Prediction and Verification of the Conditions Governing the Synthesis of Tailored Zeolite a for Heavy Metals Removal

Numerous experimental trials, exhaustive analytical and testing procedures are usually undertaken, to reach the appropriate conditions for synthesis of “Zeolite A”. However, it is possible to come-up with a semi quantitative approach, through modeling and optimization techniques, to define the approximate range of initial conditions governing the preparation of a tailored zeolite with specific characteristics including silica to alumina ratio, particle size, and cation exchange capacity to be used for the removal of heavy metals. This paper is an attempt to adopt an engineering approach essentially comprising the formulation of a mathematical model relating the characteristics of zeolite A to the synthesis conditions based on numerous experimental published results, optimization to define the synthesis conditions required to produce specific zeolite A , verification of this proposed approach with experimental results for preparation of tailored zeolite A conducted at our laboratories and the assessment of its efficiency for separation of chromium (III). The composition of the synthesized zeolite A has been as anticipated and the removal of chromium (III) has been in agreement with the developed model. These results indicate that is possible to adopt this approach in a generic manner to select the optimum synthesis conditions for the preparation of zeolites having specific performance characteristics.


Introduction
Heavy metals are common pollutants that have become an eco-toxological hazard of prime concern as confirmed by [1]. One of the most pollutive heaavy metals is chromium, which finds its way throuagh waste waters from iron and steel manufacturing, chrome leather tanning and other industrial sources as mentioned by Barros, et.al [2]. Also, Barros et. al [3,4] indicated that the ion exchange process has been applied successfully for heavy metals removal. Among the various cation exchangers, zeolites meet the requirements of good selectivity and acceptable capacity, in addition to being environmentally frien-dly and relatively low cost adsorbents.
Zeolites occur naturally and they have been ex-tensively synthesized in laboratory and industrial conditions. Due to their high cation exchange ca--pacity, zeolites are used as sorbents, catalysts, and cation exchangers [5]. Several investigations on the use of zeolites for heavy metals removal have been reported. In particular, chromium (III) has been suaccessfully removed from contaminated waters usi-ng zeolites A [1,2], zeolite X [6,7] and zeolite Y [5]. Other authors [1,8,9] explained the main features of these groups of zeolites that affect their selectivity towards chromium (III) removal. These are: the sialica to alumina ration ranging from 2 to 6, the pore diameter ranging from 4.2 to 10 A, cavity diameter ranging from 11.4 to 13 A, the void volume ranging from 0.47 to 0.5 cc/g, the surface area ranging from 600 to 950 m 2 /g, and the cation exchange capacity ranging from 3.9 to 5.45 meq/g.
Zeolite characteristics are basically governed by raw material composition & properties, relevant processing and post treatment conditions. Main praocessing conditions affect zeolite characteristics as follows: *corresponding author. Eamail: shadiatewfik@yahoo.com

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The silica to alumina ratio has been found to increase by increasing the aging time and decreasi-ng the aging temperature [10] synthesis temperature and pH [11], initial silica to alumina ratio [12], and synthesis time [13].
• The pore and cavity diameters have been found to increase by increasing the initial silica to alumina ratio, using the sodium as the cation, and by decreasing the aging time [14].
According to numerous investigations, the chr-omium exchange capacity (CrEC) of zeolite A, X, and Y reaches 5.14, 4.9, and 3.92 meq Cr 3+ /g respaectively as reported by several researchers [2,5,6]. Thus zeolite A has been selected as a model to be investigated in this study.
Thus, in order to prepare a zeolite of specific characteristics for chromium removal, as typical of heavy metal, it is necessary to go through a large number of experiments, exhaustive testing and anal-ysis procedures to reach the optimum synthesis con-ditions and consequently the required specifications. Theoretical prediction of the synthesis conditions has been attempted by several authors to minimize the number of trials required to prepare zeolite of specific characteristics and performance behaviour.
Tatlier, et.al., [23] used artificial neural networks for the estimation of zeolite molar compositions and hence the zeolite phases that may be obtained from certain reaction mixture composition for zeolites A, X, Y, HS, mordenite, and analcime. The results inadicate that using artificial neural network methods may decrease significantly the number of experimaents to be performed to discover new synthesis co-mpositions. Lechert [24] proved the possibility of predicting the silica alumina ratio of the produced zeolite from the starting ratio for faujasite zeolite and other different zeolite types.
This paper addresses the development of a sim-ple approach for the prediction of zeolite synthesis with defined specifications. A model developed on the basis of published data has been successfully verified by experimental preparations conducted in our laboratory and evaluation of results comprising zeolite characterization and (Cr 3+ ) removal in view of other reported data.

