# Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis

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## Abstract

**:**

_{2}O

_{3}) were used as an additive. The mixing was carried out according to the highest specifications adopted by the researchers, and the thermophysical properties of the fluid were carefully examined. The prepared nanofluid properties showed a limited effect of the nanoparticles on the density and viscosity of the resulting fluid. As for the thermal conductivity, it increased by increasing the mass fraction added to reach 140% for the case of adding 2% of nano-Fe

_{2}O

_{3}. The results of the zeta voltage test showed that the supplied suspensions had high stability. When a mass fraction of 0.5% nano-Fe

_{2}O

_{3}was added the zeta potential was 68 mV, while for the case of 2%, it reached 49 mV. Performance tests showed a significant increase in the efficiencies with increased mass flow rate. It was found when analyzing the performance of the two systems for nanofluid flow rates from 0.08 to 0.17 kg/s that there are slight differences between the monocrystalline, and polycrystalline systems operating in the spiral type of exchanger. As for the case of using monocrystalline PV the electrical, thermal, and total PV/T efficiencies with 2% added Fe

_{2}O

_{3}ranged between 10% to 13.3%, 43–59%, and 59 to 72%, respectively, compared to a standalone PV system. In the case of using polycrystalline PV, the electrical, thermal, and total PV/T efficiencies ranged from 11% to 13.75%, 40.3% to 63%, and 55.5% to 77.65%, respectively, compared to the standalone PV system. It was found that the PV/T electrical exergy was between 45, and 64 W with thermal exergy ranged from 40 to 166 W, and total exergy from 85 to 280 W, in the case of using a monocrystalline panel. In the case of using polycrystalline, the PV/T electrical, thermal, and total exergy were between 45 and 66 W, 42–172 W, and 85–238 W, respectively. The results showed that both types of PV panels can be used in the harsh weather conditions of the city of Baghdad with acceptable, and efficient productivity.

## 1. Introduction

_{2}O

_{3}, and MWCNT to water without surfactant on the resulting thermophysical properties. This addition caused a tiny increase in the prepared fluid density and viscosity with a significant increase in thermal conductivity. MWCNT causes the best improvement in electrical efficiency due to its superior thermal conductivity over the other two fluids. Ref. [26] studied the use of a nanofluid formed from adding copper oxide (CuO) nanoparticles to water in the cooling of the PV/T system in the laboratory. The study also dealt with the thermophysical properties of the prepared nanofluid. The results showed a limited effect of adding nanoparticles on the density and viscosity of the resulting fluid due to the small amount added. As for the thermal conductivity of the produced nanofluids, it increased significantly, reaching 100.3% (when adding 2% nano-CuO).

## 2. Materials and Methods

#### 2.1. System Description

#### 2.2. Materials

^{3}, a melting point of −14 °C, and a boiling point of 197 °C.

_{2}O

_{3}) produced by (Sky Spring Nanomaterials, Inc., Houston, TX, USA) purchased from the local market was used in this study. The used nano-Fe

_{2}O

_{3}has a purity of over 99% and its outer diameters range from 20–40 nm. These nanoparticle’s density is about 5240 kg/m

^{3}and has high thermal conductivity (TC) of (32.9 W/mK). It was selected because they have sizes suitable for suspended in the emulsions for appropriate periods (high stability period) when good mixing is achieved. Furthermore, it was sold at a very reasonable price (1 US$/g), and this price is considered one of the cheapest in the local markets. Nano-iron oxide has been used by many researchers in the production of magnetic or magnetically active nanofluids in many applications. Among these applications are: (1) Magnetic coatings and coatings designed to absorb electromagnetic waves. (2) Data storage, and high-intensity magnetic recording. (3) In magnetic detectors. (4) Many high-tech microwaves. (6) In medical applications such as magnetically controlled drug delivery, medical imaging, cell separation, and refrigeration. (7) In the purification of biological contexts and wastewater [34,35,36,37,38,39]. Table 3 lists the studied materials properties.

