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Optimization of the sintered density of aluminum oxide compacts
April 2002
Materials Letters 53 (2002) 262 – 267 www.elsevier.com/locate/matlet
Optimization of the sintered density of aluminum oxide compacts C.A. Say *, D.A. Earl, M.J. Thompson School of Ceramic Engineering and Materials Science, New York State College of Ceramics at Alfred University, 2 Pine Street, Alfred, NY 14802, USA Received 24 May 2001; accepted 26 June 2001
Abstract Effects of sintering time, peak temperature, heating rate, and binder system on the sintered density of alumina compacts were modeled using statistical methods. The traditional polyvinyl alcohol/polyethylene glycol (PVA/PEG) binder system produced more spherical spray dried granules and higher sintered densities than systems including hydroxyethylcellulose and 20,000 molecular weight PEG. D 2002 Elsevier Science B.V. All rights reserved. Keywords: Alumina; D-optimal; Binder; Statistical; Microstructure; Sintering
1. Introduction Alumina is commercially used in a wide range of applications, such as electronic substrates, high temperature and electrical insulators, and porcelain. Alumina’s important thermal, electrical, and physical properties are directly linked to its sintered density. Many processing variables influence the sintered density, including the firing rate [1], time [2], temperature [3], and binder type [4]. Gaining a better understanding of the sintering behavior and key sintering variables will aid in streamlining its processing. Polyvinyl alcohol (PVA) is a popular binder due to its relatively high off-the-press compact strength; PVA has a flexible vinyl carbon backbone and a hydroxyl side group that readily bonds to oxide particles [5] (Fig. 1). PVA has a glass transition temperature (Tg) of f 70 BC and the PVA used in this research has a vis-
*
Corresponding author.
cosity range of 5.2 – 6.2 cP at 25 BC. Polyethylene glycol (PEG) with a molecular weight of 400 is traditionally added to PVA as a plasticizer. Previous work [5] suggests that green strength increases over the traditional PVA/PEG system can be achieved with cobinder systems which incorporate hydroxyethylcellulose (HEC) and PEG with a molecular weight of 20,000. PEG 20000 has a relatively low Tg ( 15 BC) and provides excellent granule deformation without added plasticizer, burns out completely, and easily dissolves in aqueous slurry, which allows for close control of slurry density and rheology [5] (Fig. 1). HEC has a long chain of anhydroglucose rings with OH and hydroxyethyl side groups (Fig. 1); HEC is less flexible and more elastic than the vinyl and PEG molecules and has a relatively high Tg (120 BC). HEC is a good secondary binder with PEG, is readily soluble in water, and mechanically reinforces green compacts [5]. This study compared PVA/PEG 400 and HEC/PEG 20000 binder systems in alumina compacts and quantified the influence of sintering time, sintering temper-
0167-577X/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 7 - 5 7 7 X ( 0 1 ) 0 0 4 8 9 - X
C.A. Say et al. / Materials Letters 53 (2002) 262–267
263
Fig. 1. Structure of binders: (a) PVA, (b) PEG, and (c) HEC.
ature, ramp rate, and green density on the sintered density, spray dried granule morphology, and microstructure of each system.
2. Sample preparation and experimental design Samples were prepared by dry pressing spray dried granules. Three different batch compositions were
Table 1 The three batch compositions tested Binder system All batches
Material
A-16 Alumina Water Darvan 821-A Polyglycol (1) PEG 20000 PEG 20000 (2) PEG 20000/HEC PEG 20000 HEC (3) PVA/PEG 400 PVAc PEG 400
Mass (g)
Manufacturer
2000 1333.33 7 1.3 60 42 18 60 20
ALCOA (De-ionized) R.T. Vanderbilt Dow Chemical Fluka Chemika Fluka Chemika Union Carbide Air Products Union Carbide
Each system has a different binder, but all three batches contain the same amount of alumina, water, Darvan, and Polyglycol. A-16 Alumina median particle size = 0.4 um.
