Performance And Effect Of AL2O3 Nanoparticle Size On The Heat Transfer Efficiency In A Thermoelectric System

1.1 Background Of Study

Nanoparticle-based heat transfer fluids, i.e., nanofluids, have significantly improved the heat transfer process, enabling higher energy efficiency in thermoelectric system applications. Application of nanoparticles provides an effective way of improving heat transfer characteristics of fluids (Eastman et al., 1997). Particles <100 nm in diameter exhibit properties different from those of conventional solids. Compared with micron-sized particles, nanophase powders have much larger relative surface areas and a great potential for heat transfer enhancement. Some researchers tried to suspend nanoparticles into fluids to form high effective heat transfer fluids. 

(Choi et al.,1995) is the first who used the term nanofluids to refer to the fluids with suspended nanoparticles. Several parameters influence the thermal conductivity enhancement and include nanoparticle type, nanoparticles size, nanoparticles concentration, temperature, type of base fluid and the thermophysical properties of both the base fluid and the nanoparticles. Over the last three decades, since the introduction of nanoparticles in 1995, the explanations behind the enhanced heat transfer of nanofluids have been attributed to several mechanisms. 

(Mahian et al.,1999) studied the mechanisms that would aid the simulation of nanofluids flow. They highlighted that forces such as drag, lift, Brownian motion, thermophoresis, Van der Waals and electrostatic double-layer forces had a significant effect on the thermal and theological behaviour of nanofluids. Brownian motion occurs as a result of thermal diffusion and this phenomenon is increased at higher temperatures, low viscosity and smaller particle size. As promoted by the scientific community, the random collision of particles within the fluid remains the primary reason for the thermal conductivity enhancement observed with nanofluids.

However, (Jang and Choi 2001) provided three types of collisions that occur due to the rising temperature of nanofluids: collisions between the molecules of the base fluid, collisions between base fluid molecules and the nanoparticles, and the collisions between nanoparticles due to brownian motion. They concluded that the effect of Brownian motion on thermal conductivity enhancement had the least effect among the three types of collisions.

(Keblinski et al. 2001) was the first to introduce the idea of nanolayers and their effect in nanoparticles thermophysical behaviour. The nanolayer is known as the solid-like structure or the interfacial layer between the solid surface and the first layer of the fluid in contact with the solid surface. A structured, layered arrangement of the fluid molecules around the surface of the nanoparticles was observed. (Yu and Choi 1999) presented a modified Maxwell model to account for the effect of nanolayers on the thermal conductivity of nanofluids. Their results proved that the thermal model is enhanced as a result of accounting for this factor. (Xie et al.,2001) investigated the effect of the nanolayer on the effective thermal conductivity of nanoparticle–fluid mixtures. It was observed that the effective thermal conductivity increases with a decrease in particle size and an increase in nanolayer thickness. It was concluded that manipulating the nanolayer structure might be an effective method to produce higher thermally conductive nanofluids.

(Pak and Cho1998) reported experimentally the turbulent forced convection heat transfer of Al2O3 /water nanoparticles inside a circular tube. It was presented that the heat transfer enhancement of Al2O3 particles is higher. In their model effects of variety of parameters such as the ratio of the thermal conductivity of nanoparticles to that of a base fluid, volume fraction, nanoparticle size, and temperature on the effective thermal conductivity of nanofluids was included. 

Thermal conductivity of nanofluid also depends on the size of nanoparticles and has an inverse relationship. The thermal conductivity of nanofluid get improved with the decreased nanoparticle size. If the particles are of small size, Brownian motion becomes prominent. Hence, chaotic movement increases in the base fluid. Hence, thermal conductivity of nanofluid get increased. The surface to volume ratio increases if the size of particle decreases. (Teng et al. 2004) investigated the effect of Al2O3 nanoparticles size on the thermal conductivity of Al2O3/water nanofluid.