Compilation of data
Published data comprising starting molar rat-ios, synthesis conditions, and results of synthesis has been compiled and analysed. All the data used in this study has been obtained from conventional synthesis experiments using similar reactants. Data from several references [1,2,4,8,9,25a28] and others have been used.
Compiled data has been firstly analyzed for coansistency and reliability and database has been then formulated for ease of retrieval.

Formulation of empirical models
The analyzed data has been correlated by apply-ing relevant analysis methods, such as multiple non linear regression software and curve fitting to formaulate the mathematical empirical models governing the synthesis of zeolite A for chromium removal. Typical software used for the purpose includes Labf-it (V.7.2.37) and Microsoft Excel.

Determination of optimum conditions for synthesis of zeolite of specific characteristics
BOX Complex Routine [29] has been used to defiane the optimum synthesis conditions through minim-ization of an objective function comprising the squa-res of discrepancy between the target specification of zeolite product, which is zeolite Si/Al molar ratio, and the corresponding value calculated by the developed model. The optimization problem is constrained with the range of validity of the independent parameters governing the synthesis conditions. These parameters include: feed Si/Al, water to alumina, soda to alumina molar ratios, crystallization time (h), and crystallizat-ion temperature ( o C). Other dependent specifications have been then estimated, comprising: zeolite crystal size, pore diameter (A), cavity diameter (A), cation exchange capacity (CEC) (meq/g), and Cr 3+ exchange capacity (CrEC) (meq/g).

Synthesis
According to the procedure reported by several authors, for example [8,27], zeolite has been synthaesized following the predicted synthesis conditions and the starting molar ratios. The synthesis materials have been aluminum hydroxide (Panareac Quimic-asa), sodium meta silicate (Arabic Laboratory Equ-ipment Co. GPR), and sodium hydroxide (Modern Lab). First, the alumina trihydrate has been dissolv-ed in a sodium hydroxide solution under boiling wh-ile retaining constant volume. The silicate solution has been prepared similarly.
The synthesis gel has been then prepared by add-ition of the silicate solution to the aluminate solution at 65 o C, and mixing at 500 rpm for 1 h, with seeding of previously prepared zeolite of about 7.5 wt%. For comparison, two samples have been prepared one with aging of the synthesis gel at room temperature for 64 h (sample designated as I) and another one without aging (sample designated as II).
Crystallization has been then conducted at 98 o C, and continuous mixing at 250 rpm, for 2 h with coanstant solution volume. After crystallization and co-oling, the mother liquor has been separated from the product using a G 3 sintered glass filter. The product has been washed repeatedly with distilled water to pH 10.25, then, dried at 110a120 o C for 6.5 h.
Another sample (designated as III) has been preapared using another mode of addition of the reacta-nts, where the prepared aluminate solution has been added very slowly to the silicate solution over 1.5 hours after the addition of seeds. All the other steps have been completed as for sample II.

Characterization
The chemical formula, phases formed, crystallite size, and the degree of crystallinity have been char-acterized by Xaray diffraction analysis (XRD) using a computer controlled Xaray diffractometer (made by Diano Corporation, USA) of a measuring range (2q) from a20º to +150º target Xaray tube operated at 45 kV and 6 mA The prepared samples have been also analysed by Xaray fluorescence analysis (XRF) using AXIOS, WDaXRF Sequential Spectrophotometer (Panalyticaal, 2005) for determination of the Si/Al molar ratio.
The prepared zeolite particle size and morpholo-gy have been determined by using Scanning Elect-ron Microscope (SEM) images Model JEOL: JXAa 840A Electron Probe Microaanalyzer Coupled with Energy Dispersive Analysis by Xaray (EDEX). All samples were gold coated prior to measurement.
Transmission Electron Microscope (TEM) imagaes have been taken using JEOL: JEMa1230 electron microscopy, 120kV. The samples were dispersed in distilled water and ultrasonicated for 15 minutes. Subsequently, the dispersed solution was dropped on a copper grid pre-covered with a very thin amor-phous carbon film.

Performance Assessment
The adsorbents (0.1 g) was left in contact with 100 ml of the chromium nitrate solutions of 320-1000 ppm with initial pH values ranging from 3a4. The test was carried out at room temperature for 1 hour under constant shaking. The filtered solution was then analyzed to determine the final chromium concentration using DR 2000 Spectrophotometer. The adsorption capacity is expressed as the meq Cr 3+ /g zeolite.