tested, (Table 1) using binder systems PEG 20000, PEG 20000/HEC, and PVA/PEG 400. De-ionized water was used as the solvent and Polyglycol and Darvan were added as dispersants. Each system was prepared in solution and added at 10 wt.% to a milling jar with alumina and dispersing additives. The suspensions were ball milled for 8 h and then aged on a gyrotory shaker for another 16 h at 200 rpm. The slurries were spray dried with an inlet temperature of 200 BC and an outlet temperature of 110 BC; the feed rate was 0.2 l/min with an inlet pressure of 20 psi. Five-gram samples were dry pressed to either 50% or 56.5% theoretical density using a 1U diameter die. The alumina green pieces were divided into groups of eight and sintered at either 1600, 1650, or 1700 BC, held for 0.5, 4, or 8 h, and had a ramp rate of either 300 or 600 BC/h. A D-optimal statistical experimental design method [6] was used to determine the levels of independent variables tested (Table 2). The design was based on quantifying linear effects of each variable (binder type; green density; sintering peak temperature; time at the peak temperature; ramp rate and position in the furnace), and quadratic effects of time and temper-
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C.A. Say et al. / Materials Letters 53 (2002) 262–267
Table 2 The D-optimal experimental design Experimental design
Results
Experiment number
Error of prediction ratio
Sintering time (h)
Sintering temperature (BC)
Sintering rate (BC/h)
Binder type
Position in furnace
Green density (g/cm3)
Sintered density (g/cm3)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Confirmation 29 30
0.5476 0.5307 0.5464 0.5453 0.6447 0.4649 0.5471 0.4649 0.5533 0.5347 0.5504 0.5557 0.6486 0.4747 0.8044 0.4747 0.5549 0.5374 0.5530 0.5548 0.6506 0.4749 0.8058 0.4749 0.8940 0.8018 0.9888 0.8940
8 0.5 4 8 4 0.5 4 0.5 8 0.5 4 8 4 0.5 4 0.5 8 0.5 4 8 4 0.5 4 0.5 0.5 0.5 4 4
1700 1700 1700 1600 1650 1600 1600 1600 1700 1700 1700 1600 1650 1600 1600 1600 1700 1700 1700 1600 1650 1600 1600 1600 1650 1650 1600 1700
600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 300 300 600 600
1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 3 2
1 1 1 1 1 1 1 1 2 2 2 2 2 2 1 2 1 1 1 1 1 1 2 1 3 3 3 1
50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 56.5 50 50 56.5
3.173 2.101 3.029 3.121 2.883 2.039 3.120 2.061 3.190 2.159 3.067 3.163 2.892 2.073 3.096 2.108 3.285 2.183 3.185 3.282 2.979 2.126 3.208 2.119 2.879 2.602 3.018 3.205
8 0.5
1600 1600
600 300
3 2
– –
56.5 50
3.585 2.680
Binder (1) is PEG 20k, (2) is PEG 20k/HEC, and (3) is PVA/PEG 400. Position 1 is under the left heating element, 2 is in the middle of the furnace, 3 is under the right heating element.
ature. The design is also based on possible interactions between sintering time, temperature, and ramp rate. The experiments were designed to provide an average error of prediction ratio of 1.0 for the whole design space. The error of prediction ratio is: EOP ¼ Syx
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi xoVðXVXÞ1 xo
Where EOP is the regression model prediction error for experiment xo, Syx is the overall standard error of
the model, xo is the vector of one experiment in the whole design space and X is the experimental design matrix. It is estimated that effects greater than or equal to the experimental error can be quantified if the design EOP/Syx V 1.0. The sintered densities of the alumina pellets were found using the Archimedes immersion technique (ASTM standard designation C 20 – 87); the fracture surfaces of specific sintered samples were analyzed using an AMRAY 1810 SEM. Polishing was not possible on the low-density samples.
C.A. Say et al. / Materials Letters 53 (2002) 262–267
265
3. Results and discussion A statistical regression model was developed to predict the sintered density of a compact from significant independent variable levels. The parameter coefficients of variables found to be statistically significant and their corresponding t-values are listed in Table 3. The effect of sample placement in the furnace was analyzed using the indicator discrete variable technique but was found to have no effect (t = 1.8). A nonlinear time effect and interactions between the heating rate and both temperature and time are significant. Linear effects of the green density and binder are also significant. The model standard error (Syx) is 0.027, with 18 degrees of freedom, and an R2 of 0.998. Examination of the residuals shows no unexpected trends or outlier points, and the Cook values show an even leverage between experimental data points. Using a model prediction window of (+/ ) two times the standard error, additional experiments (29 and 30) were conducted that validate the model. Fig. 2 is a surface response plot of sintering temperature and time on the corresponding sintered density. The experimental data indicates that sintered density increases as soak time is increased; the relationship is polynomial and the upper limit is the theoretical maximum density. SEM images of samples that underwent longer soak times show less porosity between grains and more boundary contact between spray dried particles. The grains of both samples have typical morphology.