Enhancement of thermal conductivity was found in their investigation. Hamilton-Crosser equation of thermal conductivity demonstrates that thermal conductivity also depends on the shape of nanoparticles. Shape of the particles may be different types like spherical, cylindrical or rod type, blade, brick type shapes and so forth. Effect of particle shape on Al2O3/EG-water was investigated by (Timofeeva et al. 2005) and found that cylindrical shaped nanoparticles possesses highest thermal conductivity. Brick shaped nanoparticles possess higher thermal conductivity than platelet and blade shaped nanoparticles. The effect of various type of nanofluids on thermoelectric cooling performance has been investigated numerically. Specific liquids are used as coolants in different purposes for heat transfer since these liquids have a lower thermal conductivity than common solids.

A mixture of colloidal nanoparticles and base fluids when uniformly dispersed and stably in base fluids called nanofluids, can impressively improves the thermal properties of base fluids to boost the rate of heat transfer. Research indicates that Al2O3-water nanofluids and the thermal conductivity improvement is observed to 87% at 293K for 50wt.% . Several years back, thermoelectric system technology is one of high performance, low energy consumption devices. The physical thermoelectric properties depend on the temperature of the heating and cooling sides. 

1.2 Statement Of Study

The performance of thermoelectric system will reduce when the different temperature at the hot side and cold side exceed the maximum different temperature specification, application of nanofluid as a heat dissipation fluid improves cooling performance of thermoelectric system . The heat dissipation between the thermoelectric system and nanofluids is quite specific challenging along the way. The stability nanoparticles affect the thermophysical properties, respectively. The size and the large number of particles interacting with the base fluid present a challenge to properly understanding the nanoscale effects that support the improved thermal properties.

1.3 Purpose Of Study

The aim of this research is to study the effect of AL203 nanoparticles in a thermoelectric system to identify the role of nanofluids in the increase of heat performance of heat exchangers and to use these nanofluids in the industrial applications.

Evaluate the thermal properties of Al203 nanoparticles of different sizes impact in heat transfer. The purpose of this research is to summarize the performance of the effect of AL2O3 nanoparticle size on the heat transfer efficiency in a thermoelectric system.

1.4 Significance Of Study

The importance of alumina nanoparticle includes vast benefits to its users in various industrial application. The major benefit is its heat transfer properties, nanoparticles has a very large surface area for heat transfer, the small size of the molecules allows for free movement and very high mobility, hence which promotes heat transfer.

Alumina nanoparticle suspension in a base fluid enhances the energy transmission in the fluid, leading to improved thermal conductivity properties and better heat transfer characteristics.

1.5 Scope Of Study

In this paper, documented reports of alumina nanoparticles are reviewed based on its heat transfer properties. Various physical properties such as stability and thermophysical properties (thermal conductivity and viscosity) and size of nanoparticle will be discussed. This paper reviews the natural convective heat transfer of nanofluids performance in a thermoelectric system. Attention will be given to the result of the literature studies which will compared in terms of yield, energy efficiency and heat transfer performance. Aspect concerning optimization of alumina nanoparticles will also be discussed.

CHAPTER 2

LITERATURE REVIEW

2.1 Conceptual Framework

Nanofluid is a new type of heat transfer fluid with superior thermal performance characteristics, which is very promising for thermal engineering applications. Nanofluids are dilute suspensions of nanoparticles with at least one of their principal dimensions smaller than 100 nm. Also nanofluids are prepared by dispersing nanosize particles (less than 100 nm) into base liquid. These nanoparticles could be aluminum oxide (Al2O3), copper (Cu), copper oxide (CuO), gold (Au), silver (Ag), silica nanoparticles and carbon nanotube. There have been considerable research findings highlighting superior heat transfer performance of nanofluid. It is said that about 15-40% of heat transfer enhancement can be achieved by using various types of nanofluids. Current interest towards nanofluids is fueled by both fundamental science and applications. On the fundamental side, mechanisms of heat conduction and enhanced thermal conductivity in nanofluids are of great interest. On the application side, the enhanced thermal conductivity of nanofluids promises applications in thermal system. 

