Characterization of beef tallow biodiesel and their mixtures with soybean biodiesel and mineral diesel fuel

Tallow is a raw material for biodiesel production that, due to their highly centralized generation in slaughter/processing facilities and historically low prices, may have energy, environmental, and economic advantages that could be exploited. However beef tallow biodiesel have unfavorable properties due the presence of high concentration of saturated fatty esters. One way to overcome these inconveniences is using blending procedures. In this way, blends of beef tallow biodiesel with soybean biodiesel and with conventional mineral diesel fuel were prepared and the quality of the mixtures was monitored with the purpose to study ideal proportions of the fuels. By measurement of the viscosity, density, cold filter plugging point, and flash point, it was demonstrated that tallow biodiesel can be blended with both mineral diesel and soybean biodiesel to improve the characteristics of the blend fuels, over that of the tallow.     

Ni(II)–Mg(II)–Al(III) catalysts for hydrogen production from ethanol steam reforming: Influence of the activation treatments

The effect of the Ni(II)–Mg(II)–Al(III) layered double hydroxide (LDH) activation conditions over the surface and bulk composition and the catalytic performance in ethanol steam reforming (ESR) is studied. Ternary oxides were prepared by thermal decomposition of LDHs synthesized using the homogeneous precipitation method with urea. Catalyst precursor is submitted to two different activation treatments: calcinations at 400, 500, 600 and 700 °C with subsequent reduction at 720 °C, or direct reduction at 720 °C. The samples were characterized by sorptometry, H₂ chemisorption, ICP chemical analysis, thermogravimetric analysis, X-ray diffraction, X-ray photoelectronic spectroscopy and temperature programming reduction. The catalysts obtained by calcination at 600 °C and then reduction at 720 °C and those directly reduced at 720 °C showed the better performance in ESR. The precursor submitted to a proper thermal treatment develops, through a decoration-demixing process, a Ni(II)-poor spinel-type shell onto NiO domains.     

Implementation of a Scale-Lab Lower-Limb Exoskeleton with Motion in Three Anatomical Planes

Abstract

This work deals with modeling, simulating and construction of a lower-limb exoskeleton with motion in the three anatomical planes, as well as to evaluate its performance to resolve trajectory tracking by means of feedback control schemes. The purpose is to create a scale-lab platform of a full-actuated exoskeleton to test tracking control of the main lower-limb joints to reproduce anatomical movements of a human being with no neuromuscular diseases. This functional scale-lab platform is the first step towards the design of neuromuscular rehabilitation tests based in full-automated assistive devices such as a lower-limb exoskeleton.     

Agroecology and the conversion of lárge‐scale conventional systems to sustainable management

This paper describes the agroecological principles necessary to guide the conversion of high‐input conventional systems to a low‐input management based on crop diversification and livestook integration schemes which break the monoculture nature of conventional systems. The new crop‐crop and crop‐animal combinations result in a series of synergisms and complementarities among farming system components which lead to optimal recycling of organic matter and nutrients, and to balanced pest‐natural enemy populations. Thus, agroecological design goes beyond “input‐substitution” by establishing systems capable of sponsoring their own soil fertility, crop protection and yield constancy. These new agroecosystems provide a sustainable level of productivity with minimal need for external (conventional or organic) resources. Biological structuring sponsors the functioning of the system.     

Evaluating the deterioration of electrodes when increasing the number of pulses in the welding time using galvanised IF and HSLA steels and assigning mechanical properties in the spot welds

ABSTRACT

Resistance spot welding is the most important method in the industry of self-supporting or monocoque body joinery because of its automation, its speed, the flexibility of welding parts with a complicated shape, and it is economical because it does not require a filler metal, and it is also possible to apply pre-heating and post-heating pulses to improve the weldability of the spot weld, which is defined as the ability of the structure to adequately protect passengers against injuries in the event of a collision, and this mainly depends on the integrity and mechanical performance of the weld button. In order to extend the lifetime of vehicles, galvanized steels are produced. However, zinc coatings have increased the difficulty of weldability, with higher currents being required in the process, since there is less resistance at the weld interface due to improved electrical conductivity. This work investigates the effect of galvanizing on the reduction of the lifetime of the electrodes, for this reason, it follows that there is a loss in the mechanical properties in the weld buttons as the number of spot welds increases. The main aim of this study is to correlate the electrode wear with the mechanical properties of the weld buttons. The experiment procedure consists of making 1,000 spot welds; and every twenty-fifth spot weld after the first was examined by means of stereoscopy, hardness tests, unbuttoning tests and shear stress tests. In terms of electrode wear, the face was evaluated using impressions on carbon paper, optical microscopy and X-ray spectroscopy.     

