Optimization of viscosity of diamond and boron nitride based nanofluids for enhanced thermal management and pumping efficiency
At a Glance
Section titled âAt a Glanceâ| Metadata | Details |
|---|---|
| Publication Date | 2025-04-17 |
| Journal | Materials research proceedings |
| Authors | Aymn Abdulrahman |
| Analysis | Full AI Review Included |
Executive Summary
Section titled âExecutive Summaryâ- Core Objective: Optimization of the viscosity of hybrid diamond/boron nitride (BN) nanofluids suspended in thermal oil to minimize pumping costs and enhance overall thermal management efficiency.
- Material System: Hybrid nanofluids composed of spherical diamond (3-10 nm) and hexagonal BN (0-80 nm) nanoparticles, dispersed in High Thermal Oil (HTO) using a 1:1 ratio and Span-85 surfactant.
- Optimization Methodology: Response Surface Methodology (RSM) combined with a desirability function approach was employed, utilizing a Central Composite Design (CCD) framework.
- Key Finding (Optimal Conditions): Minimum viscosity (0.0113191 Pa.s) was achieved at the optimal combination of high temperature (65°C), mid-range concentration (0.4 wt.%), and moderate shear rate (500.5 1/s).
- Factor Significance: Temperature (T) and Nanofluid Concentration (C) were found to be the most statistically significant factors influencing viscosity (P-values < 0.0001).
- Model Reliability: The quadratic polynomial model demonstrated excellent predictive accuracy, confirmed by Analysis of Variance (ANOVA) with a high coefficient of determination (R2 = 0.9905).
- Rheological Behavior: The optimized nanofluid exhibits desirable Newtonian behavior at low shear rates and shear-thinning attributes at elevated temperatures and shear rates, ideal for advanced cooling applications.
Technical Specifications
Section titled âTechnical Specificationsâ| Parameter | Value | Unit | Context |
|---|---|---|---|
| Nanoparticle Composition | Diamond/BN (1:1 ratio) | N/A | Hybrid nanofluid in High Thermal Oil (HTO) |
| Diamond Particle Size | 3-10 | nm | Spherical morphology |
| Boron Nitride Particle Size | 0-80 | nm | Hexagonal morphology |
| Temperature Range (T) | 25 to 65 | °C | Experimental design range |
| Concentration Range (C) | 0.2 to 0.6 | wt.% | Experimental design range |
| Shear Rate Range (S) | 1 to 1000 | 1/s | Experimental design range |
| Optimal Viscosity (Predicted) | 0.0113191 | Pa.s | Achieved under optimal RSM conditions |
| Optimal Temperature | 65 | °C | Condition for minimum viscosity |
| Optimal Concentration | 0.4 | wt.% | Condition for minimum viscosity |
| Optimal Shear Rate | 500.5 | 1/s | Condition for minimum viscosity |
| Maximum Measured Viscosity | 0.058812 | Pa.s | Observed at 25°C, 0.2 wt.%, 1 1/s (Run 1) |
| Model R2 Value | 0.9905 | N/A | Predictive accuracy of the quadratic model |
| Model F-Value | 115.99 | N/A | ANOVA result, indicating highly significant model fit |
Key Methodologies
Section titled âKey Methodologiesâ- Nanoparticle Characterization: High-purity spherical diamond and hexagonal boron nitride nanoparticles were characterized using Transmission Electron Microscopy (TEM), Field Emission Scanning Electron Microscopy (FESEM), and X-ray Diffraction (XRD).
- Nanofluid Preparation (Two-Step Method): Nanoparticles were mixed in a 1:1 ratio and dispersed in High Thermal Oil (HTO). Stability was ensured by incorporating the surfactant Span-85 and using an ultrasonic probe-type homogenizer for de-agglomeration.
- Experimental Design: A face-centered Central Composite Design (CCD) was utilized within the Design of Experiments (DoE) framework to systematically vary temperature, concentration, and shear rate across 20 experimental runs.
- Viscosity Measurement: Viscosity (Pa.s) was measured across the defined experimental conditions, providing the dataset for the optimization analysis.
- Modeling and Optimization: Response Surface Methodology (RSM) was applied to the experimental data to construct a second-order polynomial equation modeling the viscosity response.
- Statistical Validation: Analysis of Variance (ANOVA) was performed to assess the modelâs effectiveness, confirm the statistical significance of the input parameters (T and C), and validate the modelâs robustness (R2 = 0.9905).
- Optimal Condition Identification: A desirability function approach was used to pinpoint the specific combination of input variables that minimized viscosity while remaining within the defined parameter space.
Commercial Applications
Section titled âCommercial Applicationsâ- Advanced Cooling Systems: Implementation in demanding thermal management settings, such as high-performance computing, data centers, and specialized industrial machinery, where reduced pumping power translates directly to operational cost savings.
- High-Temperature Heat Transfer: Use in industrial heat exchange applications (e.g., chemical processing, solar thermal energy) that rely on thermal oil, leveraging the nanofluidâs enhanced thermal properties and stability at elevated temperatures (up to 65°C).
- Energy Sector: Thermal management for large-scale energy storage systems and concentrated solar power (CSP) plants, where fluid efficiency and stability are paramount.
- Automotive and Aerospace: Integration into advanced cooling circuits for electric vehicle battery packs or high-output internal combustion engines, benefiting from the shear-thinning behavior at high operational shear rates.
- Tailored Fluid Design: The RSM approach provides a systematic method for engineers to design and predict the rheological properties of nanofluids based on specific operational constraints (T, C, S), facilitating the development of application-specific heat transfer fluids.
View Original Abstract
Abstract. The present study investigates optimizing the viscosity of hybrid nanofluids composed of diamond and boron nitride in thermal oil for high-temperature heat transfer applications. Recognizing that higher viscosity equates to increased pumping costs, the study seeks to minimize this critical parameter to enhance the overall efficiency of thermal systems. Employing Response Surface Methodology (RSM) and a desirability function approach, explored the effect of temperature (25°C to 65°C), concentration (0.2 wt.% to 0.6 wt.%), and shear rate (1 to 1000 1/s) on the viscosity of nanofluids. The optimization process pinpointed conditions that yield the minimum viscosity with the highest desirability score, signifying the most advantageous operating scenario. The results showed an optimal balance at a higher temperature and mid-range concentration, culminating in a nanofluid demonstrating Newtonian behavior at low shear rates and shear-thinning attributes at elevated temperatures and shear rates. These findings explain the potential of tailored nanofluids to substantially cut pumping costs while maintaining excellent heat transfer properties, making them ideal candidates for advanced cooling systems in demanding thermal management settings.