#### 2.3. Mixing Procedure

_{2}O

_{3}was added to them, and the components were mixed using an ultrasonic shaker. Ultrasonic vibration causes the particles to separate and diverge from each other and then spread throughout the base fluid. This method delays the agglomeration of nanoparticles and then their deposition for an appropriate period. The researchers differed in determining this appropriate period (or the nanofluids’ stability period). Ref. [41] considered the fluid to be stable if no deposition of nanoparticles occurred for a period of ten days, while Ref. [40] considered the fluid to be stable if no sedimentation occurred for more than six months. A recent study [42] considered the fluid stability of sixty days a sufficient period. The sonication time used to mix the components was three and a quarter-hour depending on the results of Ref. [43]. Furthermore, 0.1 mL of surfactant (Cetyl Trichromyl Ammonium Bromide (CTAB)) was added to the mixture to ensure longer stability of the suspension. The results of Ref. [23] were adopted in choosing the type of surfactant and its amount added.

#### 2.4. Measurements

- HOT DESK Tps 500 (KIJTALEY, Sweden) for measuring the thermal conductivity of emulsions.
- Density tester meter for prepared emulsions density.
- Brookfield Programmer Viscometer (Model: LVDV-III Ultra-programmable) is used to measure the viscosity of emulsions. This instrument is connected to a laptop to collect and store the measured data.
- Nano Zeta-Sizer (ZSN) was used to measure the stability of the prepared emulsions.

- e
_{R}: Measurements uncertainty. - R: An independent variable function V
_{1}, V_{2}, …, V_{n}or - R = R (V
_{1}, V_{2}, …, V_{n}). - e
_{i}: nth variable uncertainty interval. - $\frac{\partial R}{\partial {V}_{i}}$: A single variable measured result sensitivity.

#### 2.5. Energy Analysis

#### 2.6. Exergy Analysis

## 3. Results and Discussion

#### 3.1. Climate Conditions

^{2}) at peak hours. This value is moderate compared to measured values in July and August (more than 1000 W/m

^{2}) at the peak period [32].

#### 3.2. Thermophysical Properties

#### 3.2.1. Viscosity

_{2}powder to water, which resulted in high viscosity.

#### 3.2.2. Density

^{3}), for this reason, the water-EG blend has a higher density than water. For the nanofluids the increments in the densities as Figure 4A declares were 0.22%, 0.30%, 0.42%, and 0.53% for 0.5%, 1.0%, 1.5%, and 2% nano-Fe

_{2}O

_{3}mass fractions add to water, respectively, compared to water-EG density. These increments have a neglected impact on the system performance because of their small values. Figure 4B represents a comparison between the achieved maximum density in this study with others from the literature [25,41,51,57,58,59,60]. The result of the current study is consistent with many studies in the literature as the figure shows. As for the high-density nanofluids, the reason is due to the type of the base fluid (pure EG as in the case of the Ref. [60]) or the type of nanoparticles added, as in the case of Ref. [57].

#### 3.2.3. Thermal Conductivity

_{2}O

_{3}added mass fraction was increased in the water EG mixture. Iron oxide is one of the highly conductive metal oxides, so adding its nanoparticles to water caused a clear enhancement in the nanofluid TC amounting to 33.6%, 81.3%, 105.3%, and 123.6% for 0.5%, 1.0%, 1.5%, and 2% nano-Fe

_{2}O

_{3}mass fractions add to water-EG blend, respectively, as Figure 5A reveals. Figure 5B compares the TC enhancement rate in the recent study with others from the literature [51,61,62,63,64,65]. It is clear that the recent study’s TC is higher than the others due to the high TC of the nanoparticles used as well as for the careful mixing procedure used.

#### 3.2.4. Stability

_{2}O

_{3}was added at a mass fraction rate of 0.5%, as its zeta potential reached 64 mV, and the least stable was the suspension with a mass fraction ratio of 2% (zeta potential of 49 mV). The rate of deterioration of the zeta potential of the nanofluid was increased by increasing the nanoparticles mass fraction [14]. Good mixing using ultrasound for an appropriate period of time resulted in high stability of the prepared suspensions.

_{2}O

_{3}is suitable as a coolant for PV/T systems, as it has high stability and good thermal conductivity, in addition to the fact that the change in density and viscosity is limited.

_{2}O

_{3}with EG-water blend). The nanofluid is circulated in a spiral flow heat exchanger. The figure studies the effect of mass flow rate which ranges from 0.08 kg/s to 0.017 kg/s. Figure 7A shows the maximum electrical, thermal and total efficiencies for a system using monocrystalline PV and Figure 7B shows the same efficiencies for the working case of a polycrystalline PV system. For both cases, increasing the mass flow rate produced higher efficiencies. The monocrystalline PV/T system produced a total efficiency ranging from 59% to 72.3%, where the electrical efficiency was between 10% to 13.3% and the thermal efficiency was from 43% to 59%. When using a polycrystalline photovoltaic panel, the PV/T system produced a total efficiency ranging from 55.5% to 76.75%, where the electrical efficiency was between 11% to 13.75% and the thermal efficiency from 44.3% to 63%. These results show a partial superiority of the polycrystalline PV/T system over the monocrystalline system.

