Fumed Silica in Coconut Oil Based Nanofluids for Cooling and Lubrication in Drilling Applications

Abstract

Virgin coconut oil (VCO) is an edible vegetable oil that is eco-friendly, biodegradable, and sustainable, with high thermal and chemical stability as a phase change material (PCM). In this work, VCO filled with fumed silica A200 nanoparticles was tested as a cutting fluid in drilling processes. Silica concentrations ranging from 1 to 4 vol% were analyzed. Thermal properties were evaluated by differential scanning calorimetry (DSC) and thermal conductivity measurements at different temperatures and concentrations. Thermal conductivity showed an enhancement with the addition of silica powder and reduced with increasing temperature. Based on thermal and flow properties, VCO-3A200 was found to be the optimal concentration. The thermal images of this nanofluid taken after 60 s of drilling exhibited a reduction of 12 °C with respect to the dry process. The friction coefficient versus shear rate was also measured. With 8% VCO, a reduction in the friction coefficient of 8% compared to the dry test was achieved. The addition of 3 vol% of silica to the base oil reduced the friction coefficient by 16% compared to the dry test. The use of fumed silica dispersed in VCO has proven to be a sustainable, recyclable, and environmentally friendly refrigerant and lubricant cutting fluid.

1. Introduction

Currently, there exists a great concern about using renewable sources instead of toxic substances such as petroleum derivatives. In this regard, there is a paradigm shift in the use of cutting fluids with negative environmental effect towards renewable materials. The manufacturing industry generates a substantial effect on the environment, making this sector a key player in achieving clean manufacturing. Most of these companies recognize the importance of environmental protection and engage in improving healthy operating conditions for the worker and the surrounding media [1,2,3]. Natural plants as metal cutting fluids, which cool and lubricate, are also essentially ecological. They provide amazing solutions against different risks to the operator’s health. For example, dermal irritations, dangerous aerosols, accidental ingestion, etc., can be caused by fluids of synthetic origin. Conventional cutting fluids, such as mineral oils, have their origin in petroleum derivatives. Surfactants and other additives can be found in its composition. In addition, other compounds based on phosphorus, free sulfur, sulfur oils, fatty acids, and different nanoparticles could be included. In general, all of them damage the environment. When operators are exposed to these cutting fluids for a long time, they are susceptible to respiratory and skin diseases. Petroleum-based mineral oils must be managed with caution during storage, operation, and subsequent removal. The cost of waste disposal of metal-working fluids (MWF) is more expensive than the acquired oil [1].

Consequently, a sustainable solution for reducing the harmful effect on the environment and potential problems for the health of operators is demanded. Cutting fluids in manufacturing processes must be biodegradable to a high percentage, renewable, and fulfill their function in machines. In addition, they must be respectful of the environment. Presently, environmental concern in cutting-fluid-manufacturing companies is reaching important levels. Renewability, non-poisonousness, biodegradability, lowest possible economic cost, among others, are required, which results in an improvement of corporate social responsibility [4,5]. Hence, the demand for alternatives to conventional cutting fluids, which are biologically based, ecological, economical, sustainable, and recoverable, is growing. Typically, green cutting fluids are found in vegetable oils. They are harmless, quite renewable, biodegradable, and easy to dispose of [6,7,8]. Simultaneously, manufacturing companies focus on reducing or eliminating the usage of cutting fluids. Near-dry machining (NDM) and dry machining [9] are known techniques for green machining and have also been successfully applied in different machining processes [10,11].

Current trends focus on sustainable machining. This quest for environmentally friendly cutting fluids has opened the wide scope of research opportunities concerning vegetable oils. For that reason, available experimental data of physicochemical properties of vegetable-based materials in machining applications are needed [1]. However, researchers are encouraged to explore the use of additives and nanoparticles that can improve the performance of these fluids. Constant research in this area will lead to significant advances in the future [12].

Currently, vegetable oils are used as lubricants and coolants in different machining processes. They usually include additives and nanoparticles, which maximize their thermophysical properties, improving their lubricating power and oil stability and reducing friction and tool wear inherent to cutting processes. These additives are antioxidants, anti-wear agents, or extreme pressure (EP) additives and can increase the efficiency of vegetable oils as cutting fluids. Coconut oil has already been evaluated as an industrial lubricant and metalworking fluid (MWF). The thermal and oxidative stability of VCO is higher than that of other plant-based cutting fluids due to the high content of saturated fatty acids (86.5%), which helps against oxidation [13]. VCO possesses superior tribological properties in terms of low coefficient of friction [14,15,16]. Nano additives, such as fumed silica, exhibit superior performance in thickening, thixotropy, sag resistance, reinforcement, and caking resistance [17].

The use of nanoparticles has been explored by Perera and Wegala [18] to improve the tribological potential of coconut-oil-based green MWFs. They focus on the possibility of generating an ecological, profitable, and highly efficient MWF using the minimum quantity of lubricant (MQL) as a machining technique, which reduces the quantity of cooling-lubricant fluid from liters to milliliters. This method consists of spreading into the cutting area a mixture of air and the machining fluid in the form of a mist.

