Anais do 43º Congresso Brasileiro de Cerâmica 15501
2 a 5 de junho de 1999 - Florianópolis – S.C.
Thermal Characterization of Clay Ceramics using Phoacoustic Technique
J. Alexandre, O.C. Gonçalves, B.C. Marques, L.H. Poley, F. Saboya, C. Salles, M.S. Sthel, M.G. da Silva and H. Vargas
Universidade Estadual do Norte Fluminense
Centro de Ciência e Tecnologia
Av. Alberto Lamego, 2000, CCT Horto Campos dos Goytacazes, RJ, Brazil
CEP: 28015-620
ABSTRACT
In this paper we discuss the usefulness of the photoacoustic techniques to characterize the thermal properties of kaolinite clays, which is a very abundant mineral in some regions of Brazil. The results show strong evidence that there is a marked temperature around 950 oC above and below which there are different behaviour patterns of the measured properties of the kaolinite clay samples. The implications of the results in the manufacturing of clay bricks are briefly considered. It plays an important role in tropical regions where the knowing of the thermal properties of material used in building construction industry are highly desired.
Keywords: Photoacoustic spectroscopy, kaolinite, structure, thermal properties.
INTRODUCTION
During the past few years the photoacoustic (PA) and photothermal (PT) techniques have been gradually broadly used in different branches of science, ranging from agricultural and medical sciences to environmental sciences. For a comprehensive review on PT wave phenomenon and their applications we refer to books by Bicanic 1, Mandelis2, Rosencwaig 3 and Almond 4, and to review papers by Fork and Herbert5 and Vargas and Miranda 6.
The PA effect in solids was discovered by A.G. Bell in 1880. This effect can be detected by enclosing a specimen in an airtight cell (PA cell) and exposing it to a chopped light beam. As a result of the periodic heating of the specimen, the pressure in the air chamber oscillates at the chopping frequency. The resulting PA signal depends not only on the amount of heat generated in the specimen (i.e.; on the specimen’s optical absorption coefficient and its light-into-heat conversion efficiency), but also on how this heat diffuses through the specimen and is exchanged with the surrounding gas of the cell. The quantity that measures the rate of heat diffusion in the specimen is the thermal diffusivity , whereas the specimen thermal effusivity e, measures essentially its thermal impedance for heat exchange. These two quantities are defined as
(1)
where:
k = specimen thermal conductivity
= density
cp = heat capacity at constant pressure
In this paper we were concerned about the use of PA methodologies for investigating the thermal properties of kaolinite clay, a mineral which is very abundant in the northern Rio de Janeiro state in Brazil. This material, which composition is mostly Al2O32SiO22H2O, is used in the fabrication of ceramics, for example, brick and roof tile. The performance and efficiency of such materials in addition to many other characteristics depend critically on the thermal and physical properties of the building construction raw material. Besides, kaolinite is one of the most common clay mineral found in Brazil. During the manufacturing process of the brick, the raw material is being heated at high temperatures, and, as a consequence, changes in the chemical and physical properties of kaolinites will occur. Therefore, changes in the mechanical and thermal properties are expected. The mechanical behavour of the kaolinite after being fired at high temperatures is quite well known7. However, the thermal properties resulting from heating is still to be investigated. These thermal properties are of extreme importance in civil engineering industries mainly in tropical regions due to the high temperatures reached by the sun rays towards the building walls.
EXPERIMENTAL
Sample Preparation
The preparation procedure of the clay samples adopted in this work is described in the Reference 8.
The thermal parameters were measured using a small piece of clay, rubbed (with sand paper) to obtain samples heaving a smooth and flat surface, approximately 300 m thick. The heat treatment procedure adopted in this work consists in heating the sample for a given time in a specific temperature. All the measurements were take at room temperature.
Apparent porosity and density
The percentual apparent porosity P was calculated using the usual relation P(%)(P0 - Ps)/(P0 – Pi)100,where P0 is the moisture sample weight, Ps is the dry sample weight and Pi is the immerse-in-water sample weight. To calculate the density, we used the ratio of the dry sample weight to the sample volume.
