Thermophysical property measurements and thermal energy storage capacity analysis of aluminum alloys

Solar Energy 137 (2016) 66–72

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Thermophysical property measurements and thermal energy storage capacity analysis of aluminum alloys Gaosheng Wei ⇑, Pingrui Huang, Chao Xu, Dongyu Liu, Xing Ju, Xiaoze Du, Lijing Xing, Yongping Yang School of Energy, Power and Mechanical Engineering, Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing 102206, China

a r t i c l e

i n f o

Article history: Received 7 April 2016 Received in revised form 27 July 2016 Accepted 29 July 2016

Keywords: Aluminum alloy Thermophysical properties Phase change TES

a b s t r a c t Ten aluminum alloy samples are prepared using a casting method by carefully designing compositions of Al-Si, Al-Cu, Al-Mg, and Al-Cu-Zn alloys. This paper measures the phase change temperature, latent heat, and specific heat of the samples using a differential scanning calorimeter (DSC), the thermal diffusivity using a laser flash method, and derives the thermal conductivity of each sample. The effects of element addition and temperature on the performance of the aluminum alloy phase change materials (PCM) are comprehensively analyzed. The thermal energy storage (TES) capacities of the samples in different temperature ranges are also analyzed. The results show that adding Cu, Zn, and Si to an aluminum alloy helps reduce the melting point of the alloy. The addition of dense elements such as Cu and Zn in aluminum alloys improves the alloy’s TES capacity per volume unit. Based on experimental results, this paper also recommends fitting formulas for calculating the temperature dependent specific heat and thermal conductivity of the aluminum alloys studied. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction High temperature thermal energy storage (TES) is very important for the effective use of solar energy. It is a critical component of concentrated solar power (CSP) generation unit. An effective TES system can improve the thermal management level of a CSP unit, and ensure safe operation of the system under load during cloudy days or at night instead of shutting down due to loss of sunlight. Moreover, an efficient TES system is critical for upsizing a CSP generation unit and for improving system global efficiency by increasing the load capacity (Medrano et al., 2010; Kenisarin, 2010). Therefore, it is necessary to develop a safe and economic high temperature TES system for CSP generation unit. There are primarily three TES methods that can be used with CSP systems, namely sensible, latent, and thermochemical systems. Latent TES is current one of the most in-depth investigated methods. It can achieve TES at near constant temperature and the TES capacity of the latent method at unit volume is 5–14 times larger than with sensible TES methods (such as water, refractory brick or rock, etc.). These advantages also allow the application of latent TES in many other energy saving fields. Thus, many researchers have given considerable attention to latent TES in

⇑ Corresponding author. E-mail address: [email protected] (G. Wei). http://dx.doi.org/10.1016/j.solener.2016.07.054 0038-092X/Ó 2016 Elsevier Ltd. All rights reserved.

recent years (Kenisarin, 2010; Gil et al., 2010; Agyenim et al., 2010; Liu et al., 2012; Cheng et al., 2010a). The phase change material is undoubtedly the key factor in determining the performance of a latent TES system. A large number of materials can experience a phase change at a specific temperature. High temperature molten salts and metal alloys are currently considered two of the most understood potential phase change materials (Kenisarin, 2010; Gil et al., 2010; Agyenim et al., 2010; Liu et al., 2012; Cheng et al., 2010a). Many salt materials can store latent heat at high densities and high temperature but have a low thermal conductivity, which is a significant obstacle to heat accumulation and release rates (Michels and Pitz-Paal, 2007; Steinmann and Tamme, 2008; Dunn et al., 2012; Relloso and Delgado, 2009). Therefore, much effort has been devoted to improve the thermal conductivity of salt PCMs by utilizing a fin tube configuration, adding metal materials, etc. (Fan and Khodadadi, 2011; Liu et al., 2005; Zhao and Wu, 2011; Zhou and Zhao, 2011; Wang et al., 2015; Wu and Zhao, 2011; Do Couto Aktay et al., 2008; Ermis et al., 2007; Shabgard et al., 2010; Pincemin et al., 2008; Acem et al., 2010; Shin and Banerjee, 2011), which, however, as indicted by Wang et al. (2015), lead to significant weight and cost increasing. Liquid–solid separation and large changes in volume when melting are other issues that must be addressed when using salt as the TES medium (Kenisarin, 2010; Gil et al., 2010; Agyenim et al., 2010; Wu and

