Materials and Methods
CHAPTER 2 Materials and Methods
2.2 Preparation, characterization, optimization and application of low cost fly ash based ceramic membranes
65 2.1.4.4 Membrane cleaning
In order to regenerate a fouled membrane, the membrane was initially rinsed with water for 1 h. Subsequently, the membrane was cleaned using surf excel solution for 1 h. Finally, at higher applied pressure, water was passed through the membrane to facilitate the removal of oil droplets that adhere or adsorb to the surface of the membrane. After completing the cleaning process, the water flux was once again measured so as to confirm upon the complete restoration of water permeability
2.2 Preparation, characterization, optimization and application of low cost
66 2.2.2 Characterization
The XRD analysis, evaluation of membrane flexural strength, and chemical stability measurement procedures were elaborated in section 2.1.3. Scanning electron microscopy (SEM) was conducted to examine the surface morphology using SEM instrument (Make:
LEO, Model: 1430VP®, Oxford). ImageJ analysis software based SEM image analysis and the average membrane pore size determination was discussed in sub-section 2.1.4.2.
In order to examine the thermal transformation during sintering, thermo-gravimetric analysis (TGA) was conducted for the mixture of inorganic precursors using TGA instrument (Make NetzscR, Model: STA449F3A00). TGA was conducted using argon as a carrier gas and 10
oC/min heating rate from ambient temperature to the sintering temperature. Nano-particle size analyzer (NPSA) (Make: Beckmann Coulter, Model: Delsa nano C) was used to determine the particle size distribution of powder mixtures.
In order to evaluate the pore size of the membranes, the permeation of N2 gas through these membranes was carried out using an in-house made permeation set up as shown in Fig. 2.3.
The setup consists of a tubular shaped hollow top dome ended with circular shape (stainless steel) and at bottom, circular shaped flat plate has a facility to place membrane inside the flat plate and it was airtight by means of rubber gaskets. Then the setup was pressurized at various applied pressures by using N2 gas and the outlet gas flow rate was calculated by using digital gas flow meter (Make: Agilent Technologies, Model: ADM 1000 Universal Gas Flowmeter), which was connected to the outlet of the bottom flat plate. Each test was carried out at 25°C and before every test; the whole setup was checked for air leakage by dipping the setup in the detergent solution contained bucket. After finding out no leakage in the set up, then N2 gas permeation tests were carried out. From the nitrogen permeation experiments, the measured data corresponds to flow rate (Q) versus applied pressure (ΔP) that was generated for the membranes. The nitrogen gas effective permeability factor (K) of the membranes was
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derived from these gas permeation data and average pore radius (rg) was calculated as follows:
2
2 2
2.133 g 1.6 g
p p
r v r
K P
l q l q
(2.8)
Where, P is the average pressure acting on the membrane, ν denotes the molecular mean velocity of the gas (m/s), η describes the viscosity of gas (Pa s), q denotes the tortuosity, lp represents pore length (m) and K denotes the effective permeability factor.
The effective permeability factor is calculated using the following expression:
P Q2
K S P
(2.9)
Where, ΔP denotes the applied pressure, Q represents the volumetric flow rate (m3/s), P2 is the membrane pressure at permeate side and S denotes the permeable area of the membrane.
The average pore size of the membrane can be obtained from the following expression:
1.333
g
r B
C
(2.10)
Where B and C are the intercept and slope, respectively, obtained from the expression (2.8).
In addition, pure water flux tests were conducted to measure the hydraulic permeability using indigenously designed dead end microfiltration experimental setup (Fig. 2.2).
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Figure 2.3: Schematic of N2 gas permeation test setup
(1-N2 gas cylinder, 2-pressure regulator, 3-connecting tube, 4-pressure gauge, 5-membrane, 6-rubber gasket, 7-top compartment, 8-bottom base plate, 9-flow control valve and 10-digital flow meter)
2.2.3 Dead end flow microfiltration experiment
Section (2.1.4.1-2.1.4.3) elaborated upon the experimental setup (Fig. 2.2) and procedures followed to evaluate pure water permeability and oil permeation studies. With synthetic oil- in-water emulsions (50- 200 mg/L solution concentration), microfiltration tests were conducted in the applied pressure range of 69-345 kPa. The membrane flux (J) and rejection (R) was determined using the equations 2.6 and 2.7, respectively.
The procedure followed for the membrane regeneration was explained in sub-section 2.1.4.4.
2.2.4 RSM based simulation studies
An efficient experimental design involves detailed experimental plan with which experiments can be conducted systematically with optimal effort. The optimum experimental design
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allows the maximization of the information while performing the experiment. The design of experiments starts with concept of choosing the process model. For better performance of process optimization, CCD methodology from the RSM is effectively used and is therefore employed in the present work. At the center point location, the total number of possible combinations of experiments are obtained by the design of experiments targeted with the number of independent variables that strongly influence the process performance in terms of flux and rejection. Three levels are considered (+1,0,-1) for a particular variable while performing the CCD analysis using variables of experiments such as feed concentration (X1) and applied pressure (X2) to obtain response effects. Out of the three levels, ‘0’ level is considered as the center point or the middle level. The factorial design influences the amount of the values in high and low levels. In this case, both the high and low level of the point are chosen as 1.414, which is obtained from the relation 2(k/4) (where k = number of factors = 2).
Five levels are considered ranging from -1.414, -1, 0, +1, +1.414, for every process variable in this study. The formulae 2k +2k+n0, is used for the determination of the number of possible experiments. In this formula, the first term signifies the factorial points, second term indicates the axial points and the third indicates the central run.
In the present study, CCD method is used by considering two factors. In substituting the two factors in the above formula, 4 factorial nodes, 4 axial nodes and 5 replicates at the center point are obtained. Hence, in the present study, in total, 13 experiments were carried out using these parameter variables. A second order regression polynomial model was developed for the reconstruction of the response using the independent variables and their corresponding interactions. The process performance is denoted using the equation:
2 0
1 1 1, 1,
n n n n
i i ii i i i j ij
i i i i j j i j
Y X X X X
(2.11)
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where Y describes recovered response, β0 denotes offset parameter, βi is linear performance variation, βii is the squared effect, βij indicates effect of interaction, εij is the random error and Xi and Xj are the independent uncoded variables.
In the present work, a polynomial of second order is derived using independent uncoded parameters mentioned below:
2 2
0 1 1 2 2 12 1 2 11 1 22 2
Y X X X X X X (2.12)
Design expert software (Version 7.0) was used to carry out RSM studies that feature experimental design matrix, ANOVA studies, response surfaces, normal plots of residuals and contour points.