Seyed Borhan Mousavi

Zeinali Heris

Patrice Estellé

Viscosity, tribological and physicochemical features of ZnO and MoS 2 diesel oil-based nanofluids: An experimental study

Keywords: Viscosity, Tribological behavior, Physicochemical characteristic, Nano-ZnO, Nano-MoS 2, Diesel oil-based nanofluid nf Nanofluid np Nanoparticle

In this research, two different diesel oil-based nanofluids were prepared and the influence of temperature and nanoparticle content were examined on viscosity, tribological, and physicochemical features of diesel oil. The kinematic viscosity of samples was experimentally evaluated based on standard ASTM D445. The greatest viscosity increment was diagnosed at 0.7 wt.% and 100°C for both of the prepared nanofluids. The anti-friction behavior of the nanofluids was studied utilizing a pin-on-disc tribometer. The acquired outcomes revealed that ZnO and MoS 2 nanoparticles (NPs) could promote the tribological characteristics of pure diesel oil. By analyzing the friction coefficient values and line roughness of the wear surface (Ra), an optimal concentration of ZnO and MoS 2 nanoparticles (NPs) were found to be around 0.4 wt.% and 0.7 wt.%, respectively. The friction factor and pumping power were also measured at diverse content of nanoparticles and flow rates showing that the pumping power was enhanced by the incorporation of nanoparticles.

Introduction

The term nanofluid refers to the stable distribution of low concentrations of nanoparticles (NPs) with sizes ranging from 1 to 100 nm in a liquid [START_REF] Choi | Enhancing thermal conductivity of fluids with nanoparticles[END_REF][START_REF] Zafarani-Moattar | Stability and rheological properties of nanofluids containing ZnO nanoparticles, poly (propylene glycol) and poly (vinyl pyrrolidone)[END_REF]. Nanofluids have been widely used due to their greater thermal behaviors in comparison with the base fluid. Furthermore, having more substantial surface areas than micro-sized particles and letting more inconsiderable erosion in comparison with the traditional liquid-solid blends can be mentioned as the benefits of nanofluids [START_REF] Zeinali Heris | Thermal behavior of a two phase closed thermosyphon using CuO/water nanofluid[END_REF][START_REF] Rashidi | Heat transfer coefficient prediction of metal oxides based water nanofluids under laminar flow regime using adaptive neuro-fuzzy inference system[END_REF][START_REF] Salimi-Yasar | Influence of soluble oil-based TiO2 nanofluid on heat transfer performance of cutting fluid[END_REF][START_REF] Javadpour | Optimizing the effect of concentration and flow rate of water/MWCNTs nanofluid on the performance of a forced draft crossflow cooling tower[END_REF][START_REF] Zahmatkesh | Effect of nanoparticle shape on the performance of thermal systems utilizing nanofluids: A critical review[END_REF][START_REF] Kahani | Application of M5 tree regression, MARS, and artificial neural network methods to predict the Nusselt number and output temperature of CuO based nanofluid flows in a car radiator[END_REF]. This exceptional improvement in characteristics is associated with the size and shape of the NPs and their nature [START_REF] Mariano | Thermal conductivity, rheological behaviour and density of non-Newtonian ethylene glycol-based SnO2 nanofluids[END_REF]. Several kinds of nanoparticles including metallic and nonmetallic, with various forms and dimensions, were utilized to prepare nanofluids, and some inspiring outcomes have been evidenced; however, the usage of nanoparticles may lead to accretion in viscosity of the nanofluids owing to their viscose nature [START_REF] Wang | Thermal conductivity and rheological properties of graphite/oil nanofluids[END_REF][START_REF] Agarwal | Tribological behavior of diesel fuels and the effect of anti-wear additives[END_REF][START_REF] Salimi-Yasar | Experimental investigation of thermal properties of cutting fluid using soluble oil-based TiO2 nanofluid[END_REF][START_REF] Heris | Effect of TiO2 Nanoparticle on Rheological Behavior of Polyvinyl alcohol Solution[END_REF][START_REF] Shakouri | Effect of TiO2 nanoparticle on rheological behavior of poly (vinyl alcohol) solution[END_REF][START_REF] Yu | Experimental investigation on rheological properties of water based nanofluids with low MWCNT concentrations[END_REF][START_REF] Izadkhah | Influence of Al 2 O 3 nanoparticles on the stability and viscosity of nanofluids[END_REF][START_REF] Pourpasha | Experimental investigation of nano-TiO 2/turbine meter oil nanofluid[END_REF][START_REF] Bhaumik | Computational intelligence-based design of lubricant with vegetable oil blend and various nano friction modifiers[END_REF][START_REF] Pourpasha | The effect of multi-wall carbon nanotubes/turbine meter oil nanofluid concentration on the thermophysical properties of lubricants[END_REF][START_REF] Singh | Development of bio-based lubricant from modified desert date oil (balanites aegyptiaca) with copper nanoparticles addition and their tribological analysis[END_REF][START_REF] Singh | Chemical modification of juliflora oil with trimethylolpropane (TMP) and effect of TiO2 nanoparticles concentration during tribological investigation[END_REF][START_REF] Singh | Effect of SiC nanoparticles concentration on novel feedstock Moringa Oleifera chemically treated with neopentylglycol and their trobological behavior[END_REF]. Recently, ZnO NPs have attracted remarkable research attention owing to their capacity for advancing thermophysical qualities, tribological properties, and good dispersion traits [START_REF] Zhang | Tribological performance of CuS-ZnO nanocomposite film: The effect of CuS doping[END_REF][START_REF] Imani-Mofrad | Experimental investigation of filled bed effect on the thermal performance of a wet cooling tower by using ZnO/water nanofluid[END_REF][START_REF] Leitner | Thermodynamic properties of nanostructured ZnO[END_REF][START_REF] Lamba | ZnO catalyzed transesterification of Madhuca indica oil in supercritical methanol[END_REF][START_REF] Wang | The synergistic effect between ZnO and ZnCr2O4 on the catalytic performance for isobutanol synthesis from syngas[END_REF][START_REF] Mousavi | Experimental investigation of ZnO nanoparticles effects on thermophysical and tribological properties of diesel oil[END_REF][START_REF] Singh | Effect of ZnO nanoparticles concentration as additives to the epoxidized Euphorbia Lathyris oil and their tribological characterization[END_REF]. MoS 2 NPs have exhibited excellent anti-wear, mechanical, and thermophysical properties among various types of nanoparticles. Their lubricity characteristics associate with the inherent structure namely the vast space and weak Van der Waals forces that lead them to move easily on each other [START_REF] Xie | Lubrication performance of MoS2 and SiO2 nanoparticles as lubricant additives in magnesium alloy-steel contacts[END_REF][START_REF] Mousavi | Experimental investigation of MoS2/diesel oil nanofluid thermophysical and rheological properties[END_REF][START_REF] Padma | Structural, chemical, and electrical parameters of Au/MoS2/n-GaAs metal/2D/3D hybrid heterojunction[END_REF].