The approach of the minimum quantity of cutting fluid (MQCF) technique requires a small quantity of a phase change material doped with nanoparticles. The aim is to form a solid-like paste at room temperature but to become a fluid when heating. The purpose of this fluid is twofold: to lubricate and cool during the drilling process, as well as collect metal chips. Subsequently, these metal swarfs can be separated from the metal-working fluid (MWF) by filtration, and both can be recycled [19]. The use of an MQCF also has positive future life cycle aspects without compromising product quality. Moreover, it requires less energy inputs and costs in the process. Therefore, this technique could mitigate the use of the VCO as the cutting fluid since it can be recycled. Additionally, the possibility of being reused would reduce the impact on the food chain and increase environmental sustainability [20]. The main objective of this work was focused on the design of an environmentally friendly cutting fluid for drilling processes. This was performed by the assessment of the thermal and flow properties. This material was composed of fumed silica A200 nanoparticles suspended in virgin coconut oil (VCO) as phase change base liquid. This work is structured as follows: In Section 3.1, the thermal conductivities of the suspensions are discussed. In Section 3.2, the specific heat capacities and the melting latent heats are determined at different temperatures and particle volume fractions by differential scanning calorimetry (DSC). The possible mechanisms underlying these behaviors are also explained. In Section 3.3, the effectiveness of the cutting fluids was assessed through drilling tests. A comparison of the dry drilling versus a conventional cutting fluid and the VCO-based nanofluids was accomplished.

2. Materials and Methods

2.1. Materials

Coconut oil (CO) was purchased in a local grocery store. Lauric acid (53.70–54.06%) has been reported as the major component [21]. It has a density in the solid state of 0.916 ± 0.002 g/mL at 15 °C and 0.9015 ± 0.0005 g/mL at 25 °C in the liquid phase. Sinorcut S-1300 mineral metalworking fluid (MWF) oil was obtained from Texaco (Alicante, Spain), with 0.89 g/mL at 15 °C, 28.66 × 10⁻³ Pas at 40 °C, and 4.72 × 10⁻³ Pa·s at 100 °C; a flash point at 200 °C, a pour point at −12 °C, and a viscosity index of 100. Commercially available colloidal hydrophilic silica (A200) was purchased from Evonik Degussa Ibérica S.A., Barcelona (Spain). The specific surface area, BET (Brunauer–Emmett–Teller) was ≈200 ± 20 m²/g, according to the manufacturer’s data. The Aerosil^® Fumed Technical overview provided by Evonik Industries presents an XRD pattern of fumed silica A200 with only one broad peak at 22° (2θ), which is characteristic of an amorphous powder [17]. The real density measured value was 2.318 ± 0.012 g/cm³. The SEM (scanning electron microscope) images detected the presence of sphere-like particles arranged in aggregates (Figure 1a). The TEM (transmission electron microscope) image of silica particles (Figure 1b) revealed an average diameter of the primary particle of 20 ± 5 nm. This result was obtained by using the Matlab^® (R2023b) image-processing tool option (Mathworks, Inc.). However, the manufacturer suggests that the structure of aggregates and agglomerates predominantly chain-like or branched of even 300 nm could be formed during the pyrogenic irreversible fusion process [22]. The perforation tests were carried out on a 12 × 12 × 1.5 (cm) S275JR unalloyed structural steel plate.

2.2. Nanofluid Preparation

The nanofluid preparation was conducted by adding silica powder to coconut oil at a concentration measured in volume fractions (volume of solid/total volume) of 1, 2, 3, and 4 vol%. The mixture was stirred in an Onilab OS40-Pro system (Labbox, Barcelona Spain) at 750 rpm for 30 min. The different nanofluids were placed in vials of 35 cm³ at room temperature and sonicated at low vacuum for 30 min to disperse the powder and eliminate air bubbles. The high-angle annular dark-field (HAADF) image of a VCO-3A200 suspension (Figure 1c) also confirms the existence of silica particles as well as Mg and P atoms.

The suspension-compositional spectrum obtained with energy-dispersive spectroscopy, XEDS (Figure 1d) shows atoms of Si and O belonging to the silica powder and the atoms of Mg, P, and O attributable to the VCO. The stability of the suspensions was evaluated through the hydrodynamic diameter (HD) measurement by dynamic light scattering (DLS). The optimum sonication time was found to be 30 min, and longer times did not reveal a significant reduction in particle size. However, the diameter changed with temperature.

Table 1. Influence of temperature on the particle diameter. The polydispersity index is 25–45%.

T/°C	20	21	22	23	24	25	35	45
Dp/nm	600 ± 70	580 ± 60	550 ± 50	440 ± 90	360 ±30	270 ± 30	260 ± 40	270 ± 50

shows the influence of temperature on the particle diameter. All these values were obtained from the VCO-3A200 suspension previously warmed at 40 °C and diluted in VCO until a transmittance of 60–70% was reached. The increment of particle size at temperatures under 24 °C can be justified because of the VCO crystallization. This reduced the motion of particles and favored the formation of bigger aggregates.