Table 3 Regression model for predicting sintered density Variable
Coefficient
t-value
Intercept Time (h) Temperature (BC) Rate (BC/h) PEG 20000 PEG 20000/HEC Green density Time rate Temperature rate Time [2]
3.28 0.149066 0.001351 0.006654 0.110256 0.082834 1.052866 0.000306 0.000003 0.022102
10.228 2.949 4.672 8.423 6.407 11.148 10.184 3.387 21.045
Values of | t | z 2.0 indicate at least 90% significance. Regression model: R2 = 0.998, standard error = 0.027. Variable having no effect: position in the furnace.
Fig. 2. Model predictions for a green density of 56.5% for the PVA/ PEG 400 binder system. The effects of soak time, soak temperature, and ramp rate are shown. The plots would shift depending on the green density of the samples and the binder used according to the coefficients listed in Table 3.
Increasing the sintering temperature above 1600 BC does not increase the sintered density and depending on ramp rate may have a negative impact on sintered density. A partial first derivative of the mathematical model with respect to temperature at a ramp rate of 600 BC/h shows a slope of 0.00045 (g/cm3/BC), and with a ramp rate of 300 BC/h a slope of 0.00045 (g/cm3/ B C). This result supports German’s claim that sintering at temperatures that are too high, or times that are too long can hinder material properties due to microstructure coarsening [3]. The optimum sintering temperature for alumina under these conditions may be below 1600 BC. SEM images reveal no excessive grain growth due to increased temperature, and the porosity and morphology looked the same for both the high and low temperature samples. Ramp rate has a positive effect on sintered density. At slow ramp rates, there is a much higher sintered
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C.A. Say et al. / Materials Letters 53 (2002) 262–267
density at lower times than samples with a high ramp rate. This may be due to the lag in the sample temperature relative to the furnace and thermocouple temperature. The slower ramp rate allows the sample to soak up heat energy from the furnace to reach a higher density at lower sintering times. With enough time, the two ramp rates will converge at full density. SEM images indicate that ramp rate does not influence the size of the grains, and the particles and grains of samples from both ramp rates have a similar morphology. The relative differences in sintered densities due to the binder system are small but statistically significant, as shown in Table 3. PEG 20000 samples sintered to the lowest average density (87.5%), the PEG 20000/HEC binder system samples displayed a slightly higher average density than PEG 20000 sam-
ples (88.1%), and PVA/PEG 400 samples had the highest average sintered density (90.3%). SEM images (Fig. 3) reveal qualitatively that the PVA/PEG 400 binder had the lowest closed porosity and the least fracture through the particles. PEG 20000 and PEG 20000/HEC both had higher amounts of closed porosity, where PEG 20000/HEC had more porosity than PEG 20000. The PVA/PEG 400 samples fractured intergranular, while PEG 20000 and PEG 20000/HEC samples fractured intragranular. The type of fracture could be the reason PVA/PEG 400 showed less porosity; however, the increased porosity can be traced back to the powder morphology. SEM images of PVA/PEG 400 powder shows round separated granules, where PEG 20000 and PEG 20000/HEC granules showed distorted and agglomerated granules (Fig. 3). The granule size distribution from the PVA/
Fig. 3. Microstructural correlation between fired porosity and granule morphology. The fired compacts contain (a) PEG 20k, (b) PEG 20k/HEC, and (c) PVA/PEG 400. PEG 20k and PEG 20k/HEC samples show intragranular fracture and more closed porosity than PVA/PEG 400 samples. The PVA/PEG 400 samples fracture intergranular, which may have concealed the closed porosity. Spray dried granules (d) PEG 20k, (e) PEG 20k/HEC, and (f) PVA/PEG 400 show that particle morphology effects sintered density. PEG 20k and PEG 20k/HEC particles are agglomerated and deformed, while PVA/PEG 400 is more spherical.