n-decane dehydrogenation on bimetallic PtSn and PtGe catalysts prepared by dip-coating

The catalytic performance of Pt, PtSn and PtGe supported on γ-Al₂O₃ (γ-A) deposited by dipcoating of spheres of α-Al₂O₃ (α-A) was studied in the n-decane dehydrogenation. The effect of Sn and Ge addition to Pt on the activity and selectivity was analyzed. The catalytic characterization was carried out using cyclohexane dehydrogenation (CHD), cyclopentane hydrogenolysis (CPH), temperature-programmed reduction (TPR), hydrogen chemisorption, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and scanning electronic microscopy (SEM). Pt(0.5)Sn/γ-A/α-A catalyst had the best catalytic performance and showed a low electronic interaction between the metals, with a surface segregation of Sn and the presence of oxidized Sn stabilized on the support. PtGe catalysts presented strong interactions with probable alloy formation. The catalytic performance of these catalysts is comparable to that reported in the patents.     

Formation of Colloidal Shells on Acidic Droplets Undergoing Neutralization in Marine Diesel Engine Cylinder Oils

In this study, a novel colloidal shell formation phenomenon was observed when sulfuric acid droplets underwent neutralization in marine cylinder lubricant at 115 ± 5 °C using heating microcapillary videomicroscopy. Immediately upon injection, shells formed, wrapping the acidic droplets and detached slowly afterward. Shells were optically transparent, about 2 μm thick, and strongly cohesive and rigid since they could deform the contained acid droplet into a non-spherical shape. Shell surface is most likely hydrophobic since the acid droplets did not wet it. It is thought that these shells were made of hydrated calcium sulfate nanoparticles embedded within an organic matrix. This material was presumably formed when oil additives reacted with sulfuric acid right upon exposure. The discovery of this shell formation, which has not been previously reported in the literature, could be important since these shells could be precursors in the formation of well-known deposits found in diesel engine cylinder liners such as “liner lacquer” or “bore glaze,” which impact negatively the performance of marine diesel engines.     

Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint–Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (Évora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.     

Adsorption and Decomposition of Glycerol on Pristine and Oxygen Modified Au(111) Surfaces

Topics in Catalysis - Research on biomass derived raw materials for conventional catalytic processes, especially those directed to replace human dependence on fossil-based energy, is a high...     

Improving unsupervised saliency detection by migrating from RGB to multispectral images

Saliency detection has been an important topic during the last decade. The main goal of saliency detection models is to detect the most relevant objects in a given scene. Most of these models use RGB (Red, Green, Blue) images as an input because they mainly focus on applications where features (eg, faces, textures, colors, or human silhouettes) are extracted from color images, and there are many labeled databases available for RGB‐based saliency data. Nevertheless, the use of RGB inputs clearly limits the amount of information from where to extract the salient regions as spectral information is lost during the color image recording. On the contrary, multispectral systems are able to capture more than three bands in a single capture and can retrieve information from the full spectrum at a pixel. The main aim of this study is to investigate the advantages of using multispectral images instead of RGB images for saliency detection within the framework of unsupervised models. We compare the performance of several unsupervised saliency models with both RGB and multispectral images using a specific dataset of multispectral images with ground‐truth data extracted from observers' fixation patterns. Our results show a general improvement when multispectral information is taken into account. The saliency maps estimated by using the multispectral features are closer to the ground‐truth data, with the simplest Graph‐based visual saliency and Boolean Map‐based models showing good relative gain compared with other approaches.