Viscosity Of Hybrid Nanofluid Research Articles

Heat transfer and flow characteristics of cuo-al2o3 hybrid nanofluids in slotted finned channels

This study aimed to investigate the heat transfer coefficient of CuO-Al2O3 hybrid nanofluids within a microchannel heatsink, focusing on the impact of flow rate and volume fraction. The thermal conductivity and viscosity of hybrid nanofluids with different particle ratios were investigated. The results showed that the nanofluids have a more remarkable enhancement in thermal conductivity than water. Employing the hybrid nanofluids enhanced the heat transfer coefficient significantly. Furthermore, a slight growth in the friction factor was observed.

Investigation of the effects of various parameters and the evaluation of the optimal rheological of MWCNTs based hybrid nanolubricant and providing an optimal model

The rheological behavior of MWCNT-Al2O3 (10%−90%) / SAE40 oil hybrid nanofluid (HNF) is done with using RSM statistical method in this study. The investigation is carried out under conditions of temperature within the range T = 25–50 °C, solid volume fraction between SVF= 0.0625 until 1% and shear rate in the range of SR= 666.5–9331 s−1. In this study, three different models of 2FI, Quadratic and Cubic are evaluated using correlation indices and quality determination charts. Cubic model is chosen as the optimal model among these models and for optimization, the viscosity of HNF is used. The values of R2, C.V, C.D, P-value and Std. Dev correlation indices for the selected model are 0.9996, 1.04, −3.785 <C.D %< 4.333, 2.55e-264 and 2.12, respectively. The effects of SVF, temperature and SR parameters on viscosity are investigated. It is found that SR has the least effect and temperature has the most effect on the viscosity of HNF. Lubrication is performed for cold environment conditions. The parameters of SVF, SR, temperature and viscosity are considered at the minimum value. After performing the optimization process by DOE, the most optimal mode for the HNF viscosity is in T = 35.210°C, SVF= 0.063%, SR= 666.511 s−1 and the viscosity is 191.450 mPa.sec.

The effect of pH on stability and thermal performance of graphene oxide and copper oxide hybrid nanofluids for heat transfer applications: Application of novel machine learning technique

This paper investigates the effects of pH on stability and thermal properties of copper oxide (CuO), graphene oxide (GO), and their hybrid nanofluid (HNF) at different mixing ratios. Initially, sol-gel and Hummer’s method was employed for the synthesis of CuO and GOnanoparticles (NPs), and they are characterized with various techniques. The effects of two different surfactants were analyzed on nanofluid’s (NF’s) stability at different pH values. The properties like thermal conductivity (TC) and viscosity (VST) of NFs were measured at different volume concentration (0.1 vol% to 1.0 vol%) and temperature range of 30–60 °C, respectively. The TC and VST of GO/CuO (50:50) HNF are higher than that of GO/CuO (20:80). The figure of merit (FOM) is determined for the studied HNFs. The correlations were presented to calculate the TC as well as VST of HNFs. Two modern novel machine learning-based ensemble approaches were employed for predictive model development for TC and VST of considered HNFs. The comparison of prognostic models with Taylor’s diagram revealed that Bayesian optimized support vector machine (BoA-SVM) was superior to Bayesian optimized boosted regression trees (BoA-BRT) for both TC and VST models.

Using the RSM to evaluate the rheological behavior of SiO2 (60%) - MWCNT (40%)/SAE40 oil hybrid nanofluid and investigating the effect of different parameters on the viscosity

