Abstract
In this study, the effect of drying temperature, from 50 °C to 90 °C, on the drying characteristics of powdered peanut shell was investigated, and an isothermal procedure was used to determine the moisture diffusivity and the activation energy. All the experiments were performed using a thermogravimetric analyzer (TGA) for rapidly achieving the isothermal condition and accurately recording the mass loss of the sample. With increasing drying temperature, the drying rate increased and the drying time decreased. A short rising rate period was found in all drying processes due to increasing temperature of the sample in the beginning of drying. The predicted values by the diffusion model based on Fick’s second law were in good agreement with the experimental data obtained from the falling rate period. The values of effective moisture diffusivity ranged from 9.60 x 10-9 to 2.26 x 10-8 m2/s, and the activation energy was determined to be 21.2 kJ/mol.
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Determination of effective moisture diffusivity and activation energy for DRYING OF powdered peanut shell under isothermal conditions
Dengyu Chen, Kai Li, and Xifeng Zhu *
In this study, the effect of drying temperature, from 50 °C to 90 °C, on the drying characteristics of powdered peanut shell was investigated, and an isothermal procedure was used to determine the moisture diffusivity and the activation energy. All the experiments were performed using a thermogravimetric analyzer (TGA) for rapidly achieving the isothermal condition and accurately recording the mass loss of the sample. With increasing drying temperature, the drying rate increased and the drying time decreased. A short rising rate period was found in all drying processes due to increasing temperature of the sample in the beginning of drying. The predicted values by the diffusion model based on Fick’s second law were in good agreement with the experimental data obtained from the falling rate period. The values of effective moisture diffusivity ranged from 9.6010-9 to 2.2610-8 m2/s, and the activation energy was determined to be 21.2 kJ/mol.
Keywords: Effective moisture diffusivity; Drying activation energy; Isothermal condition; Peanut shell, TGA
Contact information: Key Laboratory for Biomass Clean Energy of Anhui Province, University of Science and Technology of China, Hefei 230026, China; *Corresponding author: xfzhu@ustc.edu.cn
INTRODUCTION
Biomass powder is widely used in thermochemical conversion technologies aimed at production of gas, liquid, and char. In preparation for such conversion it is essential to dry the biomass to a low moisture content level, as the materials often contain considerable water (Dobele et al. 2007). The effective moisture diffusivity (Deff) and the activation energy (Ea) are the important drying parameters for describing the diffusion mechanism and designing a new dryer (Albitar et al. 2011; Chen et al. 2011). In the literature, the drying parameters are generally determined under isothermal conditions by a two-step method (Elenga et al. 2011; Li and Kobayashi 2005). First, effective moisture diffusivity is calculated from the drying curves by Fick’s second law for each of several drying temperatures. Then, the well-known Arrhenius-type equation is used to correlate the set values of effective moisture diffusivity as a function of temperature, from which the activation energy and the pre-exponential factor (D0) are obtained.
In recent years, the two-step method has been widely used, and the drying parameters values have been obtained for numerous materials, such as fruits (Minaei et al. 2012), food (Doymaz and Kocayigit, 2011), fiber (Elenga et al. 2011), vegetables (Wu et al. 2007), sawdust (Chen et al. 2012), and leaves (Kaya and Aydin 2009). However, few drying studies have been carried out for biomass powder, and the drying parameters of agricultural residues such as peanut shell are unknown.
In addition, the isothermal condition has a significant influence on the accurate determination of the effective moisture diffusivity. However, drying experiments are usually not performed isothermally in practical processes due to thermal lag. A relatively large error can result when a temperature gradient exists within the sample (Srikiatden and Roberts 2006).
The thermogravimetric analyzer (TGA) is an outstanding instrument with advantages of minimal sample requirement, online recording of weight loss, and ease of operation. Most importantly, it has precise control capability that can rapidly heat the sample to the required temperature. In recent years, the TGA has been applied in biomass drying by different researchers (Cai and Chen 2008; Hu et al. 2012).
Therefore, the objectives of this work were to study experimentally the drying characteristics of powdery peanut shell under isothermal conditions, and to determine the effective moisture diffusivity and the activation energy by thermogravimetric analysis.
EXPERIMENTAL
Materials
Peanut shell was crushed into small particles using a high-speed rotary grinder. The particles of 0.125 to 0.3 mm size were selected for the experiments. Sample size was generally consistent with previous studies on dry biomass (Cai and Chen 2008; Chen et al. 2012). To make moisture distribute evenly, the sample was kept for 96 hours in a sealed vitreous container. The moisture content of peanut shell was determined by using the oven method at 105 ºC for 6 hours. As an average of the results of such measurements, it was found to be 0.079 g water/ g dry matter.
