In recent years, there has been growing concern regarding the use of petroleum-based lubricants. This concern has generated interest in readily biodegradable fluids such as vegetable oils. The present work evaluated the rheological and tribological characteristics of sunflower oil modified with silicon dioxide (SiO2) and titanium dioxide (TiO2) nanoparticles as lubricant additives at different concentrations. A parallel plate rheometer was used to evaluate the effects of concentration and shear rate on the shear viscosity, and the experimental data was compared with conventional models. The wear protection and friction characteristics of the oil-formulations were evaluated by conducting block-on-ring sliding tests. Surface analysis-based instruments, including scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and profilometry, were used to characterize the morphology and structure of the worn surfaces. The experimental results showed that the coefficient of friction decreased with the addition of SiO2 and TiO2 nanoparticles by 77.7% and 93.7%, respectively when compared to base sunflower oil. Furthermore, the volume loss was lowered by 74.1% and 70.1%, with the addition of SiO2 and TiO2 nanoparticles, respectively. Based on the experimental results, the authors conclude that modified sunflower oil enhanced with nanoparticles has the potential for use as a good biodegradable lubricant.

No abstract

No abstract

Cocoa beans are the most important raw material for the chocolate industry and an essential product for the economy of tropical countries such as Colombia. Their price mainly depends on their quality, which is determined by various aspects, such as good agricultural practices, their harvest point, and level of fermentation. The entities that regulate the international marketing of cocoa beans have been encouraging the development of new classification methods that, compared to current techniques, could save time, reduce waste, and increase the number of evaluated beans. In particular, hyperspectral images are a novel tool for food quality control. However, studies that have examined some quality parameters of cocoa using spectroscopy also involve the chemical evaluation of cocoa powder and liquor and the interior of the beans, which implies an invasive analysis, longer times, and waste generation. Therefore, in this paper, we assess the quality of cocoa beans based on their level of fermentation using a noninvasive system to obtain hyperspectral information, as well as fast image processing and spectral classification techniques. We obtained hyperspectral images of 90 cocoa beans in the range between 350 and 950 nm in an optical laboratory. In addition, each cocoa bean was classified according to its fermentation level: slightly fermented (SF), correctly fermented (CF), and highly fermented (HF). We compared this classification with that carried out by experts from the Colombia National Federation of Cocoa Growers and reported in the Colombian technical standard No. 1252. The results show that the level of fermentation of dried cocoa beans can be estimated using noninvasive hyperspectral image acquisition and processing techniques.

No abstract