Evaluation and Analysis of an Agro-Based Nano Refrigerant to Improve the Performance of a Domestic Refrigeration System

Refrigeration is a thermodynamic process that involves heat removal from an enclosed space [1]. Refrigeration has numerous applications in human activities such as food processing, storage, and transportation, air conditioning, ice manufacturing, chemical industry, civil engineering and mining (freezing of moisture in unstable water-bearing soils), biomedical applications, manufacturing, pharmaceutical industry and fundamental research [2]. Chillers are also commonly utilized for adjusting ambient temperature to make humans more comfortable through air conditioning. Refrigeration applications are classified as domestic refrigerators, commercial freezers, cryogenics, air conditioners, and heating systems [3]. These four components are useful in creating a cycle that results in the removal of heat from a body [4]. The system operates using a refrigerant as the working fluid. This fluid undergoes four main processes to reject the heat to the environment, and keep the system at a low temperature [5]. The industrial techniques of manufacturing refrigerants are hazardous to the environment, as well as expensive. It is excellent to utilize a more ecologically friendly option that improves the performance of the refrigerant and refrigeration process while utilizing agricultural waste items that would otherwise be discarded.

Nanotechnology is one of today's most exciting and rapidly evolving scientific disciplines. It is, at its core, a modern scientific field that is always changing with a change in the interest of academics and commercial institutions and new research is presented to the scientific community [6, 7]. It finds application not only in science, but also in other areas of life such as medicine and even agriculture. The use of nanotechnology and agricultural wastes as viable replacement for refrigerants has recently attracted more attetion from researchers. Afolalu et al. [8] evaluated the performance of several nanoparticles in a base mineral oil for household refrigeration systems. In the study, to make copper oxide nanoparticles, walnut shell was utilized as a reducing agent. The nanoparticle was blended with mineral oil to test if it improved the operation of the refrigeration system over ordinary mineral oil. Their results show a reduction in the pull-down time by a approximate value of 8.98% and the net refrigeration effect increased by about 9.3% for sample 0.75g, while the pull-down time was reduced by 9.51% and the net refrigeration effect increased by 19.05% for 1.25g of nanoparticle. In another study by Kumar [9], the influence of nanoparticles on refrigeration cycle performance characteristics was investigated. The study covered the behavior of several nanoparticles such as CuO ad TiO₂ throughout the vapor compression refrigeration cycle. They observed that the addition of nanorefrigerants increased the VCR system's heat transfer performance, particularly in nucleate and pool transferring boiling heat. In comparison to other nanoparticles, carbon nanotubes are the best candidate for heat transfer enhancement of base refrigerants. The rate of heat transfer increases as the nanoparticle dimension reduces, while the pressure drop lowers as the nanoparticle dimension decreases [9].

Adebisi et al. [10], investigated how to make silicon nanoparticles from agricultural waste. The goal of the study was to find a new way to use some agricultural wastes as potential supplies of silicon for PV cells, such as cassava periderm, maize stalk, and cob. The modified sol–gel process was used to make agro-based silica nanoparticles, which were then reduced with magnesium. Characterization softwares were used to characterize the products. Silicon nanoparticles with particle sizes less than 33.98 nm and purity of 98.89 percent, 31.20 nm and 99.89 percent, and 32.88 and 99.95 percent were reported. Also, Sözen [11] investigated the effect of using alumina (Al₂O₃) nanoparticles to promote passive heat transfer in an ammonia/water pair. He looked at how it was used in diffusion absorption coolers and how it affected the system's heat performance. Adding nanoparticles to a fluid improves heat transmission significantly as a result of the nanoparticles. Because of the nanoparticles, the fluid's capacity increases. As a result, the impact of Al₂O₃ nanoparticles in cooling/absorption fluid mixes on system performance was investigated in this work. The system with nanoparticles produced higher heat absorption characteristics according to the results of the studies. Because the heat transfer periods were shorter, the system's operation time was lowered. As a result, the desired temperature was achieved faster. Despite the suitability report as presented by Adebisi et al. [10] and Sözen [11], a major source of concern was the ecological consequence of using nanoparticles as refrigerant.