Nanofluids are used in various heat transfer applications due to their improved thermal and physical characteristics compared to normal cooling fluids. Heat transfer of nanofluids were constrained to the determination of their thermal conductivity, viscosity, convective heat transfer coefficient. Most of the published works concludes that nanofluids have superior heat transfer performance based on their thermo physical properties, rather than the actual application. The most important thermophysical properties of nanofluids are viscosity, convective heat transfer, thermal conductivity, specific heat. The initial promise of nanofluids as advanced heat transfer fluids was based on the increased thermal conductivity of nanoparticle suspensions. It has been shown that nanofluids exhibit much higher thermal conductivities than their base fluids even when the concentration of the suspended nanoparticles is very low. Nanofluids that are being investigated for heat transfer applications are liquids that contain a small volume fraction, up to perhaps 5%, of submicron particles. The presence of these nanoparticles has been shown to increase the static thermal conductivity of the base fluid by as much as 160% with the addition of carbon nanotubes.

The viscosity of nanofluids, which will also be important for applications like heat exchangers, has also been studied, but to a much lesser extent compared with their thermal conductivity. Brownian dynamics simulations suggest that for very small nanoparticles, less than about 30 nm, the increase in thermal conductivity is greater than the relative increase in viscosity. Only a few investigations have been conducted to date on convective and boiling heat transfer in nanofluids, and these revealed some conflicting results. Eastman found that by adding 5% volume fraction of Al2O3 (33 nm) nanoparticles in water, the thermal conductivity can be enhanced by 29%. For bigger diameter of Al2O3 nanoparticles, such as 80 nm, the enhancement was observed to be about 24% for 5% volume loading. The thermal conductivity of nanofluids increases with an increase in volume fraction of the suspended nanoparticles. Also comparison with various data indicates that the thermal conductivity of nanofluids increases with decreasing particles size. The thermal conductivity also increases with an increase in temperature. Heat transfer of nanofluids were constrained to the determination of their thermal conductivity, viscosity, convective heat transfer coefficient. 

Comparisons between experiments and the Hamilton and Crosser model show that the model can predict the thermal conductivity of nanofluids containing large agglomerated Al2O3 particles. However, the model appears to be inadequate for nanofluids containing CuO particles. This suggests that not only particle shape but size is considered to be dominant in enhancing the thermal conductivity of nanofluids. Most of the published works concludes that nanofluids have superior heat transfer performance based on their thermo physical properties, rather than the actual application. 

2.2 Theoritical Review 

Nanofluid was first and foremost presented by Choi and Eastman . According to his findings, the application of nanofluids has resulted in a greater heat transfer than that of conventional fluids. (Evans et al., 2006) suggested that the contribution of Brownian motion to the thermal conductivity of the nanofluid is very small and cannot be responsible for the extraordinary thermal transport properties of nanofluids. They also supported their argument by using molecular dynamics simulations and the effective medium theory. However, they just limited their discussion to stationary fluids, which weakens their conclusions. 

Rather than Brownian motion, liquid layering, phonon transport, and agglomeration, (Lee et al., 2006) experimentally investigated the effect of surface charge state of the nanoparticle in suspension on the thermal conductivity. They showed that the pH value of the nanofluid strongly affected the thermal performance of the fluid. The further the pH value diverged from the isoelectric point of the particles, the more stable the nanoparticles in the suspension and greater the change in the thermal conductivity. By adopting a variation of the classical heat conduction method in porous media to the problem of heat conduction in nanofluids. The majority of the results indicate that the nanofluid is more thermally conductive than the base fluids. Nanofluid is a liquid, which contains nanometer-sized strong particles. By dispersing metallic or non-metallic nanoparticles or nanofibers with a typical size of less than 100 nm in a base liquid, nanofluids can be made. The production of nanofluids is done in two different ways. These techniques are single-step strategy and two-step technique.

(Peyghambarzadeh et al., 2011). analyzed the intensity move execution of the unadulterated water, the unadulterated ethylene glycol (EG), the Al2O3-water and the Al2O3-EG nanofluids. The highest Nusselt number enhancement—up to 40%—was found in their experimental results for both nanofluids. (Tahat and Benim 2017) investigated the effect of thermal efficiency on the thermophysical properties of Al2O3/CuO/water/EG hybrid nanofluids. In their research, increasing the nanoparticle weight fraction led to a 45 percent increase in a collector’s efficiency.

