Experimental Investigation on the Thermophysical and Rheological Behavior of Aqueous Dual Hybrid Nanofluid in Flat Plate Solar Collectors

Highlights

What are the main findings?

• Hybrid nanofluids have been used, including CF-CNTs and the hBN, as working fluid;
• Successfulness of functionalization and decoration was validated by FTIR, XRD, EDS, FESEM, and HRTEM;

What is the implication of the main finding?

• The thermal efficiency increases to 24.8% for mixed nanofluids;
• Application of nanofluids may reduce the price of the working fluid.

Abstract

This work investigates the thermal–physical and rheological properties of hexagonal boron nitride/carbon nanotubes (hBN/CNTs) applied to reinforce water-based working fluid in a flat plate solar collector (FPSC). The hybrid nanoadditives of hBN and the chemically functionalized CNTs (CF-CNTs) were suspended in distilled water (DW) with a nonionic surfactant. The hybridization ratio between CF-CNTs and hBN was optimized to be 40:60. The thermal efficiency tests on the solar collector were carried out using different volumetric flow rates (2, 3, and 4 L/min) under the ASHRAE-93-2010 standard. The morphological characteristics of the hybrid nanoadditives were evaluated using X-ray diffraction (XRD), ultraviolet–visible spectroscopy (UV–vis), field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM). Different concentrations of hBN/CF-CNTs were added to the water-based working fluid to record the optimal wt.% for maximum enhancement in the FPSC’s efficiency. The results revealed that using only 0.1 wt.% of hBN/CF-CNTs with a flow rate of 4 L/min remarkably improved the collector efficiency by up to 87% when compared to the conventional working fluid used in FPSC.

1. Introduction

1.1. Research Background and Motivation

Recently, the world has concentrated on energy conservation as the foundation for human growth together with global politics and economics [1]. New energy sources should be created to reduce the environmental impact of existing energy sources [2,3]. As a result, renewable energy technologies are becoming more efficient and beneficial [4]. Furthermore, a solar collector is a heat exchanger specializing in converting sunlight into energy types. In solar thermal applications, PV/T collectors convert thermal energy into electrical and thermal energy. Solar collectors are divided into two types: concentrated solar collectors and flat plate solar collectors (FPSCs) [5,6]. FPSCs absorb and convert solar radiation into heat energy for thermal applications, after which the heat is transferred to a solar liquid that runs over them [4]. The improved thermophysical properties of nanofluids when utilized as heat transfer fluids account for their prominence in solar applications [7]. The substitution of nanofluids for conventional fluids such as water and oils has been shown to increase efficiency in solar technology, both theoretically and empirically. The evolution of nanofluid synthesis has led in the development of more modern nanofluids known as hybrid nanofluids [8]. Hybrid nanofluids are created by combining two or three nanoparticles [5,9].

1.2. Literature Review

Previous FPSC research discovered that introducing metal nanoparticles such as copper into distilled-water-based nanofluids boosted thermal efficiency by about 24% [10]. Furthermore, aluminum oxide is one of the most often employed nanoparticles as well as one of the least expensive nanoparticles in solar collector research [11,12,13,14,15,16]. Farajzadeh et al. examined numerically and experimentally the impact of aluminum oxide/titanium dioxide–water nanocomposites and aluminum oxide–water and titanium dioxide-water single nanofluids on FPSC performance [17]. The results demonstrated that the nanocomposite nanofluid outperformed water and individual nanofluids. As a result, the rate of increase in collector thermal efficiency using nanocomposite nanofluid was equal to 26%, 19%, and 21%, when compared to water, aluminum oxide–water, and titanium dioxide–water, respectively. Verma et al. [18] investigated the energy and exergy efficiency of an FPSC in the presence of magnesium oxide/MWCNTs–water; copper oxide/MWCNTs–water; and magnesium oxide–water, copper oxide–water, and multiwalled carbon–water. The findings of their experiments showed that using MWCNTs–water, single nanofluid as the working fluid under various conditions (solar radiation intensity, nanoparticle volume %, mass flow rate, and inlet temperature) resulted in maximum energy and exergy efficiency; the thermal efficiency values for magnesium oxide/MWCNTs–water and copper oxide/MWCNTs were the second and third highest, respectively. Hussein et al. [19] developed new nanocomposite nanofluids by combining CF-MWCNTs, CF-GNPs, and h-BN nanoparticles in water as the basic fluid, and then tested the performance of an FPSC. They discovered that a collector based on nanocomposite nanofluids had a greater thermal efficiency than the base fluid. The collector based on nanocomposite nanofluids was stated to have a maximum thermal efficiency gain of 20% over water. Okonkwo et al. [20] conducted an energy and exergy analysis of an FPSC using aluminum oxide/iron-water hybrid nanofluids. Their investigation revealed that aluminum oxide–water single nanofluid performed better than hybrid nanofluids. As a result, the thermal efficiency and heat transfer coefficient of the aluminum oxide–water single nanofluid increased by 2.16 and 72%, respectively, as compared to the base fluid. Furthermore, the aluminum oxide/iron-water hybrid nanofluid was 1.79 and 56%, respectively. They did, however, show that the collector’s exergy using hybrid nanofluid and single aluminum–water was 6.9% and 5.7% more efficient than water, respectively. In an experimental investigation, Wole-Osho et al. [21] used hybrid nanofluids made of aluminum oxide/zinc oxide and water to assess the performance of an FPSC. They demonstrated that the rate of increase in collector thermal efficiency using aluminum oxide/zinc oxide hybrid was equal to 7, 5, and 4.5% compared to the base fluid. They employed varied volume ratios of aluminum oxide to zinc oxide equal to 50:50, 66.66:34.34, and 33.34–66.66%. The collector exergy efficiency increase rate was equal to 6, 7.5, and 9%, respectively. According to Sundar et al. [22], who investigated the performance of an FPSC utilizing iron oxide–water nanofluid, the collector’s thermal efficiency could be increased by a maximum of 27% when employing nanofluid in comparison to the base fluid. Sundar and his team [23] examined the effect of nanodiamond/cobalt–water hybrid on FPSCs. They claimed that the hybrid collector’s thermal efficiency was 20% higher than the base fluid for a volume fraction of 0.15%. Different thermal and hydrodynamic parameters of an FPSC were evaluated using three working fluids: water, aluminum oxide/copper–water hybrid nanofluid, and aluminum oxide–single water nanofluid. The nanoparticle volume fraction was equal to 0.1%. In comparison to previous working fluids, the hybrid nanofluid collector had higher thermal efficiency. In comparison to water and aluminum oxide–water single nanofluid, its greatest improvement in collector thermal efficiency was 4.23 and 0.36%, respectively. Additionally, 3.86% more thermal efficiency was achieved using aluminum oxide–water single nanofluid than with water [24].

