Nanolayer CrAlN/TiSiN coating designed for tribological applications

With the goal to produce a hard and tough coating intended for tribological applications, CrAlN/TiSiN nanolayer coating was prepared by alternative deposition of CrAlN and TiSiN layers. In the first part of the article, a detailed study of phase composition, microstructure, and layer structure of CrAlN/TiSiN coating is presented. In the second part, its mechanical properties, fracture and tribological behavior are compared to the nanocomposite TiSiN coating. An industrial magnetron sputtering unit was used for coating deposition. X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy were used for compositional and microstructural analysis. Mechanical properties and fracture behavior were studied by instrumented indentation and focused ion beam techniques. Tribological properties were evaluated by ball-on-disk test in a linear reciprocal mode. A complex layer structure was found in the nanolayer coating. The TiSiN layers were epitaxially stabilized inside the coating which led to formation of dislocations at interfaces, to introduction of disturbances in the coating growth, and as a result, to development of fine-grained columnar microstructure. Indentation load required for the onset of fracture was twice lower for the nanolayer CrAlN/TiSiN, compared to the nanocomposite TiSiN coating. This agrees very well with their mechanical properties, with H³/E² being twice higher for the TiSiN coating. However, the nanolayer coating experienced less severe damage, which had a strong impact on tribological behavior. A magnitude of order lower wear rate and four times lower steady state friction coefficient were found for the nanolayer coating.     

Use of the Retarded Solution-Reprecipitation Process to Attain a Higher Initial Permeability in MnZn Ferrites

We investigated the effect of various amounts of liquid phase on microstructure development during sintering and the resulting magnetic permeability of MnZn ferrite (MZF) samples. Our results revealed that the microstructure and the final magnetic permeability depend on the thickness of the liquid-phase film during sintering. The solution-reprecipitation (S-R) process, which is associated with an intensive microstructure development in MZF, starts when a continuous liquid-phase film of critical thickness δ_o, which wets the MZF grains, is formed. The solid-state sintering that takes place before the formation of the continuous liquid-phase film is essential for the final microstructure of MZF.     

Prediction of the natural gas consumption in chemical processing facilities with genetic programming

Cinkarna Ltd. is a chemical processing company in Slovenia and the country’s largest manufacturer of titanium oxides (TiO₂). Chemical processing and titanium oxide manufacturing in particular requires high natural gas consumption, and it is difficult to accurately pre-order gas from suppliers. In accordance with the Energy Agency of the Republic of Slovenia regulations, each natural gas supplier regulates and determines the charges for the differences between the ordered (predicted) and the actually supplied quantities of natural gas. Yearly charges for these differences total 1.11 % of supplied natural gas costs (average 50,960 EUR per year). This paper presents natural gas consumption prediction and the minimization of associated costs. The data on daily temperature, steam boilers, sulfur acid and TiO₂ production was collected from January 2012 until November 2014. Based on the collected data, a linear regression and a genetic programming model were developed. Compared to the specialist’s prediction of natural gas consumption, the linear regression and genetic programming models reduce the charges for the differences between the ordered and the actually supplied quantities by 3.00 and 5.30 times, respectively. Also, from January until November 2014 the same genetic programming model was used in practice. The results show that in a similar gas consumption regime the differences between the ordered and the actually supplied quantities are statistically significant, namely, they are 3.19 times lower (t test, p < 0.05) than in the period in which the specialist responsible for natural gas consumption made the predictions.     

Modelling the scatter of E–N curves using a serial hybrid neural network

If structural reliability is estimated by following a strain-based approach, a material’s strength should be represented by the scatter of the ε–N (E–N) curves that link the strain amplitude with the corresponding statistical distribution of the number of cycles-to-failure. The basic shape of the ε–N curve is usually modelled by the Coffin–Manson relationship. If a loading mean level also needs to be considered, the original Coffin–Manson relationship is modified to account for the non-zero mean level of the loading, which can be achieved by using a Smith–Watson–Topper modification of the original Coffin–Manson relationship. In this paper, a methodology for estimating the dependence of the statistical distribution of the number of cycles-to-failure on the Smith–Watson–Topper modification is presented. The statistical distribution of the number of cycles-to-failure was modelled with a two-parametric Weibull probability density function. The core of the presented methodology is represented by a multilayer perceptron neural network combined with the Weibull probability density function using a size parameter that follows the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology and its application in the case of experimental fatigue data. The results show that it is possible to model ε–N curves and their scatter for different influential parameters, such as the specimen’s diameter and the testing temperature.     

Relationship between the Undrained Shear Strength, Water Content, and Mineralogical Properties of Fine-Grained Soils

The relationship between the undrained shear strength of fine-grained soils and the water content can be described with a nonlinear function in which the type of soil is determined by two parameters. It is well known that these parameters depend mainly on the mineral compositions of soils; these relationships, however, have not yet been investigated. The findings described in this paper define those mineralogical properties of soils which determine the values of both parameters. Experimentally obtained results suggest that the parameters primarily depend on the size of the clay minerals, their quantity in soil composition, and the interlayer water quantity in the expanding clay minerals. As this dependence is well defined, the parameters, and thus the undrained shear strength at different water content, can be defined from knowledge of these mineralogical soil properties.     

Layout design of manufacturable quantum-dot cellular automata

Quantum-dot cellular automaton (QCA) is an emergent technology that is not hindered by quantum effects that limit the scaling of CMOS technology, but instead employs them to perform computation. However, this brings its own impediments, such as the influence of the thermodynamic effects. Beside that, QCA has to be coupled with CMOS circuitry of different size features to enable clocking. We discussed all these facts and devised a floorplan which would facilitate manufacturability. Based on it we developed the process of QCA layout design and defined the design rules that must be considered in order to ensure correct operation. These instructions enable the automatization of designing a QCA circuit layout.     

Distributed biological computation: from oscillators,logic gates and switches to a multicellular processor and neural computing applications

Neural Computing and Applications - Ever since its foundational years, synthetic biology has been focused on the implementation of biological computing structures. In the beginning, engineered...     

The Low‐Temperature Cosintering of Cobalt Ferrite and Lead Zirconate Titanate Ceramic Composites

Magneto‐electric (ME) ceramic composites of cobalt ferrite (CoF) and lead zirconate titanate (PZT) were prepared by mechanical mixing of the constituent powders followed by cosintering. The cosintering conditions for nano‐sized CoF and submicrometer‐sized PZT powders were studied in detail. It was found that the CoF powder needs to be presintered at 700°C for 2 h to minimize the differences in the sintering kinetics of the constituent powders. Despite the low cosintering temperatures (900°C–1000°C) the interdiffusion of the cations from both phases was confirmed with energy‐dispersive X‐ray analysis and X‐ray diffraction. Efforts were made to optimize the cosintering conditions to prepare dense ceramic ME composites, which showed the converse ME effect.