Al2O3 which from research is entirely reasonable for improving warm vehicle and it’s accessibility will be utilized in this trial. As we already know there are several nano-fluids but here are the reasons we are going with Al2O3;

1. One of the essential metal oxides, alumina nanoparticles (Al2O3) have numerous applications and distinctive physiochemical properties. Alumina, in particular, has been demonstrated to possess thermal properties like a convective heat transfer coefficient and high thermal conductivity.

2. It has several properties that make them very suitable for transfer of energy like

· Concentration 20 wt. % in isopropanol

· Particle size <50 nm (DLS)

· pH level 8-10

· Density 0.79 g/cm3 at 25 °C

· Mechanical strength ranging from 300 to 630 MPa

· Compressive strength ranging from 2,000 to 4,000 MPa

· Hardness exhibiting a range from 15 to 19 GPa

· Moderate thermal conductivity is 20 to 30 W/mK

· Operating temperature without mechanical load is 1,000 to 1,500°C

2.2.1 Density and Specific Heat

The specific heat of material is quite an important property to define the thermal performance of any material. Specific heats of nanofluids may differ according to the type of base fluids, nanomaterials, and concentration of nanoparticles found in base fluids. Some nanofluids show inconsistent behavior with volume convergence. Shahrul have conducted a comparative revision on the specific heat of nanofluids used in energy applications. They have concluded that for most nanomaterials in base fluids, specific heat decreases with the increase in volume fraction. Specific heat of Al2O3/ATF gives anomalous conduct of specific heat with volume convergence. The calculation of the effective density ρeff and the effective specific heat Cp,eff of a nanofluid is straightforward. The can be estimated based on the physical principle of the mixture rule as

= = = (1 – 

eff =  

=   

==   

= (1 – +  

Which can be rewritten as 

eff  

2.2.2 Thermal Conductivity 

Currently, there is no reliable theory to predict the anomalous thermal conductivity of nanofluids. High thermal conductivity is obtained for the nanofluids by adding nanoparticle of solid materials of high thermal conductivity. Nanofluids are basically advanced heat transfer fluids as an alternative to the pure base fluids to improve the heat transfer process through the addition of nanoparticle materials that have the properties of higher thermal conductivity. From the experimental results of many researchers, it is known that the thermal conductivity of nanofluids depends on parameters including the thermal conductivities of the base fluid and the nanoparticles, the volume fraction, the surface area, and the shape of the nanoparticles, and the temperature. The prominent results reported that there are improvements of 5–10% of the thermal conductivity of nanofluids using the base fluid (water, PAO). There are no theoretical formulas currently available to predict the thermal conductivity of nanofluids satisfactorily. However, there exist several semi-empirical correlations for calculating the apparent conductivity of two phase mixtures. They are mainly based on the following definition of the effective thermal conductivity mixture

 

For particle-fluid mixtures, numerous theoretical studies have been conducted dating back to the classical work of Maxwell (1881). The Maxwell model for thermal conductivity for solid-liquid mixtures of relatively large particles (micro-/minisize) is good for low solid concentrations. The effective thermal conductivity, keff , is given 

 

where 

k is the thermal conductivity of the particle, 

kb is the thermal conductivity of the base fluid and 

ϕ is the particle volume fraction in the suspension. 

2.3 Empirical Review

(Moraveji et al., 2011) simulated water-Al2O3 nanofluid through a tube under a constant heat flux. They found that the heat transfer coefficient rises by increasing the nanoparticle concentration and Reynolds number. Furthermore, the heat transfer coefficient increases by particle diameter reduction. (Chandrasekhar et al., 2017) experimentally investigated and theoretically validated the behavior of Al2O3/water nanofluid that was prepared by chemical precipitation method. For their investigation, Al2O3/water at different volume concentrations was studied. They concluded that the increase in viscosity of the nanofluid is higher than that of the effective thermal conductivity. Although both viscosity and thermal conductivity increases as the volume concentration is increased, increase in viscosity predominate the increase in thermal conductivity. Also various other theoretical models were also proposed in their paper .