The present study predicts dynamic viscosity of SiO2 (60%) - MWCNT (40%) hybrid nanofluid (HNF) in SAE40 oil as base fluid (BF) by comparing various models of RSM. This study was conducted under laboratory conditions with solid volume fractions of SVF= 0–1%, temperature of T = 25–50 °C and shear rates of SR= 666.5–9331 s−1. Different models were used for this study, including 2FI, Quadratic, Cubic and Quartic models. These models were evaluated based on a series of quality indicators and charts. The indicators that were investigated in this study include standard deviation, coefficient of determination, P-value, correlation deviation (C.D) and coefficient of variation. After checking the quality indicators and charts for different models, the Quartic model was selected as the optimal model. In this study, the correlation functions of various models were used to determine the viscosity of HNFs. Then, according to the evaluation of the models, the Quartic model has been selected as the optimal model. The correlation function presented for the Quartic model has an acceptable accuracy in predicting the viscosity values of HNFs compared to the experimental data. Also, due to the dependence of viscosity on SR, the behavior of HNF is non-Newtonian. The values of standard deviation, coefficient of determination, P-value, correlation deviation, and coefficient of variation for the selected model were 6.67, 0.9960, 1.548584974e-218, − 4. 760 <C.D< 8.551 and 3.48, respectively. Next, the viscosity of HNF was optimized for the selected model in cold environmental conditions. The best state of viscosity of HNF in the cold environment in the conditions of SVF= 0, T = 31.958 °C and SR= 666.500 s−1 was 216.978 mPa.sec. Next, the different parameters effect on the viscosity of HNF was investigated and it has been determined that the temperature and SR parameters have the greatest and least effect on the viscosity of HNF, respectively. The findings can help to better understanding of rheological behavior of HNF and SAE40 engine oil in cold environmental conditions. By using the correlation function provided in the selected model, the viscosity of HNF can be calculated at any temperature, SVF and SR. This saves time and money and helps a lot to the industries that use this HNF and SAE40 engine oil.

Synthesis, thermophysical characterization and thermal performance analysis of novel Cu-MXene hybrid nanofluids for efficient coolant applications.

Hybrid nanofluids are considered as an alternative for conventional heat transfer fluids and mono nanofluids due to its remarkable enhancement in thermo-physical properties. However, there are some limitations in achieving the better thermo-physical properties due to the stability of nanoparticles in different base fluids at higher concentration. This work aims at synthesizing, thermo-physical characterization and thermal performance estimation of stable Cu-MXene based hybrid nanofluids using various base fluids at very low volume concentration of Cu and MXene nanostructures. Two step method is employed to prepare Cu-MXene hybrid nanofluids by dispersing the low volume concentration of as prepared Cu and MXene nanostructures (ranging from 0.01-0.05 vol%) containing SDS surfactant in various base fluids such as water, methanol, castor oil and silicon oil. Synthesized mono and hybrid nanofluids shows excellent stability against aggregation up to 7 days as evidenced from higher zeta potential values. Wettability studies conducted using contact angle measurement suggests that the castor oil, methanol and silicon oil based hybrid nanofluids exhibits hydrophilic behavior (showing contact angle less than 90°). Hybrid nanofluids display excellent enhancement in thermal conductivity at very low concentration of nanostructures (more than 70% for methanol based Cu-MXene hybrid nanofluid). Viscosity of the silicone oil based hybrid nanofluids show a remarkable enhancement followed by water, methanol and castor oil based hybrid nanofluids. Thermal conductivity and viscosity of hybrid nanofluids are effectively validated with existing theoretical models. Moreover, specific heat and pumping power of the hybrid nanofluids with respect to volume concentration of nanostructures are determined using the existing theoretical equations. Thermal performance of hybrid nanofluids was successfully estimated using Figure of Merit (FOM) analysis and suggested the better heat transfer fluid for improving the heat transfer performance under laminar and turbulent flow conditions for efficient cooling applications.

Experimental study on the thermal properties of Al 2 O 3 ‐CuO /water hybrid nanofluids: Development of an artificial intelligence model

In this work, Al2O3 and CuO nanoparticles were synthesized by a novel sol-gel method. Then, water-based Al2O3 and Al2O3-CuO (50:50) nanofluids were produced by the two-step method. The viscosity and thermal conductivity of nanofluids were determined for the concentration and temperature range of 0-1.0 vol.% and 30-60°C, respectively. Sodium dodecylbenzene sulfonate surfactant was used to enhance the nanofluid stability. Field emission scanning electron microscopy, transmission electron microscopy, and x-ray diffraction techniques were used for the morphological characterization of the nanoparticles. The pH and zeta potential were used to determine the stability of the nanofluid. The outcomes show that the maximum augmentation in thermal conductivity and viscosity of hybrid nanofluid is 14.6 and 6.5% higher than Al2O3 nanofluid for 1.0 vol.% at 60 and 30°C, respectively. The maximum viscosity enhancement of Al2O3 and hybrid nanofluid is 14.9 and 21.4% is noticed at 30°C for a concentration of 1 vol. % relative to the base liquid. The novel equations were proposed to estimate the viscosity and thermal conductivity of hybrid nanofluid based on the experimental results with R2 values of 0.99 and 0.98, respectively. A cascaded forward neural network model was developed to predict the thermal properties using experimental datasets. The performance enhancement ratio of hybrid nanofluids indicated its potential for solar energy applications.

