Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu_1-xDy_xO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu_1-xDy_xO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm^?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm^?2 and relatively high current density of 66 mAcm^?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm^?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.     

Optimization of flow in additively manufactured porous columns with graded permeability

Chemical engineering systems often involve a functional porous medium, such as in catalyzed reactive flows, fluid purifiers, and chromatographic separations. Ideally, the flow rates throughout the porous medium are uniform, and all portions of the medium contribute efficiently to its function. The permeability is a property of a porous medium that depends on pore geometry and relates flow rate to pressure drop. Additive manufacturing techniques raise the possibilities that permeability can be arbitrarily specified in three dimensions, and that a broader range of permeabilities can be achieved than by traditional manufacturing methods. Using numerical optimization methods, we show that designs with spatially varying permeability can achieve greater flow uniformity than designs with uniform permeability. We consider geometries involving hemispherical regions that distribute flow, as in many glass chromatography columns. By several measures, significant improvements in flow uniformity can be obtained by modifying permeability only near the inlet and outlet.     

Molecular structure and granule morphology of native and heat‐moisture‐treated pinhão starch

Pinhão seed is an unconventional source of starch and the pines grow up in native forests of southern Latin America. In this study, pinhão starch was adjusted at 15, 20 and 25% moisture content and heated to 100, 110 and 120 °C for 1 h. A decrease in λ max (starch/iodine complex) was observed as a result of increase in temperature and moisture content of HMT. The ratio of crystalline to amorphous phase in pinhão starch was determined via Fourier transform infra red by taking 1045/1022 band ratio. A decrease in crystallinity occurred as a result of HMT. Polarised light microscopy indicated a loss of birefringence of starch granules under 120 °C at 25% moisture content. Granule size distribution was further confirmed via scanning electron microscopy which showed the HMT effects. These results increased the understanding on molecular and structural properties of HMT pinhão starch and broadened its food and nonfood industrial applications.     

Characterizing physical habitat preferences and thermal refuge occupancy of brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) at high river temperatures

Anthropogenic influences, including climate change, are increasing river temperatures in northern and temperate regions and threatening the thermal habitats of native salmonids. When river temperatures exceed the tolerance levels of brook trout and Atlantic salmon, individuals exhibit behavioural thermoregulation by seeking out cold‐water refugia – often created by tributaries and groundwater discharge. Thermal infrared (TIR) imagery was used to map cold‐water anomalies along a 53 km reach of the Cains River, New Brunswick. Trout and salmon parr did not use all identified thermal anomalies as refugia during higher river temperature periods (>21°C). Most small‐bodied trout (8–30 cm) were observed in 80% of the thermal anomalies sampled. Large‐bodied trout (>35 cm) required a more specific set of physical habitat conditions for suitable refugia, that is, 100% of observed large trout used 30% of the anomalies sampled and required water depths >65 cm within or adjacent to the anomaly. Densities of trout were significantly higher within anomalies compared with areas of ambient river temperature. Salmon parr were less aligned with thermal anomalies at the observed temperatures, that is, 59% were found in 65% of the sampled anomalies; and densities were not significantly different within/ outside anomalies. Salmon parr appeared to aggregate at 27°C, and after several events over 27°C variability in aggregation behaviour was observed – some fish aggregated at 25°C, others did not. We stipulate this is due to variances of thermal fatigue. Habitat suitability curves were developed for velocity, temperature, depth, substrate, and deep water availability to characterize conditions preferred by fish during high‐temperature events. These findings are useful for managers as our climate warms, and can potentially be used as a tool to help conserve and enhance thermal refugia for brook trout and Atlantic salmon in similar systems.     

Drift hole mobility in strained and unstrained doped Si1-xGex alloys

Results of the drift hole mobility in strained and unstrained SiGe alloys are reported for Ge fractions varying from 0 to 30% and doping levels of 10¹⁵-10¹⁹ cm^-3. The mobilities are calculated taking into account acoustic, optical, alloy, and ionized-impurity scattering. The mobilities are then compared with experimental results for a boron doping concentration of 2×10¹⁹ cm^-3. Good agreement between experimental and theoretical values is obtained. The results show an increase in the mobility relative to that of silicon     

Modeling ion implantation of HgCdTe

Ion implantation of boron is used to create n on p photodiodes in vacancy-doped mercury cadmium telluride (MC.T). The junction is formed by Hg interstitials from the implant damage region diffusing into the MC.T and annihilating Hg vacancies. The resultant doping profile is n⁺/n^-/p, where the n⁺ region is near the surface and roughly coincides with the implant damage, the n^- region is where Hg vacancies have been annihilated revealing a residual grown-in donor, and the p region remains doped by Hg vacancy double acceptors. We have recently developed a new process modeling tool for simulating junction formation in MC.T by ion implantation. The interstitial source in the damage region is represented by stored interstitials whose distribution depends on the implant dose. These interstitials are released into the bulk at a constant, user defined rate. Once released, they diffuse away from the damage region and annihilate any Hg vacancies they encounter. In this paper, we present results of simulations using this tool and show how it can be used to quantitatively analyze the effects of variations in processing conditions, including implant dose, annealing temperature, and doping background.     

The use of residuals in statistical modeling for fatigue-crackgrowth under constant amplitude loading

Various models have been proposed over the years to fit crack growth data. Many papers have appeared in which one or more models are mooted and fitted, and various assessments made of the quality of the fit. At the basic level the data are plotted, together with the fitted curve, to show agreement of experimental and predicted values. In this paper we suggest that it can be useful and informative to go one step further, examining the residuals, i.e., the differences between the experimental and predicted values. We draw attention to certain statistical methods for such critical assessment and show by example that this can reveal deficiencies in fit not otherwise obvious. In this way suitable modifications to the model can be suggested. Additional plots of estimated parameters are also shown to be informative about models