Improvement of spectral resolution in spectroscopic imaging reflectometer using rotating-type filter and tunable aperture

Kim, Min-Gab

doi:10.1088/1361-6501/aad1e3

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Their conclusion was that the experiment was mainly driven by the growth of a ZnO thin film below the NWs and not to the NWs. Spectral domain reflectometry is a well-established technique in thin film characterization to extract its thickness and refractive index. − It has also been used to characterize light absorption enhancement due to the use of nanowires compared to thin films. − However, it has not been used for the characterization of nanowire length and nanowire fractional volume densitythat is, the nanowire/air filling ratio as considered in this work.…”

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confidence: 99%

Nanowire Length, Density, and Crystalline Quality Retrieved from a Single Optical Spectrum

et al. 2019

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We propose spectral domain attenuated reflectometry (SDAR) for fast characterization of nanomaterial growth. The method is demonstrated here for zinc oxide (ZnO) nanowires (NWs) which are grown vertically in random forest fashion showing that it is not limited to well-ordered NWs. We show how SDAR can provide, on the basis of a single measured spectrum, simultaneous information on nanowire length, nanowire density (through nanowire/air filling ratio), and crystalline quality (through band gap). The robustness of the proposed method is assessed first through comparison with information obtained from SEM and XRD taken as reference. In SDAR, the process for fast extraction of NW thickness and filling ratio values makes use of the interference pattern contrast and the spectral periodicity in the reflection response which involve a best fit of the measured spectra with simple theoretical modeling based on the effective medium approach, achieved with a mean square error down to 0.1%. The results also suggest the existence of either 2 or 3 layers of different effective refractive index, hence providing insight on possible growth mechanisms.

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confidence: 99%

Nanowire Length, Density, and Crystalline Quality Retrieved from a Single Optical Spectrum

et al. 2019

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“…This leads to an increased difference from the thin film thickness values obtained using an AFM. In addition, spectral resolution is known to affect the accuracy and precision of measurement [19]. Therefore, if improved spectral resolution is secured, better measurement performance can be expected.…”

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confidence: 99%

Spectroscopic imaging ellipsometry for two-dimensional thin film thickness measurement using a digital light processing projector

Kim

2022

Meas. Sci. Technol.

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An improved version of spectroscopic imaging ellipsometry is described for accurate reconstruction of two-dimensional thin film thickness. A digital light processing projector enables to illuminate selective area of the back focal plane of the objective lens so that the angle of incidence and the polarization state of the light source vary depending on the area of the back focal plane to be illuminated. By combining multiple images of the object plane obtained at different polarization state, every pixel in the field of view has their own ellipsometric parameters, therefore, the reconstruction of two-dimensional thin film thickness is possible. Because the proposed ellipsometry system has a co-axial optical structure in which the objective lens is arranged in the normal direction to the measurement target, the spatial resolution is improved due to the application of high magnitude objective lens. In addition, the spectroscopic analysis can be conducted using a number of band-pass filters which have each central wavelength. The effect of the proposed method on the thin film thickness measurement was evaluated by comparing the experimental result with a topographic profile obtained using a commercial AFM.

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“…In the literature, optical characterization techniques usually depend on interferometric, spectroscopic and ellipsometric techniques [16][17][18][19][20][21][22]. However, they are generally complicated and time-consuming procedures for curved surfaces as well as require a sophisticated laboratory environment.…”

Section: Introductionmentioning

confidence: 99%

Enhancing thickness determination of nanoscale dielectric films in phase diffraction-based optical characterization systems with radial basis function neural networks

Ataç

Karatay

Dinleyici

2023

Meas. Sci. Technol.

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Accurate determination of the optical properties of ultra-thin dielectric films is an essential and challenging task in optical fiber sensor systems. However, nanoscale thickness identification of these films may be laborious due to insufficient and protracted classical curve matching algorithms. Therefore, this experimental study presents an application of a radial basis function (RBF) neural network in phase diffraction-based optical characterization systems to determine the thickness of nanoscale polymer films. The non-stationary measurement data with environmental and detector noise were subjected to a detailed analysis. The outcomes of this investigation are benchmarked against the linear discriminant analysis (LDA) method and further verified by means of scanning electron microscopy (SEM). The results show that the neural network has reached a remarkable accuracy of 98% and 82.5%, respectively, in tests with simulation and experimental data. In this way, rapid and precise thickness estimation may be realized within the tolerance range of 25 nm, offering a significant improvement over conventional measurement techniques.

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Improvement of spectral resolution in spectroscopic imaging reflectometer using rotating-type filter and tunable aperture

Cited by 5 publications

References 14 publications

Nanowire Length, Density, and Crystalline Quality Retrieved from a Single Optical Spectrum

Nanowire Length, Density, and Crystalline Quality Retrieved from a Single Optical Spectrum

Spectroscopic imaging ellipsometry for two-dimensional thin film thickness measurement using a digital light processing projector

Enhancing thickness determination of nanoscale dielectric films in phase diffraction-based optical characterization systems with radial basis function neural networks

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