Numerical study of hydrodynamic and thermal behavior of Al2O3/Water nanofluid and Al2O3-Cu/Water hybrid nanofluid in a confined impinging slot jet using two-phase mixed model

This study utilizes the two-phase mixture model to conduct a numeric study of Al2O3/Water and Al2O3-Cu/Water (hybrid) nanofluid's hydrodynamic and thermal behavior in a laminar confined impinging slot jet in 50 ≤ Re ≤ 300 and nanoparticles volume fractions (NVF) ranging from 0 - 2%. This study considers various aspect ratios (H/W), including 2, 4, and 6, to investiate the confining effects. This paper gives a comparative analysis of nanofluids and hybrid nanofluids in terms of the parameters concerning the flow: Reynolds and local Nusselt number (Nux), average Nusselt number (Nuavg), flow lines' contour, and temperature distribution under similar geometric conditions and Reynolds number. In comparison with nanofluids, the hybrid nanofluids have higher local Nusselt number on the entire target surface, this advantage of hybrid nanofluid attribute to higher thermal conductivity of them. The average Nusselt numbers of nanofluids and hybrid nanofluids plotted at different Refor various aspect ratios(H/W=2,4), and the effect of aspect ratio and momentum are explained. Furthermore, pumping power of both fluid analysed for all nanoparticles volume fraction (0 - 2%) at different Reynolds number. The result shows that pumping power of hybrid nanofluid is higher than base fluid and nanofluid, because the dynamic viscosity of hybrid nanofluid is higher than base fluid (water) and nanofluid. Besides; the study identified some correlations in the hybrid nanofluids regarding the stagnation point and the average Nusselt numbers. Presumably, these correlations are valid under certain conditions: 50≤ Re ≤ 300, 2 ≤ H/W≤ 6, and volume fracture (0 - 2%).

Experimental investigation on thermophysical properties of Therminol® 55 based hybrid nanofluids with alumina and graphene nanoplatelets for medium temperature applications

In light of the stable physical and thermal properties over a wide range of temperatures, Therminol®55 (TH55) have long been used as heat transfer fluids in medium temperature applications. In addressing the demerit of low performance of thermal systems, enhancing the thermal conductivity of TH55 is one of the promising routes to improve the performance of TH55 based systems. It has been postulated that nanofluids have provided more efficient heat transfer than conventional fluids. This study aims to experimentally investigate the effect of dispersing graphene nanoplatelets (GNP) and alumina (Al2O3) nanoparticlesin TH55 on thermophysical properties such as thermal conductivity, viscosity and specific heat. It is found that the use of hybrid nanofluid resulted in an increase in the thermal conductivity of 10.28% and 3.03% as compared with TH55-Al2O3 and TH55-GNP mono-nanofluid, respectively at a temperature of 65 °C. Initially, the viscosity of hybrid nanofluid is found to be increased by 66.99% at 20 °C as compared to the base fluid, and the viscosity decreases significantly as the temperature rises from 20 °C to 90 °C. Due to the lower specific heat of nanoparticles, the specific heat capacity of TH55 based nanofluids decreases with the addition of nanoparticles. Empirical correlations have been developed using the non-linear least square method for thermal conductivity, viscosity and specific heat of the hybrid nanofluids. Results show that the TH55-GNP/Al2O3 hybrid nanofluids can be used as a suitable replacement for the conventional fluids in medium temperature applications.

Numerical investigation on natural convection of hybrid nanofluid Al2O3 – MWCNT/water inside a vertical annulus

A numerical inspection on natural convection inside a vertical annulus interior of which water based (Al2O3 + MWCNT) (7:3) hybrid nanofluid has presently been carried out using CFD solver Ansys Fluent. Finite volume method (FVM) is used to perform the numerical simulations at constant heat flux of 3kW/m2 and various volume fraction (0-0.04) of nanoparticle. The thermal conductivity and viscosity of hybrid nanofluid is computed by modified Maxwell model and Batchelor model respectively. The paper carried explicit analysis on effect of nanoparticle concentration, Nu number and heat transfer coefficient. The maximum enhancement in average heat transfer coefficient found to be 73.67% when gauged on volume fraction of 0.04.

