Optimizing the synthesis of cobalt aluminate pigment using fractional factorial designCeramics International ] (]]]]) ]]]–]]] www.elsevier.com/locate/ceramint
Optimizing the synthesis of cobalt aluminate pigment using fractional factorial design
Y.F. Gomesa,n, P.N. Medeirosa, M.R.D. Bomioa, I.M.G. Santosb, C.A. Paskocimasa, R.M. Nascimentoa, F.V. Mottaa
aDepartment of Materials Engineering, Federal University of Rio Grande do Norte, Campus Lagoa Nova, CEP 59078-900, Natal/RN, Brazil bDepartment of Materials Engineering, Federal University of Paraíba, Cidade Universitária, CEP 58051-900, João Pessoa/PB, Brazil
Received 28 April 2014; received in revised form 20 August 2014; accepted 28 August 2014
Abstract
The increasing use of experimental design techniques comes from the growing need to optimize products and processes while minimizing costs and maximizing efficiency, productivity and quality of products. Ceramic pigments have wide application in ceramic industries in which the quality and advanced properties of materials are widely investigated. However, studies are required to improve the procedure for obtaining cobalt aluminate (CoAl2O4) using the Complex Polymerization Method (CPM). With the objective of optimizing this method, a 2(5-2) fractional factorial design was performed using data from UV–vis spectroscopy analysis as a response surface. To determine the best conditions for obtaining (CoAl2O4) in this study, five factors were chosen as input variables at levels determined for this study: citric acid concentration (stoichiometric), pyrolysis time (h), temperature (1C), calcination heating time and rate (1C/min). Through statistical application in the process of obtaining CoAl2O4, it was possible to study which of these factors may have greater influence in optimizing the synthesis. The precursor powders were characterized using TG/DSC thermogravimetric analysis, and the calcined powders were analyzed using X-ray diffraction (XRD) and energy dispersive scanning electron microscopy (SEM/EDS) to confirm the structural and morphological aspects of CoAl2O4. It was found that with increased calcination temperature 700 1Co800 1Co900 1C, the UV–vis bands decreased with increasing absorbance intensity, and with increasing pyrolysis time (h), there is a proportional increase in the UV–vis bands. The model was generated with the conditions proposed in this study due to the determination coefficient of 99.9%, variance (R2), and satisfactory response surfaces, thus obtaining optimization of the process according to the needs and applicability in the ceramic industry of pigments. & 2014 Elsevier Ltd and Techna Group S.r.l. All rights reserved.
Keywords: CoAl2O4; Pigment; Optimization; Fractional factorial design; Complex Polymerization Method (CPM)
1. Introduction
CoAl2O4 has a spinel cubic structure and exhibits an intense blue color, characteristic of cobalt aluminate, which is a conse- quence of this type of structure and the existence of a tetrahedral site for the metal ion that removes the restriction of the Laporte selection rule present in the octahedral symmetries. The thermal and chemical stability is due to the location of the Co2þ ion in a compact packaging arrangement of oxide ions as investigated by
10.1016/j.ceramint.2014.08.125 14 Elsevier Ltd and Techna Group S.r.l. All rights reserved.
g author. Tel.: þ55 84 3342 2512; fax: þ55 84 3342 2406. ss: yfeliciano@gmail.com (Y.F. Gomes).
article as: Y.F. Gomes, et al., Optimizing the synthesis of cobalt x.doi.org/10.1016/j.ceramint.2014.08.125
Meseguer et al. [1] and Akdemir et al. [2]. Currently, cobalt aluminate (CoAl2O4) has received attention for use in different applications due to its colorimetric properties, being widely used for coloring plastics, inks, fibers, paper, rubber, phosphorus, glass, cement, enamel, ceramic and porcelain bodies, as well as for TV tubes and as contrast reinforcement for luminescent pigments, according to Kakihana [3], Cho et al. [4], Kock and Waal [5]. Various chemical methods have been used to synthesize inorganic pigments, such as the conventional ceramic method as reported by Costa et al. [6] and Gargori et al. [7], combustion synthesis, co- precipitation as demonstrated by Mimani, Ghosh [8] and Guna- widjaja et al. [9], sol-gel method as found that Kakihana et al. [3]
aluminate pigment using fractional factorial design, Ceramics International
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and Yang et al. [10], polymeric precursor as reported by Gaudon et al. [11] and hydrothermal method as noticed by Lu et al.[12] and Kim et al. [13].