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Zhao, 2011; Do Couto Aktay et al., 2008; Ermis et al., 2007; Shabgard et al., 2010; Pincemin et al., 2008; Acem et al., 2010; Shin and Banerjee, 2011). Many metal alloys (primarily aluminum alloys) can also store latent heat with favorable cycling stability, the thermal conductivity of metal alloys is dozens to hundreds times higher than most salts (Kenisarin, 2010; Gil et al., 2010; Agyenim et al., 2010; Liu et al., 2012; Cheng et al., 2010a), Several studies have been reported on the thermophysical properties of different metals and alloys as PCMs (Kenisarin, 2010; Shin and Banerjee, 2011). It was reported that the large latent heat on a mass or volume basis were obtained in binary and ternary alloys with abundant elements Al, Cu, Mg, Si, and Zn (Shin and Banerjee, 2011; Sun and Zhang, 2005; Achard, 1981; Gasanaliev and Gamataeva, 2000; Sun et al., 2007; Zhang et al., 2012; Birchenall and Telkes, 1976; Birehenall and Riechman, 1980; Farkas and Birehenall, 1985; Cherneeva et al., 1982; Cheng et al., 2010b; Huang et al., 1991; Wang et al., 2006; Fukahori et al., 2016; Akiyama et al., 1992). Table 1 gives a summarization of the thermophysical properties of some aluminum alloys. The use of metal alloys with high thermal conductivity as TES materials it still require an extensive work related to design and preparation of new eutectic metal alloys with specific melting temperatures and determination of thermophysical properties is required. Birchenall and Telkes (1976) first analyzed the possibility of storing thermal energy by using latent heat in metals. Birehenall and Riechman (1980) subsequently measured the melting temperature and heat of fusion using a differential scanning calorimeter (DSC) and differential thermal analysis (DTA). The melting temperature and heat fusion of some new metal eutectic alloys were also

measured by Farkas and Birehenall (1985). Achard (1981) undertook a TES study of aluminum-magnesium alloys. Gasanaliev and Gamataeva (2000) and Cherneeva et al. (1982) analyzed the TES properties of various melts, as well as studying the use of metal alloys for heat accumulation. Wang et al. (2006) measured AlSi12 and AlSi20 alloys using DSC. Fukahori et al. (2016) given thermal analysis of Al-Si alloys as high-temperature PCM and their corrosion properties with ceramic material, while Sun et al. (2007) tested the thermal reliability of Al(60 wt.%)–34 Mg–6Zn through 1000 cycles in a DSC analysis. Cheng et al., 2010a,b analyzed the effect of adding different elements on the phase change temperature and latent heat of aluminum alloys. Akiyama et al. (1992) analyzed the thermal performance of spherical capsules containing six phase change materials (PCM). The group showed that metallic PCMs are more advantageous for obtaining constant temperature heat transfer fluids due to their higher thermal conductivity. Blanco-Rodríguez et al. (2014), Rodriguez-Aseguinolaza et al. (2014) given a thermophysical and Thermodynamic study on the eutectic Mg49–Zn51 alloy for TES application, Risueño et al. (2015) given a study on Mg-Zn-Al eutectic alloys as PCM. Zhang et al., (2014), Fukahori et al. (2016), and Nomura et al. (2015) give an encapsulation study on some metal alloys by adopting different methods. Blanco-Rodríguez et al. (2015) and Kotzé et al. (2014) give a study on TES heat exchangers by adopting Al-12Si alloy and Mg-51%Zn as PCMs. Kenisarin (2010), Liu et al. (2012), Zhang et al. (2012) also give a summarization on the thermophysical properties of some metal alloys in their studies. While certain investigations have shed light on the topic, knowledge of the thermophysical properties of aluminum alloys in the literature, as mentioned by Kenisarin (2010), Zhang et al.