(Rohit S. Khedkar et al., 2017): experimental study on concentric tube heat exchanger for water to nanofluids heat transfer with various concentrations of nanoparticles into base fluids and application of nanofluids as working fluid. Overall heat transfer coefficient was experimentally determined for a fixed heat transfer surface area with different volume fraction of Al2O3 nanoparticles into base fluids and results were compared with pure water. It observed that 3 % nanofluids shown optimum performance with overall heat transfer coefficient 16% higher than water. (Jaafar et al., 2013) did an experimental study on the forced convective heat transfer and flow characteristics of a nanofluid consisting of water and different volume concentrations of Al2O3 nanofluid (0.3–2) % flowing in a horizontal shell and tube heat exchanger counter flow under turbulent flow conditions were investigated. The Al2O3 nanoparticles of about 30 nm diameter are used in the present study. The results showed that the convective heat transfer coefficient of nanofluid is slightly higher than that of the base liquid at same mass flow rate and at same inlet temperature. The heat transfer coefficient of the nanofluid increases with an increase in the mass flow rate, also with the increase of the volume concentration of the Al2O3 nanofluid. However, increasing the volume concentration cause increase in the viscosity of the nanofluid leading to increase in friction factor.  

(Kamaldeep et al., 2013) studied that nanofluids were a new class of solid- liquid composite materials consisting of solid nanoparticles, with sizes typically on the order of 1–100 nm, suspended in a heat transfer liquid. Here the experimental work had been done at different temperature range (30 to 80°C) with varying different volume concentration (0.1%,0.2%,0.5%), 20nm size of Al2O3 nanoparticle in base fluid water to study the behaviour of thermophysical properties of nanofluid and compare with the base fluid. It was found that the thermal conductivity increases significantly with the nanoparticle volume fraction. With an increase of temperature, the thermal conductivity increases for a certain volume concentration of nanofluids, but the viscosity decreases. The temperature and volume fractions have significant effects on the thermal conductivity and viscosities were investigated. Viscosity of nanofluid (Al2O3/water) is less than base fluid water. Specific heat of nanofluid decreases with the concentration as increases. (0.1 to 0.5%).

(Kazem Mahanpour et. al.,2015) did the experimental and theoretical investigations to determine the effective thermal conductivity, electrical conductivity and viscosity of Al2O3/water nanofluid are presented. Nano Al2O3 particles with particle composition and microwave assisted chemical deposition method were distributed in distilled water by sonic device. In this study, nano particles of aluminum oxide with a partial thickness of about 20nm in different volumetric concentrations of (0.15.5-3%) at constant temperature were used. So far, few studies to measure the rheological properties of nanofluid at constant temperature had been performed thermal conductivity, electrical conductivity and viscosity of nanofluid increases at constant temperature with particle volume fraction. Al2O3 Nano particles in water for different volume concentrations show Newtonian behaviour at 15.5℃. Theoretical models to predict the thermal conductivity and viscosity of nanofluids are the HC model and Einstein model. The proposed model has good agreement with experimental results.

2.4 Summary of literature review

Experimental investigation on Al2O3 nanofluids using water as base fluid has been studied by various research groups, and they concluded that the heat transfer coefficient in laminar flow increases up to 12–15% and in the case of turbulent flow, it ranges up to 8% . Therefore, most of the published works concluded that nanofluids have superior heat transfer performance based on their thermo physical properties, rather than the actual application

Majority of the experimental studies on the heat transfer of nanofluids were constrained to the determination of their thermal conductivity, viscosity, convective heat transfer coefficient without considering the performance of the nanofluids under actual application.

CHAPTER 3

METHODOLOGY

3.1 Nanoparticles

Nanoparticles are the fundamental components of Nano technology. Nano particles size ranges from 1 to 100nm which are made up of metal, metal oxides, organic matter, carbon. Nanoparticles differ from various dimensions, to shapes and sizes apart from their material Surface can be irregular with surface variations or a uniform. Among nanoparticles some are crystalline or amorphous with single or multi-crystal solids either agglomerated or loose. It is known that nanoparticles are not point objects and have three distinctive layers to them. The first and outermost layer is the surface layer. This is comprised of molecules or metal ions that will later on give function the surface of the nanoparticle. The second layer is the shell layer which is significantly different from the other two layers. The third and last layer is the core of the nanoparticle which is often a representation of the basic chemical formula of the nanoparticle itself. The thermal properties of nanoparticles are rooted to the type of metals that they are comprised of. It is general knowledge that metals like copper and the oxides of aluminum have higher thermal conductivities compared to most of the other solids or fluids of non-metallic compounds. Addition of nanoparticles of these metals and metal oxides allows the fluid that was previously a bad thermal conductor to have an improved thermal conductivity