CoAl2O4 is typically synthesized using inorganic precursors (primarily nitrate), followed by calcination at high temperature to obtain the spinel structure. A synthesis route frequently investigated in the literature for obtaining CoAl2O4 at low temperatures is the Complex Polymerization Method (CPM) as reported by Gaudon et al. [11], Lu et al.[12], Gong et al. [14], Chu et al. [15] and Onfroy et al. [16].
The Complex Polymerization Method (CPM) is based on the Pechini method and offers the possibility of preparing complexes of good homogeneity at molecular scale and a good stoichio- metric control. The temperatures required for the CPM are lower than those in conventional methods, as in the reactions between materials in the solid state or decompositions as presented by Gaudon et al. [10]. Many variables can influence the synthesis of oxides via the CPM as investigated by Ozbay et al. [17], Gunawidjaja et al. [9] and Jacroux et al. [18].
The most important statistical activity is not data analysis but rather the planning of experiments in which these data can be obtained. The essence of good planning is to design an experiment able to provide exactly the type of information important for the improvement of the process for obtaining the desired material as reported by Montgomery [19].
Fractional factorial design is a reliable method to simplify the process of identifying the most influential preparation variable. This approach reduces the number of experiments required to identify the process of variables in a statistically significant manner as demonstrated by Mason [20] and Nejad et al. [21].
Fractional factorial design was used to optimize the synthesis process of cobalt aluminate (CoAl2O4) at operating conditions to determine a means to save time, thus reducing the number of experiments analyzing the input variables that would influence the process as noticed by Kavanloui et al. [22].
This study used a factorial planning of variables of the process of obtaining resin at different citric acid concentrations and pyrolysis times along with the process of obtaining pigments at different temperatures, times, and calcination heating rates, totaling five input variables (k¼5) for the synthesis process for obtaining the ceramic pigment as discussed by Lu et al. [12], Llusar et al. [23] and Beal et al. [24].
Table 1 Values and Levels of the Operating Parameters.
Levels
Operating factors 1 0 1 Ccitric acid 2:1 3:1 4:1 time puff (h) 1 2 3 T (1C) 700 800 900 time calcination (h) 2 4 6 Calcination rate (1C/min) 5 8 11
2. Experimental procedure
Determining the parameter of greater statistical significance in the preparation of the precursor resins of cobalt aluminate (CoAl2O4) using the Complex Polymerization Method (CPM) derivative from the Pechini method was performed in two steps. The study explored the five main processing parameters in the method. Subsequently, based on this result, further analysis was designed using the fractional factorial design. This analysis corresponded to peaks of higher absorbance intensity in cobalt aluminate. Thereafter, the fractional factorial design was designed based on the final optimized factors to confirm that the interaction between the pyrolysis time (h) and the calcination heating rate
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(1C/min) has greater statistical significance compared to the other factors studied.
2.1. Materials and reagents
Aluminum nitrate (Al(NO3)39H2O), cobalt nitrate (CoN2O6
6 H2O), citric acid (C6H8O7) and ethylene glycol (HOCH2- CH2OH) were used to prepare the precursor resins of cobalt aluminate (CoAl2O4) as reported in Mimani et al. [8] and Kim et al. [13].
2.2. Experimental design and characterization of the material
The fractional factorial design used increases the amount of information obtained and reduces the number of experi- ments. The designed experiment determines the influence of these parameters on the syntheses of cobalt aluminate as demonstrated in Meseguer et al. [1], Akdemir et al. [2], Gong et al. [14], Chu et al. [15], Onfroy et al. [16] and Pavia et al. [25]. The five factors studied include citric acid concentrations (Ccitric acid), puff time (time puff (h)), temperature (T), calcina- tion time (time calcination (h)), calcination rate (1C/min) and their encoded values (Table 1). If low and high values were assigned for each of these variables, there is a 25 factorial design; as a result of the combinations, there would be 32 experiments to determine the influence of these five parameters on the synthesis of cobalt aluminate. The syntheses performed according to scheme are listed in Table 1. According to the 2(5-2) fractional factorial design, resin was
obtained based on different ratios among the citric acid masses at concentrations of 2:1, 3:1 and 4:1 and standard ethylene glycol 60/40, with a constant value of approximately 1.5 for the ratio by weight of citric acid and ethylene glycol. The pyrolysis of the resin obtained was performed at 350 1C at time intervals of 60 min, 120 min and 180 min with a calcination heating rate of 5 1C/min. The precursor powders obtained from synthesis were de-agglomerated using a mill for 90 min, 150 min and 210 min to obtain homogeneous powder. The calcinations were performed at temperatures of 700 1C, 800 1C and 900 1C in times of 120 min, 240 min and 360 min with heating rates of 5 1C/min, 8 1C/min and 11 1C/min with cooling to a temperature of 25 1C. The 2(5-2)¼23 fractional factorial approach used reduced the
number of experiments to 11, including eight factorial and three central points as reported by Montgomery [19] and Mason [20].