C.A. Say et al. / Materials Letters 53 (2002) 262–267
PEG 400 system would provide for a higher packing factor and more granule– particle contacts, resulting in a higher sintered density. As expected, green density was found to have a positive impact on the sintered density of an alumina body. As a sample’s green density is increased the corresponding sintered density increases with a magnitude shown by the coefficient listed in Table 3.
267
lower temperatures may also produce high densities. The PVA/PEG 400 binder system produced a more spherical granule morphology than the other binder systems, and the resulting sintered density was highest. This study found no benefit in using HEC/PEG co-binder systems for alumina compacts.
References 4. Conclusion The effects of sintering time, temperature, and ramp rate could be described with a partial quadratic model. The optimal firing schedule from the statistically significant variables includes an 8-h hold time, a sintering temperature of 1600 BC, a ramp rate of 600 BC/h, a green density of 2.23 g/cm3, and the use of the PVA/PEG 400 binder system. The sintering time had a much larger effect than temperature in the range of 1600 –1700 BC, and the data suggests that
[1] L. Pennisi, in: S.R. Lampman, M.S. Woods, T.B. Zorc (Eds.), Engineering Materials Handbook, vol. 4, Ceramics and Glasses, ASM International, Ohio, 1992, pp. 255 – 259. [2] K.A. Berry, M.P. Harmer, J. Am. Ceram. Soc. 69 (2) (1986) 143 – 149. [3] R.M. German, Sintering Theory and Practice, Wiley, New York, 1996, pp. 2, 8. [4] X.K. Wu, D.W. Whitman, W.L. Kaufell, W.C. Finch, D.I. Cumbers, Am. Ceram. Soc. Bull. 76 (1) (1997) 49 – 52. [5] A.S. Barnes, J.S. Reed, Am. Ceram. Soc. Bull. 76 (7) (1997) 77 – 82. [6] D.C. Montgomery, Design and Analysis of Experiments, 5th edn., Wiley, New York, 1997.
Materials Letters 53 (2002) 262 – 267 www.elsevier.com/locate/matlet
Optimization of the sintered density of aluminum oxide compacts C.A. Say *, D.A. Earl, M.J. Thompson School of Ceramic Engineering and Materials Science, New York State College of Ceramics at Alfred University, 2 Pine Street, Alfred, NY 14802, USA Received 24 May 2001; accepted 26 June 2001
Abstract Effects of sintering time, peak temperature, heating rate, and binder system on the sintered density of alumina compacts were modeled using statistical methods. The traditional polyvinyl alcohol/polyethylene glycol (PVA/PEG) binder system produced more spherical spray dried granules and higher sintered densities than systems including hydroxyethylcellulose and 20,000 molecular weight PEG. D 2002 Elsevier Science B.V. All rights reserved. Keywords: Alumina; D-optimal; Binder; Statistical; Microstructure; Sintering
1. Introduction Alumina is commercially used in a wide range of applications, such as electronic substrates, high temperature and electrical insulators, and porcelain. Alumina’s important thermal, electrical, and physical properties are directly linked to its sintered density. Many processing variables influence the sintered density, including the firing rate [1], time [2], temperature [3], and binder type [4]. Gaining a better understanding of the sintering behavior and key sintering variables will aid in streamlining its processing. Polyvinyl alcohol (PVA) is a popular binder due to its relatively high off-the-press compact strength; PVA has a flexible vinyl carbon backbone and a hydroxyl side group that readily bonds to oxide particles [5] (Fig. 1). PVA has a glass transition temperature (Tg) of f 70 BC and the PVA used in this research has a vis-
*
Corresponding author.
