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arXiv · 2005.04905

Optical Metrology of Sub-Wavelength Objects Enabled by Artificial Intelligence

Carolina Rendón-Barraza·Eng Aik Chan·Guanghui Yuan·Giorgio Adamo·Tanchao Pu·Nikolay I. Zheludev
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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.

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Carolina Rendón-Barraza, Eng Aik Chan, Guanghui Yuan, Giorgio Adamo, Tanchao Pu, Nikolay I. Zheludev. 2020-05-11. Optical Metrology of Sub-Wavelength Objects Enabled by Artificial Intelligence. https://arxiv.org/abs/2005.04905

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