^{2}. Meanwhile, minimal variations were observed for the electrical exergy produced by the PV model, which means this type of system can be considered to be thermally biased. It is noteworthy to mention that the electrical yield of the system is a high-grade form of energy, while the thermal yield is considered to be low-grade. Table 7 lists the results of some valuable studies in the literature and the current study efficiencies results. The table included the type of heat collector and the cooling fluid used for comparison. Comparison of these results may not be fair due to differences in flow type, the material of the heat exchanger, flow rate, coolant type, etc. However, such tables remain useful, as they give an indication of whether the results are acceptable or not. When comparing the results of the current study with the studies listed in Table 7, it is noted that the two systems used gave excellent results compared to the rest of the studies, except for the Ref. [89], which can be superior to using nano-PCM and nanofluid together. Such collectors are considered to be very expensive compared to cooling only with nanofluid. The issue here remains the balance between the cost and the financial return from the system.

## 4. Conclusions

_{2}O

_{3}by weight of 2% caused a limited increase in the density and viscosity of the nanofluid, but it caused a clear increase in its thermal conductivity up to 140%. The prepared nanofluids proved to be of high stability as a result of good mixing and use of sonication for a sufficient period of time. Finally, by comparing exergy and energy between the two PV/T systems working with mono and polycrystalline, it was found that the polycrystalline system produced higher energy and exergy than the monocrystalline case. The total electrical, thermal, and total efficiencies obtained were 13.75%, 63%, and 77.65% for a PV/T system with a polycrystalline PV panel. As for the highest total exergy that was reached, it was 238 W for the same system, compared to 172 W for the case of monocrystalline.

## Author Contributions

## Funding

## Conflicts of Interest

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**Figure 3.**The effect of mass fraction added on resulted nanofluid viscosity (

**A**), and a comparison between recent study viscosity and others from literature (

**B**).

**Figure 4.**The effect of mass fraction added on resulted nanofluid density (

**A**), and a comparison between recent study density and others from literature (

**B**).

**Figure 5.**The effect of mass fraction added on resulted nanofluid TC (

**A**), and a comparison between recent study TC and others from literature (

**B**).

**Figure 6.**The effect of mass fraction added on resulted nanofluid stability (

**A**), and a comparison between recent study stability and others from literature (

**B**).

Module Type | Polycrystalline | Monocrystalline |
---|---|---|

Company name | A star | Nuru Tech Fzco |

Peak power (P_{max}) | 100 W | 100 W |

Open circuit voltage (V_{oc}) | 22.5 V | 22.6 V |

Short circuit current (I_{sc}) | 5.81 A | 5.76 A |

Maximum power voltage (V_{mp}) | 18.0 V | 17.96 V |

Maximum power current (I_{mp}) | 5.56 A | 5.57 A |

Power tolerance | ±3% | ±3% |

Dimension (mm) | 1012 × 660 × 30 | 1010 × 660 × 34 |

**Table 2.**Average weather conditions per month for Baghdad city [33].

January | February | March | April | May | June | July | August | September | October | November | December | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

Max. Temp (°C) | 15.5 | 17 | 21 | 30 | 37 | 41 | 45 | 43 | 40 | 33 | 25 | 17 |

Min. Temp. (°C) | 5 | 6 | 8 | 14 | 20 | 22 | 25 | 24 | 22.5 | 16 | 10 | 5 |

Shinning hours (H) | 196 | 200 | 248 | 256 | 300 | 355 | 350 | 360 | 310 | 285 | 212 | 200 |

Precipitation (mm) | 23 | 19 | 22 | 10 | 3 | 0 | 0 | 0 | 0 | 3 | 13 | 23 |

Rainy days | 6 | 6 | 7 | 5 | 3 | 1 | 0 | 0 | 3 | 4 | 7 | 8 |

Humidity (%) | 70 | 60 | 54 | 49 | 32 | 21 | 20 | 22 | 27 | 38 | 56 | 68 |

Wind speed (m/s) | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 1 |

Particle | ρp (kg/m ^{3}) | kp (W/m·°C) | Purity | dp (nm) | Color | Source |
---|---|---|---|---|---|---|