Numerous comparisons have been performed to examine the anti-wear features and thermal performances of nano-MoS 2 additive oil-based fluids. The outcomes confirmed that the tribological and thermal aspects of the prepared nanofluids are strikingly enhanced by adding nano-MoS 2 particles to the utilized fluid [START_REF] Xie | Lubrication performance of MoS2 and SiO2 nanoparticles as lubricant additives in magnesium alloy-steel contacts[END_REF][START_REF] Janbozorgi | Improving tribological behavior of friction stir processed A413/SiCp surface composite using MoS2 lubricant particles[END_REF][START_REF] Wu | An investigation on the lubrication mechanism of MoS2 nanoparticles in unidirectional and reciprocating sliding point contact: the flow pattern effect around contact area[END_REF][START_REF] Gajrani | Thermal, rheological, wettability and hard machining performance of MoS2 and CaF2 based minimum quantity hybrid nano-green cutting fluids[END_REF]. Dinesh et al. [START_REF] Dinesh | Investigation of tribological and thermophysical properties of engine oil containing nano additives[END_REF] scrutinized the tribological and thermophysical characteristics of engine oil comprising MWCNT and Zinc

Oxide NPs. The outcomes demonstrated that MWCNT and Zinc Oxide NPs were able to advance the operational facets of the engine oil. Esfe et al. [START_REF] Esfe | Improving engine oil lubrication in lightduty vehicles by using of dispersing MWCNT and ZnO nanoparticles in 5W50 as viscosity index improvers[END_REF] analyzed the rheological attributes of engine oil utilizing MWCNT and ZnO NPs. The conclusions showed that the usability of the nano-additives in the engine oil can decrease the damages to motor sections in a cold start of the vehicle. The tribological properties of different base oils using ZnO and CuO NPs as additives have been studied by Alves et al [START_REF] Alves | Tribological behavior of vegetable oil-based lubricants with nanoparticles of oxides in boundary lubrication conditions[END_REF]. They reported that by adding nanoparticles to conventional oil, the anti-frictional features could be remarkably enhanced. A more constant tribo-film had made on the worn surface, which was adequate for the further decreased friction. Cabaleiro et al. [START_REF] Cabaleiro | Thermal conductivity of dry anatase and rutile nano-powders and ethylene and propylene glycol-based TiO2 nanofluids[END_REF] assessed the thermal features of multiple TiO 2 nanofluids. They observed that the prepared nanofluids increased thermal conductivity in comparison with pure fluids. Probes of the lubricating, rheological, and thermal performances of ZnO NPs demonstrated that adding nano zinc oxide particles to the pure fluid can develop the mentioned traits [START_REF] Battez | The tribological behaviour of ZnO nanoparticles as an additive to PAO6[END_REF][START_REF] Moosavi | Fabrication, characterization, and measurement of some physicochemical properties of ZnO nanofluids[END_REF][START_REF] Zeinali Heris | Rheological behavior of zinc-oxide nanolubricants[END_REF][START_REF] Cabaleiro | Transport properties and heat transfer coefficients of ZnO/(ethylene glycol+ water) nanofluids[END_REF][START_REF] He | Boiling heat transfer characteristics of ethylene glycol and water mixture based ZnO nanofluids in a cylindrical vessel[END_REF][START_REF] Pietruszka | Abrasion resistance of ZnO and ZnO: Al films on glass substrates by atomic layer deposition[END_REF][START_REF] Nadooshan | Evaluating the effects of different parameters on rheological behavior of nanofluids: A comprehensive review[END_REF]. Hu et al. [START_REF] Hu | Tribological properties of 3 types of MoS 2 additives in different base greases[END_REF] conducted a tribological comparison between three different types of MoS 2 in various greases. The results explicated that any MoS 2 enhanced the wear resistance of the three greases in most cases under the chosen measurement conditions.