2.3. Equipment

The A200 was weighed using a model AE-163 electronic scale from Mettler (Mettler-Toledo, Columbus, OH, USA), with an accuracy of 10⁻⁴ g. A gas displacement pycnometer medium AccuPyc II 134 Series (Anton Paar GmbH, Graz, Austria) was used for the real density measurements. The transmission electron micrographs (TEMs) were taken in a JEM-1400 TEM, JEOL, Inc., Peabody, MA, USA, with a tungsten filament of 120 kV. The powder was suspended in ethanol, and some drops were placed on Formvar (copper) grids. Finally, the solvent was evaporated, and the images were recorded. The SEM (scanning electron microscope) micrographs were performed at 15 kV in a JEOL field emission model JSM 840 SEM, which worked from 0.2 to 40 keV. Dynamic light scattering (DLS) was recorded with a Litesizer DLS 500 (Anton Paar GmbH, Graz, Austria). This instrument takes advantage of automatic optimization of the measurement backscatter angle (15°, 90° or 175°), focus position, and shorter measurement times. It is provided with a 40 mW semiconductor laser light source at 658 nm. It also has a built-in Peltier-type temperature control with a precision of ±0.01 °C. All measurements were controlled using Kalliope software. Thermal conductivity (TC) measurements were recorded in a KD2 Pro (Decagon Devices, Inc., Pullman, WA, USA) device, which had a maximum error of approximately 1%. This apparatus operates with a transient hot wire (THW) method, which minimizes the effects of natural convection. The TC measurements were recorded between 5 and 60 °C. Approximately 35 cm³ of the nanofluid was placed in a glass sample vial (30 mm in diameter and 70 mm in length). The probe used was the KS-1 stainless steel thermal probe with a diameter of 1.27 mm and a length of 60 mm. It incorporates a heating element and a thermos-resistance. The probe was introduced vertically into the sample using a specially designed system, which holds the lid of the vial to decrease the inducting convection (see details in [23]). The sealed vial was completely placed in a heater/cooler water bath made of stainless steel with an immersion thermostat. It includes a Huber Kiss K6 model KISS controller (Germany) with a temperature interval from −25 °C to 200 °C and an air-cooled refrigeration unit. To measure latent heats, phase change temperatures, and isobaric specific heat capacities of the nanofluids, the based fluid, and the powder, a differential scanning calorimeter from the company Mettler model DSC 1, Toledo (USA) was used. A three-step DSC procedure was used, which involved heating, followed by cooling, followed by another heating regime. The sample was placed in a 40 μL aluminum container for a period of 5 min at the starting temperature, before carrying out the measurements, in addition to another 5 min at the final temperature, with a Nitrogen flow rate of 50 mL/min. The imposed heat flow rate was 10 °C/min in cooling and 5 °C/min in heating, in approximately 5 mg of sample. The isobaric specific heat capacity of the samples was determined from the heat flow curves of the second heating measurements using STARe 15.01 software. The latent phase change heats were determined by the area under the peaks in the graph of W/g versus time. A Bohlin Gemini controlled stress rheometer from the company Malvern Panalytical (UK) was used to record viscosity measurements. The geometry used was a concentric cylinder with a separation of 1 mm and a precision of ±0.01 mPa·s. To eliminate previous material history, a pre-shear stage was applied, followed by a resting time before the measurements were recorded. A Peltier system controlled the temperature of the samples. The viscosity–shear rate curves were conducted from 0.01 to 1200 s⁻¹, between 20 and 30 °C in all the samples. Tribological tests were conducted in a Haake Mars 40/60 rheometer (ThermoFisher Scientific, Drieieich, Germany) using a ball-on three-plates geometry made of stainless steel, under a normal force of 3 N in the shear rate interval of 1–100 s⁻¹. Thermal images were taken using a Testo model 872 camera (Testo SE & Co. KGaA, Barcelona, Spain), with a thermal sensitivity of 0.05 °C and resolution of 320 × 240 pixels, which provides infrared and/or real images in the range of −30 °C to 100 °C. The conditions of the drilling tests were as follows: drill diameter 5 mm, depth of drilling 10 mm, drill speed 130 rad/s, time of drilling 60 s. For each sample, the test was repeated 5 times in the same conditions and with the same plate. The average temperature of the 5 tests was used. The images were taken each 5 s. Each time, the average temperature of the 5 tests carried out under the same conditions was taken. The maximum value displayed by the camera was interpreted as the temperature between the surfaces of the drill bit end and the steel plate in contact. Therefore, it was also the temperature of the cutting fluid at that point. It was considered that no gradient of temperature in the drill direction (vertical axis) was produced. The uncertainties of the TC, viscosities, and thermal images were estimated taking the standard deviations of the experimental data.