Fe_{2}O_{3} | 5240 | 30 | 99.0% | 20–40 | Red nanopowder | Sky Spring Nanomaterials Inc. (Houston, TX, USA) |

Base fluid | ρf (kg/m^{3}) | kf (W/m·°C) | cpf (J/kg·°C) | μf (nm) | ||

De-ionized water (DIW) (75%) + Ethaline glycol (25%) | 1007.1 | 0.6117 | 4773 | 0.00997 | Steam Lap. + Merck KGaA, Darmstadt, Germany |

No. | Measured Parameter | Measuring Devise | Uncertainty (%) |
---|---|---|---|

1 | Voltage and current | Multi-meter | 0.9 |

2 | Coolants flow rate | Flowmeter | 0.34 |

3 | Thermocouples | Temperature | 0.27 |

4 | Irradiance | Solar radiation intensity meter | 0.98 |

5 | Nanoparticle mass fraction weight | Sensitive weight | 0.001 |

6 | Nanofluids density | Density tester | 0.28 |

7 | Viscosity | Brookfield Programmer Viscometer (Model: LVDV-III Ultra-programmable) | 0.3 |

8 | Thermal conductivity and capacity | Hot desk Tps 500 | 1.2 |

No. | Parameter | Equation | Parameters | Ref. |
---|---|---|---|---|

(1) | Thermal efficiency | ${\eta}_{th}=\frac{{Q}_{u}}{{I}_{s}\times {A}_{c}}$ | ${\eta}_{th}$$:\mathrm{thermal}\mathrm{efficiency}(\%),{Q}_{u}:\mathrm{heat}\mathrm{gain}\left(\mathrm{W}\right)$, ${I}_{s}:\mathrm{solar}\mathrm{irradiance}\left(\frac{\mathrm{W}}{{\mathrm{m}}^{2}}\right)$$,{A}_{c}:\mathrm{collector}\mathrm{area}\left({\mathrm{m}}^{2}\right)$ | [45] |

(2) | Useful gained heat | ${Q}_{u}=\dot{m}{C}_{p}\left({T}_{o}-{T}_{i}\right)$ | ${Q}_{u}:\mathrm{heat}\mathrm{gain}\left(\mathrm{W}\right)$$,\dot{m}:\mathrm{mass}\mathrm{flow}\mathrm{rate}\left(\mathrm{kg}/\mathrm{s}\right)$, ${T}_{o}:\mathrm{outlet}\mathrm{fluid}(\mathbb{C})$$,{T}_{i}:\mathrm{inlet}\mathrm{fluid}(\mathbb{C})$ | [45] |

(3) | Electrical power | ${P}_{mp}={I}_{mp}\times {V}_{mp}$ | ${P}_{mp}:\mathrm{maximum}\mathrm{power}\mathrm{output}\left(\mathrm{W}\right),$ ${I}_{mp}:\mathrm{maximum}\mathrm{power}\mathrm{current}\left(\mathrm{A}\right)$, ${V}_{mp}:\mathrm{maximum}\mathrm{power}\mathrm{voltage}\left(\mathrm{V}\right)$ | [46] |

(4) | Electrical efficiency | ${\eta}_{e}=\frac{{P}_{mp}}{{I}_{s}\times {A}_{panel}}$ | ${\eta}_{e}:\mathrm{Electrical}\mathrm{efficiency}\mathrm{of}\mathrm{the}\mathrm{PV}(\%)$, ${P}_{mp}:\mathrm{maximum}\mathrm{power}\mathrm{output}\left(\mathrm{W}\right)$, ${I}_{s}:\mathrm{Solar}\mathrm{irradiance}\left(\frac{\mathrm{W}}{{\mathrm{m}}^{2}}\right)$, ${A}_{panel}:\mathrm{PV}\mathrm{area}\left({\mathrm{m}}^{2}\right)$ | [47] |

(5) | Total PV/T system efficiency | ${\eta}_{PVT}={\eta}_{th}+{\eta}_{PV}$ | ${\eta}_{PVT}:\mathrm{Photovoltaic}\mathrm{thermal}\mathrm{efficiency}(\%)$, ${\eta}_{th}:\mathrm{Thermal}\mathrm{efficiency}(\%)$, ${\eta}_{PV}:\mathrm{Photovoltaic}\mathrm{efficiency}(\%)$ | [47] |