Table 1 A summary of thermophysical properties of some aluminum alloys. Content (wt.%)

Phase change temperature (°C)

Density (kg/m3)

Latent heat in unit mass (kJ/kg)

Latent heat in unit volume (MJ/m3)

34 Mg 8Si 12Si 12Si 12.2Si 12.5Si 12.6Si 20Si 20Si 20Si 23.4Si 25Si 30Si 40Si 96Zn 33.2Cu Si/Fe 40Si/15Fe 53Si/30Ni 34Cu/1.7Sb 13Cu/15Zn 5.25Si/ 27Cu 5Si/ 30Cu 13.2Si,/5Mg 34Mg/6.42Zn 35Mg/6Zn 22Cu/18Mg/6Zn 24.5Cu/12Mg/18Zn 26Cu/5Mg/20.5Zn 5.2Si/28Cu/2.2Mg

450 576 576 572 580 577 576 576 580 585 575 577 580 580 381 548 577 869.4 1079.2 545 493.3–598 520 571 552 447–450 443 520 460–624 458–488.3 507

2300 – 2700 – 2620 2250 – – 2580 – – – 2540 2510 6630 3424 2600 3360 4290 4000 3420 – 2730 – 2393 2380 3140 380 0 386 0 440 0

310 428.9 560 441 499.2 515 463.4 528.4 552.6 460 395 432 644.3 721.2 138 351 515 562.2 960.3 331 158.3 365.8 422 533.1 329–316 310 305 315.3 163.8 374

713 – 1512 – 1307 1160 – – 1426 – – –

916 1200 1339 1889 4120 1324 538.8 1150 – 781–756 740 960 1 197.3 632.3 1664

Specific heat (kJ/(kg K))

Thermal conductivity (W/(m K))

Solid

Liquid

Solid

Liquid

1.73 1.058 1.038 – 1.036 1.49 1.037 0.970 0.984 – – – 0.896 0.879 – 1.11 0.939 0.762 0.653 – – 0.875 1.30 1.123 1.049 1.63 1.51 – – –

– – 1.741 –

80 – 160 – 165 180 – – 158 – – 167 140 110 – 130 180 12.8 51.7 – – – – – – – – – – –

50 – – –

– 1.741 – – – – – – – – – 1.17 – – – – 1.438 1.20 1.249 1.426 1.46 1.13 – – –

70 – – – – – – – – – 80 – – – – – – – – – – – – – –

References

Cheng et al. (2010a) Huang et al. (1991) Wang et al. (2006) Fukahori et al. (2016) Wang et al. (2015) Cheng et al. (2010a) Huang et al. (1991) Huang et al. (1991) Wang et al. (2015) Wang et al. (2006) Fukahori et al. (2016) Fukahori et al. (2016) Wang et al. (2015) Wang et al. (2015) Gasanaliev and Gamataeva (2000) Cheng et al. (2010a) Zhang (2009) Wang et al. (2015) Wang et al. (2015) Gasanaliev and Gamataeva (2000) Cheng et al. (2010b) Huang et al. (1991) Cheng et al. (2010a) Huang et al. (1991) Sun et al. (2007) Cheng et al. (2010a) Kenisarin, (2010) Cheng et al. (2010b) Cheng et al. (2010b) Gasanaliev and Gamataeva (2000)