Particle size-dependent rheological behavior and mechanism of Al2O3-Cu/W hybrid nanofluids

In order to investigate complicated interactions between nanoparticles of different sizes on the rheological characteristics of hybrid nanofluids, Al2O3-Cu/W hybrid nanofluids with volume fractions of 0.3–1.5 vol% were studied in the present study. Moreover, 50 nm Cu nanoparticles and different sizes of Al2O3 nanoparticles, including 20, 30 and 50 nm particles, were utilized in the experiments. Obtained experimental results showed that as the volume fraction increases, the viscosity increases too. When the volume fraction reaches 0.3 vol%, the viscosity increases as the nanoparticle size increases. Moreover, it was found that 20 nm-Al2O3-Cu/W has the lowest viscosity at room temperature. When the volume fraction is higher than 0.3 vol%, the viscosities of 30 nm-Al2O3-Cu/W and 50 nm-Al2O3-Cu/W are low. Moreover, 20 nm-Al2O3-Cu/W hybrid nanofluid shows Newtonian behavior only at low concentrations (<0.3 vol%) and low shear rates (<100 s−1). However, 30 nm-Al2O3-Cu/W and 50 nm-Al2O3-Cu/W are all non-Newtonian fluids. Analysis of variance (ANOVA) indicates that the volume fraction significantly affects the viscosity, contributing to more than 45% in studied temperatures, while the influence of the nanoparticle size is 25%. Finally, it is found that the synergistic effect in hybrid nanofluids affects the nanoparticle arrangement. Accordingly, low-viscosity nanofluids can be achieved by adding nanoparticles of small size at low volume fractions, while large-size nanoparticles are achieved in high volume fractions. The present article is expected to broaden the understanding of the nanoparticle size on the viscosity of hybrid nanofluids.

Experimental determination for viscosity of fly ash nanofluid and fly ash-Cu hybrid nanofluid:Prediction and optimization using artificial intelligent techniques

ABSTRACT The advanced heat transfer applications of nanofluids make it important to investigate their viscous properties. For various engineering applications, accurate measurement of dynamic viscosity of nanofluid plays a major role. This research aims to provide accurate and reliable soft computational algorithms to predict the viscosity of fly ash nanofluids and fly ash-Cu hybrid nanofluids accurately using measured data. In this work, the dynamic viscosity of water-based stable fly ash nanofluid and fly ash–Cu (80:20% by volume) hybrid nanofluid for the concentration range of 0–4 vol.% determined in the temperature range of 30–60°C experimentally. The nanoparticles are characterized by SEM, TEM, and DLS techniques. The stability of the nanofluids assessed by Zeta potential measurement. Outcomes show that the viscosity of hybrid nanofluid is found to be higher than fly ash nanofluid. Correlations are suggested using multiple linear regression analysis to predict the nanofluid viscosity based on the obtained results. We have adopted a novel soft computing technique, namely ANN and MGGP to optimize the dynamic viscosity data of nanofluids obtained experimentally. The MGGP model predicts the viscosity values for fly ash nanofluid by (R = 0.99988, RMSE = 0.0019, and MAPE = 0.25%). In addition, statical analysis reveals that the MGGP model has excellent performance for fly ash-Cu/Water hybrid nanofluid viscosity (R = 0.9975, RMSE = 0.0063, and MAPE = 0.664%). In contrast to the ANN method and multiple linear regression analysis, the MGGP approach exhibits better results in estimating nanofluid viscosity.

3S (Sonication, surfactant, stability) impact on the viscosity of hybrid nanofluid with different base fluids: An experimental study

