High speed low power optical detection of sub-wavelength scatterer

Roy, S.; Bouwens, Maryse; Wei, Lei; Pereira, Silvania F.; Urbach, H. P.; Walle, Peter van der

doi:10.1063/1.4938183

Cited by 17 publications

(18 citation statements)

References 13 publications

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“…The light intensity on each diode is then integrated separately and their difference is amplified to give the output signal. The calculation of the difference signal has been seen to reduce background noise and improve the signal to noise ratio [6]. A signal becomes non-zero when the scattering from a structure or a particle causes an asymmetry between the two halves of the light beam.…”

Section: Methodsmentioning

confidence: 99%

Multi-beam Coherent Fourier Scatterometry

Soman

Pereira

2022

EPJ Web Conf.

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Recent technological advancements in the past decades have been driven by the miniaturisation of devices using surfaces with nano-scale features. These advancements require fast, large area measurement techniques that can be used in process control to detect surface contaminations or to monitor fabrication quality. Here we present a modified version of the scanning coherent Fourier scatterometer with multiple beams that can be used to scan larger areas without increasing the scan time or decreasing the spatial resolution.

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Section: Methodsmentioning

confidence: 99%

Multi-beam Coherent Fourier Scatterometry

Soman

Pereira

2022

EPJ Web Conf.

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“…The total far field in the presence of the particle will become asymmetric as the particle is scanned through the focused beam. This implies that the left half of the field in the pupil is different from the right half, generating a nonzero photocurrent at the split detector, The recorded signals from the photodetector are the basis for the scattered maps (2D X-Y distributions) [22]. One of the significant advantages of the CFS approach is its high-sensitivity in localizing the centre of the particle in both transverse XY and longitudinal XZ, YZ planes.…”

Section: Methodsmentioning

confidence: 99%

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

Kolenov

Pereira²

2020

Opt. Express

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We present an efficient machine learning framework for detection and classification of nanoparticles on surfaces that are detected in the far-field with coherent Fourier scatterometry (CFS). We study silicon wafers contaminated with spherical polystyrene (PSL) nanoparticles (with diameters down to λ/8). Starting from the raw data, the proposed framework does the pre-processing and particle search. Further, the unsupervised clustering algorithms, such as K-means and DBSCAN, are customized to be used to define the groups of signals that are attributed to a single scatterer. Finally, the particle count versus particle size histogram is generated. The challenging cases of the high density of scatterers, noise and drift in the dataset are treated. We take advantage of the prior information on the size of the scatterers to minimize the false-detections and as a consequence, provide higher discrimination ability and more accurate particle counting. Numerical and real experiments are conducted to demonstrate the performance of the proposed search and cluster-assessment techniques. Our results illustrate that the proposed algorithm can detect surface contaminants correctly and effectively.

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“…When a particle passes through the focused beam, the far field becomes asymmetric and position dependent, generating a differential signal that can be either positive or negative, depending on the relative position of the focused laser beam with respect to the particle. In CFS, the position of the particle can be determined with high accuracy and its size can be inferred by calibration [1].…”

Section: Introductionmentioning

confidence: 99%

Particle detection enhancement by combining coherent Fourier scatterometry with synthetic optical holography

2022

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By combining coherent Fourier scatterometry (CFS) with synthetic optical holography (SOH) we show that the sensitivity of detection of isolated nanoparticles on surfaces can be substantially increased. This improvement is a result of the boost in the signal at the detector due to the added reference beam, and the reduction of background noise caused by the electronics. We demonstrate an improvement of sensitivity of about 4 dB for the case of detection of a 60 nm polystyrene latex (PSL) particle on a silicon wafer at the wavelength of 633 nm (∼ λ/10).

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High speed low power optical detection of sub-wavelength scatterer

Cited by 17 publications

References 13 publications

Multi-beam Coherent Fourier Scatterometry

Multi-beam Coherent Fourier Scatterometry

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

Particle detection enhancement by combining coherent Fourier scatterometry with synthetic optical holography

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