Modeling and performance analysis of an absorption chiller with a microchannel membrane‐based absorber using LiBr‐H2O,LiCl‐H2O,and LiNO3‐NH3

In order to develop compact absorption refrigeration cycles driven by low heat sources, the simulated performance of a microchannel absorber of 5‐cm length and 9.5 cm³ in volume provided with a porous membrane is presented for 3 different solution‐refrigerant pairs: LiBr‐H₂O, LiCl‐H₂O, and LiNO₃‐NH₃. The high absorption rates calculated for the 3 solutions lead to large cooling effect to absorber volume ratios: 625 kW/m³ for the LiNO₃‐NH₃, 552 kW/m³ for the LiBr‐H₂O, and 318 kW/m³ for the LiCl‐H₂O solutions given the studied geometry. The performance of a complete absorption system is also analyzed varying the solution concentration, condensation temperature, and desorption temperature. The LiNO₃‐NH₃ and the LiBr‐H₂O solutions provide the largest cooling effects. The LiNO₃‐NH₃ can work at a lower temperature of the heating source, in comparison with the one needed in a LiBr‐H₂O system. The lowest cooling effect and coefficient of performance are found for the LiCl‐H₂O solution, but this mixture allows the use of lower temperature heating sources (below 70°C). These results can be used for the selection of the most suitable solution for a given cooling duty, depending on the available heat source and condensation temperature.     

Fluorescent polyacrylate derivate from 4-biphenylmethanol with UV-green emission

In this paper we report the synthesis of a new polyacrylate named poly(1,1?-BP4MA) which is a derivate from 4-biphenylmethanol monomer. Poly(1,1?-BP4MA) was obtained by solution and bulk polymerization techniques to yield polymers with high molecular weight and high solubility. The study of the optical properties showed that poly(1,1?-BP4MA) is a fluorescent material with emission in the UV-green region and it has similar quantum yield to tryptophan.     

Dry Fractionation of Cupuassu (Theobroma grandiflorum) Fat: Physical–Chemical Properties and Polymorphic Behavior

Physical chemical properties of cupuassu fat were modified by dry fractionation. Stearin and olein fractions were obtained at 29, 26, and 24 °C. Polymorphic behavior of unfractionated cupuassu fat (UCF) and its fractions were studied in situ by small-angle (SAXS) and wide-angle (WAXS) X-ray scattering using synchrotron light. Polymorphic transitions were followed in real time tempering samples with a thermal cycle. For UCF, the main polymorphic form crystallized under selected conditions was the β’₂. α and β’₁-forms appeared in trace amounts. β₂-form was obtained after storage at 25 °C for 3 months. Stearins obtained at 26 (S-26) and 24 °C (S-24) showed a similar polymorphic behavior. However, S-26 with improved physical properties might be more suitable for chocolate production or as a trans-fat alternative than UCF. Stearin fraction obtained at 29 °C (S-29) had a complex polymorphic behavior. The α-form was the first polymorphic form detected followed by β’₂-form. There was a polymorphic transition from α to β’₁-form but no transition between β’-forms. They were independent to each other showing fractionation in two different solid solutions. Increased contents of the triacylglycerols (TAG) SOA and SOB together with lower contents of SOO compared to UCF led to co-crystallization because there was no complete compatibility among all TAG present in S-29. β₁-form crystallized after storage forming crystals with a double-layer arrangement and a characteristic morphology. This form could be useful for accelerating crystallization process in melted liquid systems.     

Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments

The Journal of Supercomputing - The increasing number of connected devices and the complexity of Internet of Things (IoT) ecosystems are demanding new architectures for managing and securing these...     

Recent research progress on bio-oil conversion into bio-fuels and raw chemicals: a review

Recent advances in lignocellulosic biomass valorization for producing fuels and commodities (olefins and BTX aromatics) are gathered in this paper, with a focus on the conversion of bio-oil (produced by fast pyrolysis of biomass). The main valorization routes are: (i) conditioning of bio-oil (by esterification, aldol condensation, ketonization, in situ cracking, and mild hydrodeoxygenation) for its use as a fuel or stable raw material for further catalytic processing; (ii) production of fuels by deep hydrodeoxygenation; (iii) ex situ catalytic cracking (in line) of the volatiles produced in biomass pyrolysis, aimed at the selective production of olefins and aromatics; (iv) cracking of raw bio-oil in units designed with specific objectives concerning selectivity; and (v) processing in fluidized bed catalytic cracking (FCC) units. This review deals with the technological evolution of these routes, in terms of catalysts, reaction conditions, reactors, and product yields. A study has been carried out on the current state-of-knowledge of the technological capacity, advantages and disadvantages of the different routes, as well as on the prospects for the implementation of each route within the scope of the Sustainable Refinery. © 2018 Society of Chemical Industry     

A simple approach to solving the kinematics of the 4-UPS/PS (3R1T) parallel manipulator

Journal of Mechanical Science and Technology - This work reports on the position, velocity and acceleration analyses of a four-degrees-of-freedom parallel manipulator, 4-DoF-PM for brevity, which...     

A Non-Invasive Technique for Online Defect Detection on Steel Strip Surfaces

During the production of steel strips, a large amount of surface defects can be generated, due to harsh environmental conditions. A high number of surface defects can lead to rejection by the customer, which represents significant economic losses to the production plant. Thus, it is very important to detect the presence and type of the defects generated during the production of each steel strip. Using this information, it is possible to determine whether a strip is suitable for sale, and it may also be useful to determine the origin of defects and, if possible, prevent them from being generated in subsequent strips. To perform these tasks, non-invasive inspection techniques are usually used, carried out automatically by artificial vision systems. Although the inspection conducted by humans is more accurate, they become fatigued quickly, or may even be unable to carry out the inspection correctly when the forward speed of the strip is high. In this paper, a new detection technique is proposed, based on the division of an image into a set of overlapping areas. The optimum values for the configuration parameters of the detection technique are automatically determined using a genetic algorithm. After the detection phase, all the defects are classified using a neural network. A very satisfactory success rate has been achieved in both detection and classification phases.     

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.