Study on Effective Thermal Conduction of the Nanoparticle Suspension

1. December 31, 2003 Study on Effective Thermal Conduction of the Nanoparticle Suspension Calvin Hong Li Department of Mechanical, Aerospace & Nuclear Engineering Rensselaer Polytechnic Institute Troy, NY 12180

2. Presentation Outline • Introduction • Background • Effective Thermal Conduction • Adsorption Layer • Brownian Motion • Conclusions

3. Background Nano tech is a very promising field and the current focus of the world. Nanoparticle suspension is a kind of new heat transfer material which has very novel thermal properties. The study on it has covered chemical physics, interfacial phenomena, heat and mass transfer and some even grand fundamental fields. This new material will accompany the advancing of future engineering and science development.

4. Research on Effective Thermal Conductivity • Theoretic Study Hamilton and Cross（1962） Maxwell (1881) • Experimental Study Transient Wire Method (Nagasaka & Nagashima) Thermal Probe Method Other methods

5. Working Theory • Thermal Probe Method • Transient Wire Method Calculating the effective thermal conductivity by measuring the change of voltage of the probe and wire

6. Experimental Setup

7. Current Study • Preparation of Nanoparticle Suspension • Study of Effective Thermal Conductivity • Study on Other thermal Properties and Applications

8. Objective • Measure the effective thermal conductivity • Reveal the interaction between particle and fluid • Study the effect of Brownian motion on effective thermal conductivity

9. Preparation of Nanoparticle Suspension • Methods：One-step Method Two-step Method • Stability：（1）PH Value； （2）Chemical Method； （3）Physical Method。

10. Material: SiO2 nanoparticle, Mean diameter 25nm ，Purity（>99.9%），non crystal. Pure water and ethanol Preparation of the suspension: dispersed with microwave.

11. Setups Error Evaluation Thermal Probe Transient wire

12. Experimental Results • Thermal Probe Method The higher of the suspension’s temperature, the higher the effective thermal conductivity The higher the ratio of nanoparticle in the suspension, the higher the effective thermal conductivity

13. Experimental Results • Transient Wire Method Wt ratio of 0.1%，effective thermal conductivity is 9.452% higher than pure water； Wt ratio of 0.2%， effective thermal conductivity is 10.6% higher； Wt ratio of 0.5%，17.4% higher。

14. Results Analysis With the high surface/volume ratio of nanoparticles, basefluid is adsorbed on the surface of nanoparticles. This lay of adsorbed basefluid can help nanoparticles from agglomerating. Meanwhile, the particles do the Brownian motion in the basefluid, which will help to form a micro convection around them. the adsorption and Brownian motion help the nanoparticle suspension to have very novel effective thermal conduction.

15. OH Si E基团 O Si O O Si Si O O OH OH D基团 H Si Si O OH O O Si Si 断裂线（面） Si Si O Action between surface atoms and fluid atoms or

16. Agglomeration of Nanoparticles SiO2nanoparticles Hitachi 200CX TEM 1:120,000

17. Two particle agglomerati-on Four particle agglomerati-on Multiparticl-e agglomerati-on huge agglomerati-on Single particle Distribution of particles and the agglomeration

18. Distribution of particles and the agglomeration Agglomerations

19. layer fluid particle The calculation of the thickness of adsorption layer

20. Particle, adsorbed layer and free basefluid : Two dimension surface work when ，there is here So then

21. Study on the interaction between particles and basefluid There are two ways how the heat is conducted in fluid. One is that molecules move in a area which is like a cell, the other is that some molecules can get high energy and move out the original cell to other adjacent cells. So it seems that the Brownian motion of nanoparticles will change this process greatly by breaking the cell or helping molecules move to other cell with rather low energy. And therefore the suspension shows greater effective thermal conductivity。 • Analysis force acted on nanoparticles • Simulation of the Brownian motion effect of nanoparticles having on basefluid

22. Force Analysis • （1）Thermal Swimming Force： • （2）Short range agglomerating force： • （3）Electrostatic Force： • （4）Surface tension：

23. The displacement of particles with Brownian motion per second（um）

24. 液体分子 Q 颗粒 液体温度梯度 T The Knudsen number with the particle’s diameter: is fluid molecule’s mean free moving distance, ， means the movement is in the slipping or temp. jumping area. With heat flux and the T gradient，

25. Particle Layer of fluid molecules Micro convection zone CFD Simulation

26. Flux Velocity of Brownian motion Single particle moving model v A B C Distribution of particles in suspension

27. One, two and ten particles cases Mesh for ten particles case Mesh for single particle case

28. Temp. field around one particle Pressure field around one particle Moving situation Velocity field around one particle

29. Comparing and contrasting of one and two particles cases Temperature field comparing and contrasting horizon plate Temperature field comparing and contrasting upright plate

30. Ten particles case Velocity field Temperature field

31. Conclusion • Observation on the particles and their agglomeration • Getting the effective thermal conductivity data through two kind of methods. • Calculating the thickness of adsorbing layer • Simulating the Brownian motion and its effect.

32. Other Study on Nanoparticle Suspension • Study on the viscosity • Study on the capillary performance and chemical behavior • Study on the application as the refrigerant in MEMS

33. MD Simulation • In case that there is not a good way to observe the adsorbed layer basefluid molecules，the MD method should be used to study the adsorption process and its effect on the energy. Through the MD simulation, hoping to get the information of kinetic energy, potential energy and other changes in the process.

34. Effects between fluid molecules • Since the fluid molecules have polarity, based on the L-J model，the model for the effect between fluid molecules can be Stockmayer potential model：

35. Brownian Motion Get experimental data of difference viscosity basefluid, Find out the relationship between viscosity and effective thermal conductivity. Hence reveal deeper the contribution of Brownian motion.

36. Thank you!And Happy New Year!