Zawawi et al. [START_REF] Zawawi | Thermo-physical properties of Al2O3-SiO2/PAG composite nanolubricant for refrigeration system[END_REF][START_REF] Zawawi | Experimental investigation on thermo-physical properties of metal oxide composite nanolubricants[END_REF] al. [START_REF] Minea | Natural convection heat transfer utilizing ionic nanofluids with temperature-dependent thermophysical properties[END_REF] conducted a study to compare the thermophysical qualities of diverse nanofluids. The outcomes manifested that adding alumina to the ionic liquid can exceptionally enhance thermophysical properties. Research performed by Zhengfeng et al. [START_REF] Cao | Nano-montmorillonite-doped lubricating grease exhibiting excellent insulating and tribological properties[END_REF] proved that the addition of three kinds of nano-montmorillonite as additives in the grease can enhance the lubricity attributes. Lou et al. [START_REF] Luo | Tribological properties of Al2O3 nanoparticles as lubricating oil additives[END_REF] researched to examine the lubricity aspects of the Al work is a continuation of the previous one [START_REF] Mousavi | Experimental comparison between ZnO and MoS 2 nanoparticles as additives on performance of diesel oil-based nano lubricant[END_REF] to complete the characterization and demonstrate the potential of nano-lubricants considering different measurements.

In the current investigation, diesel oil-based nanofluids were prepared using a two-step preparation technique with 0.1, 0.4, and 0.7 wt.% of ZnO and MoS 2 NPs, and the impact of nanoparticle concentration on the viscosity, tribological, and physicochemical features of the nanofluids was analyzed.

Experimental materials and methods

Materials

Zinc oxide (ZnO) and molybdenum disulfide (MoS 2 ) as the precursor, SAE-40 monograde diesel engine oil as the core fluid, and Triton X-100 as the surfactant were procured from US Research-Nanomaterials, Sigma-Aldrich, Pars oil co, and Samchun, respectively. Table 1 presents the main features of the nanoparticles from the manufacturer data. Characteristics of the base fluid are shown in Table 2. SEM characterization (Zeiss, Germany) was performed for the analysis of ZnO and MoS 2 NPs. The crystalline form of the used nanoparticles was examined using powder X-ray diffraction (XRD, PHILIPS-PW1730, Netherlands) with Cu-K radiation ( = 0.14056 nm) at room temperature. The XRD patterns were performed at room temperature ranging in at a rate of 3° min -1 . The Debye-Scherrer's formula was applied to compute the crystallite size of the nanoparticles, based on the XRD schema [START_REF] Esfe | Viscosity and rheological properties of antifreeze based nanofluid containing hybrid nano-powders of MWCNTs and TiO2 under different temperature conditions[END_REF]:

(

Where D, λ, , and are the particle size perpendicular to the regular line of plane, the wavelength of X-ray, the entire width at the half summit of the diffraction peak, and the Bragg angle of the peak.

Preparation of nanofluids

The nano-ZnO and nano-MoS 2 particles were added to the diesel oil at 0.1, 0.4, and 0.7 wt.%. The nanofluids were prepared at different concentrations from 0.02 wt.% to 0.8 wt.%; however, there were no conspicuous differences between the results for each test at the concentration below the 0.1 wt.%. The most significant reason for this phenomenon is the fact that because of the high viscosity of the base diesel oil, nanoparticles could not strikingly affect the investigated parameters at lower concentrations-that is-below the 0.1 wt.%. To possess satisfying dispersibility, Triton X-100 (mass proportion of 1 to 2 with nanoparticle) as the surfactant was poured into the nanofluid mixture. The required value of nanoparticles and surfactant were accurately balanced employing a precision electronic balance and mixed with the diesel oil. The suspension was mixed using a mechanical stirrer at 900 rpm for about 3 hours and was agitated with an ultrasonic agitator (Parsonic 2600s, Iran) for about 45 min to provide a stable nanofluid. The sonication operated at a frequency of 28 kHz and a nominal power of 70 W at room temperature. Multiple concentrations were prepared to study the influence of the nanoparticle content.