3. Results

The use of a cutting fluid employing a phase change base liquid filled with fumed silica nanoparticles could enable gel formation at a certain solid particle concentration. In this way, a reduction in the use of other toxic and more expensive drilling fluids could be achieved. The approach of using a minimal quantity of an environmentally friendly cutting fluid (MQCF) requires a deep study of thermal and flow behavior to select the more efficient substance. This could be an option of cooling and lubrication by overflowing or dry drilling. The usage of nanoparticles dispersed in a phase change material (PCM) as base fluid takes advantage of utilizing the latent heat exchange originated by the phase change. The cutting fluid should be consistent enough to collect metal swarfs and the subsequent recycling. This objective can be undertaken by setting the appropriate amount of silica powder to achieve optimal thermal and flow performance. For all these reasons, before performing drilling tests, thermal conductivities, specific heat capacities, and viscosities are going to be discussed to tailor the more appropriate composition of the cutting fluid.

3.1. Thermal Conductivity

Figure 2a displays the thermal conductivity of the nanofluids (k_nf) vs. temperature. In all cases, an increment of the k_nf during the phase change was observed. This interval of temperature can be established between 15 and 30 °C. The addition of silica powder enhanced the thermal conductivity, particularly during the phase change. At the highest volume fraction, 4 vol%, the effect of the phase change on the thermal conductivity diminished. This behavior could be better explained because of the descent in the latent heat when the silica particle amount increased. Over 30 °C, a slight reduction of k_nf was noticed. For all the samples, the experimental thermal conductivity (TC) was low because of the small thermal conductivity of the base fluid (k_bf). Low thermal TCs in vegetable oils and organic fluids have been reported [24,25], which slightly reduce with the rise in temperature [25]. In all cases, the addition of silica particles produced an increase of k_nf. Figure 2b shows the thermal conductivity enhancement (relative thermal conductivity), defined as the k_rel = k_nf/k_f ratio, of silica A200 in VCO vs. particle volume fraction at temperatures over the phase change, between 30 and 60 °C. The relative thermal conductivity increased at temperatures under the phase change (5–15 °C). Above 30 °C, slight variations of k_rel were observed. Comparable results have also been reported by other authors [26] in nanofluids of CuO, ZnO, and graphite in VCO. From Figure 2b, a linear correlation between the experimental k_rel and particle concentration can be inferred in Equation (1) [27]:

$$k_{rel}={\displaystyle \frac{k_{nf}}{k_{bf}}}=1+C_k\varphi$$

(1)

where k_rel is the thermal conductivity enhancement, ϕ is the particle volume fraction, and C_k is the normalized thermal conductivity (TC) enhancement coefficient of the liquid phase.

Table 2. Values of the coefficient C_k adjusted by means of Equation (1).

T/°C	5	10	15	30	35	40	45	50	55	60
Cₖ	8.9 ± 0.2	7.5 ± 0.3	3.4 ± 0.3	2.8 ± 0.5	2.8 ± 0.4	2.6 ± 0.1	2.6 ± 0.1	2.6 ± 0.1	2.6 ± 0.1	2.6 ± 0.1
R	0.99863	0.99397	0.96048	0.91501	0.98715	0.99357	0.98947	0.99788	0.99694	0.98414

presents the values of the C_k coefficient obtained from the adjustment of Equation (1) to the experimental TC at all the temperatures shown in Figure 2b. This parameter is independent of particle volume concentration but may depend on temperature. As can be seen in Table 2, C_k mildly reduced with the rise in temperature above 30 °C, but under the phase change, 5 to 15 °C, C_k increased. Under 15 °C, the samples showed a consistency of a solid hard paste. In general, solids possess higher TCs than liquids or soft materials. Timofeeva [27] related the values of the C_k coefficients to different particle shapes.

According to Table 2, at 15 °C, C_k = 3.4, which is nearly the value of bricks (C_k = 3.37) given by Timofeeva. Under this temperature, particles were trapped in the coconut paste, forming big aggregates and C_k augmented until 7.5 at 10 °C and 8.9 at 5 °C. These values suggested particle agglomeration, which could produce a high conductivity path and justify the enhancement in k_nf at low temperatures. Above fusion temperature, 30 °C, C_k reduced and remained constant, and C_k = 2.6, above 40 °C. Timofeeva [27] obtained 2.6 for platelet-like shapes. Therefore, these results indicated that part of these aggregates broke into smaller sizes, and platelet-like shapes were predominant. Therefore, the k_nf kept almost constant with temperature since the breakage of aggregates ceased at 40 °C. This justification is also consistent with the curves observed in Figure 2a, in which all of them are remarkably close in the interval of 30 °C to 60 °C. The k_nf behavior during the phase change could be better explained with the DSC results discussed in the next section.

3.2. DSC Assessment

The evaluation of calorimetric properties is of paramount importance because additives may affect the phase change latent heat. Consequently, the challenge should be an enhancement of the k_bf with the minimum reduction in the latent heat exchange.