3.1.1 Classification Of Nanoparticles

1. Organic nanoparticles: Micelles, Dendrimers, ferritin and liposomes etc. are commonly known polymers or organic nanoparticles. These nanoparticles are non-toxic, biodegradable, and some particles such as liposomes and micelles have a hollow core also known as nano capsules and are sensitive to thermal and electromagnetic radiation such as heat and light. The organic nanoparticles are most widely used in the biomedical field. Examples of organic nanoparticles are liposomes, dendrimers and micelles.

2. Inorganic nanoparticles: Inorganic nanoparticles are particles which are not made up of carbon. Metal and metal oxide-based nanoparticles are generally categorized as inorganic nanoparticles. Almost all the metals can be synthesised into their nanoparticles. The commonly used metals for nanoparticle synthesis are aluminium (Al), cadmium (Cd), cobalt (Co), copper (Cu), gold (Au), iron (Fe), lead (Pb), silver (Ag) and zinc (Zn). These nanoparticles can be synthesized by chemical, electrochemical, or photochemical methods. In chemical methods, the metal nanoparticles are obtained by reducing the metal-ion precursors in solution by chemical reducing agents. These have the ability to adsorb small molecules and have high surface energy. 

3.2 Aluminium Oxide 

Aluminium Oxide {Al2O3} nanoparticles, are spherical nanosized particles of alumina. It has wide applications in different consumer products and applications due to its novel characteristics. Al2O3 nanoparticles have a rod-like shape with a width around 10 nm and a length between 20–50 nm. Aluminium oxide consists of two aluminium atoms and three oxygen atoms. They are bonded collectively in a hexagonal close-packed (HCP) crystal structure. The general name of the compound is alumina, which are also the core mineral found in rubies and sapphires. Aluminum oxide is derived from mainly two sources, bauxite mineral and recycled Alumina. The main source of aluminum oxide is the ore of Aluminum the bauxite mineral. Bauxite mineral is actually not a mineral but a sedimentary rock that is comprised of Aluminum compounds in a mixture with other metals, non-metals and their oxides such as hematite (Fe 2O3), magnetite (Fe3O4) and quartz (SiO2). Alumina nanoparticles can be obtained by several methods including, pyrolysis, sputtering, sol gel and the most commonly preferred technique laser ablation. Laser ablation is convenient since it can be performed in the gas, liquid or even a vacuum environment. Aluminum nanoparticles are usually found in two states, nearly spherical shaped individual particles or as oriented fibers. It isn’t very pleasant and homogeneously oxidized. Aluminium Oxide nanoparticle shows potential as an ideal ingredient in producing advanced heat transfer fluids. It has low friction and outstanding durability, making it a good option for additive for any number of composites, as it offers an enhanced wear resistance. 

3.2.1 Properties of Aluminium Oxide Nanoparticles 

1. The concentration of the product is 20 wt. % in isopropanol

2. The particle size <50 nm (DLS)

3. The pH level of the product is 8-10.

4. The density of the product is 0.79 g/cm3 at 25 °C

5. It has good electrical insulation (1×1014 to 1×1015 Ωcm)

6. It displays high mechanical strength ranging from 300 to 630 MPa

7. It has a high compressive strength ranging from 2,000 to 4,000 MPa

8. The product has a high hardness exhibiting a range from 15 to 19 GPa

9. The Moderate thermal conductivity is 20 to 30 W/mK

10. It has high corrosion resistance and is immune to wear due to external elements with excellent gliding properties.

11. The operating temperature of the product without mechanical load is 1,000 to 1,500°C.

3.3 Al2O3 Nanoparticles: Synthesis and Characterization

3.3.1 Methods of synthesizing Al₂O₃ nanoparticles

There are several methods for synthesizing Al₂O₃ nanoparticles, including:

1. Sol-gel method: The sol–gel process is a method for producing solid materials from small molecules. The method is used for the fabrication of metal oxides, especially the oxides of silicon (Si) and titanium (Ti). The process involves the conversion of monomers into a colloidal solution (sol) that acts as the precursor for an integrated network (or gel) of either discrete particles or network polymers. Typical precursors are metal alkoxides. The sol-gel process is used to produce ceramic nanoparticles (Sol-gel process, 2022).

