Evaluation of the removal of n-butanol vapor by the poly(lactic acid)-zeolite-TiO2 composite and formation of by-products

The use of polymeric films incorporated with zeolite-TiO₂ composites associated with UV radiation can be an alternative in the removal of volatile organic compounds (VOCs) through the adsorption and photodegradation processes. This study produced poly(lactic acid) (PLA) films incorporated with 13× zeolite, TiO₂, and 13×-TiO₂ zeolite composite to remove n-butanol and evaluate the by-products generated in the process. The results showed that 13× zeolite and TiO₂ added individually or as a composite to PLA, gave the polymer matrix a significant increase in the removal capacity of n-butanol. The best performance was presented by the zeolite-TiO₂, composite, confirming a synergistic effect. However, the formation of CO and CO₂ exceeded the expected values, with the verification that the polymeric matrix underwent photodegradation action by TiO₂. The polymeric film only containing zeolite is the most suitable for the removal of VOCs, as it did not present degradation of the PLA, generating a lower concentration of by-products.     

Effect of different surface treatments on polypropylene composites reinforced with yerba mate fibers: Physical,mechanical, chemical,and morphological properties

This study presents the preparation of post-consumer polypropylene (r-PP) composites filled with 30 wt% yerba mate (YM) stick particles. To improve the fiber–matrix adhesion, three surface treatments were performed: alkaline treatment with sodium hydroxide (NaOH) and use of 3-aminopropyltriethoxysilane (APTS) and maleic anhydride graft polypropylene copolymer (PP-g-MA) as coupling agents. Mechanical properties including tensile, flexural, and impact resistance were determined, and chemical (Fourier transform infrared spectroscopy [FTIR]), physical (water absorption), and morphological analyses were performed. The main findings show that the treatments were efficient in improving the mechanical properties of the composites, with emphasis on the r-PP/YM30/APTS and r-PP/YM30/PP-g-MA composites, which proved to be superior in tensile, flexion and impact strength and absorption of water compared to the untreated composite. The morphological analysis showed a better interaction between the fiber and the polymeric matrix for the composites with YM/APTS and YM/PP-g-MA, which corroborates the results of tensile and flexural strength, as well as with the spectra of FTIR in which the chemical modification of the fibers is observed. However, the results show that these treatments are promising in obtaining composites with recycled matrix with better properties.     

Influence of deposited amine-functionalized Si-MCM-41 in polyacrylonitrile electrospun membranes applied for separation of water in oil emulsions

Among several oil/water emulsion separation technologies, the utilization of nanoparticle-decorated membranes with diverse functionalities has received considerable attention in recent years, particularly if the antifouling capacity can be improved. In this article, we propose a new membrane based on surface-hydrolyzed polyacrylonitrile electrospun membranes and/or decorated with amine-functionalized Si-MCM-41 nanoparticles to be used as oil/water emulsion separation treatment and to determine their antifouling ability. X-Ray photoelectron spectrometry, attenuated total reflectance Fourier transform infrared spectroscopy, and toluidine blue O assay, scanning electron microscopy, contact angle measurements for oil under water and thermogravimetry were used for characterizing the membranes and an assay of permeability was developed to quantify the diffusion of oil molecules across the electrospun membrane. The electrospun and/or decorated membranes showed an underwater oleophobic wettability, which can separate oil-in-water emulsions with 87% separation efficiency, results of fouling experiments, evaluated in terms of rejection and flux recovery ratio, exhibited good antifouling ability, but the membrane decoration process did not lead to superior outcomes compared with undecorated membranes.     

A finite volume–finite difference method with a stiff ordinary differential equation solver for advection–diffusion–reaction equation

A model for atmospheric pollutant transport is proposed considering an advection–diffusion–reaction equation. A splitting method is used to decouple the advection, diffusion and reaction parts. A scheme based on finite volume, finite difference and backward differentiation formula is used for solving an atmospheric transport-chemistry problem.     

Design complexity control in truss optimization

Truss optimization based on the ground structure approach often leads to designs that are too complex for practical purposes. In this paper we present an approach for design complexity control in truss optimization. The approach is based on design complexity measures related to the number of bars (similar to Asadpoure et al. Struct Multidisc Optim 51(2):385–396 2015) and a novel complexity measure related to the number of nodes of the structure. Both complexity measures are continuously differentiable and thus can be used together with gradient based optimization algorithms. The numerical examples show that the proposed approach is able to reduce design complexity, leading to solutions that are more fit for engineering practice. Besides, the examples also indicate that in some cases it is possible to significantly reduce design complexity with little impact on structural performance. Since the complexity measures are non convex, a global gradient based optimization algorithm is employed. Finally, a detailed comparison to a classical approach is presented.     

Application execution path analysis for the automatic parallelisation of binary codes in the Intel x86 platform

Traditionally, computer programs have been developed using the sequential programming paradigm. With the advent of parallel computing systems, such as multicore processors and distributed environments, the sequential paradigm became a barrier to the utilisation of the available resources, since the program is restricted to a single processing unit. To address this issue, we propose a transparent automatic parallelisation tool with a binary rewriter. The steps of our approach are: the disassembly of the Intel x86 application, its transformation into an intermediary language; the analysis of this intermediary representation to obtain the flow and dependency graphs; the partitioning of the application into parallel units, using the obtained graphs; and, finally, the reassembly of the application back into the original Intel x86 architecture. By transforming the compiled application software, we aim at obtaining a program which can better explore the parallel resources, with no extra effort required from users or developers.     

QoS aggregation for service orchestrations based on workflow pattern rules and MCDM method: evaluation at design time and runtime

Service consumers satisfaction is considered today as one of the main concern to be ensured by service providers, especially with the spread of concurrency and the increase of functionally equivalent services. This satisfaction is closely related to quality of service (QoS) perceived by service consumers. In this context, we propose an approach to determine the satisfaction degree corresponding to the QoS of service-based applications, with regard to service consumers’ QoS expectations. Our approach is based on a preference model, which is built only on the basis of service consumer’s provided information. This preference model is also based on the 2-additive Choquet operator that takes into account preferential dependencies. In this paper, we target both design time and runtime aggregation of QoS of service-based applications.     

Note: a high transmission Faraday optical isolator in the 9.2 μm range

We have fabricated and characterized an n-doped InSb Faraday isolator in the mid-IR range (9.2 μm). A high isolation ratio (31(2) dB) and low insertion loss (1.9(3) dB) are obtained. Temperature dependance is analyzed. Further possible improvements are discussed, including the realization of a two-stage isolator. A similar design can be used to cover a wide wavelength range (λ ~ 7.5-30 μm).     

Multi-objective optimization with an adaptive resonance theory-based estimation of distribution algorithm

The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective ones. One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs). However, it has been pointed out that current MOEDAs have an intrinsic shortcoming in their model-building algorithms that hamper their performance. In this work, we put forward the argument that error-based learning, the class of learning most commonly used in MOEDAs is responsible for current MOEDA underachievement. We present adaptive resonance theory (ART) as a suitable learning paradigm alternative and present a novel algorithm called multi-objective ART-based EDA (MARTEDA) that uses a Gaussian ART neural network for model-building and a hypervolume-based selector as described for the HypE algorithm. In order to assert the improvement obtained by combining two cutting-edge approaches to optimization an extensive set of experiments are carried out. These experiments also test the scalability of MARTEDA as the number of objective functions increases.