JunPus DXSquare Elite

Product Images

General Information

Manufacturer

JunPus

Designation

DXSquare Elite

Manufacturer Specifications

Bulk Thermal Conductivity λ

18.3

Density

2.58 g/cm³

Working Temperature

-40 to 180 °C

Accessories

Spatula

Container

Bag

Container

Bag

Notes and Recommendations

CPU

GPU

Difficulty

Conclusion

Good paste with estimated normal durabiliy on GPUs in long term use. Not bad at all and sticky enough for a good appliction

Measurements

Thermal Conductivity (W/m·K)

4.7

Min BLT

12

Interface Resistance

3.2

Heat Conducting Particles and Matrix

Al2O3, ZnO, Silicone

Particle Size

<=12 µm

Material Testing and TIMA Protocol (on request)

Microscopy and Particles

Measurement Process

Thermal Resistances R_th

Let's start with the most important aspect, the thermal resistance R_th. The key feature of R_th is that it correlates linearly with the layer thickness, while thermal conductivity follows a different curve and is far from linear. But experienced readers already know this. We are mainly interested in layer thicknesses of 200 µm or less for CPUs, and usually 100 µm or much thinner for GPUs, depending on bending.

I have now prepared a bar chart comparing the relevant layer thicknesses from 50 to 400 µm for R_th.

Minimum Possible Layer Thickness

That's exactly why I wanted to see how far we could go with a bit of pressure and how much a paste can still be compressed. Here, I use the usual 9N pro cm², which is more than sufficient and higher than what, for instance, a GPU cooler would achieve.

Effective Thermal Conductivity and Cooling Simulation

As is always the case in my other reviews: once you have R_th, λ_eff (effective thermal conductivity) is not really needed. We can also see how the values change across BLT (Bond Line Thickness), though we can't expect a linear curve anymore due to the included area and BLT.

I have now prepared a bar chart comparing the relevant layer thicknesses from 50 to 400 µm for λ_eff.