Kinematic viscosity analysis

The kinematic viscosity was assessed based on ASTM D445. The kinematic viscosity was assessed using an Opaque viscometer (Accuracy: 0.3%) at atmospheric pressure. The viscometer bath was employed to control the temperature. All analyses were conducted three times. Kinematic viscosity of the prepared nanofluids was discovered at 40°C -100°C.

Tribological analysis

The tribological features of the produced nanofluids at various concentrations were assessed and compared to the base diesel oil using a pin-on-disc tribometer based on the ASTM G99. The tribological experiments were carried out at 25℃ with a sliding velocity of 150 rpm and a weight of 75 N. The analyses were carried out under various loading bars varying from 20 N to 75 N; however, because of the high viscosity of diesel oil, lower loading bars could not affect, and significant change was not seen in the recorder COF values. Thus, 75 N was considered as the loading bar. The sliding length was 1000 m. The material of the pins was hardened bearing steel (AISI 52100). The diameter and length of the pins were 5 mm and 50 mm, respectively. Before the tribological examination, the pin and disc were purified utilizing acetone. The normal force was applied applying load rings. The specimen is rotated at a selected speed. The rotation of the sample and the sample holder were controlled by the motor. The examinations were done using the prepared nanofluids, and outcomes were compared with the pure diesel fluid. The friction coefficient values were reported; furthermore, the surface roughness R a was measured. All tests were replicated at least three times, and the average value of each was determined.

Friction factor determination

The friction factor and the pressure drop of nano-lubricants in a copper tube were measured using an experimental setup described as follows. The system consisted of a pump to transport the working fluids at different velocities, a fluid tank, valves, pressure gauges, and a flow meter.

Fig. 1 exhibits the schematic of the system.

Data and uncertainty analysis

The theoretical friction factor (f) for laminar flow and Reynolds number are obtained as [START_REF] Chen | An explicit equation for friction factor in pipe[END_REF][START_REF] Mckeon | Friction factors for smooth pipe flow[END_REF]:

(

where , , and are the diameter of the pipe as a specific length, velocity, and kinematic viscosity, and is Reynolds number. Velocity and flow rate circumscribed by Eqs. ( 4) and ( 5), sequentially [START_REF] White | Fluid mechanics[END_REF].

where , , , and are time, volume, the cross-section area of the pipe, and flow rate.

Theoretical ( ) pressure difference was defined by Eq. ( 6) [START_REF] Peiyi | Measurement of friction factors for the flow of gases in very fine channels used for microminiature Joule-Thomson refrigerators[END_REF].

L and are the pipe length and density of the fluid.

The pumping power was determined by utilizing Eq. ( 7).

(

) 7
Considering the devices employed in this research have various precision and the parameters were estimated with these tools possess errors, it is essential to examine the impact of analysis error on these outcomes. If P is a function of empirical variables such as x 1 , x 2 , x 3 , …, x n , the subsequent formula is applied to assess the determination error of the parameter x i [START_REF] Holman | Experimental methods for engineers[END_REF]:

(8)
where x i is the assessable quantity and is the determination error. The highest error of parameter P is determined by merging the error of per parameter x i utilizing the subsequent formula:

As stated earlier, the Reynolds number is determined as , and the generated error from the Reynolds number is proved as follows: [START_REF] Wang | Thermal conductivity and rheological properties of graphite/oil nanofluids[END_REF] Given that , is computed as follows:

(11)

Additionally, the generated error by the volumetric flow rate is determined as that is defined by Eq. ( 12).

(

) 12
The error of the friction factor ascertainment is similar to the error correlated with the Reynolds number.

(

) 13
Hence, the highest friction factor error in the analyses reached 1.1%.