1.3. Research Objectives

According to the literature review, hybrid nanofluids can produce the desired effects in solar collectors by choosing the correct pair of nanomaterials. However, there has been insufficient research completed on how hybrid nanofluids operate when two nanomaterials are combined in various weight ratios. Although carbon-based nanoparticles such as MWCNTs have poor rheological properties, placing them in a fluid with the correct ratios can improve the thermal properties of hexagonal boron nitride (hBN). Therefore, this study aimed to investigate the preparation of a water-based hBN/CF-CNTs hybrid nanofluid system and its impact on the thermal performance of FPSCs when used as a working fluid. The thermal–physical properties of the nanocomposites were measured at different temperatures. Moreover, the thermal performance was tested under different conditions, for example, mass fractions and parameters such as energy efficiency, heat transfer, and hydrodynamic properties. Finally, a performance index (PI) was chosen as an appropriate parameter to measure the effectiveness and usefulness of using different nanofluids as working fluids in FPSCs.

2. Methodology

2.1. Preparation and Fabrication of the Hybrid Nanofluid

In this study, pure CNTs were acquired from XG Sciences, Lansing, MI, USA, with an individual dimension of 15 nm in diameter, 5 μm in length, and 95% purity. The white solid nanoparticles with layered construction of hexagonal boron nitride (hBN) and purity > 99%, molar mass = 24.82 g/mol, density = 2.27 g/cm³, and melting point = 2973 °C were procured from Sigma-Aldrich Co., Selangor, Malaysia. Sulfuric acid 95–97% (H₂SO₄) and nitric acid 65% (HNO₃) were acquired from Sigma-Aldrich Co., Selangor, Malaysia, and were utilized as functionalized strong-medium.

The functionalization process and the CF-CNTs nanofluid preparation were based on the method described in [25]. Before the thermophysical analysis, the hybrid nanofluid was first synthesized at varying weight concentrations, 0.05, 0.08, and 0.1 wt.%, via a two-step method using 40% CF-CNTs with 60% hBN/water.

Table 1. Details of the samples with different ratios of hybrid nanofluid following preparation.

Ratio	CF-CNTs + h-BN
	20 + 80%	30 + 70%	40 + 60%
Zeta potential (mV)	22.8	26.1	−30.5
Particle size (nm)	2630	2377	2423
Thermal conductivity at 60 °C (W/m-K)	0.844	0.853	0.869

shows the sample compositions used to determine the optimal powder amounts for different ratios of hybrid nanofluid. The different concentrations of hybrid nanofluid solution were initially prepared by weighing the sample in mass equilibrium, while the specific heat of the different samples was measured immediate in FPSC. In the first step, the mixing was moved for 30 min before being soaked in an ultrasonic water bath for 2 h at 60 °C, followed by stirring in an ultrasonic agitator for 30 min at 750 ± 50 Hz for 1 h. The first solution of CF-CNTs/water with the highest concentration was prepared by adding DW as the base working fluid. In the second step, hBN and Tween-80 were added at a ratio of 1:1 into the solution with the required quantity. To define the optimum Tween-80 in the hybrid nanofluid, the stability, foaming, and aggregation of the hybrid nanofluid samples were prepared at different concentrations. The container was frequently cooled to block the surface-active agent from evaporating during the nanofluid preparation. The synthesized hybrid nanofluid indicated uniformity and good stability with no sedimentation while being monitored visually for 48 h. Figure 1 shows graphically the molecular construction of the mixing nanofluid. The nanoparticles remained a sedimentary coagulate under a stationary state [26].

