Intermetallics as advanced cathode materials in hydrogen production via electrolysis

Intermetallics phases along Mo–Pt phase diagram have been investigated as cathode materials for the production of hydrogen by electrolysis from water KOH solutions, in an attempt to increase the electrolytic process efficiency. These materials were compared with conventional cathodes (Fe and Ni), often used in the alkaline electrolysis, and also with the intermetallic Ti–Pt. An significant upgrade of the electrolytic efficiency using intermetallics in pure KOH electrolyte was achieved in comparison with conventional cathode materials.     

Improving bulk FinFET DC performance in comparison to SOI FinFET

The implementation of FinFET structure in bulk silicon wafers is very attractive due to low-cost technology and compatibility with standard bulk CMOS in comparison with silicon-on-insulator (SOI) FinFET. SOI and bulk FinFET were analyzed by a three-dimensional numerical device simulator. We have shown that bulk FinFET with source/drain-to-body (S/D) junctions shallower than gate-bottom has equal or better subthreshold performance than SOI FinFET. By reducing S/D junction depth, fin width scaling for suppression of short-channel-effects (SCEs) can be relaxed. On-state performance has also been examined and drain current difference between the SOI and bulk FinFET at higher body doping levels has been explained by investigating enhanced conduction in silicon-oxide interface corners. By keeping the body doping low and junctions shallower than the gate-bottom, bulk FinFET characteristics can be improved with no increase in process complexity and cost.     

A comparison of machine learning methods for cutting parameters prediction in high speed turning process

Support vector machines are arguably one of the most successful methods for data classification, but when using them in regression problems, literature suggests that their performance is no longer state-of-the-art. This paper compares performances of three machine learning methods for the prediction of independent output cutting parameters in a high speed turning process. Observed parameters were the surface roughness (Ra), cutting force \((F_{c})\), and tool lifetime (T). For the modelling, support vector regression (SVR), polynomial (quadratic) regression, and artificial neural network (ANN) were used. In this research, polynomial regression has outperformed SVR and ANN in the case of \(F_{c}\) and Ra prediction, while ANN had the best performance in the case of T, but also the worst performance in the case of \(F_{c}\) and Ra. The study has also shown that in SVR, the polynomial kernel has outperformed linear kernel and RBF kernel. In addition, there was no significant difference in performance between SVR and polynomial regression for prediction of all three output machining parameters.     

The effect of fusing Sentinel-2 bands on land-cover classification

The Sentinel-2 satellite currently provides freely available multispectral bands at relatively high spatial resolution but does not acquire the panchromatic band. To improve the resolution of 20 m bands to 10 m, existing pansharpening methods (Brovey transform [BT], intensity–hue–saturation [IHS], principal component analysis [PCA], the variational method [P + XS], and the wavelet method) required adjustment, which was achieved using higher resolution multispectral bands in the role of a panchromatic band to fuse bands at a lower spatial resolution. After preprocessing, six bands at lower resolution were divided into two groups because some image fusion methods (e.g. BT, IHS) are limited to a maximum of three input bands of a lower resolution at a time. With respect to the spectral range, the higher resolution band for the first group was synthesized from bands 4 and 8, and band 8 was selected for the second group. Given that one of the main remote sensing applications is land-cover classification, the classification accuracy of the fusion methods was assessed as well as the comparison with reference bands and pixels. The supervised classification methods were Maximum Likelihood Classifier, artificial neural networks, and object-based image analysis. The classification scheme contained five classes: water, built-up, bare soil, low vegetation, and forest. The results showed that most of the fusion methods, particularly P + XS and PCA, improved the overall classification accuracy, especially for the classes of forest, low vegetation, and bare soil and in the detection of coastlines. The least satisfying results were obtained from the wavelet method.     

State equation of mineral sands

The pressure-volume analogy between compressible fluids and macroscopic sand bodies (Ivsic et al. in Phys A, 277:47–61, 2000) is further extended using quantitative determination of corresponding empirical constants based on adapted van der Waals state equation. The isothermal constants obtained by interpretation of triaxial sand tests at so called “critical state of sand” are clearly related to the universal ideal gas properties and molar properties of mineral sands. The corresponding constants for sand and gases or other volatile liquids have the same order of magnitude. The apparent bulk repulsion/attraction effects in sand bodies are also discussed.     

Reduction of Postharvest Decay of Peach and Nectarine Caused by Monilinia laxa Using Hot Water Dipping

The effect of hot water dipping (HWD) at 40, 44 and 48 °C for 6 and 12 min on germination of conidia of brown rot fungus (Monilinia laxa) in vitro and the effect of HWD at 48 °C for 6 and 12 min on the fruit quality and development of M. laxa on peach cv. “Roig” and nectarine cv. “Venus” after artificial inoculation in cold storage were studied. Temperature and duration of treatment significantly affected germination of conidia. After HWD at 48 °C for 12 min, the lowest germination of conidia (9%) was recorded, which was more than 10 times lower than control (93%). After 3 days from inoculation, there were 80% of inoculated spots with visual symptoms of decay caused by M. laxa on control peaches and 40% of such spots on control nectarines. Successful infections were recorded on only 5% of inoculated spots of nectarine and 10% of inoculated spots of peach after HWD at 48 °C for 12 min. HWD at 48 °C for 12 min significantly decreased titratable acidity and increased soluble solids concentration/titratable acidity ratio in nectarines. No visual symptoms of heat damage were found on fruits as a consequence of any of the studied treatments. The results show that it is possible to control postharvest brown rot (M. laxa) on peach using HWD at 48 °C for 12 min and on nectarine using HWD at 48 °C for 6 min without a significant loss of fruit quality.     

Mixed meshless formulation for analysis of shell-like structures

An efficient mixed meshless computational method based on the Local Petrov–Galerkin approach for analysis of plate and shell structures is presented. A concept of a three-dimensional solid is applied allowing the use of complete three-dimensional constitutive equations, and exact shell geometry can be described. Discretization is carried out by using both the moving least square approximation and the polynomial functions. Independent field variables are the strain and stress tensor components expressed in terms of the nodal values, which are then replaced by the nodal displacements by using the independent displacement interpolation. A closed global system of equations with only nodal displacements as unknown variables is derived. The undesired locking phenomena are fully suppressed. The proposed mixed formulation is numerically more efficient than the available meshless fully displacement approach, as demonstrated by the numerical examples.     

Revisiting the Ziegler–Nichols process dynamics characterization

The Ziegler–Nichols process dynamics characterization is based on the estimation of the ultimate gain k_u and ultimate frequency ω_u. The angle φ of the tangent to the Nyquist curve at the frequency ω_u is introduced, as an additional parameter in the frequency domain. The essential dynamic characteristics of the process can be captured by using the tangent rule, proposed here as an extension of the Ziegler–Nichols approach. The validity of the tangent rule is confirmed by using the PID controller optimization on a test batch consisting of stable, integrating and unstable processes, including dead-time. Parameters k_u, ω_u and φ can be determined from the sustained oscillations, using the phase-locked loop identifier module.