Errors for all measured parameters are calculated as follows:

The mass of base fluid:

The mass of nanoparticle:

The nanoparticle weight fraction:

The temperature:

The kinematic viscosity:

Results and discussion

Materials: characterization

The SEM pictures of the nano-ZnO and nano-MoS 2 particles are displayed in Fig. 2. Based on the SEM pictures, the nano-ZnO and nano-MoS 2 particles have a nearly spherical form and platelet-like shape with an average diameter of 30 nm and 90 nm, respectively. The XRD patterns of the nano-ZnO and nano-MoS 2 particles are displayed in Fig. The maximum viscosity increment was obtained at 0.7 wt.% and 100 °C for both prepared nanofluids. Considering the results, it can be concluded that the ZnO nanofluids were more resistant to move in comparison with the MoS 2 diesel oil-based nanofluids. One of the commonly utilized formulas for evaluating the relation between the viscosity and temperature of the manufacturing oils is Walther function, which is characterized by Eq. ( 14)

Viscosity

[81]:

Where , , and T are the kinematic viscosity (mm 2 /s), 0.7 for the kinematic viscosity greater than 2 mm 2 /s, the temperature (K), and b and n attribute to fixed parameters that are specified Einstein proposed the dependency of viscosity on the volume portion of the nanoparticles.

Einstein assumed that the particles were in very dilute suspensions, namely solid spheres without interactions, and the improvement in the shear makes the rotary movement of the particles; thus, raises the dispersal viscosity. The Einstein formula, which can be utilized for suspensions having a particle volume portion below 0.01 ( ) is depicted as follows [START_REF] Einstein | Investigations on the Theory of the Brownian Movement[END_REF]:

(15) (16)
where , , , and, are viscosity, the volume fraction of nanoparticles, mass, and density.

Many equations have been proposed to calculate the relative viscosity ( ) using the volume portion of nanoparticles which are noted in Table 4. In equations, the diameter of the molecule of base fluid ( ) was defined by Eq. ( 17).

(

) 17
Where , , and are the molecular mass of the diesel oil, Avogadro number, and the mass density of diesel oil calculated at temperature K.

is the diameter of the nanoparticles.

The calculated values of the relative viscosity applying various models at different volume fractions of MoS 2 nanofluids are listed in Table 5. The alteration of the relative viscosity for MoS 2 nanofluids using different models and also the comparison between these models with the experimental data are presented in Fig. 5. As can be noticed in these figures, the theoretical models could not foretell the relative viscosity-mass fraction of the nanoparticles relation since these models did not ponder the size, shape, sort of the nanoparticles, sort of base fluids, and agglomeration of the nanoparticles, as well as temperature, while above-mentioned factors have a significant impression on the viscosity of nanofluids. As it is shown, the Einstein model unpredicted viscosity and this model was only developed for sphere nanoparticles. Numerous studies have also asserted similar conclusions considering different nanofluids, in which empirical results are not agreeable with the considered models [START_REF] Kole | Effect of aggregation on the viscosity of copper oxide-gear oil nanofluids[END_REF][START_REF] Kole | Role of interfacial layer and clustering on the effective thermal conductivity of CuO-gear oil nanofluids[END_REF][START_REF] Rashin | Viscosity studies on novel copper oxide-coconut oil nanofluid[END_REF][START_REF] Kotia | Effect of copper oxide nanoparticles on thermophysical properties of hydraulic oil-based nanolubricants[END_REF]. determined that the average COFs of the nanofluids diminished with the content ranging from 0.1 wt.% to 0.7 wt.%. Fig. 6 shows that the friction coefficient diminished when the content of nano-ZnO particles was under 0.4 wt.%. However, when the content exceeded 0.4 wt.%, the friction coefficient increased. On the other hand, Fig. 7 6. Based on the computed surface roughness ( ), it can be discerned that the worn surfaces became smooth after the friction experiment due to the polishing impact of the diesel oil. Moreover, the roughness average of surfaces ( ) decreased with the addition of the nanoparticles to the diesel oil. (g)

Friction characteristics

Friction factor

The friction factor and the experimental pressure difference values were acquired using the devised laboratory at diverse flow rates for different nanofluids and the results were compared to the pure diesel oil. The variety of the friction factor at the measured flow rates, inlet velocity, Reynolds number, kinematic viscosity, the difference between the experimental and theoretical pressures at various content of nanoparticles are listed in Table 7. According to the data listed in Considering Fig. 10, it can be comprehended that the pumping power was enhanced by adding the nano-additives to the base fluid, as expected. The reason for this phenomenon is the fact that the pressure drops increased by increasing the flow rate, hence the increment in the pressure drop caused an augmentation in pumping power.