3.2.1. Isobaric Specific Heat Capacity

Figure 3a displays the temperature effect on the specific heat capacity, c_p, of the liquid phase, the solid particles A200, and the dispersions 1, 2, 3, and 4 vol% of silica in VCO. In this Figure, only small variations of this parameter with temperature were detected.

During melting and crystallization, c_p suddenly rose. This is a consequence of the latent heat exchange when heating and cooling. From this picture, it can be stated that c_p increased more pronouncedly at 1 and 2 vol% of silica, and the lowest value was reached at 4 vol%. Figure 3b shows the effect of particle concentration on the specific capacity at distinct temperatures. It could be stated that the maximum value of this parameter was found at 2 vol% for all the temperatures in the heating and cooling processes out of the phase change. Other researchers have also found a reduction in the heat capacity with powder addition [28]. The crystallization process of coconut oil is characterized by two peaks at −5.74 °C and 1.33 °C, respectively. These values slightly shifted to higher temperatures with the addition of silica A200, see Figure 3a (cooling). However, the melting peak of VCO was produced at 24.16 °C. This temperature remained almost constant independently of the silica concentration. Contrary to the crystallization process in which heat conduction is the predominant heat exchange mechanism, in the melting process, heat transfer involves mechanisms of both thermal conduction and natural convection. This complexity of the melting process is reflected in the heat absorption as a broad peak with the same phase change temperature for all the samples, around 24 °C. Since the use of the tailored cutting fluid was as a refrigerant, latent melting heat exchange attracted more interest in this approach, and it is briefly discussed in Section 3.2.2.

3.2.2. Latent Melting Heat

Figure 4 represents the experimental values of the latent heat reduction rate (h_nf/h_bf) vs. particle volume fraction. As is observed in this Figure, there is a reduction in the experimental latent heat with particle addition, which approximately fits a linear relationship. However, several experimental results [29,30] have shown a reduction in the latent melting heat for nanofluids, which is under the mass loss prediction. It is also confirmed that this melting heat decrease is lower than expected by traditional theories and independent of particle volume fraction [31]. The results of these experiments show that the reduction rate magnitude grows when particle diameter reduces. This apparent diameter dependence suggests an influence of the interface effects on nanofluid melting-heat reduction. This behavior has served as a starting point to propose possible mechanisms for the reduction in latent melting heat in nanofluids [32].

The slope of the lines in Figure 4, σ, can be expressed as the reduction in the liquid phase latent heat over particle volume fraction. Theoretically, the composite material’s latent melting heat linearly diminishes with the increment of solid particles, according to the following Equation (2) [32]:

$$h_{nf}={\displaystyle \frac{{\rho }_{bf,s}{h}_{bf}(1-{\varnothing }_p)}{{\rho }_{nf}}}$$

(2)

where ρ_bf,s denotes the base fluid density in solid phase; h_bf, the latent melting heat; ∅_p, the particle volume fraction; and ρ_nf, the nanofluid density obtained with the mixing rule expression: ${\rho }_{nf}=\varnothing {·\rho }_p+(1-\varnothing ){\rho }_{bf}$. The addition of solid powder causes a reduction in the latent melting heat of the nanofluid due to the mass or volume of the particles within the nanofluid not contributing to the latent phase change heat.

However, experimental values of latent heat demonstrate a further reduction beyond the mass loss prediction. This fact suggests the possibility of an additional base fluid volume represented by effective volumes of the deformed base fluid molecular structure, which requires less energy for melting breakage. The reason for the molecular strain layer (or semisolid layer) is attributed to interfacial phenomena, such as: Brownian motion, interfacial liquid layering, and particle clustering. All of them depend on particle diameter. It is proven that in a smaller particle size, the reduction effect is higher. Hence, these phenomena could be applied to justify probable mechanisms of the experimental value reduction in the nanofluid fusion heat. Brownian motion has been demonstrated to be too slow to transport enough heat to explain the latent heat reduction associated with mass loss [32]. The other two mechanisms are evaluated in the following Sections.

• The interfacial liquid layering;

This mechanism explains the latent heat reduction through the weakening of a base fluid molecular structure built around the particle. This rearrangement is caused by the weak effects of the van der Waals forces, which form a thin width of molecular layer. Molecules beyond this film do not undergo significant movement. The interface volume fraction (∅_i) is defined as ${\varnothing }_i={\displaystyle \frac{V_i}{V_{nf}}}$, where $V_i$ is the base fluid molecule volume at the solid–liquid interface. $V_{nf}$ is the total nanofluid volume. As it is already known, the particle volume fraction is defined as ${\varnothing }_p={\displaystyle \frac{V_p}{V_{nf}}}$. Then, ${\varnothing }_i$ and ${\varnothing }_p$ are related as follows [32]:

$${\varnothing }_i={\varnothing }_p\left({\displaystyle \frac{V_i}{V_p}}\right)$$