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The values of the wavelengths related to higher peak absorbance of the pigments obtained by analysis of the UV–vis spectroscopy (Y) are the response variables as demonstrated by Llusar et al. [23]. Based on this analysis in Yahiaoui et al. [26] and Kaladhar et al. [27], the general equation of the second-order or quadratic model may be generated, as represented in Eq. (1):
Y ¼ β0þ ∑ k
k
j ¼ 1 βjjx
2 j þε ð1Þ
where Y is the expected response, wavelength (nm), Xi are the encoded or non-encoded values of factors (citric acid concentra- tions (Ccitric acid), puff time (time puff (h)), temperature (T), and calcination time (time calcination (h), and calcination rate (1C/min)), 0 is a constant, i is the leading coefficient for each variable, and ij is the effect of the interaction of coefficients as demonstrated by Ozbay et al. [17], Montgomery et al. [19], Mason et al. [20] and Raj et al. [28].
The values of polynomial coefficients and the response surface of the second-order model were obtained using the STATISTICA software 7.0, and the model was validated for the process conditions used in this study.
The response function (regression model) developed and the response surface placed over the region around the current selected conditions can be used to predict the response resulting from any adjustment of the independent factors as reported by Saravanan et al. [29].
Table 3 Analysis of Variance (ANOVA) for the Suggested Model.
Source DF SS MS F P
(1)Ccitric acid 1 120.125 120.125 90.094 0.010918 (2)timepuff(h) 1 153.125 153.125 114.844 0.008595 (3)T (1C) 1 1770.125 1770.125 1327.594 0.000752 (4)timecalcination(h) 1 210.125 210.125 157.594 0.0006286 (5)Calcination rate (1C/min) 1 153.125 153.125 114.844 0.008595 2 by 3 1 153.125 153.125 114.844 0.08595 2 by 5 1 136.125 136.125 102.094 0.009653 1n2n4 1 371.095 371.095 278.321 0.003574 Pure error 2 2.667 1.333 Total 10 3069.636
3. Results and discussion
Preliminarily, the identification of the significant factors was performed by a 2(5-2) fractional factorial design with three replications at the center point, with preliminary UV–vis spectroscopy results corresponding to peaks of higher absor- bance intensity in cobalt aluminate powder as the response surface as investigated by Kavanloui et al. [22] and Hesse et al. [30].
The experimental results presented in Table 2 were analyzed using the STATISTICA software and analysis of variance
Table 2 Design Matrix Fractional Factorial 2(5-2) with real, coded values and the results.
run no. Code of syntheses Coded Values of Parameters
Ccitric acid timepuff(h) T (1C)
1 S1 1 1 1 2 S2 1 1 1 3 S3 1 1 1 4 S4 1 1 1 5 S5 1 1 1 6 S6 1 1 1 7 S7 1 1 1 8 S8 1 1 1 9 S9 0 0 0 10 S10 0 0 0 11 S11 0 0 0
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(ANOVA), which evaluates whether the effect and interaction between the investigated factors are of significance with regard to the experimental error. The significance of the main factors and their interactions was evaluated by the F-test with a confidence level of 95% and the Pareto method as discussed by Montgomery [19] and Mason [20]. The results of the ANOVA are presented in Table 3 and
indicate that all of the effects and interactions between factors are significant (po0.05) as discussed by Zolgharnein et al. [31]. The estimated effects and coefficients are listed in Table 4.