cosity range of 5.2 – 6.2 cP at 25 BC. Polyethylene glycol (PEG) with a molecular weight of 400 is traditionally added to PVA as a plasticizer. Previous work [5] suggests that green strength increases over the traditional PVA/PEG system can be achieved with cobinder systems which incorporate hydroxyethylcellulose (HEC) and PEG with a molecular weight of 20,000. PEG 20000 has a relatively low Tg ( 15 BC) and provides excellent granule deformation without added plasticizer, burns out completely, and easily dissolves in aqueous slurry, which allows for close control of slurry density and rheology [5] (Fig. 1). HEC has a long chain of anhydroglucose rings with OH and hydroxyethyl side groups (Fig. 1); HEC is less flexible and more elastic than the vinyl and PEG molecules and has a relatively high Tg (120 BC). HEC is a good secondary binder with PEG, is readily soluble in water, and mechanically reinforces green compacts [5]. This study compared PVA/PEG 400 and HEC/PEG 20000 binder systems in alumina compacts and quantified the influence of sintering time, sintering temper-
0167-577X/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 7 - 5 7 7 X ( 0 1 ) 0 0 4 8 9 - X
C.A. Say et al. / Materials Letters 53 (2002) 262–267
263
Fig. 1. Structure of binders: (a) PVA, (b) PEG, and (c) HEC.
ature, ramp rate, and green density on the sintered density, spray dried granule morphology, and microstructure of each system.
2. Sample preparation and experimental design Samples were prepared by dry pressing spray dried granules. Three different batch compositions were
Table 1 The three batch compositions tested Binder system All batches
Material
A-16 Alumina Water Darvan 821-A Polyglycol (1) PEG 20000 PEG 20000 (2) PEG 20000/HEC PEG 20000 HEC (3) PVA/PEG 400 PVAc PEG 400
Mass (g)
Manufacturer
2000 1333.33 7 1.3 60 42 18 60 20
ALCOA (De-ionized) R.T. Vanderbilt Dow Chemical Fluka Chemika Fluka Chemika Union Carbide Air Products Union Carbide
Each system has a different binder, but all three batches contain the same amount of alumina, water, Darvan, and Polyglycol. A-16 Alumina median particle size = 0.4 um.
tested, (Table 1) using binder systems PEG 20000, PEG 20000/HEC, and PVA/PEG 400. De-ionized water was used as the solvent and Polyglycol and Darvan were added as dispersants. Each system was prepared in solution and added at 10 wt.% to a milling jar with alumina and dispersing additives. The suspensions were ball milled for 8 h and then aged on a gyrotory shaker for another 16 h at 200 rpm. The slurries were spray dried with an inlet temperature of 200 BC and an outlet temperature of 110 BC; the feed rate was 0.2 l/min with an inlet pressure of 20 psi. Five-gram samples were dry pressed to either 50% or 56.5% theoretical density using a 1U diameter die. The alumina green pieces were divided into groups of eight and sintered at either 1600, 1650, or 1700 BC, held for 0.5, 4, or 8 h, and had a ramp rate of either 300 or 600 BC/h. A D-optimal statistical experimental design method [6] was used to determine the levels of independent variables tested (Table 2). The design was based on quantifying linear effects of each variable (binder type; green density; sintering peak temperature; time at the peak temperature; ramp rate and position in the furnace), and quadratic effects of time and temper-
264
C.A. Say et al. / Materials Letters 53 (2002) 262–267
Table 2 The D-optimal experimental design Experimental design
Results
Experiment number
Error of prediction ratio
Sintering time (h)
Sintering temperature (BC)
Sintering rate (BC/h)
Binder type
Position in furnace
Green density (g/cm3)
Sintered density (g/cm3)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Confirmation 29 30
0.5476 0.5307 0.5464 0.5453 0.6447 0.4649 0.5471 0.4649 0.5533 0.5347 0.5504 0.5557 0.6486 0.4747 0.8044 0.4747 0.5549 0.5374 0.5530 0.5548 0.6506 0.4749 0.8058 0.4749 0.8940 0.8018 0.9888 0.8940
8 0.5 4 8 4 0.5 4 0.5 8 0.5 4 8 4 0.5 4 0.5 8 0.5 4 8 4 0.5 4 0.5 0.5 0.5 4 4
1700 1700 1700 1600 1650 1600 1600 1600 1700 1700 1700 1600 1650 1600 1600 1600 1700 1700 1700 1600 1650 1600 1600 1600 1650 1650 1600 1700
600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 600 600 300 600 300 300 600 600
1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 3 2
1 1 1 1 1 1 1 1 2 2 2 2 2 2 1 2 1 1 1 1 1 1 2 1 3 3 3 1
50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 56.5 50 50 56.5
3.173 2.101 3.029 3.121 2.883 2.039 3.120 2.061 3.190 2.159 3.067 3.163 2.892 2.073 3.096 2.108 3.285 2.183 3.185 3.282 2.979 2.126 3.208 2.119 2.879 2.602 3.018 3.205
8 0.5
1600 1600
600 300
3 2
– –
56.5 50
3.585 2.680
Binder (1) is PEG 20k, (2) is PEG 20k/HEC, and (3) is PVA/PEG 400. Position 1 is under the left heating element, 2 is in the middle of the furnace, 3 is under the right heating element.