(3)

where the subscripts i and p indicate interface and particle, respectively. Considering platelet-shaped particles of diameter (d_p = 20 nm) and height (h) surrounded by a molecular layer of thickness (w), Equation (3) can be expressed as Equation (4) [32]:

$${\varnothing }_i={\varnothing }_p\left({\displaystyle \frac{\pi h\left[{\left(\frac{d_p}{2}+w\right)}^2-{\left(\frac{d_p}{2}\right)}^2\right]}{\pi h{\left(\frac{d_p}{2}\right)}^2}}\right)={\varnothing }_p\left({\displaystyle \frac{4w}{d_p}}+{\displaystyle \frac{4w^2}{d_p^2}}\right)$$

(4)

Experimental studies and molecular dynamics simulation have demonstrated that the width around particles (w) is about 1–2 nm [33,34]. Including the quantity of silica particle measured by ${\varnothing }_p$ and the interface volume fraction ${\varnothing }_i$, Equation (2) should be converted into Equation (5) [32]. It is assumed that the interfacial phase structure is completely broken down and does not contribute to the melting latent heat.

$$h_{nf}={\displaystyle \frac{{\rho }_{bf,s}{h}_{bf}(1-{\varnothing }_p-{\varnothing }_i)}{{\rho }_{nf}}}$$

(5)

The values of ${\varnothing }_i$ were obtained from Equation (4), considering a width, w = 2 nm. With these values, the h_nf from Equation (5) was determined. The values of ${\varnothing }_i$ assuming the liquid layer mechanism are presented in

Table 3. Values of the parameters shown in Figure 5a: The parameter w’ represents the width of liquid layering, which fits the experimental latent melting heats. All the uncertainties are under 10%.

	Liquid Layering		Particle Clustering
$\mathit{\varnothing }$nf	w’/nm	$\mathit{\varnothing }$int	Ra/nm	$\mathit{\varnothing }$int
0.01	4.42	0.0044	436.5	0.00998
0.02	5.58	0.0088	247.26	0.01997
0.03	7.29	0.0132	177.3	0.02997
0.04	7.73	0.0176	140.0	0.03997

. Knowing ${\varnothing }_i$ for each ${\varnothing }_p$, using Equation (5), the reduction rate was calculated with the liquid-layering approach.

The latent heat reduction calculated through Equation (5) considering the liquid-layering approach is represented in Figure 4. These h_nf values fairly fitted the experimental data at low concentration, 1 vol%, but failed at higher volume fractions. This means that the semisolid layer around particles should be wider to fit the experimental data. Figure 5a shows an extended width, named as w’, which included more base fluid molecules. The values of this semisolid layer for all the suspensions, which fitted the experimental latent heat, are shown in Table 3. Obviously, the thickness of the w’ layer increased with particle loading but not linearly.

• Particle clustering;

Keblinski [35] describes aggregation of particles as a possible mechanism of heat transmission in suspensions. It considers that the effective aggregate volume in clusters is greater than the volume of nanoparticles within the cluster. This phenomenon can boost the thermal conductivity of the dispersion with respect to the base fluid. In highly packed aggregates, the base fluid surrounding the particles could occupy up to 25% of the cluster volumes, filling the spaces between the particles. The formation of aggregates can be explained based on the Dejarguin–Landau–Verwey–Overbeck (DLVO) theory, which is based on repulsive and attractive potential energies between nanoparticles. Aggregates are formed when the interparticle attractive forces of van der Waals overcome repulsive forces. The strained base fluid molecules surrounding aggregates within clusters can justify the extra interface volume, which is required to explain the reduction in the experimentally measured latent heat. Prasher et al. [36] assume spherical monodispersed particles and characterize the aggregates by the radius of gyration (R_a), which is defined as the root mean square of the average radius from the aggregate mass center. The values of the maximum R_a can be estimated from the following Equation [36]:

$$R_a=\left({\displaystyle \frac{d_p}{2}}\right){\left({\varnothing }_p\right)}^{{\displaystyle \frac{1}{d_{f-3}}} }$$

(6)

where d_p is the mean particle diameter, 20 nm in silica A200, ${\varnothing }_p$ particle concentration, and d_f is the fractal dimension of the aggregates; d_f = 1.8 is stated for a weak repulsive barrier in nanofluids [37]. The values of R_a and $\varnothing$_int for a d_p = 20 nm are presented in Table 3. At higher concentrations, the gyration radius, R_a, decreased. It could be explained by considering more densely packed particle aggregates with the increase in the volume fraction, see Table 3. The volume fraction of particles within the clusters, $\varnothing$_i, is given by the expression of Potanin and Russel [38] as follows:

$${\varnothing }_i={\left({\displaystyle \frac{2R_a}{d_p}}\right)}^{d_f-3}$$

(7)

Substituting ${\varnothing }_i$ from Equation (7) into Equation (5), the nanofluid latent melting heats were calculated. The normalized results obtained from Equation (5) are represented in Figure 4. As can be appreciated in this picture, the particle-clustering approach is valid for concentrations under 2 vol%, whereas the liquid-layering approach fails above 1 vol%. Although, both approaches improved the experimental latent heat reductions with respect to the mixing rule. Figure 5b shows a TEM micrograph of a VCO-3A200 suspension around 15 °C. In this picture, agglomerates of different shapes surrounded by base liquid molecules are clearly seen. Part of this fluid does not contribute to the melting heat. The gyration radius, R_a, and the high conductivity path are outlined. This picture provides a graphical scheme of the aggregates encircled by semisolid base fluid layers that could be formed and account for the latent heat reduction in nanofluids. Therefore, particle clustering was proposed as the more probable mechanism that better justifies the experimental melting latent heat reductions, as is represented in Figure 4.