The sol-gel process is a more chemical method (wet chemical method) for the synthesis of various nanostructures, especially metal oxide nanoparticles (Bokov, et al., 2021).

This method involves heating a mixture of aluminum nitrate and citric acid until a gel is formed. The amorphous gel structure is then dried and sintered at high temperatures to produce Al₂O₃ nanoparticles (Mohamad et al., 2019).

Fig 2.1 Stages involved in the Sol-gel technique (Sol-gel process, 2022)

2. Using waste aluminum foil: Al₂O₃ nanoparticles can be obtained from waste aluminum foils and hydrochloric acid and two salts (sodium chloride and sodium carbonate) while drying (Nduni et al., 2021).

3. Modified Pechini method: This method involves using an α-hydroxycarboxylic-containing compound to form a polybasic acid chelate with metal cations, which successively polymerize with a polyhydroxy compound to form a precursor. The precursor is then calcined to produce Al₂O₃ nanoparticles (Zaki et al., 2012).

4. Polymer co-precipitation method: This method involves preparing a solution of aluminum nitrate and a polymer, then adding a precipitating agent to form Al(OH)₃. The Al(OH)₃ is then calcined to produce Al₂O₃ nanoparticles (Farahmandjou and Golabiyan, 2019).

Fig. 2.2 Synthesis scheme for the formation of alumina nanoparticles.

5. Formamide method: This method involves synthesizing γ-alumina (Al₂O₃) nanoparticles via a method that incorporates the use of formamide and the non-ionic surfactant Pluronic P123 (Ali et al., 2019).

These methods offer different advantages and disadvantages depending on the specific application and desired properties of the Al₂O₃ nanoparticles.

3.4. Characterization techniques to analyze the size, shape, and surface properties

There are various characterization techniques that can be used to analyze the size, shape, and surface properties of materials. These techniques provide valuable information about the physical and chemical characteristics of a material’s surface. Some commonly used techniques include:

1. Microscopy-based Techniques: These techniques involve the use of microscopes to observe and analyze the surface of a material at a microscopic level. Examples include Transmission Electron Microscopy (TEM), High-Resolution Transmission Electron Microscopy (HRTEM), and Atomic Force Microscopy (AFM). These techniques provide information on the size, morphology, and crystal structure of the material (Mourdikoudis et al., 2018). Transmission electron microscopy (TEM) can be used to determine the size, shape, and distribution of the nanoparticles. TEM can also provide information on the crystal structure and lattice spacing of the nanoparticles (Ismardi et al., 2016). Scanning electron microscopy (SEM) is a method that can also be used to determine the morphology and size of the nanoparticles. SEM can also provide information on the surface area and porosity of the nanoparticles (Farahmandjou & Golabiyan, 2019).

Fig. 2.3 SEM of Aluminum oxide nanoparticles 

2. Spectroscopic Techniques: Spectroscopic techniques involve the interaction of electromagnetic radiation with the material’s surface. They can provide information about the chemical composition, molecular structure, and surface functional groups. Examples include X-ray Photoelectron Spectroscopy (XPS), Fourier Transform Infrared Spectroscopy (FTIR), and Raman Spectroscopy (Rowell, 2012). X-ray diffraction (XRD) can be used to determine the crystal structure and phase purity of the nanoparticles. XRD can also provide information on the average crystallite size and lattice parameters of the nanoparticles (Amalraj & Michael, 2019). Fourier transform infrared spectroscopy (FTIR) can be used to determine the functional groups present on the surface of the nanoparticles. FTIR can also provide information on the chemical composition and bonding of the nanoparticles (Nduni et al., 2021).

