Scatterometry

Calaon, Matteo; Madsen, Morten Hannibal; Leach, Richard

doi:10.1007/978-3-642-35950-7_16855-1

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…The were saved in hdf5 format, and the files contain the wavelengths, intensities for the reference, the background, and the DOEs, and the diffraction efficiencies calculated for each grating. Figure 4 shows examples of the intensity spectra required to calculate the diffraction efficiency calculated using equation (2).…”

Section: Scatterometer Measurementsmentioning

confidence: 99%

“…Scatterometers measure the properties of light that has interacted with a diffractive structure. The most common categories of scatterometers are angular and spectral scatterometers [2].…”

Section: Introductionmentioning

confidence: 99%

“…Spectral scatterometry is a fast method but does not measure the parameters of the sample directly. Usually, the measured spectrum is compared to a theoretical signature with known grating parameters [2]. This is often done using library search or non-linear regression.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Artificial neural network assisted spectral scatterometry for grating quality control

Mattila,

Nysten,

Heikkinen

et al. 2024

Meas. Sci. Technol.

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Spectral scatterometry is a technique that allows rapid measurements of diffraction efficiencies of diffractive optical elements (DOEs). The analysis of such diffraction efficiencies has traditionally been laborious and time consuming. However, machine learning can be employed to aid in the analysis of measured diffraction efficiencies. In this paper we describe a novel system for providing measurements of multiple measurands rapidly and concurrently using a spectral scatterometer and an Artificial Neural Network (ANN) which is trained utilizing transfer learning. The ANN provides values for the pitch, height, and line widths of the DOEs. In addition, an uncertainty evaluation was performed. In the majority of the studied cases, the discrepancies between the values obtained using a scanning electron microscope (SEM) and artificial neural network assisted spectral scatterometer (ANNASS) for the grating parameters were below 5 nm. Furthermore, independent reference samples were used to perform a metrological validation. An expanded uncertainty ($k = 2$) of 5.3 nm was obtained from the uncertainty evaluation for the measurand height. The height value measurements performed employing ANNASS and SEM are demonstrated to be in agreement within this uncertainty.

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Section: Scatterometer Measurementsmentioning

confidence: 99%

“…Scatterometers measure the properties of light that has interacted with a diffractive structure. The most common categories of scatterometers are angular and spectral scatterometers [2].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial neural network assisted spectral scatterometry for grating quality control

Mattila,

Nysten,

Heikkinen

et al. 2024

Meas. Sci. Technol.

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“…Several optical microscopy techniques have been developed to improve the signal-to-noise ratio (SNR) and spatial resolution for the metrology and inspection of semiconductor nanopatterns. For example, scatterometry ,, has been widely used for measuring the dimensions of the fine patterns on a semiconductor wafer owing to its high measurement speed. Although scatterometry has ability to capture subwavelength periodic structures, it has been limited to measure isolated or nonperiodic structures. , Various sensing methods such as optical pseudoelectrodynamics microscopy, optical interferometric microscopy have been developed to obtain high SNR in the inspection of semiconductors.…”

mentioning

confidence: 99%

Super-Resolution Fluorescence Imaging for Semiconductor Nanoscale Metrology and Inspection

et al. 2022

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The increase in the number and complexity of process levels in semiconductor production has driven the need for the development of new measurement methods that can evaluate semiconductor devices at the critical dimensions of fine patterns and simultaneously inspect nanoscale contaminants or defects. However, conventional optical inspection methods often fail to resolve device patterns or defects at the level of tens of nanometers required for device development owing to their diffraction-limited resolutions. In this study, we used the stochastic optical reconstruction microscopy (STORM) technique to image semiconductor nanostructures with feature sizes as small as 30 nm and detect individual 20 nm-diameter contaminants. STORM imaging of semiconductor nanopatterns is based on the development of a selective labeling method of fluorophores for a negative silicon oxide surface using the charge interaction of positive polyethylenimine molecules. This study demonstrates the potential of STORM for nanoscale metrology and in-line defect inspection of semiconductor integrated circuits.

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In-situ calibration of the objective lens of an angle-resolved scatterometer for nanostructure metrology

et al. 2023

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Due to the advantages of being non-contact, non-destructive, highly efficient, and low in cost, scatterometry has emerged as a powerful technique for nanostructure metrology. In this paper, we propose an angle-resolved scatterometer composed of a scattered light acquisition channel and a spatial imaging channel, which is capable of detecting multi-order diffracted light in a single measurement. Since the high numerical aperture objective lens is usually employed in an angle-resolved scatterometer, the polarization effect of the objective lens introduced by the non-normal incidence and installation stress should be considered. An in-situ calibration method for the objective lens’s polarization effects is proposed, in which a known analyzer is appended to the output light path to enable the extraction of the ellipsometric parameters of isotropic samples. Then the polarization effect of the objective lens can be determined in-situ by fitting the measured ellipsometric parameters to the calculated ones. With the objective lens polarization effect being considered, significant improvements in the accuracy and repeatability precision can be achieved in the metrology of the film thickness and grating topography parameters.

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Scatterometry

Cited by 3 publications

References 12 publications

Artificial neural network assisted spectral scatterometry for grating quality control

Artificial neural network assisted spectral scatterometry for grating quality control

Super-Resolution Fluorescence Imaging for Semiconductor Nanoscale Metrology and Inspection

In-situ calibration of the objective lens of an angle-resolved scatterometer for nanostructure metrology

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