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(2012) and summarized in Table 1, is still imperfect. The values for the various thermophysical properties presented by the various researchers summarized above are different, while the nature of the influence of different elements on the physical properties of aluminum alloys is woefully inadequate. The TES capacities at unit volume in different alloys must be examined carefully. To this end, ten aluminum alloy samples are prepared in this work, and the corresponding thermophysical properties are measured. The effects of the temperature and performance of aluminum alloy PCMs from adding Cu, Zn, and Mg to aluminum are comprehensively analyzed. The results of this work should provide some useful guidance for metal alloy PCM development. 2. Experimental part 2.1. Preparation of test samples Table 1 gives the purities of the raw materials used to prepare the samples. The related aluminum alloy phase diagrams have been given in Figs. S1–S6 in Appendix (Li et al., 2012; Liu et al., 2014). By referring to these phase diagrams, ten samples of aluminum alloy were designed and prepared by casting after high temperature melting of the raw materials in a vacuum resistance furnace. Firstly, the raw materials (except polycrystalline silicon powder) given in Table 2 are broken into small pieces, and weighted with electronic scales. The raw materials with a certain weight proportions are then put into the ceramic crucible. The ceramic crucible together with the raw materials is put into a vacuum resistance furnace for melting. Argon gas was used to prevent sample oxidation during the high temperature melting process. The furnace was heated up to 1500 °C for Al-Si alloy preparations, up to 750 °C for Al-Mg alloy preparations, and up to 1100 °C for rest of the samples preparations. All of them were isothermally maintained for 30 min to ensure an appropriate diffusion time, and the necessary stirring were made before the crucible was taken out for casting. A copper mold was used for the casting in atmospheric environment. Table 3 gives the designed element components and densities for each of the prepared samples. The elemental components of the samples were measured at the National Testing Center of Nonferrous Metals and Electronic Materials Analysis of China. Titrimetry was used to measure the copper content in samples 02, 03, 04, 07, and 08, while the gravimetric method was used to measure the silicon content in sample 9. Inductively coupled plasma atomic emission spectroscopy (ICPAES) was used to measure the copper, zinc, and magnesium contents in the rest of the samples. Table 3 shows that the measured element components of the resulting samples were very close to the amounts melted to produce the samples. Fig. 1 gives the metallographic structures of the investigated samples, they were measured at the Testing Center of USTB Co. Ltd. It can be seen that the relative uniform structures have been got by this method.

Number

Designed (wt.%)

Measured (wt.%)

Density q (g/cm3)

01 02 03 04 05 06 07 08 09 10

Al-10Cu Al-20Cu Al-30Cu Al-40Cu Al-20Si Al-5Mg Al-5Cu-5Zn Al-10Cu-10Zn Al-20Cu-10Zn Al-30Cu-10Zn

Al-10.35Cu Al-20.39Cu Al-30.12Cu Al-40.13Cu Al-19.7Si Al-3.52Mg Al-4.91Cu-5.04Zn Al-10.30Cu-9.84Zn Al-20.50Cu-10.45Zn Al-26.98Cu-10.10Zn

2.8887 3.1425 3.4298 3.7395 2.6341 2.6602 2.8931 3.1105 3.3749 3.6235

the protection of a constant stream of Argon gas with a flow rate of 50 ml/min. An Al2O3 crucible was used for the phase change temperature and latent heat measurements over a temperature range of 30–900 °C, and an Al crucible used for the specific heat measurement over a temperature range of 30–500 °C. Three times have been measured at least for each sample and the average values are used. A Netzsch LFA427 laser flasher thermal analyzer was used to measure the thermal diffusivity of the prepared samples over a temperature range of 30–500 °C at 7 different temperature spots, and in a vacuum condition. Three times have been measured for each sample and the average values are used here. The thermal conductivity of the samples was then calculated by using the measured thermal diffusivity and specific heat data as according to

k ¼ aqC P

A high-temperature differential scanning calorimetric apparatus (Netzsch DSC404C) was used to measure the phase change temperature, latent heat, and specific heat of the prepared samples. The tests were performed with a heating rate of 20 °C/min under Table 2 Purity of the raw materials prior to sample preparation. Aluminum ingot

Copper rode

Zinc rode

Magnesium ingot

Polycrystalline silicon powder

99.7

99.9

99.9

99.9

99.9999

ð1Þ

Here, a is the thermal diffusivity (m2/s), q is density (kg/m3), and Cp is the specific heat (J/(g K)). 2.3. Uncertainty analysis in thermophysical properties measurements Many factors can affect the accuracy of DSC measurements, including changes in the crucible, the position offset of the crucible in different measurements, the stability of the purging gas, the heat capacity deviation between the standard sample and the measured sample, the contact status of the sample with the crucible, and the homogeneity of the prepared samples. In order to minimize measurement errors in this work, the DSC apparatus was calibrated before the experiment. A fixed purging gas value was adopted for the entire measurement process. All of the samples except for Al40Cu (because of its brittleness) were rolled in order to improve the uniformity of the sample, with relatively larger samples adopted for the measurement process. Three samples were measured for each type of material, with the average value adopted for its thermophysical property data. All of the above factors have been considered independently to assess the measurement uncertainties, and the following uncertainty propagation law is adopted to assess the combined uncertainty of the measurement.

