scholarly journals Super-Resolution Raman Spectroscopy by Digital Image Processing

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Motohiro Tomita ◽  
Hiroki Hashiguchi ◽  
Takuya Yamaguchi ◽  
Munehisa Takei ◽  
Daisuke Kosemura ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Spatial Resolution ◽  
Numerical Aperture ◽  
Super Resolution ◽  
Force Model ◽  
Stress Distributions ◽  
Si Substrate ◽  
Resolution Method ◽  
Strained Si ◽  
Edge Force

We demonstrate the results of a strain (stress) evaluation obtained from Raman spectroscopy measurements with the super-resolution method (the so-called super-resolution Raman spectroscopy) for a Si substrate with a patterned SiN film (serving as a strained Si sample). To improve the spatial resolution of Raman spectroscopy, we used the super-resolution method and a high-numerical-aperture immersion lens. Additionally, we estimated the spatial resolution by an edge force model (EFM) calculation. One- and two-dimensional stress distributions in the Si substrate with the patterned SiN film were obtained by super-resolution Raman spectroscopy. The results from both super-resolution Raman spectroscopy and the EFM calculation were compared and were found to correlate well. The best spatial resolution, 70 nm, was achieved by super-resolution Raman measurements with an oil immersion lens. We conclude that super-resolution Raman spectroscopy is a useful method for evaluating stress in miniaturized state-of-the-art transistors, and we believe that the super-resolution method will soon be a requisite technique.

Evaluation of Strained Silicon by Electron Back Scattering Pattern Compared with Raman Measurement and Edge Force Model Calculation

2011 ◽  
Vol 470 ◽  
pp. 123-128 ◽  
Author(s):  
Motohiro Tomita ◽  
Daisuke Kosemura ◽  
Munehisa Takei ◽  
Kohki Nagata ◽  
Hiroaki Akamatsu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Model Calculation ◽  
Biaxial Stress ◽  
Force Model ◽  
Si Substrate ◽  
Strained Si ◽  
Biaxial Tensile ◽  
Uv Raman Spectroscopy ◽  
Uv Raman ◽  
Edge Force

Global and local strained-Si samples, namely strained-Si on insulator (SSOI) wafer and a Si substrate with a patterned SiN film were each evaluated by electron backscattering pattern (EBSP). In the EBSP measurements for SSOI, biaxial tensile stresses (biaxial tensile strains and compressive strain perpendicular to the surface) were obtained, whose values were consistent with those obtained by UV-Raman spectroscopy. One-dimensional stress distributions in the Si substrate with the patterned SiN film were obtained by EBSP, UV-Raman spectroscopy with a deconvolution method, and edge force model calculation. The results were well consistent with each other. EBSP allows us to measure stress and strain in the patterned SiN sample with 150-nm wide space. Furthermore, anisotropic biaxial stress including shear stress was also obtained by EBSP.

scholarly journals Nanoscale Spatial Resolution in Far-Field Raman Imaging Using Hyperspectral Unmixing in Combination with Positivity Constrained Super-Resolution

2020 ◽  
Vol 74 (7) ◽  
pp. 780-790
Author(s):  
Dominik J. Winterauer ◽  
Daniel Funes-Hernando ◽  
Jean-Luc Duvail ◽  
Saïd Moussaoui ◽  
Tim Batten ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Spatial Resolution ◽  
Single Channel ◽  
Near Field ◽  
Resolution Enhancement ◽  
Super Resolution ◽  
Resolving Power ◽  
Far Field ◽  
Hyperspectral Unmixing ◽  
Better Than

This work introduces hyper-resolution (HyRes), a numerical approach for spatial resolution enhancement that combines hyperspectral unmixing and super-resolution image restoration (SRIR). HyRes yields a substantial increase in spatial resolution of Raman spectroscopy while simultaneously preserving the undistorted spectral information. The resolving power of this technique is demonstrated on Raman spectroscopic data from a polymer nanowire sample. Here, we demonstrate an achieved resolution of better than 14 nm, a more than eightfold improvement on single-channel image-based SRIR and [Formula: see text] better than regular far-field Raman spectroscopy, and comparable to near-field probing techniques.