ature. The design is also based on possible interactions between sintering time, temperature, and ramp rate. The experiments were designed to provide an average error of prediction ratio of 1.0 for the whole design space. The error of prediction ratio is: EOP ¼ Syx
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi xoVðXVXÞ1 xo
Where EOP is the regression model prediction error for experiment xo, Syx is the overall standard error of
the model, xo is the vector of one experiment in the whole design space and X is the experimental design matrix. It is estimated that effects greater than or equal to the experimental error can be quantified if the design EOP/Syx V 1.0. The sintered densities of the alumina pellets were found using the Archimedes immersion technique (ASTM standard designation C 20 – 87); the fracture surfaces of specific sintered samples were analyzed using an AMRAY 1810 SEM. Polishing was not possible on the low-density samples.
C.A. Say et al. / Materials Letters 53 (2002) 262–267
265
3. Results and discussion A statistical regression model was developed to predict the sintered density of a compact from significant independent variable levels. The parameter coefficients of variables found to be statistically significant and their corresponding t-values are listed in Table 3. The effect of sample placement in the furnace was analyzed using the indicator discrete variable technique but was found to have no effect (t = 1.8). A nonlinear time effect and interactions between the heating rate and both temperature and time are significant. Linear effects of the green density and binder are also significant. The model standard error (Syx) is 0.027, with 18 degrees of freedom, and an R2 of 0.998. Examination of the residuals shows no unexpected trends or outlier points, and the Cook values show an even leverage between experimental data points. Using a model prediction window of (+/ ) two times the standard error, additional experiments (29 and 30) were conducted that validate the model. Fig. 2 is a surface response plot of sintering temperature and time on the corresponding sintered density. The experimental data indicates that sintered density increases as soak time is increased; the relationship is polynomial and the upper limit is the theoretical maximum density. SEM images of samples that underwent longer soak times show less porosity between grains and more boundary contact between spray dried particles. The grains of both samples have typical morphology.
Table 3 Regression model for predicting sintered density Variable
Coefficient
t-value
Intercept Time (h) Temperature (BC) Rate (BC/h) PEG 20000 PEG 20000/HEC Green density Time rate Temperature rate Time [2]
3.28 0.149066 0.001351 0.006654 0.110256 0.082834 1.052866 0.000306 0.000003 0.022102
10.228 2.949 4.672 8.423 6.407 11.148 10.184 3.387 21.045
Values of | t | z 2.0 indicate at least 90% significance. Regression model: R2 = 0.998, standard error = 0.027. Variable having no effect: position in the furnace.
Fig. 2. Model predictions for a green density of 56.5% for the PVA/ PEG 400 binder system. The effects of soak time, soak temperature, and ramp rate are shown. The plots would shift depending on the green density of the samples and the binder used according to the coefficients listed in Table 3.
