Determination of the layer thickness and roughness of polymer films by X-ray reflectivity

Polymer thin films have demonstrated numerous potential applications in various fields. However, commonly used deposition techniques, such as spin coating on solid state substrates, often have difficulty precisely controlling the layer thickness.

Moreover, surface and interface roughness are crucial quality factors for the deposited films. It is thus essential to measure both the film thickness and the surface/interface roughness accurately in order to optimize the deposition procedure.

X-ray reflectivity (XRR) is one of the most reliable techniques to determine film thickness and surface/interface roughness. It has the advantages of being nondestructive and requires no special sample preparation when compared to other analysis methods.

The key to the high accuracy of the layer thickness and roughness measurements with XRR is the sample alignment. If the alignment is done incorrectly or imprecisely, the measured results can be inaccurate. Rigaku's SmartLab multipurpose diffractometer now ensures this kind of measurement can be done correctly and precisely even if an operator has no prior experience in XRR measurements. Sample alignment is completely automated with Rigaku's proprietary Guidance data acquisition software. XRR profile taken from a polymer film deposited on a Si wafer

In the figure on the left, an XRR profile taken from a polymer film deposited on a Si wafer is displayed, along with the fitting results. The agreement between the measured and calculated curves is excellent. The film thickness, surface and interface roughness are determined to be 1.282 nm, 0.402 nm, and 0.255 nm, respectively.
 


The SmartLab is the most novel high-resolution diffractometer available today. Perhaps its most novel feature is the SmartLab Guidance software, which provides the user with an intelligent interface that guides you through the intricacies of each experiment. It is like having an expert standing by your side. Read more...

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