$$\varnothing \times 100=\frac{\left[W_{particle}/{\rho }_{particle}\right]}{\left[W_{particle}/{\rho }_{particle}]+[W_{fluid}/{\rho }_{fluid} \right]}$$

(1)

2.2. Performance of Flat Plate Solar Collector (FPSC)

Using DW as the absorber fluid, the thermal performance of the FPSC was conducted from April to August 2020 on sunny days between 8 a.m. and 5 p.m. under steady-state conditions. The average wind speed measured using a thermo-anemometer was 2 m/s, while the transient effects were ignored. A Tenmars Solar Meter was used to record the solar radiation. In addition, a Bronkhorst electromagnetic flow meter was employed to measure the volume flow rate with an accuracy of 1%. The efficiency of the hybrid nanofluid on the FPSC performance was determined using three different flow rates: 2, 3, and 4 L/min. The experimental data were recorded after a 15 min interval by examining the test as a quasi-steady reaction. Consistent experimental data used for a set of operative conditions were then selected for analysis to ensure repeatability. The experimentally measured information was fit to a linear curve to determine the actual parameters of the FPSC.

2.3. Characterization Analysis

The dispersion stability of the hybrid nanofluid was assessed by ultraviolet–visible (UV–vis) spectrophotometry (UV-800/900, Lambda Company, San Francisco, CA, USA), which measures the light absorbance of the suspension in the range 200–800 nm to quantify the stability. All models were situated and measured at confirmed time intervals for more than 30 days using specific quartz cuvettes suitable for the UV–vis region. Prior to measurement, all models were diluted with DW at a ratio of 1:20 to achieve sufficient light transmission.

The main structure of the synthesized water-based hBN/CF-CNTs hybrid nanofluid was analyzed using high-resolution transmission electron microscopy (HRTEM) (E.A. Fischione Instruments, Inc., Export, PA, USA). A lacey carbon connection was put onto a drip of all FETEM samples after the water-based hBN/CF-CNTs hybrid nanofluid was sonicated in deionized water for 15 min before analysis. In addition, FESEM (JEM-2100F, Tokyo, Japan) was used to examine the synthesized water-based hBN/CF-CNTs hybrid nanofluid. Moreover, FTIR spectroscopy was ideal for evaluating the samples during a wavenumber in the range 400–4000 cm⁻¹. Additionally, an Empyrean X-ray Diffractometer (XRD) (Panalytical) was employed to determine the phase composition with a Cu–Kα irradiation above a 2θ range of 20–80°. The XRD profiles were compared to the Joint Committee on Powder Diffraction and Standards using PANalytical X’Pert HighScore software.

The Anton Paar rotating rheometer with double gap DG 26.7 (Physica MCR 92, Enigma Business Park, Grovewood Road, Malvern, UK) was applied to determine the steady-shear rheological property of DW and water-based hBN/CF-CNTs hybrid nanofluid. The rotational rheometer comprises a parallel stationary cylindrical surface and a moving cylindrical plate with a small interval between them. The temperature and concentration ranges (20–60 °C and 0.05–0.1 wt.%, respectively) were used to test all samples. Furthermore, the thermal conductivity of the synthesized nanofluid was determined using a KD2 Pro analyzer (Decagon Devices, Inc., Pullman, WA, USA) with approximately 5% accuracy. A KS-1 probe was equipped via the hot wire transient method with its operating principle based on a single-needle sensor with 1.3 mm diameter and 60 mm length. The WNB22 water bath (Memmert, Germany) with a 1.4 kW power source was applied to maintain the preferred temperature of the samples with 0.1 °C accuracy during the measurements. Moreover, the specific heat capacity of the hybrid nanofluid and base fluid was determined using a DSC 8000 (Perkin Elmer, Waltham, MA, USA) with ±1.0% accuracy.

2.4. Experimental Procedure and Calculation

Figure 2 shows the experimental steps of a slightly modified standard commercialized solar water heater equipped with FPSC. The FPSC was inclined at a 10° angle under laminar conjugated mixed-convection heat transfer. The test rig consists of an automatic water heating system that harnesses and stores solar energy in a hot water storage tank at a daily average temperature of 50–70 °C. In addition, electrical immersion heaters were also installed as a reserve heating component to regulate and raise the hot water temperature. Figure 2a shows the schematic back view of the installed setup on the platform, which includes FPSC, storage tank, expansion tank, solar meter, air vent, pump station, and hand pump as the main components. The graphical diagram of the setup is shown in Figure 2b. The specification of the FPSC is given in detail in

Table 2. Specifications of the flat plate solar collector system.

