Deeply sub-wavelength non-contact optical metrology of sub-wavelength objects
| Autor: | Nikolay I. Zheludev, Carolina Rendon-Barraza, Tanchao Pu, Giorgio Adamo, Guanghui Yuan, Eng Aik Chan |
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| Přispěvatelé: | School of Physical and Mathematical Sciences, Centre for Disruptive Photonic Technologies (CDPT), The Photonics Institute |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Diffraction
Microscope Materials science genetic structures Opacity Computer Networks and Communications Ion beam lithography law.invention Optics Deep Learning Optical microscope law Physics [Science] Astronomical interferometer Applied optics. Photonics Physics business.industry Laser Atomic and Molecular Physics and Optics Ptychography Metrology Numerical aperture TA1501-1820 Lens (optics) Wavelength Optical Metrology business |
| Zdroj: | APL Photonics, Vol 6, Iss 6, Pp 066107-066107-5 (2021) |
| ISSN: | 2378-0967 |
| Popis: | 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 λ. Metrology of sub-wavelength objects, however, was deemed impossible due to the diffraction limit. We report the measurement of the physical size of sub-wavelength objects with deeply sub-wavelength accuracy by analyzing the diffraction pattern of coherent light scattered by the objects with deep learning enabled analysis. With a 633 nm laser, we show that the width of sub-wavelength slits in an opaque screen can be measured with an accuracy of ∼λ/130 for a single-shot measurement or ∼λ/260 (i.e., 2.4 nm) when combining measurements of diffraction patterns at different distances from the object, thus challenging the accuracy of scanning electron microscopy and ion beam lithography. In numerical experiments, we show that the technique could reach an accuracy beyond λ/1000. It is suitable for high-rate non-contact measurements of nanometric sizes of randomly positioned objects in smart manufacturing applications with integrated metrology and processing tools. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) Published version The authors acknowledge the Singapore Ministry of Education (Grant No. MOE2016-T3-1-006); the Agency for Science, Technology and Research (A∗ STAR), Singapore (Grant No. SERC A1685b0005); and the Engineering and Physical Sciences Research Council UK (Grants No. EP/N00762X/1 and No. EP/M0091221), and the European Research Council (Advanced grant FLEET786851). T.P. acknowledges support from the China Scholarship Council (CSC No. 201804910540). |
| Databáze: | OpenAIRE |
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