The particle-clustering approach could justify thermal conductivity enhancement during the phase change. It was found to have a maximum of 2 vol% of silica. This behavior presented the same trend observed in the specific heat capacity with the powder addition. Keblinski [35] suggests, as a heat transfer mechanism, the aggregation of particles separated by thin liquid layers, named “liquid-mediated clustering”. This microstructure can be observed in Figure 5b.

Although, the mechanism which underpins the improvement of c_p in nanofluids is not fully grasped. The formation of aggregates of particles which are surrounded by liquid molecules would enlarge specific surface areas. This microstructure would also enhance surface energies and the specific heat capacities [39]. The VCO-A200 nanofluids were proven to have a microstructure in which clusters of particles encircled by liquid molecules are formed. The TEM photo of silica in VCO illustrated in Figure 5b shows a graphical scheme of particle agglomerates with fractal structure surrounded by layers of base fluid molecules. The smaller the amount of solid, the greater the thickness of the liquid layer enclosing the particles; see in Table 3 how R_a increased at 1 and 2 vol%. This reasoning could explain the maximum c_p attained at lower particle concentration, 2 vol%, see Figure 3b. Contrarily, the mass loading contributed to the strengthening of the nanofluid microstructure. If the semisolid layering becomes too thick, the formation of strong microstructures occurs, and the specific heat capacity could be reduced as the compressed layer of fluid molecules diminishes. This argument could be applied to 3 and 4 vol%, which exhibited smaller heat capacities. Experimentally, these behaviors are reflected in Figure 2b. Similar reasonings have been used to explain the improvement of c_p in salt-based nanofluids. Researchers suggest that this is due to a compressed layer formation around the nanoparticle surface, which is composed by the salt ions. This layering appears when small particles nucleate the surrounding liquid promoting a semisolid phase formation around them [40,41].

3.3. Drilling Applications

In this study, the use of nanofluids as metal working fluids (MWFs) requires a detailed composition of the material based on its thermal and flow properties. The optimal composition of the nanofluid requires a good thermal conductivity and specific heat capacity without great reduction in the latent phase change heat and a sufficient viscosity to maintain a solid shape with the minimum quantity of material. The VCO-3A200 suspension gave good values of the thermal properties in terms of thermal conductivity and latent heat, but high viscosity was also needed. Figure 6 presents the viscosity vs. volume fraction at two distinct shear rates in the range of 19–30 °C. Figure 6a represents viscosities at 0.1 s⁻¹, close to the rest state and Figure 6b at 130 s⁻¹, which approaches the drilling-machine angular speed. According to this picture, the viscosity of the VCO-3A200 at 0.1 s⁻¹ and 20 °C was 12,870 ± 10 Pa·s. It was high enough to keep a solid shape before the drilling process initiated and descended to 17.25 ± 0.05 Pa·s at 30 °C. At 130 s⁻¹, the viscosity decreased, as occurs in non-Newtonian fluids, from 8.5 ± 0.1 Pa·s at 20 °C until 0.56 ± 0.04 Pa·s at 65 °C. This last value was estimated from the flow curve at different temperatures with the Arrhenius model and the data shown in Figure 6b. While the VCO-4A200 suspension developed gel microstructure and the latent heat decreased by 19% with respect to that of the base fluid, the latent heat the VCO-3A200 dispersion reduced only 13%.

Therefore, the composition of the VCO-3A200 nanofluid was considered the most suitable to be used as a cutting fluid. The efficiency of this material was checked in drilling tests. Figure 7a exhibits the VCO positioned on the stainless-steel plate at t = 0 s and 20 °C. Figure 7b displays the appearance of the VCO after 60 s of drilling. Figure 7c shows the thermal image of (b). Figure 7d displays the pre-drilling image using VCO-3A200 as the cutting fluid. Figure 7e shows how the metal swarf is wrapped by the VCO-3A200 dispersion, and the corresponding thermal image is presented in Figure 7f. In addition to the temperature reduction, the higher viscosity of the nanofluid compared to that of the base fluid was another advantage of the phase change cutting fluid. The solid consistency of the cutting fluid not only allowed for the metal chips to be collected but also permitted the use of a small amount of material.