Increasing the sintering temperature above 1600 BC does not increase the sintered density and depending on ramp rate may have a negative impact on sintered density. A partial first derivative of the mathematical model with respect to temperature at a ramp rate of 600 BC/h shows a slope of 0.00045 (g/cm3/BC), and with a ramp rate of 300 BC/h a slope of 0.00045 (g/cm3/ B C). This result supports German’s claim that sintering at temperatures that are too high, or times that are too long can hinder material properties due to microstructure coarsening [3]. The optimum sintering temperature for alumina under these conditions may be below 1600 BC. SEM images reveal no excessive grain growth due to increased temperature, and the porosity and morphology looked the same for both the high and low temperature samples. Ramp rate has a positive effect on sintered density. At slow ramp rates, there is a much higher sintered
266
C.A. Say et al. / Materials Letters 53 (2002) 262–267
density at lower times than samples with a high ramp rate. This may be due to the lag in the sample temperature relative to the furnace and thermocouple temperature. The slower ramp rate allows the sample to soak up heat energy from the furnace to reach a higher density at lower sintering times. With enough time, the two ramp rates will converge at full density. SEM images indicate that ramp rate does not influence the size of the grains, and the particles and grains of samples from both ramp rates have a similar morphology. The relative differences in sintered densities due to the binder system are small but statistically significant, as shown in Table 3. PEG 20000 samples sintered to the lowest average density (87.5%), the PEG 20000/HEC binder system samples displayed a slightly higher average density than PEG 20000 sam-
ples (88.1%), and PVA/PEG 400 samples had the highest average sintered density (90.3%). SEM images (Fig. 3) reveal qualitatively that the PVA/PEG 400 binder had the lowest closed porosity and the least fracture through the particles. PEG 20000 and PEG 20000/HEC both had higher amounts of closed porosity, where PEG 20000/HEC had more porosity than PEG 20000. The PVA/PEG 400 samples fractured intergranular, while PEG 20000 and PEG 20000/HEC samples fractured intragranular. The type of fracture could be the reason PVA/PEG 400 showed less porosity; however, the increased porosity can be traced back to the powder morphology. SEM images of PVA/PEG 400 powder shows round separated granules, where PEG 20000 and PEG 20000/HEC granules showed distorted and agglomerated granules (Fig. 3). The granule size distribution from the PVA/
Fig. 3. Microstructural correlation between fired porosity and granule morphology. The fired compacts contain (a) PEG 20k, (b) PEG 20k/HEC, and (c) PVA/PEG 400. PEG 20k and PEG 20k/HEC samples show intragranular fracture and more closed porosity than PVA/PEG 400 samples. The PVA/PEG 400 samples fracture intergranular, which may have concealed the closed porosity. Spray dried granules (d) PEG 20k, (e) PEG 20k/HEC, and (f) PVA/PEG 400 show that particle morphology effects sintered density. PEG 20k and PEG 20k/HEC particles are agglomerated and deformed, while PVA/PEG 400 is more spherical.
C.A. Say et al. / Materials Letters 53 (2002) 262–267
PEG 400 system would provide for a higher packing factor and more granule– particle contacts, resulting in a higher sintered density. As expected, green density was found to have a positive impact on the sintered density of an alumina body. As a sample’s green density is increased the corresponding sintered density increases with a magnitude shown by the coefficient listed in Table 3.
267
lower temperatures may also produce high densities. The PVA/PEG 400 binder system produced a more spherical granule morphology than the other binder systems, and the resulting sintered density was highest. This study found no benefit in using HEC/PEG co-binder systems for alumina compacts.
References 4. Conclusion The effects of sintering time, temperature, and ramp rate could be described with a partial quadratic model. The optimal firing schedule from the statistically significant variables includes an 8-h hold time, a sintering temperature of 1600 BC, a ramp rate of 600 BC/h, a green density of 2.23 g/cm3, and the use of the PVA/PEG 400 binder system. The sintering time had a much larger effect than temperature in the range of 1600 –1700 BC, and the data suggests that
[1] L. Pennisi, in: S.R. Lampman, M.S. Woods, T.B. Zorc (Eds.), Engineering Materials Handbook, vol. 4, Ceramics and Glasses, ASM International, Ohio, 1992, pp. 255 – 259. [2] K.A. Berry, M.P. Harmer, J. Am. Ceram. Soc. 69 (2) (1986) 143 – 149. [3] R.M. German, Sintering Theory and Practice, Wiley, New York, 1996, pp. 2, 8. [4] X.K. Wu, D.W. Whitman, W.L. Kaufell, W.C. Finch, D.I. Cumbers, Am. Ceram. Soc. Bull. 76 (1) (1997) 49 – 52. [5] A.S. Barnes, J.S. Reed, Am. Ceram. Soc. Bull. 76 (7) (1997) 77 – 82. [6] D.C. Montgomery, Design and Analysis of Experiments, 5th edn., Wiley, New York, 1997.