The experimental error and the main factors and their interac- tions were evaluated by the F-test with a confidence level of 95% as told in Rincón et al. [32]. UV–vis spectra were used to study the optical properties of the
cobalt aluminate synthesized (Fig. 1). The bands located in the blue region of the electromagnetic spectrum are 195, 280, 485, 506, 560 and 680 nm, typical of spinel-type cobalt aluminate; with increasing calcination temperature, the visible bands are more clearly defined, resulting in a shift of the bands of higher intensity and thus to a decrease of the absorbed visible bands as demonstrated in Klockenkamper et al. [33]. Fig. 2(a-c) presents photographs of cobalt aluminate powders
calcined according to the planning fractional factorial design for a qualitative analysis of visual denotation of the variation in the
Absorbance (nm)
timecalcination(h) Calcination rate(1C/min)
1 1 592 1 1 627 1 1 628 1 1 626 1 1 588
1 1 589 1 1 590 1 1 587 0 0 591 0 0 589 0 0 591
aDF ) degree of freedom, SS ) sum of square, MS ) mean square, and F ) F-test.
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Table 4 Estimated Effects and Coefficients for the Suggested Design Matrix Fractional Factorial 2(5-2).
Factor Effect Std.Err T P 95% Cnf.Limt þ95 Cnf.Limt
Mean/ Interc. 590.3333 0.666667 885.5000 0.000001 587.4649 593.2018 (1)Ccitric acid 7.7500 0.816497 9.4918 0.010918 4.2369 11.2631 (2)timepuff(h) 8.7500 0.816497 10.7165 0.008595 5.2369 12.2631 (3)T (1C) 29.7500 0.816497 36.4362 0.000752 33.2631 26.2369 (4)timecalcination(h) 10.2500 0.816497 12.5536 0.006286 13.7631 6.7369 (5)Calcination rate (1C/min) 8.7500 0.816497 10.7165 0.008595 12.2631 5.2369 2 by 3 8.7500 0.816497 10.7165 0.008595 12.2631 5.2369 2 by 5 8.2500 0.816497 10.1041 0.009653 4.7369 11.7631 1n2n4 26.0833 1.563472 16.6830 0.003574 19.3563 32.8104
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blue hue; the changes in color of blue spinel CoAl2O4 span a total range from a dark grayish blue (Fig. 2(a)) to an intermediate blue (Fig. 2(b)) and finally to a clear blue (Fig. 2(c)). These variations are discussed above and related to the increase or decrease in the band intensity in the UV–vis spectral range as reported in Lu et al. [12] and Llusar et al. [23].
Fig. 3(a, b) shows the thermogravimetric analysis and differential scanning calorimetry curves (TGA/DSC) of the cobalt aluminate precursor material obtained according to the fractional factorial design. No mass loss was observed at tempera- tures above 460 1C, indicating crystallization of the material, and therefore, calcination can be achieved at temperatures in the range of 700 1C to 900 1C. Differential scanning calorimetry (DSC) curves exhibit an exothermic peak in the temperature range from 250 1C to 460 1C corresponding to the precursor combustion and the removal of carbon residues corresponding to exothermic peaks at approximately 414 1C, as reported in Kock et al. [5], Lu et al. [12] and Llusar et al. [23].
X-ray diffraction was used to verify the crystal structures and purity of the samples. Fig. 4 presents the X-ray diffractograms of cobalt aluminate pigments obtained according to the experi- mental plan, showing its crystallization with the presence of a single phase of cobalt aluminate (CoAl2O4) with spinel-type cubic structure of Fd3m (JCPDS 44–0160) geometry. The peaks observed for CoAl2O4 in 2θ¼31.161, 36.731, 44.731, 48.961, 55.571, 59.191, 65.031, 73.951, and 77.181 are in agreement with JCPDS 44–0160 values, with the peak line d¼2.44 Å in the plane (3 1 1), which is observed in XRD patterns, in agreement with previous studies involving cobalt aluminate as told in Lu et al. [12] and Klockenkamper et al. [33].
SEM images of the CoAl2O4 material of experiments 4, 9 and 7 are shown in Fig. 5(a-c). The powders were calcined at (a) 700 1C, (b) 800 1C and (c) 900 1C of cobalt aluminate powders obtained from the proposed experimental plan that had the same configuration among all syntheses performed. Fig. 5(a-c) shows irregular particles and clusters, regardless of temperature, puff duration, calcination heating time and rate, which are input variables to the fractional factorial design study.
Fig. 6 shows the predicted values versus observed values using the model equation obtained from the data of the response surface of UV–vis absorbance. Effects with less than 95% significance according to the F-test used in this study are not reported.