DU ¼

2.2. Measurement of thermophysical properties

Purity (%)

Table 3 The element components and densities of the prepared samples.

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi DU 21 þ DU 22 þ DU 23 þ   

ð2Þ

By using the law of uncertainty propagation Eq. (2), the calculated combined uncertainty of the phase change temperature is less than 2.6 °C, the overall measurement uncertainty of latent heat is less than 3.6 percent, and the overall uncertainty of the specific heat is less than 4.8 percent. Many factors may also affect the accuracy when determining thermal conductivity, including the effect of carbon sprayed on the sample surface (which improves the absorptance of the sample to laser energy), the uniformity of the laser pulse, the thickness uniformity of the samples, and the density variation of the sample with temperature. These factors were not taken into consideration when calculating the thermal conductivity using Eq. (1). Any

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(a) Al-10.35Cu

(b) Al-20.39Cu

(f) Al-3.52Mg

(c) Al-30.12Cu

(g) Al-4.91Cu-5.04Zn

(d) Al-40.13Cu

(e) Al-19.7Si

(h) Al-10.30Cu-9.84Zn (i) Al-20.50Cu-10.45Zn (j) Al-26.98Cu-10.10Zn

Fig. 1. Metallographic structures of the investigated samples.

uncertainties in the measured specific heat values also affect the final thermal conductivity values. However, all of the above factors were comprehensively considered as part of the uncertainty determination, making it quite certain that the combined uncertainty in the thermal diffusivity measurement in this work is less than 3 percent, and the overall uncertainty in the thermal conductivity values is less than 6 percent.

1.6

Specific heat cp [J/g]

02

3. Results and discussion 3.1. Phase change temperature, latent heat, and specific heat of the samples The phase change temperature and latent heat of each sample, as well as the specific heats at ambient temperature and at 500 °C are shown in Table 4. The variation in specific heat of the prepared samples with respect to temperature is shown in Fig. 2. We can see from Table 4 that adding Cu, Zn, or Si to an aluminum alloy reduces the melting point of the sample. The Al-10.30Cu-9.84Zn alloy exhibits the lowest melting point of 518 °C, as well as having the lowest latent heat and a wide phase change temperature range more than 100 °C. The results in the table also show that a certain content of copper in the alloy improves the latent heat of the aluminum alloy and effectively reduces its melting point, while an Al-Cu alloy with thirty percent copper has the maximum latent heat per unit mass of all the tested samples, and with a narrow phase change temperature range no more than 12 °C. The phase diagram of Al-Cu alloy

01

1.4

03

1.2

04 05

1.0

06 0.8

07 08

0.6

09 10

0.4 0

100

200

300

400

500

Temperature T [°C ] Fig. 2. Variation in specific heat of the prepared samples with respect to temperature.

(Fig. S1) also shows that it has minimum phase change temperature range at about thirty weight percent of copper content. There was no significant effect on latent heat or specific heat from adding zinc to an aluminum alloy. Similarly, adding small amounts of Mg to the aluminum alloy did not greatly affect latent heat or specific

Table 4 DSC measurements of the prepared samples. Samples

Al-10.35Cu Al-20.39Cu Al-30.12Cu Al-40.13Cu Al-19.7Si Al-3.52 Mg Al-4.91Cu-5.04Zn Al-10.30Cu-9.84Zn Al-20.50Cu-10.45Zn Al-26.98Cu-10.10Zn

Phase change temperature range (°C)

Latent heat DH In mass (J/g)

