Effective thermal conductivity of nanofluids containing spherical nanoparticles

By Yajie Ren, Huaqing Xie, An Cai. 2005

145 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computational Mechanics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/31bbbaa9b2628afb3ad00e8044343ef51de4657a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Stephen U. S. Choi
2. S. Jang
3. Ji-Hwan Lee
4. Hrishikesh E. Patel
5. Sarit K. Das
6. J. Meyer
7. C. Choi
8. Ali J. Chamkha

In Computational Mechanics

1. J. Meyer
2. Sarit K. Das
3. S. Jang
4. Jacob Eapen
5. Ji-Hwan Lee
6. Stephen U. S. Choi
7. C. Choi
8. Seunghyun Lee

In Mechanical Engineering

1. Stephen U. S. Choi
2. Hrishikesh E. Patel
3. Ji-Hwan Lee
4. Sarit K. Das
5. S. Jang
6. J. Meyer
7. C. Choi
8. Jacob Eapen

Citations in the corpus

• A Review of Thermal Conductivity Models for Nanofluids (2015, methodology): “[31] offered a model that is based on kinetictheory-based microconvection, liquid layering, and conduction through both particles and liquid.”
• Heat Transfer in Nanofluids—A Review (2006, background): “[67], who considered kinetic theory-based micro-convection and liquid layering in addition to liquid and particle conduction.”
• A Review of Thermal Conductivity Data, Mechanisms and Models for Nanofluids (2010, background): “[91] considered kinetic-theory-based microconvection and liquid layering in addition to liquid and particle conduction.”
• The Classical Nature of Thermal Conduction in Nanofluids (2008, background): “These include Brownian motion of the nanoparticles [36, 37], fluid convection at the microscales [38-44], liquid layering at the particle-fluid interface [45-50], nanoparticle shape [51, 52], cluster agglomeration [53, 54], or a combination of aforesaid mechanisms [55-59].”