Conclusion

The effects of ZnO and MoS 2 NPs on the viscosity, tribological, and physicochemical attributes of diesel oil were evaluated. The following outcomes can be presented:

1. It was noticed that the kinematic viscosity and viscosity index of the samples raised with the incorporation of nanoparticles. Furthermore, the rise in kinematic viscosity grew by rising nanoparticle concentration. At each concentration of nanoparticles, ZnO nanofluids had higher kinematic viscosity compared to the MoS 2 nanofluids. The maximum rise in the kinematic viscosity was seen at 0.7 wt.% for each nanofluid. Walther equation 3. Evaluating the effect of the nanoparticles content on friction factor at the measured flow rates and inlet velocities showed that the friction factor increased by adding the NPs to the base fluid. In addition, the pumping power was enhanced by the incorporation of nanoparticles.

  studied thermal conductivity and viscosity behaviors of three diverse mixtures of nanoparticles in the base lubricant (PAG composite nano-lubricants) at diverse nanoparticle volume levels and temperatures. They found that the usage of nanoparticles in the pure lubricant improved the thermophysical traits such as thermal conductivity and dynamic viscosity. Coelho et al. [50] analyzed the thermophysical qualities of CuO nanofluids. The results declared that both permittivity and electrical conductivity developed with the addition of nano-CuO particles. Ding et al. [51] conducted a study for understanding the tribological features of silica NPs water-based lubricants. They published that the silica NPs can significantly improve the tribological performances when added to the base lubricant. Empirical research of the thermal characteristics of Al 2 O 3 /water nanofluid proved that adding Al 2 O 3 NPs as an additive can substantially raise the thermal traits of the nanofluid [52-56]. Karimi et al. [57] estimated the thermal conductivity acts of NiFe 2 O 4 nanofluids at diverse concentrations. They noticed that the thermal conductivity of the samples raised with the increasing temperature and content. Minea et

Fig. 1 .

 1 Fig. 1. Design of the laboratory device.

Fig. 2 . 13 Fig. 3 .

 2133 Fig. 2. SEM images of (a) ZnO NPs, (b) MoS 2 NPs.

Fig. 4 .

 4 Fig. 4. depicts the impact of the ZnO and MoS 2 NPs concentration and temperature on the kinematic viscosity of the diesel oil, at 40°C -100°C. According to Fig. 4, it can be seen that the kinematic viscosity of all specimens including ZnO and MoS 2 NPs, has increased concerning the pure diesel oil. The increase was more substantial at greater concentrations because of the agglomeration of the increase in nanoparticles. While the temperature rises, the kinematic viscosity of all specimens was reduced since the intermolecular strengths are weakened by increasing the temperature. At each measured temperature, ZnO nanofluids showed higher viscosity values than diesel oil comprising nano-MoS 2 particles since the ZnO nanofluids are

Fig. 4 .

 4 Fig. 4. Variation of kinematic viscosity of diesel oil containing ZnO and MoS 2 NPs at different concentrations with temperature.

Figs. 6 8 .

 68 Figs. 6 and 7 illustrate the recorded friction coefficients (COFs) vs time for the base sample, ZnO, and MoS 2 diesel oil-based nanofluids with various contents (0.1 0.7 wt.%) at rotating speed of 150 rpm and applied load of 75 N. The mean values of the COFs are also shown in Fig.8. The performance of diesel oil without and with nanoparticles was assessed. The outcomes reveal that all the samples lead to an initial short running-in period and the COF stabilizes almost 300 seconds after the starting of the tribological analysis. Other researchers[START_REF] Mosarof | Assessment of friction and wear characteristics of Calophyllum inophyllum and palm biodiesel[END_REF][START_REF] Ripoll | In situ tribochemical sulfurization of molybdenum oxide nanotubes[END_REF][START_REF] Cheah | Physicochemical and tribological properties of microalgae oil as biolubricant for hydrogen-powered engine[END_REF] also noticed similar conclusions concerning different nanofluids proving that the continuance of the run-in phase is reliant on various factors of the contact surfaces such as geometrical, chemical, and physical; moreover, the capacity of the lubricating fluid to produce a proper tribo-film. It is

1 Fig. 6 . 20 Fig. 7 .

 16207 Fig. 6. Friction coefficient (COF) of the ZnO nanofluids with various contents as a function of time.

Fig. 8 .Fig. 9

 89 Fig. 8. Average friction coefficient (COF) values of the nanofluids at various concentrations.

Fig. 9 .

 9 Fig. 9. Profile curve of wear scar of (a) pure diesel oil, (b) 0.1 wt.% ZnO nanofluids, (c) 0.4 wt.% ZnO nanofluids, (d) 0.7 wt.% ZnO nanofluids, (e) 0.1 wt.% MoS 2 nanofluids, (f) 0.4 wt.% MoS 2 nanofluids, (g) 0.7 wt.% MoS 2 nanofluids.

Fig. 10 exhibits

 10 Fig. 10 exhibits the change of pumping power based on flow rates at various contents.

Fig. 10 .