548.0–638.9 551.7–611.8 554.0–568.7 559.0–569.4 587.1–597.1 637.3–650.8 626.7–646.9 518.4–620.6 527.6–583.3 528.7–542.7

284.9 291.8 326.2 305.8 372.1 290.0 335.3 267.1 298.0 283.6

Specific heat at 30 °C

Specific heat at 500 °C

In volume (J/cm3)

In mass (J/(g K))

In volume (J/(cm3 K))

In mass (J/(g K))

In volume (J/(cm3 K))

823.0 917.0 1118.8 1143.5 980.1 771.5 970.1 830.8 1005.7 1027.6

0.8895 0.9208 0.6479 0.5900 0.9621 0.7148 0.8702 0.8531 0.6354 0.6435

2.5694 2.8935 2.2223 2.2063 2.5341 1.9016 2.5176 2.6536 2.1443 2.3317

0.9035 1.0828 0.9963 0.5131 1.4079 0.9048 1.1431 0.8356 0.6483 0.9503

2.6098 3.4026 3.4171 1.9189 3.7084 2.4069 3.3070 2.5993 2.1879 3.4434

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Table 5 Fit expressions for the specific heat of the measured aluminum alloys (30 °C 6 T 6 500 °C). Samples

Expressions

Maximum deviations (%) 5

Al-10.35Cu

C P ¼ 0:84999 þ 9:19982  10

T

4.6

Al-20.39Cu

C P ¼ 0:84908 þ 2:91358  104 T

5.8

Al-30.12Cu

C P ¼ 0:59075 þ 7:57875  104 T

6.1

Al-40.13Cu

C P ¼ 0:54948  1:16513  104 T

6.0

Al-19.7Si

C P ¼ 1:11513 þ 5:0358  104 T

4.7

Al-3.52Mg

C P ¼ 0:69058 þ 4:57306  104 T

3.6

Al-4.91Cu-5.04Zn

C P ¼ 0:94403  5:82262  104 T þ 2:06044  106 T 2

9.1

Al-10.30Cu-9.84Zn

C P ¼ 0:96562  0:00149T þ 2:32876  106 T 2

9.3

Al-20.50Cu-10.45Zn

C P ¼ 0:71747  0:00131T þ 2:19015  106 T 2

9.8

Al-26.98Cu-10.10Zn

C P ¼ 0:73675  0:00135T þ 3:221  106 T 2

8.2

imum deviation with experimental results of less than 6.1% through a temperature range of 30–500 °C. The secondorder polynomial fit expressions of the ternary aluminum alloys in this study are also given in Table 5, with maximum deviations from the experimental results of less than 9.8% in the measured temperature range.

3.2. Thermal conductivities of the samples The thermal conductivities of the prepared samples were determined by using the thermal diffusivity data over a temperature range of 30–500 °C obtained with the Netzsch LFA427 laser flasher thermal analyzer and the specific heat data from the DSC measurements described above. The thermal conductivities of the measured samples at ambient temperature are shown in Fig. 3. The temperature dependent thermal conductivities of the samples are shown in Fig. 4. The figures show that the thermal conductivities of all the studied aluminum alloys are much lower than that of pure Al. The maximum observed thermal conductivity at ambient temperature is with the Al-10.35Cu alloy, similar to the thermal conductivity of the Al-19.7Si sample. However, the thermal conductivity of Al-10.35Cu decreases as the temperature increases, while the thermal conductivity of Al-19.7Si increases with increasing temperature. We can see from Fig. 3 that the thermal conductivity of the Al-Cu alloys decrease as the Cu content in the alloy increases. A similar phenomenon occurs with the ternary Al-CuZn alloys. None of the samples studied show a remarkable change in thermal conductivity with changing temperature. In fact, the variation in solid-state thermal conductivity with respect to temperature is

