Cross-sectional shape evaluation of a particle by scatterometry

Hoshino, Tetsuya; Itoh, Masahide

doi:10.1016/j.optcom.2015.09.063

Cited by 5 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The approximate analysis was performed based on Fraunhofer diffraction [ 25,118,179 ] and on the interference between different orders of scattered radiation. [ 27,119–123 ] The observed LSP oscillation frequencies linearly depend on the particle size, which holds in the remarkably wide range of particle characteristics.…”

Section: Characterization Methods and Inverse Problemsmentioning

confidence: 99%

See 1 more Smart Citation

Single‐Particle Characterization by Elastic Light Scattering

Romanov

Yurkin

2021

Laser & Photonics Reviews

View full text Add to dashboard Cite

The field of light‐scattering characterization of single particles has seen a rapid growth over the last 30 years largely due to the progress in measurement and simulation capabilities. In particular, several methods have been developed to reliably characterize various particles, described by a model with several characteristics, with geometric resolution significantly better than the diffraction limit. However, their development has been largely fragmentary, limited to specific experimental set‐ups. To fill this gap, these lines of development are reviewed within a unified framework. While focusing on characterization algorithms themselves, the experimental aspects related to the isolation and measurement of single particles are also discussed. The existing characterization methods are divided into three classes. The widest class is that of model‐driven methods based on solving parametric inverse light‐scattering problems, using a direct inversion of a low‐dimensional mapping, a nonlinear regression, or neural networks. Other classes include model‐free reconstruction methods and data‐driven classification methods. This review is designed to be extensive in including all relevant literature, but the discussion of semi‐quantitative imaging methods, such as tomography or holography‐based reconstruction, is deliberately omitted. Throughout the review the development of various characterization methods is described, they are critically compared, and promising directions of future research are highlighted.

show abstract

Section: Characterization Methods and Inverse Problemsmentioning

confidence: 99%

“…Hoshino and Itoh [ 179 ] used the FFT sizing in the framework of Fraunhofer diffraction and combined it with measurements for multiple incident directions (similar to the methods in Section 4.2) for a shape classification and better sizing accuracy.…”

Section: Characterization Methods and Inverse Problemsmentioning

confidence: 99%

Single‐Particle Characterization by Elastic Light Scattering

Romanov

Yurkin

2021

Laser & Photonics Reviews

View full text Add to dashboard Cite

show abstract

“…S1 [2,3,[7][8][9]. In this report, two-layered rectangles are analyzed by CSDaVe, in addition to conventional ellipses, rectangles, and triangles [10][11][12]. At a minimum, CSDaVe's analysis is possible if the diffraction pattern can be calculated by RCWA without simulator power issues, and it can be assumed that the shape is one of these structures.…”

Section: High Accuracymentioning

confidence: 99%

“…This section discusses accuracy and resolution to verify the effectiveness of the vector field theory. The layer number and number of incident angles affect the resolution [11]. Here, to simplify the situation, the simulation condition is that the only parameter is w1 and that there is only one incident angle.…”

Section: Supplement C: Effect Of Width On Diffraction Patterns In Sim...mentioning

confidence: 99%