Thermal gradient <10°C for a FAST/SPS sample: Myth or Reality?

Why aim for a small thermal gradient?

It is now well-known that Spark Plasma Sintering (SPS) can produce high-performance samples with higher material properties compared to conventional processes. However, as samples get larger it is much harder to manage the thermal gradients inside the part. This could result in several drawbacks that can discourage the #SPS user:

• Melting of the material. Especially with metals, where the sintering temperature is close to the melting point.
• Microstructure inhomogeneity. The temperature strongly affects the densification and the grain size, and thus, the physical properties of the final part.
• Cosmetic purposes. The use of pigments in some material is very sensitive to the temperature and can result in a non-uniform color of the final part. 

How to reduce the thermal gradient?

Several tools are now available to the SPS user to limit thermal gradient inside its parts, even for large samples. Two examples illustrating this are the use of carbon fiber-reinforced plates and mold design optimization.

• ·Use of carbon fiber-reinforced carbon (CFC) plates:

Carbon fiber-reinforced plates are increasingly used in the SPS community thanks to their ability to limit the thermal gradient inside the sintered parts as well as reducing the global SPS power. In the case of a 100mm zirconia sample, the use of CFC plates between the punches and spacers the mold can reduce the thermal gradient by about 75%. However, the resulting gradient of 51°C can still be too high for certain applications.

• Mold design optimization:

On top of using CFC plates, the user can also optimize the design of their mold since it has a significant impact on the resulting part. For the same 100mm zirconia sample, using a higher and slightly thinner mold will reduce the thermal gradient to only 12°C. With this level of temperature difference inside the zirconia, no density or microstructure discrepancy is expected. 

This makes SPS a valuable and reliable process to produce high-performance materials.

Antoine Van der Laan, Ph.D in Modeling of complex shapes by SPS

Head of Digital Simulation