From the values obtained from response surfaces from UV–vis spectroscopy analysis, it was possible to obtain an
Please cite this article as: Y.F. Gomes, et al., Optimizing the synthesis of cobal (2014), http://dx.doi.org/10.1016/j.ceramint.2014.08.125
empirical model with first-order interactions that is able to make predictions within the study range for the five variables under study. The multiple regression analysis of the resulting empirical data in the process of obtaining the visible band range for the cobalt aluminate pigment (CoAl2O4) correspond- ing to the blue hues obtained led to the following model expressed in Eq. 2:
Y ¼ 590:33¼ ð4:375 tpuf f Þð14:875 Tð 3CÞÞ ð4:375 tpuf f Tð 3CÞÞþð4:125 Tx tpuf f Þ þð13:042 Ccitric acid tpuf f tcalcinationÞ43:875 ð2Þ
The wavelength model equation is expressed for the following interval (–1, 0, þ1), i.e., variables of citric acid concentration (Ccitric acid), puff time (time puff (h)), temperature (T), calcination time (time calcination (h)), and calcination rate (1C/min) are valid in the range from –1 to þ1. The equation with coded values is used for independent variables or interactions between variables, whereas the response variable (Y) is the wavelength given in nanometers (nm). Eq. (1) was used to predict the wavelength in which the
model function is valid for the defined interval, i.e., for the variables of citric acid concentration (Ccitric acid), puff time (time puff (h)), temperature (T), calcination time (time calcination
(h)), and calcination rate (1C/min) in the valid range from –1 to þ1 for the experimental conditions used in this study, the determination coefficient of the proposed mathematical model
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Fig. 4. X-ray diffraction diagram of powder samples of CoAl2O4 (experiments 4, 9 and 7) prepared by CPM and annealed at: (a) 700 1C, (b) 800 1C and (c) 900 1C.
Fig. 3. TGA (a) and DTA (b) curves of the as-prepared cobalt aluminate precursor obtained by CPM.
Fig. 2. CoAl2O4 obtained from experiments 4, 9 and 7 heated at: (a) 700oC, (b) 800 1C and (c) 900 1C.
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can explain approximately 99.9% of the variance (R2) as demonstrated in Montgomery et al. [19] and Mason et al. [20].
Among the five factors studied, the citric acid concentration alone has lower statistical significance when compared with the puff time (h), which is less statistically significant when compared with the temperature (1C). Furthermore, the tem- perature (1C) has greater statistical significance than the calcination time, which has lower statistical significance compared to the calcination heating rate (h). The relationship between factors studied in ascending significance order is calcination temperature (1C)4calcination time (h)4heating rate (1C / min)4puff time (h)4 (Ccitric acid).
The interactions between the factors puff time (h) (or pyrolysis) interacting with calcination temperature (1C) and calcination heating rate (1C/min) were found to have statistical significance. The calcination time (h) has high statistical significance alone and/or in the interaction with citric acid concentration and puff time (h) (or pyrolysis).
For the levels studied, the factors were found to be relevant because the p value was below 5%. The standard deviation values are smaller than the actual value of effects and parameter, thus validating the mathematical model proposed as told in Montgomery et al. [19] and Yahiaoui et al. [26].
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Fig. 7 illustrates the Pareto chart in which the five input variables with values greater than 10.71 (p¼0.05) at the right of the line were significant; the calcination temperature (1C) has greater statistical significance compared to the other factors
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Fig. 7. Significant interaction graphs. Fig. 6. A comparative plot between experimental yield and the predicted yield.
Fig. 5. SEM micrographs of the CoAl2O4 powders (experiments 4, 9 and 7): (a) 700 1C, (b) 800 1C and (c) 900 1C.
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studied. The negative value of –36.43 indicates higher values of the visible band range to the lower level with respect to the calcination temperature (1C).
The calcination time (h) among the variables studied has the second highest statistical significance, with a negative value of –12.55, indicating higher values within the visible range for the shorter calcination time. The puff time (h) and the calcination heating rate exhibit the same numerical value of 10.71, and the puff time (h) with a positive value indicates an increase in the visible band range when the puff time (h) increases toward its maximum level. The calcination heating rate (1C/min) with a negative value indicates higher values in the visible band range toward the lower level of the heating rate. The citric acid concentration exhibits a positive numeric value of 9.49, indicating an increase in the visible band range when the citric acid concentration increases to its maximum level as reported in Jacroux et al. [18], Kaladhar et al. [27], Saravanan et al. [29] and Sudhakaran et al. [34].
