Feature-based filter design for resolution enhancement of known features in microscopy

Loh, Eng Liang; Chen, Rui; Agarwal, Krishna; Chen, Xudong

doi:10.1364/josaa.31.002610

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…A proof of concept is shown in Ref. [29], where it is proposed to design filters for ASIL microscopy that are specifically suitable for imaging features of a known geometry and material. It is seen that a simple two-layer binary phase filter can be used in the focusing path to image three-bar features of half-pitch λ=12.5, about 85 nm for λ ¼ 1064 nm.…”

Section: E Future Of This Technologymentioning

confidence: 99%

Crossing the Resolution Limit in Near-Infrared Imaging of Silicon Chips: Targeting 10-nm Node Technology

Agarwal

Chen

Koh³

et al. 2015

Phys. Rev. X

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The best reported resolution in optical failure analysis of silicon chips is 120-nm half pitch demonstrated by Semicaps Private Limited, whereas the current and future industry requirement for 10-nm node technology is 100-nm half pitch. We show the first experimental evidence for resolution of features with 100-nm half pitch buried in silicon (λ=10.6), thus fulfilling the industry requirement. These results are obtained using near-infrared reflection-mode imaging using a solid immersion lens. The key novel feature of our approach is the choice of an appropriately sized collection pinhole. Although it is usually understood that, in general, resolution is improved by using the smallest pinhole consistent with an adequate signal level, it is found that in practice for silicon chips there is an optimum pinhole size, determined by the generation of induced currents in the sample. In failure analysis of silicon chips, nondestructive imaging is important to avoid disturbing the functionality of integrated circuits. High-resolution imaging techniques like SEM or TEM require the transistors to be exposed destructively. Optical microscopy techniques may be used, but silicon is opaque in the visible spectrum, mandating the use of near-infrared light and thus poor resolution in conventional optical microscopy. We expect our result to change the way semiconductor failure analysis is performed.

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Section: E Future Of This Technologymentioning

confidence: 99%

Crossing the Resolution Limit in Near-Infrared Imaging of Silicon Chips: Targeting 10-nm Node Technology

Agarwal

Chen

Koh³

et al. 2015

Phys. Rev. X

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Versatile focal field design using cascaded artificial neural network

Luan

Jun

2022

AIP Advances

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Both forward and inverse design methods have been developed for focal field engineering, which has applications in many areas including super-resolution imaging and optical lithography, high-density optical storage, and particle manipulation. However, a certain method is normally targeted at a unique focal field distribution. Here, we report on a versatile focal field design method based on a cascaded artificial neural network (CANN) for the inverse design of focal field distributions in a high numerical aperture focusing system. The CANN consists of a forward and an inverse artificial neural network. Once trained properly, the CANN can predict modulation phase patterns for multiple focal field distributions. We demonstrate the effectiveness of the CANN by the design of focal field distributions along the optical axis including a uniform optical needle and an anti-point spread function with lengths up to 14 wavelengths and multiple focal spots with controllable intensities as well as those in the focal plane including flat-top and sub-diffraction focal spots.

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Focus shaping of high numerical aperture lens using physics-assisted artificial neural networks

et al. 2021

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We present a physics-assisted artificial neural network (PhyANN) scheme to efficiently achieve focus shaping of high numerical aperture lens using a diffractive optical element (DOE) divided into a series of annular regions with fixed widths. Unlike the conventional ANN, the PhyANN does not require the training using labeled data, and instead output the transmission coefficients of each annular region of the DOE by fitting weights of networks to minimize the delicately designed loss function in term of focus profiles. Several focus shapes including sub-diffraction spot, flattop spot, optical needle, and multi-focus region are successfully obtained. For instance, we achieve an optical needle with 10λ depth of focus, 0.41λ lateral resolution beyond diffraction limit and high flatness of almost the same intensity distribution. Compared to typical particle swarm optimization algorithm, the PhyANN has an advantage in DOE design that generates three-dimensional focus profile. Further, the hyperparameters of the proposed PhyANN scheme are also discussed. It is expected that the obtained results benefit various applications including super-resolution imaging, optical trapping, optical lithography and so on.

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Feature-based filter design for resolution enhancement of known features in microscopy

Cited by 3 publications

References 27 publications

Crossing the Resolution Limit in Near-Infrared Imaging of Silicon Chips: Targeting 10-nm Node Technology

Crossing the Resolution Limit in Near-Infrared Imaging of Silicon Chips: Targeting 10-nm Node Technology

Versatile focal field design using cascaded artificial neural network

Focus shaping of high numerical aperture lens using physics-assisted artificial neural networks

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