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Thermal conductivity of nanocomposite matrix + particles

Posted Oct 16, 2023, 12:05 p.m. EDT Heat Transfer Version 6.1 3 Replies

Alexey Gunya
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Dear colleagues

I need to measure thermal conductivity of nanocomposite polyurethan(matrix)+aluminium(particles). I must be, naturally, something between 0.01 and 100 W/m K. Does somebody know how simple and algorithm for evaluation this parameter? Thanks!

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3 Replies Last Post Oct 23, 2023, 9:39 a.m. EDT
Jeff Hiller COMSOL Employee

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Posted: 6 months ago Oct 17, 2023, 9:25 a.m. EDT
Updated: 6 months ago Oct 17, 2023, 9:24 a.m. EDT

Hello Alexey,

It is certainly possible to evaluate the effective properties of an inhomogeneous material using simulation. See this tutorial for an example. If your composite is periodic, you may be able to get away with simulating a single cell, as illustrated in this second example. If on the other hand you need to generate a large number of nanoparticles randomly distributed in the matrix, see this blog post on how to do it through a script.

Best,

Jeff

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Jeff Hiller
Hello Alexey, It is certainly possible to evaluate the effective properties of an inhomogeneous material using simulation. See [this tutorial](https://www.comsol.com/model/effective-diffusivity-in-porous-materials-978) for an example. If your composite is periodic, you may be able to get away with simulating a single cell, as illustrated in [this second example](https://www.comsol.com/model/equivalent-properties-of-periodic-microstructures-23621). If on the other hand you need to generate a large number of nanoparticles randomly distributed in the matrix, see [this blog post](https://www.comsol.com/blogs/how-to-create-a-randomized-geometry-using-model-methods/) on how to do it through a script. Best, Jeff
Alexey Gunya
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Posted: 6 months ago Oct 22, 2023, 10:43 a.m. EDT

Hello Alexey,

It is certainly possible to evaluate the effective properties of an inhomogeneous material using simulation. See this tutorial for an example. If your composite is periodic, you may be able to get away with simulating a single cell, as illustrated in this second example. If on the other hand you need to generate a large number of nanoparticles randomly distributed in the matrix, see this blog post on how to do it through a script.

Best,

Jeff

I'm grateful for response. I successfully created the geometry of nanocomposite. The only one problem now is how to measure thermal conductivity? Is there some standart algorithm in COMSOL?

>Hello Alexey, > >It is certainly possible to evaluate the effective properties of an inhomogeneous material using simulation. See [this tutorial](https://www.comsol.com/model/effective-diffusivity-in-porous-materials-978) for an example. If your composite is periodic, you may be able to get away with simulating a single cell, as illustrated in [this second example](https://www.comsol.com/model/equivalent-properties-of-periodic-microstructures-23621). If on the other hand you need to generate a large number of nanoparticles randomly distributed in the matrix, see [this blog post](https://www.comsol.com/blogs/how-to-create-a-randomized-geometry-using-model-methods/) on how to do it through a script. > >Best, > >Jeff I'm grateful for response. I successfully created the geometry of nanocomposite. The only one problem now is how to measure thermal conductivity? Is there some standart algorithm in COMSOL?
Jeff Hiller COMSOL Employee

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Posted: 6 months ago Oct 23, 2023, 9:39 a.m. EDT
Updated: 6 months ago Oct 23, 2023, 9:45 a.m. EDT

You derive the equivalent conductivity of a sample from the formula q=-k*grad(T) .

You run a simulation with an imposed heat flux through the sample and obtain from that simulation the temperature drop; then using the formula above (and the length of the sample, as you can approximate ) you get k.

Jeff

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Jeff Hiller
You derive the equivalent conductivity of a sample from the formula q=-k*grad(T) . You run a simulation with an imposed heat flux through the sample and obtain from that simulation the temperature drop; then using the formula above (and the length of the sample, as you can approximate grad(T) \approx \Delta T / L ) you get k. Jeff

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