Next Article in Journal
Orbit Determination of Resident Space Objects Using the P-Band Mono-Beam Receiver of the Sardinia Radio Telescope
Next Article in Special Issue
A Traceable High-Accuracy Velocity Measurement by Electro-Optic Dual-Comb Interferometry
Previous Article in Journal
Artificial-Hand Technology—Current State of Knowledge in Designing and Forecasting Changes
Previous Article in Special Issue
A Mesh-Based Monte Carlo Study for Investigating Structural and Functional Imaging of Brain Tissue Using Optical Coherence Tomography
Open AccessArticle

Dependence-Analysis-Based Data-Refinement in Optical Scatterometry for Fast Nanostructure Reconstruction

1
Hubei Key Laboratory of Manufacture Quality Engineering, Hubei University of Technology, Wuhan 430068, Hubei, China
2
State Key Laboratory for Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(19), 4091; https://doi.org/10.3390/app9194091
Received: 16 August 2019 / Revised: 27 September 2019 / Accepted: 27 September 2019 / Published: 30 September 2019
Optical scatterometry is known as a powerful tool for nanostructure reconstruction due to its advantages of being non-contact, non-destructive, low cost, and easy to integrate. As a typical model-based method, it usually makes use of abundant measured data for structural profile reconstruction, on the other hand, too much redundant information significantly degrades the efficiency in profile reconstruction. We propose a method based on dependence analysis to identify and then eliminate the measurement configurations with redundant information. Our experiments demonstrated the capability of the proposed method in an optimized selection of a subset of measurement wavelengths that contained sufficient information for profile reconstruction and strikingly improved the profile reconstruction efficiency without sacrificing accuracy, compared with the primitive approach, by making use of the whole spectrum. View Full-Text
Keywords: optical scatterometry; inverse problem; profile reconstruction; dependence analysis; data refinement optical scatterometry; inverse problem; profile reconstruction; dependence analysis; data refinement
Show Figures

Figure 1

MDPI and ACS Style

Dong, Z.; Chen, X.; Wang, X.; Shi, Y.; Jiang, H.; Liu, S. Dependence-Analysis-Based Data-Refinement in Optical Scatterometry for Fast Nanostructure Reconstruction. Appl. Sci. 2019, 9, 4091.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop