Theoretical and Experimental Study of the Magnetic Separation of Pollutants from Wastewater

This Thesys reports the study of a HGMS (High GradientMagnetic Separation) process for the treatment of industrialwastewaters that considers an assisted chemical-physical pre-treatment for the removal of heavy metals through the bound by adsorption with added iron-oxide particulate matter (hematite). The considered filter, constituted by ferromagnetic stainless steel wool and permanent magnets, is studied with a new approach based on a statistical analysis that requires the study of the trajectories of the particles. Experimental activity on a laboratory device has been carried out in order to test the model.

Continuous, Passive Liquid-Liquid Extraction and Emulsion Separation Within Microfluidic and Millifluidic Devices

Liquid-liquid extraction (LLE) is a method used to separate compounds based on their relative activity in two immiscible phases. By significantly reducing the scale of liquid-liquid extraction to the micro- and milli-fluidic levels, this separation process can bemade suitable for low volume, high value materials.

Separation of n-paraffins by selective adsorption

A study has been undertaken of the vapor-phase adsorptive separation of n-alkanes from Kuwait kerosene (Kuwait National Petroleum Company, heavy kerosene) using zeolite molecular sieves. Due to the shortage of information on the adsorption of multicomponent systems in the open literature, the present investigation was initiated to study the effect of feed flowrate, temperature, and zeolite particle size on the height of mass transfer zone (MTZ) and the dynamic capacity of the adsorbent for multicomponent n-alkanes adsorption on a fixed-bed of zeolite type-5A. The optimum operating conditions for separation of the n-alkanes has been identified so that the effluent would also be of marketable quality. The effect of multicycle adsorption-desorption stages on the dynamic behaviour of zeolite using steam as a desorbing agent has been studied and compared with n-pentane and n-hexane as desorbing agents. The separation process comprised one cycle of adsorption using a fixed-bed of zeolite type-5A. The bed was fed with vaporized kerosene until saturation had been achieved whereby the n-alkanes were adsorbed and the denormalized material eluted. The process of adsorption-desorption was carried out isobarically at one atmosphere. A mathematical model has been developed to predict the breakthrough time using the method of characteristics. The results were in a reasonable agreement with the experimental values. This model has also been utilized to develop the equilibrium isotherm. Optimum operating conditions were achieved at a feed flowrate of 33.33 x 10-9 m3/s, a temperature of 643 K, and a particle size of (1.0 - 2.0) x 10-3 m. This yielded an HMTZ value and a dynamic capacity of 0.206 m and 9.6S3 x 10-2 kg n-alkanes/kg of zeolite respectively. These data will serve as a basis for design of a commercial plant. The purity of liquid-paraffin product desorbed using steam was 83.24 wt%. The dynamic capacity was noticed to decrease sharply with the cycle number, without intermediate reactivation of zeolite, while it was kept unchanged by intermediate reactivation. Normal hexane was found to be the best desorbing agent, the efficiency of which was mounted to 88.2%.

In situ imaging and height reconstruction of phase separation processes in polymer blends during spin coating

Spin coating polymer blend thin films provides a method to produce multiphase functional layers of high uniformity covering large surface areas. Applications for such layers include photovoltaics and light-emitting diodes where performance relies upon the nanoscale phase separation morphology of the spun film. Furthermore, at micrometer scales, phase separation provides a route to produce self-organized structures for templating applications. Understanding the factors that determine the final phase-separated morphology in these systems is consequently an important goal. However, it has to date proved problematic to fully test theoretical models for phase separation during spin coating, due to the high spin speeds, which has limited the spatial resolution of experimental data obtained during the coating process. Without this fundamental understanding, production of optimized micro- and nanoscale structures is hampered. Here, we have employed synchronized stroboscopic illumination together with the high light gathering sensitivity of an electron-multiplying charge-coupled device camera to optically observe structure evolution in such blends during spin coating. Furthermore the use of monochromatic illumination has allowed interference reconstruction of three-dimensional topographies of the spin-coated film as it dries and phase separates with nanometer precision. We have used this new method to directly observe the phase separation process during spinning for a polymer blend (PS-PI) for the first time, providing new insights into the spin-coating process and opening up a route to understand and control phase separation structures. © 2011 American Chemical Society.

Magneto-vibratory separation of glass and bronze granular mixtures immersed in a paramagnetic liquid

A fluid-immersed granular mixture may spontaneously separate when subjected to vertical vibration, separation occurring when the ratio of particle inertia to fluid drag is sufficiently different between the component species of the mixture. Here, we describe how fluid-driven separation is influenced by magneto-Archimedes buoyancy, the additional buoyancy force experienced by a body immersed in a paramagnetic fluid when a strong inhomogeneous magnetic field is applied. In our experiments glass and bronze mixtures immersed in paramagnetic aqueous solutions of MnCl2 have been subjected to sinusoidal vertical vibration. In the absence of a magnetic field the separation is similar to that observed when the interstitial fluid is water. However, at modest applied magnetic fields, magneto-Archimedes buoyancy may balance the inertia/fluid-drag separation mechanism, or it may dominate the separation process. We identify the vibratory and magnetic conditions for four granular configurations, each having distinctive granular convection. Abrupt transitions between these states occur at well-defined values of the magnetic and vibrational parameters. In order to gain insight into the dynamics of the separation process we use computer simulations based on solutions of the Navier-Stokes' equations. The simulations reproduce the experimental results revealing the important role of convection and gap formation in the stability of the different states.

Cromatografia de afinidade por íons metálicos imobilizados (IMAC) de biomoléculas: aspectos fundamentais e aplicações tecnológicas

Immobilized Metal Ion Affinity Cromatography - IMAC - is a group-specific based adsorption applied to the purification and structure-function studies of proteins and nucleic acids. The adsorption is based on coordination between a metal ion chelated on the surface of a solid matrix and electron donor groups at the surface of the biomolecule. IMAC is a highly selective, low cost, and easily scaled-up technique being used in research and commercial operations. A separation process can be designed for a specific molecule by just selecting an appropriate metal ion, chelating agent, and operational conditions such as pH, ionic strength, and buffer type.

Enhanced short wavelength response in laser-scanned-photodiode image sensor using an a-SiC : H/a-Si : H tandem structure

We report in this paper the recent advances we obtained in optimizing a color image sensor based on the laser-scanned-photodiode (LSP) technique. A novel device structure based on a a-SiC:H/a-Si:H pin/pin tandem structure has been tested for a proper color separation process that takes advantage on the different filtering properties due to the different light penetration depth at different wavelengths a-SM and a-SiC:H. While the green and the red images give, in comparison with previous tested structures, a weak response, this structure shows a very good recognition of blue color under reverse bias, leaving a good margin for future device optimization in order to achieve a complete and satisfactory RGB image mapping. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications. The physics behind the device functioning is explained by recurring to a numerical simulation of the internal electrical configuration of the device.

Recuperação parcial da água de lavagem dos filtros utilizados no tratamento da água de piscinas de uso público

Mestrado em Engenharia Química. Ramo optimização energética na indústria química

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Application of OSN in membrane cascade for purification of the API Amoxicillin

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Development and modulation of magnetic responsive supported ionic liquid membranes

The work presented in this thesis aims at developing a new separation process based on the application of supported magnetic ionic liquid membranes, SMILMs, using magnetic ionic liquids, MILs. MILs have attracted growing interest due to their ability to change their physicochemical characteristics when exposed to variable magnetic field conditions. The magnetic responsive behavior of MILs is thus expected to contribute for the development of more efficient separation processes, such as supported liquid membranes, where MILs may be used as a selective carrier. Driven by the MILs behavior, these membranes are expected to switch reversibly their permeability and selectivity by in situ and non-invasive adjustment of the conditions (e.g. intensity, direction vector and uniformity) of an external applied magnetic field. The development of these magnetic responsive membrane processes were anticipated by studies, performed along the first stage of this PhD work, aiming at getting a deep knowledge on the influence of magnetic field on MILs properties. The influence of the magnetic field on the molecular dynamics and structural rearrangement of MILs ionic network was assessed through a 1H-NMR technique. Through the 1H-NMR relaxometry analysis it was possible to estimate the self-diffusion profiles of two different model MILs, [Aliquat][FeCl4] and [P66614][FeCl4]. A comparative analysis was established between the behavior of magnetic and non-magnetic ionic liquids, MILs and ILs, to facilitate the perception of the magnetic field impact on MILs properties. In contrast to ILs, MILs show a specific relaxation mechanism, characterized by the magnetic dependence of their self-diffusion coefficients. MILs self-diffusion coefficients increased in the presence of magnetic field whereas ILs self-diffusion was not affected. In order to understand the reasons underlying the magnetic dependence of MILs self-diffusion, studies were performed to investigate the influence of the magnetic field on MILs’ viscosity. It was observed that the MIL´s viscosity decreases with the increase of the magnetic field, explaining the increase of MILs self-diffusion according to the modified Stokes- Einstein equation. Different gas and liquid transport studies were therefore performed aiming to determine the influence of the magnetic behavior of MILs on solute transport through SMILMs. Gas permeation studies were performed using pure CO2 andN2 gas streams and air, using a series of phosphonium cation based MILs, containing different paramagnetic anions. Transport studies were conducted in the presence and absence of magnetic field at a maximum intensity of 1.5T. The results revealed that gas permeability increased in the presence of the magnetic field, however, without affecting the membrane selectivity. The increase of gas permeability through SMILMs was related to the decrease of the MILs viscosity under magnetic field conditions.(...)

Development of filter media treatments for liquid filtration

Woven monofilament, multifilament, and spun yarn filter media have long been the standard media in liquid filtration equipment. While the energy for a solid-liquid separation process is determined by the engineering work, it is the interface between the slurry and the equipment - the filter media - that greatly affects the performance characteristics of the unit operation. Those skilled in the art are well aware that a poorly designed filter medium may endanger the whole operation, whereas well-performing filter media can make the operation smooth and economical. As the mineral and pulp producers seek to produce ever finer and more refined fractions of their products, it is becoming increasingly important to be able to dewater slurries with average particle sizes around 1 ¿m using conventional, high-capacity filtration equipment. Furthermore, the surface properties of the media must not allow sticky and adhesive particles to adhere to the media. The aim of this thesis was to test how the dirt-repellency, electrical resistance and highpressure filtration performance of selected woven filter media can be improved by modifying the fabric or yarn with coating, chemical treatment and calendering. The results achieved by chemical surface treatments clearly show that the woven media surface properties can be modified to achieve lower electrical resistance and improved dirt-repellency. The main challenge with the chemical treatments is the abrasion resistance and, while the experimental results indicate that the treatment is sufficiently permanent to resist standard weathering conditions, they may still prove to be inadequately strong in terms of actual use.From the pressure filtration studies in this work, it seems obvious that the conventional woven multifilament fabrics still perform surprisingly well against the coated media in terms of filtrate clarity and cake build-up. Especially in cases where the feed slurry concentration was low and the pressures moderate, the conventional media seemed to outperform the coated media. In the cases where thefeed slurry concentration was high, the tightly woven media performed well against the monofilament reference fabrics, but seemed to do worse than some of the coated media. This result is somewhat surprising in that the high initial specific resistance of the coated media would suggest that the media will blind more easily than the plain woven media. The results indicate, however, that it is actually the woven media that gradually clogs during the coarse of filtration. In conclusion, it seems obvious that there is a pressure limit above which the woven media looses its capacity to keep the solid particles from penetrating the structure. This finding suggests that for extreme pressures the only foreseeable solution is the coated fabrics supported by a strong enough woven fabric to hold thestructure together. Having said that, the high pressure filtration process seems to follow somewhat different laws than the more conventional processes. Based on the results, it may well be that the role of the cloth is most of all to support the cake, and the main performance-determining factor is a long life time. Measuring the pore size distribution with a commercially available porometer gives a fairly accurate picture of the pore size distribution of a fabric, but failsto give insight into which of the pore sizes is the most important in determining the flow through the fabric. Historically air, and sometimes water, permeability measures have been the standard in evaluating media filtration performance including particle retention. Permeability, however, is a function of a multitudeof variables and does not directly allow the estimation of the effective pore size. In this study a new method for estimating the effective pore size and open pore area in a densely woven multifilament fabric was developed. The method combines a simplified equation of the electrical resistance of fabric with the Hagen-Poiseuille flow equation to estimate the effective pore size of a fabric and the total open area of pores. The results are validated by comparison to the measured values of the largest pore size (Bubble point) and the average pore size. The results show good correlation with measured values. However, the measured and estimated values tend to diverge in high weft density fabrics. This phenomenon is thought to be a result of a more tortuous flow path of denser fabrics, and could most probably be cured by using another value for the tortuosity factor.

Técnica para seleção de variáveis aplicada à separação de gases

This paper describes an experimental design technique, known as variables search, developed to expose the critical variables and screen out the irrelevant ones. It is easy to learn and use and clearly dissociates the main and interactions effects from each other. An example of air separation process by pressure swing adsorption was used to demonstrate how the variables search technique works. The phases of identification of the critical variables is shown, step by step,.

Cromatografia de afinidade por íons metálicos imobilizados (IMAC) de biomoléculas: aspectos fundamentais e aplicações tecnológicas

Immobilized Metal Ion Affinity Cromatography - IMAC - is a group-specific based adsorption applied to the purification and structure-function studies of proteins and nucleic acids. The adsorption is based on coordination between a metal ion chelated on the surface of a solid matrix and electron donor groups at the surface of the biomolecule. IMAC is a highly selective, low cost, and easily scaled-up technique being used in research and commercial operations. A separation process can be designed for a specific molecule by just selecting an appropriate metal ion, chelating agent, and operational conditions such as pH, ionic strength, and buffer type.

PREPARAÇÃO E CARACTERIZAÇÃO DE MEMBRANAS DE CELULOSE REGENERADA A PARTIR DA CELULOSE EXTRAÍDA DE RESÍDUOS AGROINDUSTRIAIS PARA APLICAÇÃO EM PROCESSOS DE SEPARAÇÃO

The aim of this study was to produce membranes using the adapted cuprammonium method. The cellulose utilized was obtained from recycled agroindustrial residues: sugarcane bagasse, corn stover and soybean hulls. The levels of Cu (II) ions in regenerated cellulose membranes produced with cellulose from bagasse, corn stover and soybean hulls were 0.0236 wt%, 0.0255 wt% and 0.0268 wt%, respectively. These levels were approximately 15 times lower than those observed in previous studies (0.3634 wt%). Cellular viability data show that membranes produced from bagasse cellulose do not present toxicity to the cellular cultures studied. These results demonstrate an evolution in production of regenerated cellulose membranes from agroindustrial residues mainly due to a decrease in the Cu (II) ions level, showing the possibility of application of these systems with improved membranes processing.