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.     

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.     

Selective Al-Ti reactivity in laser-processed Al/Ti multilayers

Multilayers consisting of five (Al/Ti) bilayers were deposited on (100) silicon wafers. On top was deposited the Ti layer, aimed at preventing Al from diffusing to the surface upon laser treatment. The total thickness of the thin-film structure was 200?nm. Laser irradiations with Nd:YAG picoseconds laser pulses in the defocused regime were performed in air. Laser beam energy was 4?mJ and laser spot diameter on the sample surface was 3?mm (fluence 0.057?J?cm^?2). The samples were treated with different numbers of laser pulses. Structural characterizations were performed by different analytical methods and nano-hardness was also measured. Laser processing induced layer intermixing, formation of titanium aluminides, oxidation of the surface titanium layer and enhanced surface roughness. Aluminum appears at the sample surface only for the highest density of laser irradiation. Laser processing induces increment of nano-hardness by approximately 20% and decrease of residual Young’s modulus for a few percentages from the starting value of the untreated samples. These results can be interesting toward achieving structures with a selective extent of Al-Ti reactivity in this multilayered system, within the development of biocompatible materials.     

Analysis of multi-agent activity using petri nets

This paper presents the use of place/transition petri nets (PNs) for the recognition and evaluation of complex multi-agent activities. The PNs were built automatically from the activity templates that are routinely used by experts to encode domain-specific knowledge. The PNs were built in such a way that they encoded the complex temporal relations between the individual activity actions. We extended the original PN formalism to handle the propagation of evidence using net tokens. The evaluation of the spatial and temporal properties of the actions was carried out using trajectory-based action detectors and probabilistic models of the action durations. The presented approach was evaluated using several examples of real basketball activities. The obtained experimental results suggest that this approach can be used to determine the type of activity that a team has performed as well as the stage at which the activity ended.     

Adaptive content-based music retrieval system

This paper presents a tunable content-based music retrieval (CBMR) system suitable the for retrieval of music audio clips. The audio clips are represented as extracted feature vectors. The CBMR system is expert-tunable by altering the feature space. The feature space is tuned according to the expert-specified similarity criteria expressed in terms of clusters of similar audio clips. The main goal of tuning the feature space is to improve retrieval performance, since some features may have more impact on perceived similarity than others. The tuning process utilizes our genetic algorithm. The R-tree index for efficient retrieval of audio clips is based on the clustering of feature vectors. For each cluster a minimal bounding rectangle (MBR) is formed, thus providing objects for indexing. Inserting new nodes into the R-tree is efficiently performed because of the chosen Quadratic Split algorithm. Our CBMR system implements the point query and the n-nearest neighbors query with the O(logn) time complexity. Different objective functions based on cluster similarity and dissimilarity measures are used for the genetic algorithm. We have found that all of them have similar impact on the retrieval performance in terms of precision and recall. The paper includes experimental results in measuring retrieval performance, reporting significant improvement over the untuned feature space.