No.	Factors	Specification	Unit
1	Dimensions	1988 × 1041 × 90	mm
2	Weight	37.2	kg
3	Gross Area	2.07	m2
4	Absorber Area	1.89	m2
5	Absorptance (%)	95	--
6	Emittance (%)	3	--
7	Number of Risers	10	--
8	Thickness of Glass	4	--
9	Transmittance of Glass	91%	mm
10	Insulation Material	Rockwool	--
11	Max. Operating Pressure	10 bar	--

. The performance parameters of the FPSC were calculated as follows: The instantaneous solar thermal efficiency that links the valuable energy to the total irradiation incident on the solar thermal surface is defined by Duffie [27] in Equations (2)–(4):

$${\mathsf{\eta }}_i=\frac{Q_u}{Ac · G_t}$$

(2)

$$Q_u=m ·C_p \left(T_{out}-T_{in}\right)$$

(3)

$${\mathsf{\eta }}_i=F_R\left(\tau \alpha \right)-F_R{U}_L\frac{\left(T_{in}-T_a\right)}{ G_t}$$

(4)

The heat removal factor (F_R) is expressed by Equation (5) as:

$$F_R=\frac{m ·C_p \left(T_{out}-T_{in}\right)}{A_c\left[S-U_L \left(T_{in}-T_a\right)\right] }$$

(5)

For a thermal solar collector operating under steady radiation and working fluid flow rate, the F_RU_L and F_R (τα) factors are almost constant. If the thermal efficiencies are plotted against T_in − T_a/G_t, a normal line results. S is the effective radiation on the collector. The intercept (joint of the line with the vertical thermal efficiency axis) equals the F_R (τα), and the slope of the line equals the F_RU_L. This slope indicates how much energy was removed from the solar collector. The intercept demonstrates maximum thermal efficiency when the fluid temperature entering the collector equals the ambient temperature.

2.5. Uncertainty Analysis

According to the ASME guidelines [28], the true absolute measurement could not be measured. The experimental measurements are also biased to specific errors, which may be contributed by systematic errors (calibration and data recording) and random errors (data fluctuations due to unsuitable instruments). The main sources of uncertainty during the experimentation were the errors that corresponded with the temperature, flow rate, and solar radiation measurement in Equation (2). Therefore, the measurement uncertainties were evaluated to analyze the deviation between the accuracy of measurements and the experimental parameters. The general equation for the uncertainty test is fixed as [29]:

$$U_y^2={\sum }_{i=1}^n{U}_{xi}^2\dots$$

(6)

where U_y is defined as the overall uncertainty of the studied details and U_xi represents the root sum square of disarranging and the mensuration uncertainty of all parameters. Thus, the complex uncertainty of the solar thermal efficiency Uƞ was obtained via the root sum square process, as follows [30]:

$$U_{{\mathsf{\eta }}_i}=\sqrt{(\frac{\Delta m}{m}}{)}^2+{(\frac{\Delta \left(T_{out}-T_{in}\right)}{T_{out}-T_{in}})}^2+{(\frac{\Delta G_t}{G_t})}^2$$

(7)

The mistakes in specific heat capacity (C_p) and (A_c) were considered insignificant. Similar relevance was used to measure the thermophysical properties of the nanofluid.

Table 3. Technical properties, accuracy, and overall uncertainty of the tools.

Device	Operating	Accuracy	Overall Uncertainty
Flow meter	0–4 L/min	±1%	±0.000128%
Data logger	0–1200 °C	±0.8%	±9.6 °C
Fluid flow rate	0–10 kg/s	±0.5%	0.05 kg/s
Thermometer	0–150 °C	±0.15	±0.077 °C
Pyranometer	0–1900 W/m2	±1.5%	±1.5%
Thermocouple	0–1300 °C	±0.1	±0.14%
Anemometer	0–20 m/s	±0.01 m/s	±0.011%
Fluid pressure drop	0–25 kPa	±0.3%	±0.075%
Solar irradiation	1300 W/m2	±5%	65 W/m2
Thermal efficiency	-	±0.1	±1.83%

describes the experimental data’s procedural qualifications, precision, and overall uncertainty within an acceptable range.

3. Results and Discussion

3.1. Characterization of hBN@CNTs Hybrid Nanofluid

Figure 3 illustrates the XRD pattern of the hBN-coated CF-CNTs. The peak at 23° indicates the CF-CNTs structure, while the three diffraction peaks at 20°, 26°, and 58° correspond to the (111), (200), and (220) lattice cubic hBN planes (JCPDS card no. 00-001-1194). The XRD profiles verified the absence of unexpected reactions during the chemical reduction, acid treatment, and hBN-coating procedures. It can also be inferred that hBN nanoadditives are present and successfully deposited on the CF-CNTs.