Drying Experiments
The drying experiments were performed at five temperatures (50, 60, 70, 80, and 90 °C) using a thermogravimetric analyzer (TGA, Q5000IR, TA Instruments, USA). The specification of the sample pan (Platinum) was 100 μL with a height of 1 mm. The material was distributed uniformly in the sample pan. Thus the thickness of the material was nominally 1 mm, and the sample weight stabilized at 9 mg for each experiment. The air flow rate was kept at 100 mL/min with a velocity of 0.01 m/s for all experiments. The relative humidity of air was 20%. More information about the experimental procedure can be obtained from the literature (Li and Kobayashi 2005).
A computer connected to the TGA automatically recorded the changes in weight and temperature. Each drying experiment was repeated twice, and the average values were used for drawing the drying curves. Sample shrinkage can be negligible in the tested temperature range, and moisture was distributed evenly inside the sample. These selected conditions were in agreement with other drying studies by TGA (Chen et al. 2012; Hu et al. 2012).
Data Analysis
The moisture ratio (MR) of peanut shell was calculated by the following equation,
(1)
where M is the moisture content at any time (g water/g dry matter), M0 is the initial moisture content (g water/g dry matter), and Me is the equilibrium moisture content (g water/g dry matter). The value of Me was determined as the moisture content at the end of drying when the sample ceased to lose mass.
Effective Moisture Diffusivity and Activation Energy
There are many methods to determine drying parameters, of which the most common is the Fick’s second law of diffusion, as shown in Eq. (2).
(2)
The solution of Eq. (2), as shown in Eq. (3), has been widely used to describe the drying process. Assumptions inherent in the use of these equations include that the process took place under isothermal conditions, that moisture transport was dominated by internal diffusion, that there was a uniform initial moisture distribution, and that there was negligible shrinkage.
(3)
In Eq. 3, t is the drying time (min), L is the half thickness of the sample (m), and n is a positive integer. In this study, Deff was determined by non-linear regression based on the simplex method. These calculations were performed by mathematical software (Origin 8.0). The maximum value of n was set to 1000.
Temperature dependence of the effective diffusivity has been shown to follow an Arrhenius relationship,
(4)
where Ea is the drying activation energy (kJ/mol), D0 is the pre-exponential factor (m2/s), T is the drying temperature (°C), and R is the ideal gas constant (J/mol K). The drying activation energy can be calculated by plotting ln(Deff) versus 1/(T+273.15).
RESULTS AND DISCUSSION
Evaluation of the Isothermal Condition
During the drying process, an ideal isothermal condition means that the tempera-ture gradient can be negligible in the sample and that the temperature remains constant throughout the drying. The material’s surface can easily reach the desired temperature, while the interior usually cannot, especially in large particles. The temperature gradient has a significant effect on the determination of the effective moisture diffusivity (Srikiatden and Roberts 2006). On the other hand, the sample’s temperature often varies with drying time. This phenomenon is relatively common in high moisture content material (Rovedo et al. 1995). Moreover, the sample’s temperature may exceed the drying temperature because too much energy is supplied at high heating rate by TGA (Li and Kobayashi 2005). Thus, the temperature overshoot should be avoided.
In this study, temperature data of the sample were recorded online by TGA. The results of the temperature profiles are shown in Fig. 1. It can be observed that there was no indication of a temperature overshoot, although the material was heated quickly to the drying temperature. A short time of within 50 seconds was needed to heat the material to the drying temperatures (50, 60, 70, 80, and 90 °C), and then the material’s temperature remained constant over a long period of time. Owing to minimal material used in the experiment and low heat capacity of the samples, as well as precise temperature control capability of TGA, the temperature gradient in the sample can be negligible. Therefore, the important assumption of isothermal drying condition was generally met for proper determination of the drying parameters.
Fig. 1. Temperature profiles of peanut shell under isothermal drying conditions
Evaluation of the Internal Diffusion
The effect of drying temperature on the moisture ratio is shown in Fig. 2, and the drying rate curves are shown in Fig. 3. It can be seen that temperature significantly affected the drying process. With increasing drying temperature, the drying rate loss was increased, and the time needed to achieve specific moisture content was reduced notably. Similar results have been reported for cotton straw (Hu et al. 2012) and pine forest residues (Phanphanich and Mani 2010).
Fig. 2. The moisture ratio of peanut shell at different drying temperatures
Fig. 3. Drying rates of peanut shell at different drying temperatures
As seen from Fig. 3, there was no constant rate period, but a long falling rate period was found in all drying processes. A short rising rate period appeared in the beginning of each drying process, lasting about 60 seconds. In particular, biomass heating to the drying temperature also occurred in this period (see Fig. 1). According to previous studies, the rising drying rate could be attributed to increased moisture evaporation on the surface of biomass due to increasing temperature in the beginning of drying (Kaya and Aydin, 2009; Minaei et al. 2012; Shi et al. 2008). Figure 3 clearly indicates that the short rising rate period was not a diffusion process. In order to obtain accurate results, this period should be excluded from the determination of the drying parameters. Thus, it is very important to reduce the thermal lag.
