Optical Metrology for Particle Detection and Nanostructures Characterization

Dear Colleagues,

Over the years, optical techniques for nanostructure characterization have been widely used in the industry, particularly that of semiconductors, in order to monitor the quality of printed nanostructures. The advantage of optical techniques, as compared to electron-beam imaging or atomic force microscopy, is that they are fast, noninvasive, and require relatively simple set-ups and can be implemented in-line so that inspection can be performed during the entire fabrication process. In addition to nanostructure characterization, optical techniques have also been applied for nanoparticle contamination detection and for sample alignment. Scatterometry and dark field imaging are two examples of techniques that have been successfully implemented in recent decades, not only in the semiconductor industry for wafer inspection and contamination control, but also in other areas that use other substrates, such as compound semiconductors, plastic- or glass-based substrates for applications in plastic electronics, power electronics devices, organic solar cells and OLEDs. Optical techniques have also been applied for the characterization of aerosols to the level of < 1 micron nano-particles and for the label-free characterization of biological particles. However, with the increasing need for the inspection of nanostructures and their contamination, since they are much smaller than the light wavelengths, the present challenge is to push the limits of these techniques to meet these new requirements. This includes the use of all properties of light, namely wavelength, amplitude, phase, polarization, coherence, angular momentum, illumination and detection systems as well as substrate engineering, which are tailored to particular applications that can be applied for inspection, alignment or contamination detection at the nanometer level. These techniques also require the precise electromagnetic modelling of the interaction between light and nanostructures, and in these past years, a lot of progress has been made to improve the understanding of the physical phenomena that are involved in, for example, the light scattering process after its interaction with a nano-object. Lately, machine learning and deep learning techniques have been considered and implemented for accurate and fast contamination detection and nanostructure characterization.

In this Special Issue, we report reviews of recently obtained results, and new ideas that have been researched worldwide in this area.

Kind regards,

Assoc. Prof. Dr. Silvania F. Pereira
Guest Editor

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