Hence, Vamshi et al.'s [12] study on the thermophysical parameters of a nano-refrigerant or nano-lubricant and their performance proved that the use of nanorefrigerant would not only ensure better performance for the system, but was also ecologically friendly. The review determined that as concentration rises, thermal conductivity rises as a result of rising temperature, and that nanoparticle concentration has a direct link with viscosity. Pressure drop increases as viscosity rises, necessitating high pumping power and hence high energy consumption to sustain flow. The industrial methods of synthesizing refrigerants are environmentally unfriendly and unsafe and expensive [13-15]. Although some hydro-chlorofluorocarbons (HCFCs) were first employed as a replacement for CFCs, they will be phased out globally between 2020 and 2030 due to their environmental consequences. HFCs, like CFCs and HCFCs, are artificial substances that do not exist in nature. As a result, it is obvious and far preferable to consider other natural sources [16], hence the need for agrowastes. This study therefore examines the use of an eco-friendly alternative that can boost the performance of the refrigerantsusing abundantly available agricultural wastes. Summarily, although previous studies on the use of nanomaterials and agrowastes in refrigerating systems have shown interesting results such as increased coefficient of performance, increase in cooling and heat absorption, however some of these refrigerant types have been confirmed as harmful to the environment and is currently being phased out. Some others are averagely expensive and should be better replaced with more affordable working fluid types. This current study is therefore unique as it presents the idea of nanorefrigerants developed from agrowaste which is readliy available in abundance [17].

3.1 Spectroscopical examination

The Electro-Dispersive X-ray spectroscopy (EDS) was used to determine the composition of elements in the synthesized SiO₂ nanoparticles and Rice husk ash. The micrograph in the Figure 4 for the Rice husk ash shows the percentage of silica in the sample. Nine elements were detected with varying concentrations with silica having the highest percentage concentration. The SiO₂ Nanoparticles were also analyzed using the Electro-Dispersive X-ray spectroscopy. The results showed an increased concentration of silica, Si (74.60%), with comparatively high concentrations of carbon and oxygen. The greater concentration being silica assures that the nanoparticles are silica nanoparticles. The nanoparticles were also analyzed through the spectrometer for the FT-IR analysis. This was used to identify organic materials. The technical technique obtained an infrared spectrum of absorption or emission of the particles while concurrently measuring its intensity over a limited range of wavelengths per time.

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Figure 4. (a) EDS Micrograph of Rice Husk Ash; (b) EDS Micrograph of developed nanoparticles; (c) FTIR graph for developed nanoparticles

3.2 Coefficient of performance

The coefficient of performance of a refrigerator is the ratio of net refrigerating effect and compressor work. A greater COP would lead to lower efficiency [18], power consumption and therefore lower cost of operations.

COP$=\frac{\left(h_1-h_4\right)}{\left(h_2-h_1\right)}$

The Table 1 shows the variations of the coefficient of performance for each sample with time.

Table 1. Variation in coefficient of performance

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Figure 5. Variation of COP

From the graph in Figure 5, the results indicate that the samples, 0.2wt% (S1), 0.3wt% (S2) and 0.4wt% (S3) had the highest COP with a 31.23, 23.7 and 35.1% increase in the COP compared to the control value respectively. The sample, 0.6wt% (S4) had the lowest COP, 14% lower than that of the control.

3.3 Pull down time

This is the necessary time to cool down the refrigerator from its ambient temperature to the desired temperature. The temperature values were gotten using thermocouples. The Table 2 indicates the readings for the different volume concentrations of the nano-refrigerant.

The graph in Figure 6 indicates a continuous decrease in the cabinet temperature across all samples from the initial start-up. A high reduction in the cabinet temperature after start-up signifies a high cooling rate [19, 20]. The sample 0.6wt% (S4) and 0.5wt% (S3) showed the best pull down time with temperatures of -6.1 and -3.1℃ at 240 minutes respectively. The sample 0.2wt% (S1) displayed a fairly constant temperature reading after 140 minutes. The sample 0.3wt% (S2) had the lowest cabinet temperature after 240 minutes.

Table 2. Pull down time per concentration

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Figure 6. Graph of pull down time per concentration

3.4 Discharge temperature

This is the temperature of the refrigerant exiting the compressor as depicted in Table 3. This was measured using the thermocouple K for each concentration and plotting against time.

The graph in Figure 7 shows a steady rise of the discharge temperature from the start of the experiment. The sample 0.6wt% (S4) having the greatest discharge temperature, approximately 2% greater than that of the control. On the other hand, the samples 0.2wt% (S1), 0.3wt% (S2) and 0.5wt% (S3) having low discharge temperatures that are 7, 17 and 16% lower than that of the control sample respectively. This is desirable as a lower discharge temperature would mean less compressor work [21, 22].

Table 3. Variation of discharge temperature with time

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Figure 7. Graph of variation of discharge temperature with time