The morphological characterizations of the hBN-coated CF-CNTs nanoadditives are given in Figure 4a. The regular distribution of hBN engagement on the CF-CNTs can be noted in FESEM from Figure 4c,d. The hBN nanoadditives attachment to CF-CNTs can indicate a successful chemical treatment, ensuring a decrease in practical clusters, which are finally responsible for suitable unchanging attachment of hBN on CF-CNTs. The EDX measurements (Figure 4b) indicate three nanocomposite components: carbon, oxygen, and boron.

The FTIR spectra of the CF-CNTs and hBN-coated CF-CNTs hybrid are presented in Figure 5. The spectral bands at 1100 cm⁻¹ of the chemically treated CF-CNTs are associated with C-O stretching vibration of the C-C bonds and phenol/lactone group, while the peak at 1600 cm⁻¹ is designated as aromatic C=C bond stretching [31]. A number of emerging peaks in the 3400–3460 cm⁻¹ region are attributed to the -OH group in the atmospheric water molecules on the material’s surface [32]. The peaks also appeared sharper, which may be due to the functionalization process that introduced functional groups onto the nanotube surfaces [31]. Lower intense peaks were detected in the 3400–3460 cm⁻¹ region in the hybrid sample, which are absent in the chemically treated CF-CNTs, signifying the existence of hBN in the form of hBN-OH and the carboxyl group on the chemically treated CF-CNTs sidewalls [30]. Furthermore, the band at 2920 cm⁻¹ is consistent with the stretching vibration of the C-H bond, which decreased in strength as hybridization was established (Figure 5a), proving the presence of hBN on the chemically treated CF-CNTs surface. In terms of the functionalized CNTs, the 1710 cm⁻¹ adsorption peak corresponds to the stretching vibration of the C=O in the -COOH group. The shifting of the 1650 cm⁻¹ peak to 1600 cm⁻¹ in the hybrid samples implies that the attached -COOH group on the chemically treated CF-CNTs was accountable for the interaction with hBN. Finally, the 500 cm⁻¹ adsorption peak, shown in Figure 5b, represents the vibrational properties of the hBN-O bond, which further indicates the presence of hBN.

UV–vis spectrophotometry was performed to analyze the nanoparticle dispersion in water, which is commonly associated with the homogeneity of the suspension for absorbance. According to Beer–Lambert’s law, the absorbance property of a solution immediately corresponds to the weight concentration of the absorbing form, for example, the concentration of nanoparticles in a solution. Based on Figure 6a, UV–vis of different hBN/CF-CNTs hybrid nanofluid system ratios recorded a sharp peak at 220 nm, indicating the appearance of CF-CNTs and hBN nanoparticles. Figure 6b,c present the details of nanoparticle size distribution and zeta potential for hBN@CF-MWCNTs after 20 days; hBN/CF-CNTs recorded a high zeta potential (−26.2 mV) 20 days after preparation. Water-based hBN/CF-CNTs hybrid nanofluids presented diffident zeta potential values for 20 days, respectively. Thus, it is concluded that water-based hBN/CF-CNTs nanofluids at 0.1 wt.% are suitable via the presence of additional stably eminent nanofluids relative to other hybrid nanofluids. The common size distribution for water-based hBN/CF-CNTs hybrid nanofluids at 0.05 wt.% was additional land sliding compared with the same view for 0.1 wt.%. The nanoparticle size dispersal for water-based hBN/CF-CNTs hybrid nanofluids at 0.05 wt.% was 1882 nm after 20 days. However, the synthesis of nanofluids at 0.1 wt.% was 2100 nm, comparatively similar for both systems.

Moreover, there was minimal agglomeration or sediment generated in the nanofluid after 30 days. The most significant factors that participate in the high stability of the aqueous hybrid nanofluid dispersion were determined, as shown in Figure 6b,d.

3.2. Thermophysical Properties of Nanofluids

It is essential to conduct a thorough characterization analysis and quality evaluation of the developed nanofluid to understand the transmission features of the absorber working fluid prior to being applied in the FPSC.