Figure 8a (top) shows the average temperatures vs. time comparing the effect of three cutting fluid versus dry machining. This Figure represents the maximum temperatures measured by the camera during the drilling tests for the four samples investigated. Dry drilling showed a maximum temperature at 30 s, 64 ± 2 °C. Conventional Sinorcut is preferably used as lubricant, although it slightly reduced the peak temperature of the drill to 63 ± 2 °C. The VCO reduced to 62 ± 2 °C. In all cases, after 30 s, the temperature decreased more sharply. However, the VCO-3A200 cutting-fluid temperature was progressively increasing to 49 ± 1 °C at 45 s and slightly diminished until 47 ± 1 °C at 60 s. Figure 8a (bottom) expresses more clearly the reduction in temperature with respect to the dry drilling. Although the base fluid VCO reduced the drilling temperature with respect to both the conventional Sinorcut oil and the dry machining, the best performance was achieved by the suspension VCO-3A200. This nanofluid was able to reduce by 33% the dry drilling temperature peak. Hence, the suspension VCO-3A200 showed the best thermal and lubricant properties compared to conventional mineral cutting fluids and the vegetable oil VCO. Figure 8b (top) shows the temperature gradient and profile of the cutting fluid VCO-3A200 in the horizontal axis. Although this gradient is nonlinear, a mean value of 1.4 °C/mm could be inferred. According to this thermal image, the drill temperature was 49.5 °C, the cutting fluid extended to 15 mm, and the temperature reached at this point was 28.6 °C. A tribological experiment was also performed, and a reduction in the friction coefficient with silica particle addition at higher shear rates was achieved. This result is graphed in Figure 8b (bottom right). An abrupt reduction in the friction coefficient was observed, from an average value of 0.5 for the dry test to an average value of 0.15 for VCO. The addition of 3A200 reduced the friction coefficient by 5–20% up to a shear rate of 40 s⁻¹. At a higher speed, 40–100 s⁻¹, the reduction in the friction coefficient of the VCO-3A200 MWF was between 20 and 40% compared to the base fluid. As was mentioned in previous works [19], this method of drilling also enables the recovery of the maximum percentage of chips, as well as a rapid and effective recycling of the nanofluid. The substance would be easily recoverable for reuse in a specifically designed machine, which was described in [19]. To check the thermal stability of the VCO-3A200 nanofluids, three measurements of the thermal conductivity at 30 °C were performed after heating and cooling for 25 cycles in the temperature range of 15–130 °C. It was found that the measurements were dispersed around an average value of 0.165 ± 0.005 W/m·K at 29.65 ± 0.03 °C vs. the previous value of 0.166 ± 0.004 W/m·K at 29.57 ± 0.02 °C. The standard deviation of these measurements was below the accuracy given by the KD2 Pro apparatus, showing the thermal stability of the nanofluid. The viscosity of the suspension was also measured three times, after heating at 130 °C and cooling at 15 °C for 25 cycles. The value obtained at 30 °C for 130 s⁻¹ was 0.182 ± 0.003 Pa·s, which represented a reduction of 8.5% of the previous viscosity, 0.199 ± 0.002 Pa·s. The standard deviation of these measurements was in the range of accuracy given by the rheometer.

4. Conclusions

A new ecofriendly cutting-fluid composition based on vegetable coconut oil as base fluid and fumed silica powder A200 as filler was proposed. The evaluation of the thermal and flow behaviors was the first step to select the suspension optimal composition. From previous studies, it was proven that suspensions with high viscosities are more useful than conventional cutting fluids in drilling machinery. This method minimizes the quantity of material employed and reduces costs. The main results are as follows:

• The thermal conductivity of VCO-A200 nanofluids increased with particle loading and reduced at higher temperatures. During the phase change the TC rose more than two times that of the base VCO. The specific capacity enhanced during the phase change and presented a maximum at 2 vol%.
• The effect of temperature (from 20 °C to 30 °C) and silica volume fraction (from 1 to 4 vol%) on the suspension viscosity were measured at two distinct shear rates, 0.1 s⁻¹ (at rest) and 130 s⁻¹ (drilling speed). It was proven that at 20 °C, the viscosity of the suspension 3 vol% was high enough to maintain the shape over the steel plate. At greater temperatures, the viscosity reduced and the nanofluid was able to act as lubricant by melting during the heat exchange of the drilling process.
• Combining flow and thermal properties, it was proposed that the nanofluid VCO-3A200 fulfilled the appropriate conditions for the application as the minimum quantity of cutting fluid (MQCF) in drilling processes. It was demonstrated that the VCO-3A200 nanofluid exhibited sufficient viscosity to gather the metal swarf and reduce the steel plate temperature by about 12 °C without spreading along the plate.
• The behavior of the TC and the specific heat capacity during the phase change was justified by the cluster formation. The aggregation of particles separated by thin liquid layers, named as “liquid-mediated clustering”, could also explain the reduction in the nanofluid latent melting heat under the mass loss prediction.

In summary, this innovative approach of an ecological, sustainable, and recoverable cutting fluid might also result in benefit for manufacturing industries because of good production economics.