Afterwards, with less free water available on the surface, the drying rate started to decrease. The drying process occurred mainly in the falling rate period, during which most of the water was removed. Similar results were obtained for blueberries (Shi et al. 2008) and poplar sawdust (Chen et al. 2012). It should be noted that the evidence presented here is not sufficient to demonstrate a diffusion mechanism in this study, because a similar falling rate period can exist without being a diffusion process at low air flow speed. In the range of flow speed that can be controlled, the drying curve was almost the same. The flow speed cannot increase so high as to verify the diffusion mechanism for the limit of TGA. Nevertheless, it can be first assumed that the falling rate period was dominated by internal diffusion. The diffusion model based on Fick’s second law was then used to predict dry curves in order to verify the reasonableness of the assumption. Therefore, the falling rate period was modeled as process diffusion. Equation (1) was replaced by MR = (M–Me)/(Mto–Me) before using Eq. (2) to calculate the drying parameters, where to is the initial time point of the falling rate period.
Fig. 4. The relationship between ln(Deff) and 1/(T+273.15)
Determination of Drying Parameters
Equation (3) was used for determining the Deff during the falling rate period. The initial values of D0 and Ea were set rationally according to the previous studies in the literature (Chen et al. 2012). The calculated values of Deff were 9.6010-9, 1.1610-8, 1.4110-8, 1.8510-8, and 2.2610-8 m2/s at 50, 60, 70, 80, and 90 °C, respectively. Deff
increased with increasing drying temperature. The high moisture diffusivity could be due to more energy being provided at high drying temperature, which increased the activity of water molecules and increased the drying rate. The difference between predicted values and experiments data was evaluated by the coefficient of determination (R2). The R2 values were 0.9850, 0.9831, 0.9783, 0.9789, and 0.9789 for drying at 50, 60, 70, 80, and 90 °C, respectively. The predicted values by the diffusion model based on Fick’s second law were in good agreement with the experimental data obtained from the falling rate period. Therefore, the drying process of peanut shell in this study was mainly controlled by diffusion mechanisms. The activation energy was determined using Eq. (4). A linear relationship between ln(Deff) and (1/(T+273.15)) was found in Fig. 4. The activation energy was determined as 21.2 kJ/mol by means of the slope of the line.
Evaluation of the Determination Results
The determined values of peanut shell have a certain reliability and comparability compared with the results of other biomass. Table 1 shows the effective moisture diffusivity of the present study as well as information available in the literature. It can be seen that the values obtained for peanut shell in the present study were within the general range of 10-10 to 10-8 m2/s for forestry and agricultural residues, as reported in the literature (Erbay and Icier 2010). The activation energy of peanut shell was also similar to some agricultural residues. Table 2 shows the activation energy values of different biomass. The activation energy of peanut shell in the present study was close to that of mung beans but higher than wheat straw, olive-waste cake, and cotton stalk.
It should be noted that the results are limited to the TGA used in this study, because many factors, such as drying apparatus, moisture content, material type, and temperature range have an influence on the experimental results. However, the present study demonstrates the methodology and provides guidance for isothermal procedure by TGA as an effective and alternative way for determining the drying parameters.
Table 1. Comparison of the Deff for Peanut Shell and Other Biomass
Table 2. Comparison of the Ea for Peanut Shell and Other Biomass
CONCLUSIONS
- Increasing drying temperature increased the drying rate and decreased the drying time. A short rising rate period appeared in all drying curves due to increasing temperature of the sample in the beginning period of drying. The drying process mainly was accomplished during the falling rate period. It is very important to reduce the thermal lag for accurately determining the drying parameters by the isothermal procedure.
- The predicted values by the diffusion model based on Fick’s second law were in good agreement with the experimental data obtained from the falling rate period. Therefore, the drying process of the falling rate period was mainly controlled by diffusion mechanisms. The effective diffusivity values changed from 6.9610-9 to 2.2610-8 m2/s within the given temperature range, and the activation energy was calculated to be 21.2 kJ/mol.
ACKNOWLEDGMENTS
The authors are grateful for the support of the National Natural Science Foundation of China (Grant No. 50930006), National High Technology Research and Development Program (Grant No. 2012AA051803), and National Key Technology R&D Program (Grant No. 2011BAD22B07).
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Article submitted: April 21, 2012; Peer review completed: May 19, 2012; Revised version received and accepted: June 22, 2012; Published: June 26, 2012.