Atomistic Investigation of Viscoelastic Nanofluids as Heat Transfer Liquids for Immersive-Cooling Applications
Ravikumar, B. ORCID: 0000-0001-7095-2195, Karathanassis, I. K., Smith, T. & Gavaises, M. (2024). Atomistic Investigation of Viscoelastic Nanofluids as Heat Transfer Liquids for Immersive-Cooling Applications. Industrial & Engineering Chemistry Research, 63(48), pp. 21023-21037. doi: 10.1021/acs.iecr.4c01832
Abstract
A comparative assessment of the thermal properties and heat transfer coefficients achieved by viscoelastic nanofluids suitable for immersion cooling is presented, with the candidate samples exhibiting distinct differences based on the nanoparticle chemistry and shape. Molecular dynamics simulations of different nanoparticles such as copper nanosphere, two-dimensional pristine graphene, and single-walled carbon nanotube (CNT) dispersed in PAO-2 of concentrations of approximately equal to 2.6% by weight are performed in the present investigation. While carbon-based nanoparticles increase the specific heat capacity of the nanofluids, copper-based nanofluids show a decrease in the corresponding values. Moreover, the heat conduction in copper-based nanofluids is dependent on the higher degree of phonon density of states (DOS) matching between the copper and solvent atoms, whereas the high intrinsic thermal conductivity of graphene and CNT compensates for the lower degree of DOS matching. The addition of an OCP polymer chain to impart viscoelasticity in the nanofluids exhibits a heat transfer coefficient enhancement of more than 80% during Couette flow as a result of chain expansion, indicating their suitability for immersive-cooling applications.
Publication Type: | Article |
---|---|
Additional Information: | This publication is licensed under CC-BY-NC-ND 4.0. |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Departments: | School of Science & Technology School of Science & Technology > Engineering |
SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (3MB) | Preview
Export
Downloads
Downloads per month over past year