Figure 7 shows the thermal conductivity result with respect to the weight concentration and temperature of the hBN/CF-CNTs in water. The average thermal conductivity error of approximately 1.172% corresponds with the National Institute of Technology and Standards [33] and is within the recommended measurement limits Figure 7a. As depicted in Figure 7b, the thermal conductivity improved by increasing the testing temperature. From the results, the thermal conductivity of the aqueous hybrid nanofluid improved significantly at 0.1 wt.%, the thermal conductivity enhanced by 4.665, 4.667, 13.964, 22.017, and 34.361 for 20, 30, 40, 50, and 60 °C, respectively. The reduced interfacial thermal contact resistance among the base working fluid and solid nanoadditives at elevated temperatures can probably induce the thermal conductivity of the hybrid nanofluid [34,35]. It is assumed that the outstanding improvement of the thermal conductivity of hBN/CF-CNTs nanofluid was primarily due to the synergistic reaction between the 1D CF-CNTs and 2D hBN in the base liquid. The use of the percolation model conveniently describes the nanofluid, which indicates the nanofluid’s high thermal conductivity, showing the extended bonds of complex networks produced by the CF-CNTs served as the conducting paths [36]. Since forming such networks with hBN normally requires a high-aspect ratio for nanotube geometry, a colloidal mixture comprising CF-CNTs with a high-aspect ratio and hBN networks served as excellent heat-transmitting conducting paths to strengthen the thermal conductivity of the hybrid nanofluid, which justifies the outstanding performance of the hybrid nanofluid.

As illustrated in Figure 8, the viscosity evaluation corresponded well with the NIST standards (average error of ±3.25%) [32]. In this research, we apply water-based hybrid of CF-CNTs with hBN with three different quantities of weight concentration of nanoadditives (0.05, 0.08, and 0.1 wt.%). Figure 8a,b illustrate the viscosity variation with different temperature and shear rates for two water-based hybrids of CF-CNT with hBN. Both water-based hybrids show non-Newtonian conduct because the dynamic viscosity of the two nanofluids is different nonlinearly by shear rate. Conversely, decorated CF-CNTs water-based nanofluids show the dilatant conduct in which the dynamic viscosity of the nanofluid samples increases relative to increasing shear rate. It was found that in all decorated CF-CNTs water nanofluids, viscosity decreases with increasing temperature and increasing concentration [37]. The comparison results between nanofluid of CF-CNTs with hBN at 20 °C and 0.1 wt.% are given in Figure 8a. As can be seen, the dynamic viscosity of CF-CNT with hBN (0.1 wt.%) nanofluid is higher than that of CF-CNTs with hBN (0.05 and 0.08 wt.%). It can be established that the section of CF-CNTs in the water-based hybrid of CF-CNTs with hBN (0.1 wt.%) is higher than that of CF-CNTs with hBN (0.05 and 0.08 wt.%). Therefore, the high viscosity of CF-CNTs with hBN (0.1 wt.%) can be attributed to the appearance of a high section of CF-CNTs. In overall-decorated hybrid nanofluids, dynamic viscosity decreases with increasing temperature and increasing weight concentration.

Under different temperature conditions, the standard specific heat values compiled by Arnold [38] were used to compare the reliability of the specific heat measurement of DW. Furthermore, Figure 9 depicts the reduced and elevated specific heat capacities of the hybrid nanofluid with respect to the nanoparticle concentration and temperature. At 60 °C, the hybrid nanofluid at 0.05 wt.% recorded a specific heat capacity of 4.025 J/g °C. Given that effective thermal conductivity increased with the weight concentration, the increase in the specific heat of the hybrid nanofluid with temperature was marginal when compared to the decrease in particle concentration, as expected. The specific heat capacity of the hybrid nanofluid is a vital parameter in thermal management systems, where the thermal conductivity enhancement relies on the specific heat capacity of the hybrid nanofluid. Nevertheless, the comparative analysis of the influence of particle weight concentration toward the specific heat of nanofluids is limited [39,40].

3.3. Water as Working Fluid

Figure 10 demonstrates the average solar radiation (G_t), ambient temperature (T_a), and the fluid temperature at the inlet (T_i) and outlet (T_o) collector when water was utilized as the working fluid during a clear sky. The experimental results were analyzed based on the solar collector efficiency against the decreased temperature parameter ((T_i − T_a)/G_t). The reproducibility of the experimental results was influenced by various factors, such as cloudy periods and a sudden change in weather. Figure 11 shows the data collection for solar insolation on a clear day and a cloudy day to analyze the performance of the solar collector. At the same time, Figure 12 depicts the varying solar collector efficiency according to base fluid flow rate and distilled water as the absorber’s working fluid. The FPSC efficiency improved when the DW flow rate increased. Additionally, F_RU_L refers to the drop of the curve fit line of the plotted data. F_RU_L at flow rates of 2 and 4 L/min were approximately 6.3265 and 6.5424, respectively. Conversely, the F_R (τα) represents the intercept of the curve fit line of the plotted data. The F_R (τα) at flow rates of 2 and 4 L/min were 0.6876 and 0.7405, respectively.

Table 4. Values for the removed energy parameter and the absorbed energy parameter, and the regression coefficient for the base working fluid at difference flow rates.

Working Base Fluid	FRUL	FR (τα)	R2
DW at 21 pm	6.3265	0.6876	0.9816
DW at 31 pm	6.6567	0.7187	0.9930
DW at 41 pm	6.5424	0.7405	0.9965

summarizes the F_RU_L, F_R (τα), and regression coefficient (R²) values for the curve line based on the plotted data.