(6) | Primary energy saving efficiency | ${E}_{f}=\frac{{\eta}_{PVT}}{{\eta}_{P}}+{\eta}_{th}$ | ${\mathrm{E}}_{f}:\mathrm{Primary}\mathrm{energy}-\mathrm{saving}\mathrm{efficiency}(\%)$, ${\eta}_{th}:\mathrm{Thermal}\mathrm{efficiency}(\%)$, ${\eta}_{PVT}:\mathrm{Photovoltaic}\mathrm{thermal}\mathrm{efficiency}(\%)$, ${\eta}_{P}:\mathrm{electric}\mathrm{power}\mathrm{generation}\mathrm{efficiency}(\%)$ | [46] |

No. | Parameter | Equation | Parameter | Ref. |
---|---|---|---|---|

1 | The general exergy balance | $\sum}{E}_{{x}_{in}}-{\displaystyle \sum}{E}_{{x}_{o}}={\displaystyle \sum}{E}_{{x}_{d}$ | ${E}_{{x}_{in}}:\mathrm{Exergy}\mathrm{input}\left(\mathrm{W}\right)$, ${E}_{{x}_{o}}:\mathrm{Exergy}\mathrm{output}\left(\mathrm{W}\right)$, ${E}_{{x}_{d}}:\mathrm{Exergy}\mathrm{destruction}\left(\mathrm{W}\right)$ | [48,49,50] |

2 | The general exergy balance | $\sum}{E}_{{x}_{in}}-{\displaystyle \sum}\left({E}_{{x}_{th}}+{E}_{{x}_{pv}}\right)={\displaystyle \sum}{E}_{{x}_{d}$ | ${E}_{{x}_{in}}:\mathrm{Exergy}\mathrm{input}\left(\mathrm{W}\right)$, ${E}_{{x}_{o}}:\mathrm{Exergy}\mathrm{output}\left(\mathrm{W}\right)$, ${E}_{{x}_{d}}:\mathrm{Exergy}\mathrm{destruction}\left(\mathrm{W}\right)$, ${E}_{{x}_{th}}:\mathrm{Thermal}\mathrm{exergy}\left(\mathrm{W}\right)$, ${E}_{{x}_{pv}}:\mathrm{PV}\mathrm{exergy}\left(\mathrm{W}\right)$ | [48,49,50] |

3 | The input exergy | ${E}_{{x}_{in}}={A}_{c}{N}_{c}I\left[1-\frac{4}{3}\left(\frac{{T}_{a}}{{T}_{s}}+\frac{1}{3}{\left(\frac{{T}_{a}}{{T}_{s}}\right)}^{4}\right)\right]$ | ${E}_{{x}_{in}}:\mathrm{Exergy}\mathrm{input}\left(\mathrm{W}\right)$, ${A}_{c}:\mathrm{Cell}\mathrm{area}\left({\mathrm{m}}^{2}\right)$, ${N}_{c}:\mathrm{number}\mathrm{of}\mathrm{cells}$, $I:\mathrm{solar}\mathrm{irradiance}\left(\mathrm{W}/{\mathrm{m}}^{2}\right)$, ${T}_{a}:\mathrm{Ambient}\mathrm{temperature}\left(\mathrm{K}\right)$, ${T}_{s}:\mathrm{Sun}\mathrm{temperature}\left(\mathrm{K}\right)$ | [48,49,50] |

4 | The thermal exergy | ${E}_{{x}_{th}}={Q}_{u}\left(1-\frac{{T}_{a}+273}{{T}_{o}+273}\right)$ | ${E}_{{x}_{th}}:\mathrm{Thermal}\mathrm{exergy}\left(\mathrm{W}\right)$, ${Q}_{u}:\mathrm{heat}\mathrm{gain}\left(\mathrm{W}\right)$, ${T}_{a}:\mathrm{Ambient}\mathrm{temperature}\left(\mathrm{K}\right)$, ${T}_{o}:\mathrm{Outlet}\mathrm{temperature}\left(\mathrm{K}\right)$ | [48,49,50] |

5 | The PV exergy | ${E}_{{x}_{PV}}={\eta}_{c}{A}_{c}{N}_{c}I$ | ${E}_{{x}_{pv}}:\mathrm{PV}\mathrm{exergy}\left(\mathrm{W}\right)$, ${\eta}_{c}:\mathrm{Cell}\mathrm{efficiency}(\%)$, ${A}_{c}:\mathrm{Cell}\mathrm{area}\left({\mathrm{m}}^{2}\right)$, ${N}_{c}:\mathrm{number}\mathrm{of}\mathrm{cells}$, $I:\mathrm{solar}\mathrm{irradiance}\left(\mathrm{W}/{\mathrm{m}}^{2}\right)$ | [48,49,50] |