Thermal diffusivity measurements: the open-cell detector
As detector it was used a commercial electret microphone9. The experimental arrangement (Fig. 1) consisted of a 25 mW He-Ne laser whose beam was mechanically chopped and focussed onto the sample. The sample was mounted in such a way as to cover the opening of the microphone. The signal from the microphone was connected to a lock-in amplifier (PAR, model 5210) used to register both signal amplitude and phase. These were recorded as a function of modulation frequency.
Figure 1 -Experimental arrangement for the P.A. thermal diffusivity measurements.
In the thermal diffusivity measurements using the OPC detector, the pressure fluctuation p in the air chamber, for the rear-side illumination configuration, Fig. 4, is predicted by the thermal diffusion model10 and given by:
(2)
where is the air heat capacity ratio, P0(T0) is the ambient pressure (temperature), I0 is the radiation intensity, f is the modulation frequency and li, ki and i are the length, thermal conductivity and thermal diffusivity of medium i, respectively. Here, the subscript i denotes the absorbing sample (s) and the air (g), respectively. is the complex thermal diffusion coefficient of material i. In arriving at eqn. (2) we have assumed that the sample is optically opaque to the incident radiation and that the heat flux into the surrounding air is negligible. The optical opaqueness condition means that all the radiation is absorved at the outer sample surface. Eqn.(2) is further simplified for thermally thick samples, namely , it reduces to:
(3)
Eqn.(3) means that, for a thermally thick sample, the amplitude fo the PA signal decreases exponentially with the modulation frequency as , where . In this regime s can be obtained by fitting the experimental data with the coefficient b, by using eqn.(3) in the form:
(4)
The constant A, in the measured signal S, apart from geometric factors, includes all other factors such as the gas thermal properties, and so on. We thus have two adjustable parameters A and b to describe the PA monitoring of the thermal diffusivity of the sample.
Measurements of heat capacity, cp
The heat capacity per unit of volume, cp, was measured using the temperature rise method, under continuous white light illumination. The experimental arrangement is shown in Fig. 2.
Figure 2 -Experimental arrangement used for thermal conductivity measurements.
The samples were sprayed on both surfaces with a very thin film with black paint. A light-absorbing surface and the same heat-transfer coefficient were thus assured for each side of the sample. The samples were suspended in a Dewar flash, which an entrance glass window through which the continuous white-light beam was focused onto one of the sample surfaces. A thermocouple was used to monitor the temperature evolution. Since the sample thicknesses are typically on the order of 300 m and much smaller than their widths (e.g., 0.6 cm), the simple one-dimensional heat diffusion equation with radiation losses could be applied to our measurements. Solving the one-dimensional heat equation, it can be shown that the long-term time evalution (i.e., for times greater than the heat diffusion time l2/, where l is the sample thickness and the thermal diffusivity) of the back surface temperature rise is given by:
(5)
where I0 is the intensity of the incident light is the rise time. Here, is the radiative heat-transfer coefficient, where is the Stefan-Boltzmann constant and T0 is the ambient temperature. The parameter is determined by fitting the experimental data with eqn. (6). The thermal conductivity k is readily obtained from the previous value of , calculated by using .
RESULTS AND DISCUSSION
In Fig. 3 we show the PA amplitude as a function of the modulated square root of the frequency for the a) 360 m thick sample (kaolinite clay) heated at 950° C and b) 320 m thick sample of kaolinite clay heated at 600 ° C. The solid curves in Fig. 3, represent the fitting of experimental data to eqn. (4). The resulting values of thermal diffusivity from the data fitting was = 27.0x10-3 cm2/s for the kaolinite clay heated to 950° C and 1.33x10-3 cm2/s for the sample heated at 600° C. Note that within the frequency range from 20 to 70 Hz the samples were thermally thick, i.e., their thermal diffusion lengths (/f)1/2 were much more smaller than their thickness. The same procedure was applied to the other samples. In Table 1, we summarize the results of the thermal diffusivity of our samples as a function of the heated temperature. The density and the porosity of the samples as a function of the heated temperature are also included. In Fig. 4 we show the thermal diffusivity as a function of the heated temperature.At higher temperature the thermal diffusivity decreases as shown in Fig. 4. The observed decrease in may be attributed to an increase in the density of our sample. In Table 1 we present the density of the samples as a function of the heated temperature. Between 500 oC and 800 oC the density increases which entails that should decreases providing a constant ratio k/cp. In this case the sample becomes amorphous and heat does not flow as easily as for the sample heated with temperature above 800 oC.