1-Compilation & formulation
Acknowledging the range of validity of the an-alysed screened data and in view of the predictive nature of the developed approach, the following em-pirical equations have been developed: Where S/A Z : zeolite Si/Al molar ratio, S/A F : feed Si/Al molar ratio, H/A F : feed water to alumina molar ratio, N/A F : feed soda to alumina molar ratio, C t : crystallization time (h), C T : crystallization temaperature ( o C), C S : average crystal size (µ), P D : pore diameter (A), C D : cavity diameter (A), CEC: cation exchange capacity (meq/g), CrEC: chromium exchaange capacity (meq/g).
Tables (1) and (2) represent the calculated values using the developed empirical models as compared to the compiled data from various published reports. The range of validity as obtained from the original source has been given for each parameter in the co-rresponding equation. The % error and the correlatiaon coefficient R 2 have been also mentioned for each formulated equation.
Table (1) shows that the calculated S/A Z manifes-ts zero error in the investigated range while table (2) shows that the calculated C S manifests minor error in the a6 to +5% ranges. Moderate error in the range from a14 to 16% is observed for the calculated zero error in the PD values. The shown % error ranges seems acceptable in the prediction stage. The calcul-ated C D , CEC and CrEC values manifest minor error % as compared to original values.
Moreover, verification of the efficiency of the deaveloped equations is illustrated by a parity plot for Cs. Figure (1) represents a parity plot for equation (2) where the original and calculated Y values (avaerage crystal size) are plotted against the original X values (crystallization time).

In general, the calculated Y values in both tables
(1) and (2) demonstrates the reliabilities of equatio-ns 1a6 as sound predictive tools of zeolite A syntheasis conditions.
It should be emphasized that the developed modaels should be used as integrated predictive set within the indicated validity range.

2-Prediction & optimization
BOX COMPLEX routine has been adopted to find the values of the synthesis conditions that wouald minimize the following objective function: where S/A Z is defined by equation (1).
Consequently, equations (1 to 6) have been used to calculate other parameters using the defined optiamum for the independent variables. Results are pre-sented in table (3).
It is noted that, the predicted values are in agreaement with the characteristics of zeolite A as shown in tables (1) and (2) and with the specifications of zeolite A prepared within the scope of this work .

3-Experimental verification
Prepared samples, according to predicted set, have been subjected to experimental verification using the initial data set shown in table (3). The characterization and performance data are outlined below. Characterization X-ray diffraction (XRD) System: cubic with unit cell parameter a=24.61. The identified Si/Al molar ratio agrees with the value predicted from the model as depicted in table (3). Also results are in agreement with the published work as mentioned by several authors [2,4,8].
The close resemblance of the XRD charts for the prepared samples clearly indicates the negligible inf-luence of both the aging time [15] and the mode of reactants addition.

X-Ray Fluorescence (XRF)
XRF was also used to emphasize the performed zeolite structure. It resulted in Si/Al ratio of 1.01, 1.03 and 1for samples I, II and III respectively, whiach agrees with the XRD identified Si/Al molar ratio. It also agrees with the value predicted from the moadel as depicted in table (3). The SEM images show well defined highly crystallaine small crystals with the characteristic cube shape LTA zeolite. The images have been analysed by im-age analysis software and they show that the small zeolite particles formed range in size from a minim-um of 0.2 to a maximum of 1.2 µ for sample I, 0.6 µ for sample II, and 2 µ for sample III respectively.
The maximum observed particle size almost ag-rees with that predicted from the model as depicted in table (3). The particle size in sample III may be affected by the mode of addition of the reactants.

Transmission Electron Microscopy (TEM)
The synthesized zeolite samples have been char-acterized by (TEM) as shown in figure 4.
The TEM figures show high crystalline small zeaolite crystallites formed ranging from 15a 63 nm for sample I, 28a 86 nm for sample II, and 28a 62 nm for sample III. The latter sample is characterized by realatively minimum crystallite size range as compared to samples I & II.

Performance Assessment
The average Cr 3+ adsorption capacity of the pre-pared zeolites in the tested range has been found to be 2.5 meq Cr 3+ /g for sample I, 2.84 meq Cr 3+ /g for sample II, and 2.9 meq Cr 3+ /g for sample III. These values are relatively close and comparable with the predicted value of 3.05 meq Cr 3+ /g for chromium exachange capacity as presented in table (3). Thus the experimental adsorption results tend to confirm the validity of the adopted prediction approach within the investigated range of validity.

Conclusions
The formulated rational scheme has proved to be a powerful tool for the prediction of synthesis cond-itions required to prepare the zeolite A, with specific tailored characteristics, for Cr 3+ removal. The prep-ared samples were characterized using XRD, XRF, SEM and TEM. Further, the adsorption capacity of Cr 3+ for several prepared samples has been assess-ed. The results are in agreement with the predicted values from the model. Further work shall include the development of the prediction scheme for other zeolite types and other heavy metals with expanded validity range. The formulated predictive scheme will support the development of target zeolite with minimum experimental trials.