200

Al-10.35Cu Thermal conductivity [W/(m·K)]

heat, and had little effect on reducing the melting point. The specific heat of Al-3.52 Mg alloy illustrates an apparent increase when temperature lower than 325 °C and has no obvious increase when temperature higher than 325 °C. By consulting to Al-Mg phase diagram (Fig. S3), it can be known that eutectic Al-3.52 Mg has transformed to solid solution of monophase at about 325 °C. No more samples of Al-Mg were made note that it is difficult to prepare Al-Mg alloys by the method in this study due to the volatile characteristics of Mg. The Al-19.7Si alloy exhibits the highest latent heat of 372.1 J/g. While this value is larger than the latent heat value exhibited by the other samples, it is apparent less than the literature values given by different authors for Al-20Si as listed in Table 1, e.g. 460 J/g by Wang et al. (2006), 528.4 J/g by Huang et al. (1991), and 552.6 J/g by Wang et al. (2015). These differences can be attributed to different raw materials, experimental synthesis conditions, heating and cooling rates as well as with or without heat treatment of the samples. The casting of the samples in atmospheric condition with relative higher cooling rate in this study may have great effect on latent heat of the alloy. No heat treatment of the samples in our study may also have great effect on these differences. Huang et al. (1991) have indicated in their study that the latent heat value of Al-Si alloy increases apparently with the increase of thermal cycles and the prolonging of the heat preservation time. These differences also indicate the importance of the research on heat treatment effect on latent heat of metallic alloys in future studies. The Al-19.7Si alloy has the highest specific heat of all the prepared samples, increasing with temperature as shown in Fig. 2. Both the specific heat at ambient temperature (0.965 J/g) and phase change temperature (587.1 °C) of the Al-19.7Si alloy are quite close to the values of 0.970 J/g and 585.8 °C, respectively, measured by Huang et al. (1991). Also note that, if we consider the latent heat and specific heat by unit volume as shown in Table 4, the superiority of the Al-19.7Si alloy in terms of latent heat and specific heat over the Al-Cu alloys disappears because the AlCu alloys have a much higher density. The experimental results also show that the specific heat of the investigated Al-Cu and Al-Si alloys varies almost linearly with increasing temperature. By referring to phase diagram, it can be known that no solid-solid phase transitions occurring for these two kinds of alloys. However, the specific heat of the ternary aluminum alloys fluctuates considerably with the temperature increase. They all illustrate a minimum value at a certain temperature for Al-4.91Cu-5.04Zn alloy at 340 °C, Al-10.30Cu-9.84Zn at 360 °C, Al-20.50Cu-10.45Zn at 312 °C, and Al-26.98Cu-10.10Zn at 320 °C corresponding to different solid–solid phase transitions at these temperatures. We did not give the detailed studies of these phase transitions since they do not affect the application for the materials as PCMs. The linear fit expressions of the binary aluminum alloys in this study are given in Table 5, showing a max-

Al-19.7Si

180

Al-20.39Cu

160

Al-4.91Cu-5.04Zn 140

Al-10.30Cu-9.84Zn Al-30.12Cu

120

Al-3.52Mg Al-40.13Cu Al-26.98Cu-10.10Zn

100

Al-20.50Cu-10.45Zn 80 0

2

4

6

8

10

Sample numbers Fig. 3. Thermal conductivity of the prepared samples at ambient temperature.

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2700

220

[W/(m·K)]

180 160 140 120

01 02 03 04 05 06 07 08 09 10

2400

Heat capacity [J/cm3]

01 02 03 04 05 06 07 08 09 10

200

2100 1800 1500 1200

100 900 80

0

100

200

300

400

500

100

600

200

300

400

500

T [°C]

Temperature [°C] Fig. 4. The variation in thermal conductivity of the prepared samples with respect to temperature.