The present experimental investigation describes the impact of surfactants (such as Benzalkonium chloride (BAC), Cetrimonium chloride (CTAC), Ammonium lauryl sulphate (ALS), PLS (Pottasium lauryl sulphate), Brij 700, and Span 80), sonication time (30–240 min.), and temperature (55 °C ~ 80 °C), on the stability and viscosity of hybrid nanoparticle (CeO2 + MWCNT) for different base fluids (water, silicone oil, EG, and therminol VP-I). The results of Zeta potential analysis indicated that BAC surfactant shows the best impact on hybrid nanofluid stability (HNF). The observed optimum sonication time is 60, 120, 90, and 120 min, respectively, for silicon oil, EG, water, and therminol VP-I for which HNF yields maximum zeta potential value. With the increment in operating temperature range, the stability of prepared HNF using different base fluids and adding six different surfactants has decreased. Furthermore, it is found that with the increase in sonication time, the viscosity of HNF firstly decreases up to an optimum time, after which it increases gradually. The rheological behavior of working HNF for various practical applications of the current suspensions is also reported. From 3S analysis such as sonication, surfactant, and stability, De-Ionized (DI) Water is advisable to be used as a base fluid for the particle combination of CeO2 + MWCNT with 80:20 mixture ratio as it provides long-term stability and marginal viscosity enhancement. Finally, results show that the CeO2 + MWCNT (80,20)/ DI water nano colloidal behaves as a Non-Newtonian fluid as there is no linear agreement found between shear stress and shear rate.

Experimental Investigation on Stability, Viscosity, and Electrical Conductivity of Water-Based Hybrid Nanofluid of MWCNT-Fe2O3.

The superiority of nanofluid over conventional working fluid has been well researched and proven. Newest on the horizon is the hybrid nanofluid currently being examined due to its improved thermal properties. This paper examined the viscosity and electrical conductivity of deionized water (DIW)-based multiwalled carbon nanotube (MWCNT)-Fe2O3 (20:80) nanofluids at temperatures and volume concentrations ranging from 15 °C to 55 °C and 0.1–1.5%, respectively. The morphology of the suspended hybrid nanofluids was characterized using a transmission electron microscope, and the stability was monitored using visual inspection, UV–visible, and viscosity-checking techniques. With the aid of a viscometer and electrical conductivity meter, the viscosity and electrical conductivity of the hybrid nanofluids were determined, respectively. The MWCNT-Fe2O3/DIW nanofluids were found to be stable and well suspended. Both the electrical conductivity and viscosity of the hybrid nanofluids were augmented with respect to increasing volume concentration. In contrast, the temperature rise was noticed to diminish the viscosity of the nanofluids, but it enhanced electrical conductivity. Maximum increments of 35.7% and 1676.4% were obtained for the viscosity and electrical conductivity of the hybrid nanofluids, respectively, when compared with the base fluid. The obtained results were observed to agree with previous studies in the literature. After fitting the obtained experimental data, high accuracy was achieved with the formulated correlations for estimating the electrical conductivity and viscosity. The examined hybrid nanofluid was noticed to possess a lesser viscosity in comparison with the mono-particle nanofluid of Fe2O3/water, which was good for engineering applications as the pumping power would be reduced.

Experimental study on the viscosity of hybrid nanofluid and development of a new correlation

The present experimental analysis targeted on the preparation of water based (Al2O3-SiC-TiO2) ternary hybrid nanofluids by the mistreatment of two-stage methodology. Each vol. fraction sample of ternary hybrid nanofluids consists of an equal proportion of Al2O3-SiC-TiO2 nanoparticles for this analysis. The result for the dynamic viscosity of ternary hybrid nanofluids was examined for a temperature range of 35–40 °C and within a vol. fraction range of (0.01–0.1%). Analysis extended to the morphology characterization study through SEM image, together with an EDX analysis for 0.1% vol. fraction ternary hybrid nanofluid. Furthermore, based on the supported results, a new correlation was projected for the dynamic viscosity of ternary hybrid nanofluid, and also compared with the relevant literatures. The results revealed that the rise in vol. fraction, contains a larger role in increasing the interior resistance of fluid and the low vol. fractions have a weaker result on the viscosity of ternary hybrid nanofluids. The best relative consistency was discovered within 0.1% vol. fraction and, consistent with the obtained results, the margin of deviation within the intervals of ±2.6%.

Effect of Chitosan Surfactant Concentration on the Thermal Conductivity and Viscosity of Al2O3 + CNT Hybrid Nanofluid

In this paper, the effect of chitosan surfactant concentration on the thermal conductivity and viscosity of Al2O3 + CNT/water hybrid nanofluid is reported. SEM was used to characterize the nanoparticles. The hybrid nanofluid of 0.01% volume fraction was prepared with 1:1 ratio of Al2O3& CNT nanoparticles. Different concentrations of chitosan surfactant as 0.25, 0.5, 0.75, 1.0, and, 1.25 wt.% are employed as stabilizers. Zeta potential measurements were carried out to check the stability of prepared hybrid nanofluid. Thermal conductivity and viscosity of hybrid nanofluid were measured at a constant temperature of 25°C. Finally, the optimum concentration of surfactant using the results obtained is determined.For the most stable suspension, thermal conductivity ratio is 1.0065 and viscosity is 30.2% more than that of the base fluid.