3. Thermodynamic Techniques: Thermodynamic techniques measure the thermal properties of a material’s surface. These techniques can provide information about surface energy, surface tension, and adsorption behavior. Examples include Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) (Rowell, 2012). Thermogravimetric analysis (TGA) can be used to determine the thermal stability and weight loss of the nanoparticles as a function of temperature (Ismardi et al., 2016).

4. Nanomechanical Techniques: Nanomechanical techniques measure the mechanical properties of a material’s surface at the nanoscale. These techniques can provide information about hardness, elasticity, and adhesion. Examples include Atomic Force Microscopy (AFM) and Nanoindentation (Rowell, 2012).

It is important to note that different techniques may be more suitable for specific materials or properties. Researchers often use a combination of techniques to obtain a comprehensive understanding of the size, shape, and surface properties of a material.

3.5 Thermoelectric System

Thermoelectric materials convert heat energy to electrical energy based on Seebeck and Peltier effect. This leads to utilize hardly usable or almost lost thermal energy into productive applications as efficient as possible. The efficiency of conversion of heat is characterized by the figure of merit which is related to the Seebeck coefficient S, thermal conductivity k, electrical conductivity σ and absolute temperature T.

The Seebeck effect is when electricity is created between a thermocouple when the ends are subjected to a temperature difference between them. The Peltier effect occurs when a temperature difference is created between the junctions by applying a voltage difference across the terminals. A hot surface in contact with the cold junction of the TE will be cooled down and vice versa, a cold surface in contact with the hot junction will be heated up. This effect can be used as a heat pump for heating (TEH) and cooling (TEC) applications. 

In thermal performance intensification, nano-sized particles can be used in heat transfer fluid. The nanofluids (NFs) technology has been successfully used in diverse energy systems. Over the years, many advancements and efficient computational tools have been developed for accurately predicting the nanofluid impacts on performance enhancements. Different nanofluids have been considered, and many aspects of using nanofluids such as the shape effects of nanoparticles (NPs), non-Newtonian behavior and different modeling strategies have been considered.

In thermoelectric installed systems, the utilization of nanofluids has been addressed in many studies. The nanofluid type and its loading amount are among the important factors for controlling the overall efficiency energy of the thermoelectric- installed systems, while different performance improvements were reported depending upon the nanoparticle type. The shape effects of nanoparticles in heat transfer devices have been considered in many studies. Along with the nanoparticle loading, the shape effects of the nanoparticles are important for the overall thermal performance of heat transfer equipment.

In the heat transfer fluid, nanoparticles shape effects of alumina in water are considered along with its loading amount in the base fluid. In the literature, some aspects of nanoparticles such as the non-Newtonian behavior of nanofluids have been addressed by using the thermoelectric system mounted systems, non-Newtonian nanofluids have been used. In the work of, a thermoelectric system module was mounted in between the chaotic channels where non Newtonian nanofluid was considered in the channels. 

However, in the literature, there is no study that considers the shape factor effects of nanoparticles in thermoelectric installed systems. Thermoelectric system performance is characterized by power output, conversion efficiency, and energy efficiency. When an electric current flows through a thermoelectric generator (TEG), it becomes a heat pump, which transports thermal energy from one side to another: the direction and magnitude of the heat depend on the electric current strength. This phenomenon is known as the Peltier effect. 

The thermal conductivity and viscosity of various shapes of alumina nanoparticles in a fluid consisting of equal volumes of ethylene glycol and water were investigated. Experimental data were analyzed and accompanied by theoretical modeling. Enhancements in the effective thermal conductivities due to particle shape effects expected from Hamilton–Crosser equation are strongly diminished by interfacial effects proportional to the total surface area of nanoparticles. On the other hand, the presence of nanoparticles and small volume fractions of agglomerates with high aspect ratios strongly increases viscosity of suspensions due to structural constrains. Nanoparticle surface charge also plays an important role in viscosity. It is demonstrated that by adjusting pH of nanofluid, it is possible to reduce viscosity of alumina nanofluid without significantly affecting thermal conductivity. Efficiency of nanofluids (ratio of thermal conductivity and viscosity increase) for real-life cooling applications is evaluated in both the laminar and turbulent flow regimes using the experimental values of thermal conductivity and viscosity.

References

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