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.     

A survey of nitrate and nitrite content of fruit and vegetables grown in Slovenia during 1996-2002

Monitoring of nitrate (NO₃^-) and nitrite (NO₂^-) content in agricultural products in Slovenia has been carried out since 1996. The results of monitoring over the period 1996-2002 are presented. During this time 924 samples of 14 different agricultural products (potato, lettuce, apples, carrot, silage maize, cabbage, grapes, peaches, string beans, cereals, pears, cucumbers, strawberries and tomato) were analysed. The samples were taken at the time of maturity directly from growing sites and they were analysed using segmented flow analysis. The average nitrate contents were the highest in lettuce (1074 mg kg^-1), cabbage (881 mg kg^-1), string beans (298 mg kg^-1) and carrot (264 mg kg^-1), and they were moderately high in potato (158 mg kg^-1), silage maize (122 mg kg^-1), strawberries (94 mg kg^-1), cucumbers (93 mg kg^-1) and cereals (49 mg kg^-1). Low nitrate contents (below 6 mg kg^-1) were found in fruit (grapes, peaches, apples and pears) and tomato. With the exception of cereals (8.9 mg kg^-1), apples (1.5 mg kg^-1), potato (1.2 mg kg^-1) and pears (1.0 mg kg^-1) the content of nitrites did not exceed 0.5 mg kg^-1. It may be concluded that the results of the monitoring were in most cases similar to the results of investigations obtained in other countries.     

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.     

A large-displacement 65Pb(Mg1/3Nb2/3)O3–35PbTiO3/Pt bimorph actuator prepared by screen printing

In this paper we present a novel approach to preparing large-displacement 65Pb(Mg_1/3Nb_2/3)O₃–35PbTiO₃/Pt (65/35 PMN–PT/Pt) bimorph actuators. These “substrate-free”, bending-type actuators were prepared by screen-printing the 65/35 PMN–PT and Pt thick-film pastes as the electrodes on alumina substrates. After this screen printing and the subsequent firing the 65/35 PMN–PT/Pt composites were peeled off from the substrates. Displacements of nearly 100 μm at 18 V were achieved for actuators with dimensions of 1.8 cm × 2.5 mm × 50 μm for the 65/35 PMN–PT layer. The normalized displacement (the displacement per unit length) was 40 μm/cm at 18 V. The experimental results together with a computation procedure were used to obtain the material parameters for a finite-element analysis of the 65/35 PMN–PT/Pt bimorph actuators.     

Influence of Particle Size Distribution,Moisture Content,and Particle Shape on the Flow Properties of Bulk Solids

Abstract

There has been a great deal of research on characterising bulk solids. However, some of the characteristics, particularly the time‐dependent and random changes of properties, still remain insufficiently understood. The focus of this article is to study the influence of particle size, size distribution, moisture content, and particle shape on the unconfined yield strength of bulk solids. We present some interesting results about the influence of the particle size distribution on the unconfined yield strength of a bulk solid and a new method for determining the influence of particle shape on the unconfined yield strength of a bulk solid, which was made possible by the design and use of a novel attritor.     

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.     

Permutation routing in double-loop networks: design and empirical evaluation

A double-loop network is an undirected graph whose nodes are integers 0,1,…,n−1 and each node u is adjacent to four nodes u±h₁(mod>n), u±h₂(mod>n), where 0<h₁<h₂<n/2. There are initially n packets, one at each of the n nodes. The packet at node u is destined to node π(u), where the mapping uπ(u) is a permutation. The aim is to minimize the number of routing steps to route all the packets to their destinations. If ℓ is the tight lower bound for this number, then the best known permutation routing algorithm takes, on average, 1.98ℓ routing steps (and 2ℓ routing steps in the worst-case).Because the worst-case complexity cannot be improved, we design four new static permutation routing algorithms with gradually improved average-case performances, which are 1.37ℓ, 1.35ℓ, 1.18ℓ, and 1.12ℓ. Thus, the best of these algorithms exceeds the optimal routing by at most 12% on average.To support our algorithm design we develop a program which simulates permutation routing in a network according to the given topology, routing model as well as communication pattern and measure several quality criteria. We have tested our algorithms on a large number of double-loop networks and permutations (randomly generated and standard).