A rapid method for interfacial tension calculation between rock plug and crude oil based on contact angles, application for EOR

"Interfacial tension and contact angle are two specific important parameters to take decisions for enhanced oil recovery, for instance, proper chemicals to use for surface tension reduction, expected wettability of solids, interaction between crude oil and rock. For this purpose, the article presents a method for easy calculation of the solid-liquid interfacial tension based on contact angle measurements applying Neumann's correlation and Young's equation. The main idea stands on the calculation of the rock parameters, like wettability, with known substances and extend these results to crude oils. It was possible, based on the results obtained, to establish a relationship between solid-liquid interfacial tension and contact angle for the crude oil – rock system, which can definitively be used for the calculation of interfacial tension of any other fluid spread out on the same kind of rock. A linear regression was obtained with an accuracy as good as R2 = 0.9989. Viscosity as a function of contact angle could also be obtained for the studied crude oils in the same kind of rock.

Viscosity and normal stress forces of Lennard-Jones chains using reverse non-equilibrium molecular dynamics

"Reverse non-equilibrium molecular dynamics was applied for the calculation of the viscosity for different chain lengths. Each chain consisted of m tangent spherical sites, where m was 1, 2, 4, 8 or 16, respectively. From these results, shear thinning was observed at high shear rates. The normal stress forces were also estimated via the calculation of the total stress tensor, and they were related to the shear thinning effect depending on the length of the chain. Furthermore, a power law equation was used to fit the rheological curves of each chain, making possible the calculation of the viscoelasticity as a function of the sites involved in the chains.

Compatibilizante basado en redes interpenetadas poliméricas (IPN) para reciclar mezclas de polímeros

"A compatibilizer including a thermoplastic elastomer and an acrylic polymer. The thermoplastic elastomer and the acrylic polymer form an interpenetrating polymeric network.""Se sintetizó un nuevo compatibilizante basado en una red polimérica interpenetrada (IPN), compuesto por un elastómero termoplástico (TPE) y ciertos poliméricos con base en ácidos carboxílicos. El compatibilizante es útil en mazclas de ciertos polímeros para su reciclaje.

Packing material comprising starch-modified polyurethane for the biofiltration of organic compounds present in gaseous or liquid effluents, production methods thereof and biofiltration system

"La presente invención describe un material de empaque para biofiltros que comprende un polímero de poliuretano y almidón. El material de empaque es resistente a la compactación, es capaz de sorber compuestos orgánicos contaminantes y reduce el tiempo de arranque del biofiltros. El material de empaque puede ser utilizado como soporte en la biofiltración de compuestos orgánicos volátiles y/o semi-volátiles presentes en efluentes gaseosos o líquidos.""The invention relates to a packing material for biofilters, having a polyurethane polymer and starch. The packing material is resistant to compaction, can sorb pollutant organic compounds and reduces the start-up time of the biofilter. The packing material can be used as a substrate in the biofiltration of volatile and/or semi-volatile organic compounds present in gaseous or liquid effluents.

A New Catalytic System for the Photodegradation of Endocrinal Disruptors: Synthesis and Efficiency Modeling and Optimization

"Nowadays, the challenge of understanding relationships between catalysts properties and performance in the context of heterogeneous catalysis is a hot topic. Indeed, catalytic processes are generally affected by many different operational parameters that need to be modeled and optimized. The challenge can be addressed using artificial neural networks due to their flexibility to work without mathematical description of the process. The present work enters within the framework of the photodegradation of water contaminants using ZnObased catalysts. ZnO is a non-toxic cheap material with an interesting photocatalytic potential. However, its application is reduced because of its poor efficiency, photocorrosion and difficulties for recovery. The objective of this work is to improve this efficiency, regarding particularly the photodegradation of an endocrinal disruptor: bisphenol-A (BPA), via the synthesis of a new catalytic system based on ZnO and the modeling of both the synthesis process and photocatalytic performance of this new catalytic system. Modeling and optimization will be carried out using artificial neural network tools coupled to an evolutionary algorithm. The connection between the two artificial neural network models will make it possible to identify the optimal synthesis parameters that lead to the maximum photocatalytic efficiency (within the studied domain), thus shedding light on the association of the system structure with its photocatalytic performance.

Modeling and optimization of a photocatalytic process: degradation of endocrine disruptor compounds by Ag/ZnO

"Artificial neural network (ANN) modeling was applied to study the photocatalytic degradation of bisphenol-A. The operating conditions of the Ag/ZnO photocatalyst synthesis and its performance were simultaneously modeled and subsequently optimized to target the highest efficiency in terms of the degradation reaction rate. Two ANN models were developed to simulate the stages of the photocatalyst synthesis and photodegradation performance, respectively. A direct dependence between the two networks was also established, thus making it possible to directly relate the degradation rate of the contaminant, not only to the photodegradation conditions, but also to the photocatalyst synthesis conditions. In this respect, an optimization study was carried out, by means of an evolutionary algorithm, in order to identify the optimal synthesis and photodegradation conditions that would result in the degradation of a maximal amount of the contaminant. Through this integrated approach it was demonstrated that neural network models can be proven valuable tools in the evaluation, simulation and, ultimately, the optimization of different stages of complex photocatalytic processes towards the maximization of the efficiency of the synthesized photocatalyst.

Experimental data in support of characterization of the CePO4 dispersion into transparent PMMA/PU IPNs by the sequential route

"This article is focused on the complementary data referring to the article "Dispersion of upconverting nanostructures of CePO4 using rod and semi-spherical morphologies into transparent PMMA/PU IPNs by the sequential route". It contains the XPS data of CePO4, photographs and DSC thermograms of transparent PMMA/PU IPNs as well as with CePO4 dispersed in different wt.%, Confocal laser scanning micrographs, transmission electron microscopy (TEM), optical images of surface, and visual inspection (photographs) before and after aging of hybrid materials.