The removed energy parameter and F_R ($\tau \alpha$) of the base fluid at a flow rate of 4 L/min were enhanced by 25.8% and 12.2%, respectively, compared to that at 2 L/min. The findings indicate that the FPSC efficiency may be improved by elevating the flow rate of the absorber fluid since the F_R ($\tau \alpha$) values increased with an elevated flow rate while the F_RU_L values remained approximately fixed.

3.4. Hybrid Nanofluid as the Working Fluid

Furthermore, the quasi-steady empirical outputs were recorded according to the FPSC efficiency against the decreased temperature (T_i − T_a)/G_t within 15 min. Note that this study examined consistent empirical data only. Based on Figure 12, the elevated volume flow rate of the base fluid results in increased F_R (τα) values, which subsequently improved the performance of the FPSC. Whereas, F_RU_L remained constant, as reflected by the curve fit line slope. Hence, the increased absorber fluid flow rate significantly improved the FPSC efficiency.

The linear graph in Figure 13 demonstrates the relationship between the FPSC efficiency and the decreased temperature parameters for each hybrid nanofluid. The graph linearity follows the governing relation, as expressed in Equation (4). The efficiency line from the numerical outcome was also detected at a flow rate of 4 L/min. It is reasonable to suggest that the radiation intensity influenced the collector efficiency. Additionally, Figure 14 shows the experimental FPSC efficiency of hBN/CF-CNTs nanofluid against the reduced temperature parameter (T_i − T_a)/G_t) at 0.05 wt.% and different flow rates of 2, 3, and 4 L/min. A linear trend line is added to each flow rate group in this figure to highlight the effect of flow rate on efficiency. As a result, it is evident that as the flow rate increases, the collector’s efficiency increases, which may be attributed to lower surface temperature, resulting in less heat loss from the collector, i.e., greater collector efficiency [41]. Moreover, the FPSC efficiency of hybrid nanofluid with different mass fractions at 4 L/min against the reduced temperature parameter (T_i − T_a)/G_t is presented in Figure 15. It obvious that at a constant flow rate, the thermal efficiency of FPSCs was enhanced by increasing the nanoparticle mass fraction. This enhancement can be attributed to the enhancement of thermal conductivity and heat transfer coefficient by increasing the amount of nanomaterials in the base fluid [42].

The experimentally measured data were fitted with a linear curve to identify the characteristics.

Table 5. Comparison of removed energy parameter and absorbed energy parameter for hybrid nanofluids given various weight concentrations and different flow rates, together with their regression coefficients.

Hybrid Nanofluid (wt.%)	Flow Rate (L/min)	FRUL	FR (τα)	R2
0.05	2	9.9864	0.7920	0.9921
	3	7.4332	0.8133	0.9874
	4	7.8876	0.8234	0.9936
0.08	2	7.9330	0.8121	0.9941
	3	8.1451	0.8333	0.9974
	4	8.9672	0.8410	0.9897
0.1	2	9.3220	0.8212	0.9986
	3	10.2155	0.8486	0.9992
	4	10.7422	0.8677	0.9987

lists the comparison among the F_RU_L, F_R ($\tau \alpha$), and R² values at various weight concentrations and flow rates of the hybrid nanofluid. At a flow rate of 4 L/min, the enhanced F_R ($\tau \alpha$) was 6.8%, 6.2%, and 17% for the absorber fluid at 0.05, 0.08, and 0.1 wt.%, respectively, compared to that of the working base fluid. The improvement of the removed energy parameter and absorbed energy parameter for the hybrid nanofluid at various concentrations and flow rate compared to the corresponding flow rate of the base working fluid is shown in

Table 6. Enhancement of removed energy parameter and absorbed energy parameter for hybrid nanofluid, compared with DW.

Hybrid Nanofluid (wt.%)	Flow Rate (L/min)	FRUL (%)	FR (%)
0.05	2	53.6	7.1
	3	15.3	5.7
	4	22.8	6.8
0.08	2	24.7	6.7
	3	24.3	5.5
	4	40.9	6.2
0.1	2	41.5	14.8
	3	52.4	15.4
	4	56.3	17