Fig. 8 shows that the major interactions are between the citric acid concentration, puff time (h) and calcination time (h), which exhibit a positive value of 16.68, indicating that the visible band range will increase if these three variables all go toward the upper or lower level.
The interaction between puff time (h) and temperature (1C) has a negative value of –10.71, indicating an increase in the
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visible band range if the variables go in opposite directions, that is, a variable toward the upper level and the other toward the lower level. The interaction between puff time (h) and calcination heating rate (1C/min) has a positive value of 10.10, indicating an increase in the visible band range if these variables both go toward the lower or upper level. Fig. 8(a) shows the relationship between puff time (or
pyrolysis) and temperature (1C), which provides a better view through the contour line; it could be inferred that the interaction between puff time (h) and temperature (1C) leads to an increase in the response surface in the visible band range when the variables are moving in opposite directions. For example, if the variable temperature (1C) is toward the lower level (–1) at 700 1C and the puff time (h) is toward the upper level (þ1) at 3 h, then there is a higher value for the response surface in the visible band range of 610 nm, corresponding to a dark grayish blue as told in Beal et al. [24] and Rincón et al. [32]. In another situation, in the case of two variables, temperature (1C) and puff time (h), both going toward the upper level (þ1) or toward the lower level (–1), there will be a lower value for the response surface in the visible band range of 590 nm and 580 nm as demonstrated in Igushi et al. [35], Cheng et al. [36], Routray et al. [37], Salem et al. [38], Sirijaruphan et al. [39] and Santos et al. [40]. Increasing the values of the levels of variables at higher levels (þ1) with the
t aluminate pigment using fractional factorial design, Ceramics International
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relationship variables of puff time (h) and temperature (1C) results in a visible band of approximately 570 nm that is a shade of lighter blue.
Fig. 8(b) shows the interaction between parameters with respect to the puff time (h) and calcination heating rate (1C/min). There is an increase in the visible band range if both variables are in the same direction, either to the lower or upper level. The variables puff time (h) and calcination heating rate (1C/min) were observed to go toward the lower level (–1), with the actual values of 1 h and 5 1C/min, respectively, and response surface value within the visible band range of 570 nm, i.e., a grayish blue. In the case of two variables, the calcination heating rate (1C/min) and puff time (h), going in opposite directions, if the calcination heating rate (1C/min) and puff time (h) both are at the upper level (þ1) with actual values of 11 1C/min and 3 h, respectively, or if the calcination heating rate (1C/min) and puff time (h) both are at the lower level (–1) with actual values of 5 1C/min and 1 h, respectively, there will be a smaller value for the response surface in the visible band range of 590 nm and 580 nm, obtaining an intermediate blue color. If the variable puff time (h) and calcination
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heating rate (1C/min) are toward the upper level (þ1), with their actual values of 3 h and 11 1C/min, respectively, there will be a value of 580 nm for the response surface in the visible band range. Thus according to the RSM, the tonal ranges of grayish blue, intermediate blue and light blue are defined by the conditions chosen in the range of temperatures studied 700 1Co800 1Co900 1C.
4. Conclusion
The Complex Polymerization Method is an efficient means for the single-phase synthesis of cobalt aluminate. The 2(5-2)
fractional factorial design composed of eight factorial points plus three central points proved the statistical interactions between input variables and the response surface. The Pareto chart indicated that the interactions of greater significance for the formation of response surfaces are pyrolysis time (h) and temperature (1C), with a negative value of –10.71, which indicated an increase in the visible band range if the variables are trending in opposite directions. The interaction between pyrolysis time (h) and calcination heating rate (1C/min), with a positive value of 10.10, indicated an increase in the visible band range if the two variables are both trending to the upper or lower level. The mathematical model generated with the determination coefficients can explain approximately 99.9% of the variance (R2), with an empirical model considering first- order interactions able to predict, within the valid study range (–1) to (þ1), the empirical results in the visible band range corresponding to the cobalt aluminate pigment (CoAl2O4). The evaluation of the optimal conditions for the parameters puff time (h) and temperature (1C) satisfactorily establish the tonal conditions of grayish blue, intermediate blue and light blue through the performance of RSM; the heat treatment condi- tions studied of 700 1Co800 1Co900 1C allow for these conditions, with the improved performance and applicability according to the desired traits in the ceramic industry.
Acknowledgments
The authors thank the financial support of the Brazilian research financing institutions: CNPq and CAPES.
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t aluminate pigment using fractional factorial design, Ceramics International
Introduction
Results and discussion