6 | The photovoltaic thermal exergy | ${E}_{{x}_{PVT}}={E}_{{x}_{Th}}+{E}_{{x}_{PV}}$ | ${E}_{{x}_{PVT}}:\mathrm{PVT}\mathrm{exergy}\left(\mathrm{W}\right)$, ${E}_{{x}_{th}}:\mathrm{Thermal}\mathrm{exergy}\left(\mathrm{W}\right)$, ${E}_{{x}_{pv}}:\mathrm{PV}\mathrm{exergy}\left(\mathrm{W}\right)$ | [48,49,50] |

7 | The exergy destruction or irreversibility | ${E}_{{x}_{d}}={T}_{a}{S}_{gen}$ | ${E}_{{x}_{d}}:\mathrm{PVT}\mathrm{exergy}\left(\mathrm{W}\right)$, ${T}_{a}:\mathrm{Ambient}\mathrm{temperature}\left(\mathrm{K}\right)$, ${S}_{gen}:\mathrm{Rate}\mathrm{of}\mathrm{Entropy}\mathrm{generation}$ | [48,49,50] |

8 | The exergy efficiency | ${\eta}_{ex}=1-\frac{{E}_{{x}_{d}}}{{E}_{{x}_{in}}}$ | ${E}_{{x}_{d}}:\mathrm{Exergy}\mathrm{destruction}\left(\mathrm{W}\right)$, ${E}_{{x}_{d}}:\mathrm{PVT}\mathrm{exergy}\left(\mathrm{W}\right)$, ${E}_{{x}_{in}}:\mathrm{Exergy}\mathrm{input}\left(\mathrm{W}\right)$ | [48,49,50] |

Ref. No. | Electrical Efficiency | Thermal Efficiency | Total Efficiency | Cooling Fluid | Collector Design |
---|---|---|---|---|---|

[83] | 9.5 | 50 | 59.5 | Water | Flat plate |

[84] | 9 | 38 | 47 | Water | Corrugated polycarbonate panel |

[85] | 11 | 51 | 62 | Water | Aluminum-alloy flat-box |

[86] | - | - | 64.9 | Water | Flat-box absorber |

[87] | 9.87 | 40 | 49.87 | Water | Flat-box Al-alloy absorber plate |

[88] | 13 | 45 | 58 | Nano-Al_{2}O_{3}-Water | Spiral flow absorber |

[25] | 17.2 | 54.8 | 72 | MWCNT-water | Copper sheet and tube |

[63] | 9.9 | 54.28 | 64.18 | Nano-SiC—water | Direct-flow configuration |

[89] | 16 | 70 | 86 | Nano-SiC—water +Nano-paraffin | Copper tubes in heat storage tank |

Current study (Monocrystalline) | 13.3 | 59 | 72.3 | Nano-Fe_{2}O_{3}-water-EG | Spiral flow absorber |

Current study (Polycrystalline) | 13.75 | 63 | 76.75 | Nano-Fe_{2}O_{3}-water-EG | Spiral flow absorber |

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**MDPI and ACS Style**

Al Ezzi, A.; Chaichan, M.T.; Majdi, H.S.; Al-Waeli, A.H.A.; Kazem, H.A.; Sopian, K.; Fayad, M.A.; Dhahad, H.A.; Yusaf, T.
Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis. *Energies* **2022**, *15*, 3870.
https://doi.org/10.3390/en15113870

**AMA Style**

Al Ezzi A, Chaichan MT, Majdi HS, Al-Waeli AHA, Kazem HA, Sopian K, Fayad MA, Dhahad HA, Yusaf T.
Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis. *Energies*. 2022; 15(11):3870.
https://doi.org/10.3390/en15113870

**Chicago/Turabian Style**

Al Ezzi, Amged, Miqdam T. Chaichan, Hasan S. Majdi, Ali H. A. Al-Waeli, Hussein A. Kazem, Kamaruzzaman Sopian, Mohammed A. Fayad, Hayder A. Dhahad, and Talal Yusaf.
2022. "Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis" *Energies* 15, no. 11: 3870.
https://doi.org/10.3390/en15113870