Pin-on-Disc Testing of Low-Metallic Friction Material Sliding Against HVOF Coated Cast Iron: Modelling of the Contact Temperature Evolution

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A pin-on-disc study on the dry sliding behavior of a Cu-free friction material containing different types of natural graphite

Abstract This research investigates the influence of graphite's granulometry on the dry sliding behavior of a copper-free friction material against pearlitic cast iron. Samples were designed and fabricated using three different types of commercial natural graphite. A sample without graphite was also considered as a reference. Tests were carried out with a pin-on-disc tribometer at room temperature (RT), at 400 °C, and at RT after the high temperature tests. The results show that both the shape and size of the graphite particles influence the coefficient of friction and the specific wear rate. The friction material featuring a lower particle size and equiaxed grains of natural graphite exhibits a better behavior, as compared to coarser graphite with plate-like grains. The results were obtained comparing specific characteristics (i.e., morphology and chemical composition) of the friction layers formed on each friction material under the different testing conditions

friction wear and airborne particle emission from cu free brake materials

Abstract Cu is required to be abated in brake pads due to its toxicity. There are on the market several Cu-free brake pads. These Cu-free brake pads are only evaluated regarding their friction and wear performance, whereas, their airborne particle emissions are not considered. A pin-on-disc tribometer is used to evaluate the friction, wear and airborne particle emission from two Cu-free commercial brake pads used in the Europe. Moreover, a commercial brake pad containing Cu is evaluated as a reference. The results indicate that Cu-free brake pads yield comparable coefficient of friction as the Cu-contained brake pad. All three brake materials result in similar wear to the mating brake rotor. Cu-free brake pads generate more airborne particles than Cu-contained brake pad

The role of graphitic carbon nitride in the formulation of copper-free friction composites designed for automotive brake pads

In this study, graphitic carbon nitride (g-C3N4, labelled as gCN) was tested in the formulation of copper-free (Cu-free) friction mixtures, which are potentially interesting for brake pad manufacturing. Three formulations of friction composites were prepared starting from a common Cu-free master batch: (i) without graphite, (ii) with graphite and (iii) with gCN. The mixtures were pressed in the form of pins by hot-press moulding. The friction-wear performance of the prepared pins was investigated using a pin-on-disc (PoD) test at room temperature (RT), high temperature (HT) (400 degrees C) and, again, at room temperature (H-RT). The values of the friction coefficient (mu) for the composites with gCN (or graphite) were as follows: (i) RT test, mu(RT) = 0.52 (0.47); (ii) HT test, mu(HT) = 0.37 (0.37); (iii) RT after the HT tests, mu(H-RT) = 0.49 (0.39). With respect to wear resistance, the samples with graphite performed better than the samples without this solid lubricant. To the best of our knowledge, this is the first report regarding the evaluation of the role of gCN in friction composites designed for automotive brake lining applications. The results indicate the main role of gCN as a soft abrasive.Web of Science121art. no. 12

Photodegradation of Pollutants in Air: Enhanced Properties of Nano-TiO2Prepared by Ultrasound

Nanocrystalline TiO2samples were prepared by promoting the growth of a sol–gel precursor, in the presence of water, under continuous (CW), or pulsed (PW) ultrasound. All the samples turned out to be made of both anatase and brookite polymorphs. Pulsed US treatments determine an increase in the sample surface area and a decrease of the crystallite size, that is also accompanied by a more ordered crystalline structure and the samples appear to be more regular and can be considered to contain a relatively low concentration of lattice defects. These features result in a lower recombination rate between electrons and holes and, therefore, in a good photocatalytic performance toward the degradation of NOxin air. The continuous mode induces, instead, the formation of surface defects (two components are present in XPS Ti 2p3/2region) and consequently yields the best photocatalyst. The analysis of all the characterization data seems to suggest that the relevant parameter imposing the final features of the oxides is the ultrasound total energypervolume (Etot/V) and not the acoustic intensity or the pulsed/continuous mode

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Tradition and innovation between the Mesolithic and early Neolithic in the Adige Valley (northeast Italy). New data from a functional analysis of trapezes from the Gaban rock-shelter

The Neolithisation of the Northern Italy is particularly interesting since archaeological data show dynamics of interaction between the last hunters and the early farmers of the region. In this paper the authors present the results of use-wear and residues analyses carried out on an assemblage of trapezes from one of the key-sites of the Neolithisation in the Adige Valley: Gaban rockshelter. The functional data have been compared and discussed with other strands of archaeological evidence available for the region.Študij procesa neolitizacije v severni Italiji je zanimiv zato, ker arheološki podatki kažejo na dinamike interakcij med zadnjimi lovci in nabiralci ter prvimi poljedelci v regiji. V članku predstavimo rezultate analiz sledov uporabe in ostankov na trapezoidnih kamenih orodjih z enega ključnih najdišč v dolini Adiže: v spodmolu Gaban. Rezultate analiz primerjamo in analiziramo v kontekstu ostalih arheoloških podatkov v regiji

Cradle to Cradle:Architecture beyond LCA

The Cradle to Cradle (C2C) approach is based on the eco-efficiency in accordance with strategies of expansion, up-cycling and enhancement of products both in environmental and social terms. Being this method currently under development, it has been mainly tested in the industrial production cycle, while in the building sector clear guidelines for the application and exhaustive reference cases are still lacking. This paper presents and discusses the application of the C2C methodology to a test building, designed for research purposes, the ZEFiRe - Zero-Energy Fishfarming Research module