. Additionally, Figure 16, Figure 17 and Figure 18 depict the varying pressure drop, pumping power, and average Nusselt number of the FPSC with respect to Reynolds number for different water-based hBN/CF-CNTs hybrid nanofluids. The pressure drop increased linearly with Reynolds number, which was similar to all nanofluids. Interestingly, the density of nanofluid was also a crucial factor influencing the pressure drop. As previously stated, the density of the hybrid nanofluid increased correspondingly with the nanoparticle weight concentration. Therefore, the frictional loss and density gradient were greater at higher nanoparticle weight concentrations, although the pressure drop later increased. Since the water-based hBN/CF-CNTs hybrid nanofluid exhibited the highest density, it recorded the largest pressure drop compared to other nanofluids. Apart from density, dynamic viscosity was identified as another factor that influenced the pressure drop. Although nanoclusters support more excellent thermal transport properties, the viscosity gradient eventually increases. The power consumption of a heat transfer loop is significant because we must evaluate both energy consumption and energy savings to optimize thermal system energy utilization. Figure 17 shows the pumping power using 0.05, 0.8, and 0.1 wt.% of hybrid nanofluids. Once the pressure drop at 0.1 wt.% hybrid nanofluid reached the highest threshold, the corresponding pumping power was relatively high, which increased by 3.4%, 5%, and 6.2% at 0.05, 0.08, and 0.1 wt.% hybrid nanofluid concentrations, respectively, compared to that of water. Moreover, Figure 18 indicates the average Nusselt number using 0.05, 0.8, and 0.1 wt.% of hybrid nanofluids versus Reynolds number. As per the fundamental of heat transfer, the fluid with the highest Prandtl number (Pr) presented the highest value of the Nusselt number and vice versa. In this study, at 30 °C, the value of Pr using DW, 0.05 wt.%, 0.08 wt.%, and 0.1 wt.% equaled 5.874, 6.157, 6.357, and 6.495, respectively. The influence of the Prandtl number on the Nusselt number at a given Reynolds number is clear in this regard.

Figure 19 depicts the collector efficiency of the hBN/CF-CNTs hybrid nanofluid at varied weight concentrations and volume flow rates. Thus, it was deduced that the hybrid nanofluid demonstrated exceptional heat transfer properties, which relates to nanoconvection as the possible mechanism that influences energy transport.

Furthermore, the high thermal conductivity of dispersion and the corresponding Brownian motion of particles are suggested as the major factors contributing to the improved thermal conductivity. As shown in Figure 15, the efficiency of the FPSC is directly associated with the concentration and flow rate of the hybrid nanofluid. The FPSC achieved a maximum efficiency and flow rate of 87% and 4 L/min, respectively, at 0.1 wt.% hybrid nanofluid. Meanwhile, the performance index values improved as the weight concentration increased from 0.05 to 0.08 and 0.1 wt.% hybrid nanofluid, as depicted in Figure 20. Irrespective of the weight concentration and flow rate, the values of all the performance indexes were higher than 1, indicating that the FPSC efficiency was superior to the pressure drop. Therefore, the water-based hBN/CF-CNTs hybrid nanofluid system developed in the present study could be used as an alternative working fluid in FPSC applications. Figure 21 summarizes the comparison of the performance of carbon nanotube-based nanofluids from several recently published studies. The overall research findings highlight that using low-weight concentrations can achieve sufficient thermal efficiency in medium-temperature applications.

4. Conclusions

This study successfully developed a water-based hBN/CF-CNTs hybrid nanofluid and its effect as a working fluid on the thermal performance of FPSCs. The chemical functionalization process synthesized a homogeneous and stable dispersion of CNTs in the hybrid system. The optimum combined ratio of the CF-CNTs and hBN was 40:60. The thermal conductivity of the aqueous hybrid nanofluid at 0.1 wt.% improved up to 40% and 8% at 60 and 20 °C, respectively, when compared to conventional water-based working fluids, indicating the significance of thermal conductivity on the convective heat transfer. In addition, the average density and specific heat of the hybrid nanofluid distilled water increased up to 0.18% and 14.5%, respectively, at 0.1 wt.% and 60 °C.

Furthermore, the FPSC efficiency improved with the increased flow rate, where the highest F_R (τα) value was obtained at a flow rate of 4 L/min. Overall, the flow rates of 2, 3, and 4 L/min recorded enhanced collector performances of 10.8%, 18.6%, and 24.8%, respectively, with only 0.1 wt.% nanoadditives. Additionally, the application of the hybrid nanofluid substantially increased the absorption efficiency of the FPSC. With only 0.1 wt.% hBN/CF-CNTs, the heat absorption efficiency was remarkably enhanced by 17% relative to distilled water, followed by 6.2% and 6.8% improvement with the addition of 0.05 and 0.08 wt% nanofluid, respectively. The highest observed F_RU_L and F_R (τα) at 4 L/min volume flow rate and 0.05 wt.%, the corresponding values at 0.08 and 0.1 wt.% showed an enhancement of 6.2% and 17%, respectively.

According to the FPSC energy efficiency and performance index, it was concluded that the water-based hybrid nanofluid at 0.1 wt.% was the most effective working fluid to achieve optimum FPSC performance. The improved thermal efficiency offers convincing evidence that the proposed hybrid nanofluid exhibits higher additive or nanoparticle concentrations, which can be utilized as an alternative to replace conventional working fluids and promote greater energy efficiency in renewable energy systems.