An experimental investigation into the effect of particle mixture ratio on specific heat capacity and dynamic viscosity of Al2O3-ZnO hybrid nanofluids

Hybrid nanofluids are gaining a wide range of applications due to their reported improvement in heat transfer properties. This study presents an experimental investigation into the specific heat and viscosity of Al2O3-ZnO water hybrid nanofluids at three mixture ratios. The specific heat and viscosity measurements are taken over different temperatures at different volume concentrations. The study compared the experimental data to classical models and observed that the specific heat model overestimated and the viscosity model underestimated experimental obtained values. According to results, the particles mixture ratio has a significant effect on both specific heat and viscosity of the hybrid nanofluids. Viscosity increases while specific heat decreases by increasing the volume concentration. Al2O3-ZnO water hybrid nanofluids at 2:1 mixture ratio have a maximum viscosity increase of 96.37% and maximum specific heat decrease of 30.12% at a temperature of 25 °C and volume concentration 1.67%.

Numerical investigation of heat transfer enhancement of a water/ethylene glycol mixture with Al2O3–TiO2 nanoparticles

This paper presents a numerical study of a four-component hybrid nanofluid consisting of binary nanoparticles, Al2O3 and TiO2, dispersed into a double base fluid mixture of water and ethylene glycol. The nanofluid were modeled as a single phase fluid with volume concentrations of 2.5% Al2O3–1.5% TiO2 and 5% Al2O3–3% TiO2 respectively. The nanoparticles are suspended in a double base fluid of water and ethylene glycol mixture with a 70:30 vol ratio. The simulations were conducted for turbulenct flow through a pipe at working temperatures of 293 K and varying Reynolds numbers (7800–2000). Constant heat flux of 129,983 W/m2 heat flux was applied to the pipe wall. The thermal conductivity was enhanced by 24% and 11% at concentrations of 5–3% and 2.5–1.5%, respectively. While, viscosity of hybrid nanofluids was rising up to 70% and 67% at the same concentration. The avarage heat transfer coefficient of Al2O3–TiO2 hybrid nanofluids were enhanced with increase of temperature and volume concentration. It was noted that the maximum heat transfer enhancement is 52% higher than the base fluid for a volume concentration of 5–3%. There is a slight increase in the friction factor of Al2O3–TiO2 hybrid nanofluids with higher volume concentration.

Viscosity of hybrid nanofluids: Measurement and comparison

Viscosity of hybrid nanofluids: Measurement and comparison

Thermal conductivity and electrical properties of hybrid SiO2-graphene naphthenic mineral oil nanofluid as potential transformer oil

Hybrid SiO2-graphene nanoparticles were synthesised by sol gel centrifugation technique under four different pH levels ranging from 9 to 12. Stability, thermal conductivity, viscosity and electrical conductivity of hybrid SiO2-graphene and pure graphene dispersed in naphthenic oil were investigated. Nanofluids were synthesied at three different nanoparticle concentrations (0.01, 0.04 and 0.08 wt%) while the temperature was varied from 20 °C to 100 °C. Field emission scanning electron microscopy (FESEM), x-ray spectroscopy and Fourier transform infrared (FTIR) spectrometer show successful coating of SiO2 on graphene surface. The growth units and size distribution of SiO2 nanoparticles increased with pH level. Moreover, the presence of SiO2 improved the dispersion behaviour of the nanofluid as confirmed by visual observation and UV–Vis studies. Zeta potential measurements show the hybrid nanofluids at pH 11 are most stable due to its optimum amount and size of SiO2 coated on graphene surface while at pH 12 shows least stability due to precipitation. The presence of SiO2 on graphene further enhanced the thermal conductivity by 80% at pH 9. Also, the viscosity of hybrid nanofluids was higher than pure graphene based nanofluids due to increase in density and particle size. Moreover, the addition of hybrid SiO2-graphene nanoparticles significantly reduced the electrical conductivity enhancement of base fluid from 557% to 97%.