 10 Fig. 10. Change of pumping power as a function of flow rate at different concentrations.

Table 1

 1 Properties of the nanoparticles.

	Properties	ZnO	MoS 2
	Color	White	Gray/Black
	Purity (%)	99.9	99
	Density (g/cm 3 )	5.6	5.06
	Size (nm)	30	90

Table 2

 2 Characteristics of the diesel oil.

	Base Fluid	Physical properties	Value
		Pour point, °C	-17.8
		Flash point, °C	238
	Monograde diesel oil (SAE-40)	Density, Kg/cm 3 at 15 °C Kinematic viscosity, cSt at 40 °C	0.893 162.53
		Kinematic viscosity, cSt at 100 °C	14.62
		Viscosity Index (VI)	86.85

  [START_REF] Zeinali Heris | Thermal behavior of a two phase closed thermosyphon using CuO/water nanofluid[END_REF]. The XRD pattern of the ZnO NPs shows peaks at 2 = 31.88, 34.58, 36.43, 47.73, 56.73, 62.93, 66.83, 68.03, and 69.13, which can be classified to the (100), (002), (101), (102), (110), (103), (200), (112) and (201) planes of ZnO. All diffraction peaks were in arrangement with the diffraction data of the standard card (JCPDS card number 36-1451) [79]. The XRD pattern of the MoS 2 NPs displays diffraction peaks at 2 = 14.63, 29.18, 32.88, 39.73, 44.38, 50.13, 60.48 and 70.23 matching to the (002), (004), (100), (103), (104), (105), (112), and (200) crystal planes of the MoS 2 structureaccording to the source data of JCPDS card number 37-1492[START_REF] Wu | Fabrication and tribological properties of oil-soluble MoS2 nanosheets decorated by oleic diethanolamide borate[END_REF]. No impurity peaks were identified. The crystallite sizes of ZnO and MoS 2 calculated according to the principal peak breadth in the XRD schema by Eq. (1) were 14.2 nm and 32.6 nm, respectively. The nanoparticles are presented with an agglomeration of several crystals; thus, in most cases, the average diameter of nanoparticles is higher than the crystallite size. Comparing the average diameter and crystallite size of nanoparticles, it can be concluded that ZnO NPs are more agglomerated.

  on the oil sort. The parameters b and n obtained from Eq. (14) for different concentrations of the ZnO and MoS 2 NPs are gathered in Table3. According to the values, it can be asserted that the aforementioned model can properly determine the changes in the kinematic viscosity of the ZnO and MoS 2 NPs with temperature in the studied range.

		200 180	162,53	169,50	170,81	171,89	172,61	[VALEUR]	176,79							0 0.1 wt.% MoS2 0.1 wt.% ZnO
		160														0.4 wt.% MoS2
	2 /s) (mm	140														0.4 wt.% ZnO 0.7 wt.% MoS2
	Kinematic viscosity	60 80 100 120							58,72	61,69	62,17	62,93	63,03	64,10	64,41	0.7 wt.% ZnO
		20 40													27,08	28,53	28,76	29,03	29,21	29,61	29,74	14,62	15,45	15,56	15,70	15,80	16,02	16,10
		0
						40						60				80	100
													Temperature (°C)

based

Table 3

 3 Parameters acquired from the fitting of alteration in kinematic viscosity with temperature using the Walther function.

	Concentration (wt.%)	b	n
	0	9.23	3.56	0.99
	0.1 ZnO	9.07	3.49	0.99
	0.4 ZnO	9.02	3.47	0.99
	0.7 ZnO	8.99	3.46	0.99
	0.1 MoS 2	9.08	3.50	0.99
	0.4 MoS 2	9.04	3.48	0.99
	0.7 MoS 2	9.02	3.47	0.99

Table 4

 4 Classic equations to calculate the relative viscosity.

	Author	Equation
	Corcione [87]
	Sharma [88]

Table 5

 5 Relative viscosity of MoS 2 nanofluids at diverse volume fractions. Relative viscosity as a function of volume fraction for MoS 2 nanofluids.

	Nanoparticle

  Having considered the pure diesel oil, the reduction of the values after the test was 3.64%, 21.33%, and 11.14% for 0.1 wt.%, 0.4 wt.%, and 0.7 wt.% ZnO nanofluids, respectively. MoS 2 nanofluids. Hence, MoS 2 nanofluids showed lower values compared to those of ZnO nanofluids proving better anti-friction behavior of the MoS 2 NPs.

	Whereas the reduction of the	values was 12.82%, 43.95%, and 60.75% for 0.1 wt.%, 0.4
	wt.%, and 0.7 wt.%

Table 6

 6 The measured surface roughness ( ) values of the worn surfaces before and after the test at different concentrations of ZnO and MoS 2 nanofluids.