Table 6 Linear fit expressions for the thermal conductivities of the measured aluminum alloys (30 °C 6 T 6 500 °C). Samples

Expressions

Maximum deviations (%)

Al-10.35Cu Al-20.39Cu Al-30.12Cu Al-40.13Cu Al-19.7Si Al-3.52Mg Al-4.91Cu-5.04Zn Al-10.30Cu-9.84Zn Al-20.50Cu-10.45Zn Al-26.98Cu-10.10Zn

k ¼ 181:69  0:031t k ¼ 165:91 þ 0:0047t k ¼ 120:3 þ 0:0816t k ¼ 112:67  0:0513t k ¼ 183:36 þ 0:07343t k ¼ 111:11 þ 0:0888t k ¼ 152:63 þ 0:07515t k ¼ 129:49 þ 0:01033t k ¼ 99:99  0:02373t k ¼ 98:39 þ 0:02264t

2.3 3.7 3.4 5.2 3.2 3.5 5.8 2.3 3.6 3.9

accurately depicted by a linear relationship for all of the samples, as illustrated in Table 6.

3.3. TES capacities of the samples The TES capacity of PCMs includes both latent and sensible components because some temperature difference occurs during the TES process. The TES capacities of the prepared samples at different temperature ranges are shown in Fig. 5. Considering that the volume of a PCM has more effect than mass on the performance and cost of a heat exchanger, this paper presents the heat capacities referred to volume instead of mass. Fig. 5 shows that the TES capacity of the samples all increase linearly as the change in temperature increases, given the constant specific heat value of 500 °C adopted for the calculations. The figure also shows that the unit volume TES capacity of Al-19.7Si is not obviously larger than the unit volume TES capacity of some of the other samples, although the TES capacity of Al-19.7Si per unit mass is largest of all the samples due to its high latent heat per unit mass. The TES capacities of Al-30.12Cu and Al-26.98Cu-10.10Zn are equivalent to Al-19.7Si through the entire temperature difference range due to the larger density of the Al-30.12Cu and Al-26.98Cu-10.10Zn samples. Note that the Al-40.13Cu sample also has significant TES capacity at relatively low temperature differences, but its TES capacity increases slowly with increasing temperature difference due to it’s relatively smaller specific heat. These results also illustrate that the addition of elements with high densities into aluminum alloys—such as Cu and Zn—are very helpful for improving the TES capacity per unit volume of the material. It should also be noted that many factors must be comprehensively considered for proper PCM selection—in-

Fig. 5. TES capacity per unit volume of the samples for different temperature differences.

cluding the phase change temperature of the PCM, the operating temperature range of the exchanger, TES capacities, and cost of materials, and not simply focus on materials with high latent heat. 4. Conclusions This paper conducted experimental thermophysical property measurements for ten aluminum alloys prepared through casting method. A DSC analyzer was used to measure the phase change temperature, latent heat, and specific heat of the samples. A laser flash method was used to measure the thermal diffusivity, and further to derive the thermal conductivity of the samples. The results can be concluded as follows: (1) Additions of Cu, Zn, and Si in the samples all helped reduce the melting point of the aluminum alloys, with the Al30.12Cu and Al-40.13Cu alloys possessing the suitable phase change temperature range no more than 12 °C. The Al-19.7Si alloy sample had the highest latent heat of 372.1 J/g as well as the maximum specific heat of all the prepared samples, which increased with temperature. (2) If we consider the latent heat and specific heat per unit volume, the superiority of the Al-19.7Si alloy disappeared compared with the Al-Cu alloy due to the much higher density of the Al-Cu alloy. The TES capacity per unit volume of Al-30.12Cu and Al-26.98Cu-10.10Zn are equivalent to Al19.7Si through the entire temperature difference range observed in the experiments. The addition of elements such as Cu and Zn with high densities into the aluminum alloys was very helpful in improving the TES capacity per unit volume of the respective samples. (3) Linear fit expressions were used to depict the specific heat of the binary aluminum alloys, with a maximum deviation from the experimental results of less than 6.1%. A secondorder polynomial expression was used to depict the specific heat of the ternary aluminum alloys, with a maximum deviation from experimental results of less than 9.8%. Both sets of observations were over a temperature range of 30–500 °C. Linear fit expressions accurately depicted the change in solid-state thermal conductivity with respect to temperature for all samples. (4) A more in-depth study of thermal cycles and the heat preservation time effect on thermophysical properties, especially on latent heat of metallic alloy PCMs is still required in order to comprehensively unravel the TES properties of different metallic alloy PCMs.

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