Modeling of the Magnetization and Magnetocaloric Effect in Ni2MnGa Heusler Alloy with the Effective Field Theory

Journal of Low Temperature Physics - This study modeled and investigated the magnetocaloric effect in Ni2MnGa Heusler alloy characterized by its magnetic entropy change (ΔSm) and its...     

Resistive organic memory devices based on nitrogen-doped CNTs/PSS composites

Journal of Materials Science: Materials in Electronics - Non-volatile organic memory devices were fabricated using polystyrene sulfonate (PSS)?+?nitrogen-doped multi-walled carbon...     

Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.     

Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...     

Intermetallic and dispersoid structures in aa3104 Aluminum alloy during two-step homogenisation

During homogenisation of the AA3104 cast ingot, a phase transformation of intermetallic particles from β-Al₆(Fe,Mn) orthorhombic phase to harder α-Al_x(Fe,Mn)₃Si₂ cubic phase occurs. The large constituent intermetallic particles, regardless of phase, assist in the recrystallisation nucleation process through particle stimulated nucleation (PSN). Ultimately, this helps to refine grain size. The sub-micron dispersoids act to impede grain boundary migration through a Zener drag mechanism. For this reason, the dispersoids that form during homogenisation are critical in the recrystallisation kinetics during subsequent rolling, with smaller dispersoids being better suited to reverse rolling mills. This work simulates an industrial two-step homogenisation practice with variations in the peak temperature of the first step between 560 °C and 580 °C. The effect of this temperature variation on the intermetallic particle-phase evolution is investigated. The aim is to identify the ideal intermetallic phase balance and the dispersoid structure that are best suited for hot rolling on a single stand reversing mill, in order to minimise recrystallisation during rolling through maximising Zener drag and maintaining galling resistance. The results indicate a trend where an increase in homogenisation temperature from 560 °C to 580 °C yields, firstly, an increase in the volume fraction of the α-phase particles to greater than 50% of the total volume fraction at both the edge and the center of the ingot and, secondly, it yields an increased dispersoid size. Thus, in the context of a reverse rolling operation, a lower temperature homogenisation practice produces a near-ideal combination of intermetallic particle-phase distribution, as well as dispersoid size, which is critical for Zener drag and the minimization of recrystallisation during the hot rolling processes.

Graphical abstract

SEM BEI images and corresponding EDS maps, highlighting the variation in intermetallic particle phase balance, size and morphology after homogenisation at different temperatures. With a focus on the exaggerated differences seen between material the center of and at the edge of a DC cast ingot of AA3104 Aluminum alloy.

     

Strength assessment of Al2O3 and MgAl2O4 using micro- and macro-scale biaxial tests

Journal of Materials Science - The application of ceramics in advanced functional applications often requires thicknesses below a few hundred micrometers, rendering an assessment of the...     

Pursuit Problem for Fractional Differential Systems with Pure Delay

Cybernetics and Systems Analysis - The pursuit problem for linear fractional differential systems with pure delay is considered. A scheme of the method of resolving functions for these...     

Assessment of technological attributes of autochthonous starter cultures in Turkish dry fermented sausage (sucuk)

The study aims to evaluate the technological properties of autochthonous strains (Lactobacillus sakei S15, Lactobacillus plantarum S24, L. plantarum S91, Pediococcus pentosaceus S128b and Staphylococcus carnosus G109) in Turkish dry fermented sausage (sucuk). After 24 h of fermentaPtion, all lactic acid bacteria strains reduced the pH to below 5.0, while the pH in the control group was above 5.3. The number of lactic acid bacteria strains reached 10⁸–10⁹ cfu g⁻¹ during fermentation. Staphylococcus carnosus G109 remained at the inoculation level of 10⁶ cfu g⁻¹ during ripening. Lactobacillus sakei S15 as mono-culture showed higher TBARS values compared to other strains. The control group had the lowest L* value and autochthonous strains caused no significant difference for a* value. According to principal component analysis results, most volatile compounds were positively correlated with the group containing only L. sakei S15.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.