	Concentration (wt.%)	(before test)/µm	(after test)/µm	/µm
	0 (pure diesel oil)	6.922	5.136	1.786
	0.1 ZnO	6.971	5.120	1.851
	0.4 ZnO	5.942	3.775	2.167
	0.7 ZnO	6.395	4.410	1.985
	0.1 MoS 2	4.601	2.586	2.015
	0.4 MoS 2	5.016	2.445	2.571
	0.7 MoS 2	5.279	2.413	2.866

Table 7 ,

 7 it can be concluded that the friction factor and Reynolds number had an opposite relation since the kinematic viscosity of the samples was increased by adding the nano-additives.At each flow rate, higher amounts of the friction factor were seen in comparison with the base fluid without nano-additives because by increasing the content of the nanoparticles, the kinematic viscosity of the nanofluids increased. By comparing the experimental and theoretical pressure values, it can be concluded that the laboratory had a proper performance. Based on the acquired outcomes, the pressure drops in the tube increased with the rising in the Reynolds number or inlet velocity. Recently, researchers have stated the identical trend for other nanofluids[START_REF] Mousavi | Experimental investigation of MoS2/diesel oil nanofluid thermophysical and rheological properties[END_REF][START_REF] Naddaf | An experimental study on heat transfer performance and pressure drop of nanofluids using graphene and multi-walled carbon nanotubes based on diesel oil[END_REF]. The friction factor was raised in all contents of ZnO and MoS 2 NPs with the

	highest increment of 8.2 % and 8.3% for ZnO and MoS 2 nanofluids happening at 0.7 wt.% with
	the lowest inlet velocity.

Table 7

 7 The difference of friction factor at diverse flow rates for different nanofluids.

	1
	Concentration (wt.%)	(m 3 /s)	(m/s)		(m 2 /s)			Disparity (%)
		1.022	0.161	6.18	234.065	10.36	14654.91	3.58
		1.211	0.190	8.82	194.273	7.26	14302.62	4.35
	0 (pure diesel oil)	3.614	0.568	29.67	172.341	2.16	38029.63	4.94
		5.311	0.835	43.59	172.341	1.47	55932.20	5.42
		1.022	0.161	5.90	245.058	10.84	15331.46	2.29
		1.211	0.190	8.41	203.804	7.61	14989.75	4.94
	0.1 ZnO	3.614	0.568	28.24	181.016	2.27	39959.97	3.13
		5.311	0.835	41.50	181.016	1.54	58586.32	5.44
		1.022	0.161	5.85	247.333	10.95	15479.58	5.68
		1.211	0.190	8.32	205.830	7.69	15140.03	4.10
	0.4 ZnO	3.614	0.568	27.96	182.889	2.29	40292.60	4.82
		5.311	0.835	41.08	182.889	1.56	59318.58	2.43
		1.022	0.161	5.71	253.322	11.21	15839.33	6.37
		1.211	0.190	8.13	210.767	7.87	15486.79	6.69
	0.7 ZnO	3.614	0.568	27.31	187.248	2.34	41152.09	11.29
		5.311	0.835	40.12	187.248	1.60	60809.62	5.38
		1.022	0.161	5.95	243.190	10.76	15218.06	3.24
		1.211	0.190	8.47	202.245	7.56	14891.01	5.31
	0.1 MoS 2	3.614	0.568	28.46	179.629	2.25	39607.22	4.13
		5.311	0.835	41.83	179.629	1.53	58204.90	2.10
		1.022	0.161	5.87	246.436	10.91	15421.96	4.36
		1.211	0.190	8.36	205.024	7.66	15079.92	5.40
	0.4 MoS 2	3.614	0.568	28.07	182.141	2.28	40113.88	2.81
		5.311	0.835	41.25	182.141	1.55	58934.26	2.17
		1.022	0.161	5.70	253.585	11.22	15851.55	4.43
		1.211	0.190	8.12	210.872	7.88	15504.60	2.55
	0.7 MoS 2	3.614	0.568	27.30	187.278	2.34	41147.15	3.08
		5.311	0.835	40.12	187.278	1.60	60802.32	3.62

Flow rate (cubic m/s) foretells

  well the kinematic viscosity temperature relation. The selected theoretical models do not predict the relative viscosity enhancement with nanoparticle volume fraction.2. Having fewer COF values and lower the roughness average of surfaces ( ), it can be inferred that the ZnO and MoS 2 nanofluids had more desirable tribological characteristics. The optimal content of ZnO and MoS 2 NPs were 0.4 wt.% and 0.7 wt.%, respectively.

		3500
		3000
	power (mW)	1500 2000 2500
	Pumping	500 1000
		0	1,02E-05	1,21E-05	3,61E-05	5,31E-05
		Base	144,409	165,665	1306,461	2809,519
		0.1 (ZnO)	153,096	172,568	1398,979	2942,294
		0.4 (ZnO)	149,212	175,837	1385,969	3074,007
		0.7 (ZnO)	151,563	174,990	1319,291	3055,949
		0.1 (MoS2)	150,490	170,751	1372,236	3026,208
		0.4 (MoS2)	150,745	172,749	1408,918	3062,057
		0.7 (MoS2)	154,833	182,982	1441,263	3112,246