Table 1 - Values of the porosity density and crystallinity surements as a function of the heat treatment
Temperature(oC) / Difusivity
(10-3cm2/s) / Porosity
(%) / Density
(g/cm3) / cp
(J.cm-3.K-1) / Conductivity
(10-3W.cm-1.K-1)
300 / 1.54 / 0.50 / 1.152 / 0.43 / 0.66
500 / 1.11 / 0.69 / 1.220 / 0.44 / 0.49
600 / 1.33 / 0.74 / 1.247 / 0.44 / 0.59
700 / 2.68 / 0.70 / 1.303 / 0.45 / 1.21
800 / 1.17 / 0.65 / 1.311 / 0.46 / 0.54
850 / 6.60 / - / - / 0.43 / 2.84
900 / 15.40 / 0.58 / 1.332 / 0.62 / 9.55
950 / 27.05 / 0.49 / 1.381 / 0.42 / 1.14
1000 / 4.73 / 0.43 / 1.559 / 0.53 / 2.51
1050 / - / 0.26 / 1.842 / - / -
1200 / 4.60 / 0.08 / 2.586 / 0.41 / 1.89
Figure 3 -Dependence of the PA signal amplitude as a function of the frequency square root for a) the 360 m thick sample heated at 950 oC and b) the 320 m thick sample heated at 600 oC. The solid curves represent the fit of the experimental data to eqn. 4.
Figure 4 -Thermal diffusivity as a function of heated temperature.
Fig. 5 shows the back surface temperature rise as a function of time, after commencement of illumination for a sample heated with 700oC. This figure also shows the cooling of the back surface of the sample when the illumination is switched off. The solid line in Fig. 5 represents the result of the best fit of the experimental data to eqn. (5) using as an adjustable parameter. From the values of we got the experimental value of the thermal capacity, cP. We found cp= 0.45 J.cm-3K-1 for the sample heated at 700oC. The same procedure was applied to the other samples, and the values are given in Table 1.
Anais do 43º Congresso Brasileiro de Cerâmica 1551
2 a 5 de junho de 1999 - Florianópolis – S.C.
Figure 5 -Back surface temperature evolution for kaolinite clay samples. The solid line represents the result of the best fit of the experimental data to eqn. (5) using as an adjustable parameter.
It is known that both crystalline and amorphous phases of the same compound have nearly equal heat capacity 11. However, in the vicinity of a phase transition, the behaviour is different. As can be observed in Table 1, the heat capacity of the sample at 950 oC abruptly separates from the remainder of the cp value. This result is consistent with the well known behavior of the heat capacity at critical points. It is an obvious example of detection of a phase transition from measurements of heat capacity per unit of volume.
Finally, the thermal conductivity k was determined using the measured values of thermal capacity cP and the previously determined values of the thermal diffusivity , eqn(1). The values are shown in Table 1. We observe that the thermal conductivity k reaches a maximum at 950 oC. The analysis of this phenomenon is essentially the same for the values. A large amount of heat flows per unit of time for the sample heated at 950 oC, which is the ideal temperature to manufacture clay bricks.
CONCLUSION
In conclusion we have investigated kaolinite clays using the photoacoustic technique. We note that the PA–determined thermal diffusivity and thermal conductivity are indeed sensitive parameters for monitoring the amorphous-crystalline solid transformation occurring during the heating of the kaolinite clay sample. A relatively simple experimental arrangement enable us to discriminate different samples by means of thermal diffusivities, and may serve as a quality indicator for the product. A clay with favorable thermal properties can keep a mild room temperature, preventing both heat to flow in and fresh air to flow out of the room. This is of particular importance in development countries where the low-budget constructions and energy saving plans play a fundamental social role.
ACKNOWLEDGMENTS
This work was partially financed by CNPq and FENORTE (RJ), whose support is gratefully acknowledged.
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