Optical Metrology of Sub-Wavelength Objects Enabled by Artificial Intelligence
Abstract
Microscopes and various forms of interferometers have been used for decades in optical metrology of objects that are typically larger than the wavelength of light {\lambda}. However, metrology of subwavelength objects was deemed impossible due to the diffraction limit. We report that measurement of the physical size of sub-wavelength objects with accuracy exceeding {\lambda}/800 by analyzing the diffraction pattern of coherent light scattered by the objects with deep learning enabled analysis. With a 633nm laser, we show that the width of sub-wavelength slits in opaque screen can be measured with accuracy of 0.77nm, challenging the accuracy of electron beam and ion beam lithographies. The technique is suitable for high-rate non-contact measurements of nanometric sizes in smart manufacturing applications with integrated metrology and processing tools.
Cite
@article{arxiv.2005.04905,
title = {Optical Metrology of Sub-Wavelength Objects Enabled by Artificial Intelligence},
author = {Carolina Rendón-Barraza and Eng Aik Chan and Guanghui Yuan and Giorgio Adamo and Tanchao Pu and Nikolay I. Zheludev},
journal= {arXiv preprint arXiv:2005.04905},
year = {2020}
}