simulation and an analytic approach. Experimental results demonstrate that the estimator has a mean error of 2.6% and computes its estimation 2848 times faster compared to a cycle accurate simulator.