Residual Stresses in Tungsten Lines: Analysis of Experimental- (Micro-Raman Spectroscopy, Xrd) and Numerical Results

1995 ◽  
Vol 391 ◽  
Author(s):  
I. De Wolf ◽  
H.E. Maes ◽  
J. Moffet ◽  
M. Ignat
Keyword(s):  
Raman Spectroscopy ◽  
Residual Stresses ◽  
Theoretical Models ◽  
Numerical Results ◽  
Analytical Modelling ◽  
Experimental Techniques ◽  
Force Model ◽  
Micro Raman Spectroscopy ◽  
Stress Components ◽  
Edge Force

AbstractMicro-Raman spectroscopy, XRD, and analytical modelling are used to study stresses in and surrounding tungsten lines of different widths and spacing. The stress in the lines and in the adjacent substrate is calculated using a concentrated- and a distributed edge force model. Both models are adapted such that the substrate-stress components can also be calculated for an array of lines. The results from XRD and micro-Raman spectroscopy and the results from the distributed edge force model are in agreement. The combination of data from the two experimental techniques is shown to give some important feed-back to the theoretical models.

Study of Ni(Pt) germanosilicides formation on fully-strained Si0.9Ge0.1 and Si0.899Ge0.1C0.001 by Raman Spectroscopy

2004 ◽  
Vol 810 ◽  
Author(s):  
J. Y. Y. Chaw ◽  
K. L. Pey ◽  
P. S. Lee ◽  
D. Z. Chi ◽  
J. P. Liu
Keyword(s):  
Raman Spectroscopy ◽  
Thermal Annealing ◽  
Raman Spectra ◽  
Rapid Thermal Annealing ◽  
Sharp Increase ◽  
Si Substrate ◽  
Strained Si ◽  
Low Resistivity ◽  
Transverse Acoustic ◽  
Phonon Peak

ABSTRACTIn this work, Raman spectroscopy was used to study the reaction of pure Ni and Ni(Pt 5 at. %) with fully-strained Si0.9Ge0.1 and Si0.899Ge0.1C0.001. With pure Ni, it was found that the incorporation of 0.1% C in the substrate resulted in out-diffusion of Ge from the germanosilicide film at a lower rapid thermal annealing (RTA) temperature compared to that of pure Ni on Si0.9Ge0.1. This Ge out-diffusion phenomenon is evident from the gradual shift in the NiSi1-wGew (w ≤ x) Raman peak from ∼213 cm−1 to higher wavenumbers, closer to 217 cm−1 as reported for pure Ni/Si, indicating that Ge is being depleted from the film with increasing RTA temperatures. In addition, it was found that severe agglomeration of the germanosilicide film occurred at a lower RTA temperature for the Ni/Si0.899Ge0.1C0.001 system. This corresponds to the observations from the Raman spectra, where a sharp increase in the Si substrate peak at 520 cm−1 was observed, coupled with the appearance of the transverse acoustic (TA)-phonon peak of Si at 301 cm−1. When Pt was introduced into the Ni film, significant improvements were observed for the germanosilicide films on Si0.9Ge0.1 and Si0.899Ge0.1C0.001 substrates, both in terms of Ge out- diffusion and agglomeration. Initial findings show that the addition of Pt promotes the formation of the low resistivity mono-germanosilicide phase at temperatures as low as 300°C.

Microspectroscopy Using a Solid Immersion Lens

2001 ◽  
Vol 7 (S2) ◽  
pp. 148-149
Author(s):  
C.D. Poweleit ◽  
J Menéndez
Keyword(s):  
Spatial Resolution ◽  
Focal Plane ◽  
Numerical Aperture ◽  
Normal Incidence ◽  
Spot Size ◽  
Index Of Refraction ◽  
Objective Lens ◽  
Improvement Factor ◽  
Oil Immersion ◽  
Long Time

Oil immersion lenses have been used in optical microscopy for a long time. The light’s wavelength is decreased by the oil’s index of refraction n and this reduces the minimum spot size. Additionally, the oil medium allows a larger collection angle, thereby increasing the numerical aperture. The SIL is based on the same principle, but offers more flexibility because the higher index material is solid. in particular, SILs can be deployed in cryogenic environments. Using a hemispherical glass the spatial resolution is improved by a factor n with respect to the resolution obtained with the microscope’s objective lens alone. The improvement factor is equal to n2 for truncated spheres.As shown in Fig. 1, the hemisphere SIL is in contact with the sample and does not affect the position of the focal plane. The focused rays from the objective strike the lens at normal incidence, so that no refraction takes place.

Technique for measuring the residual strain in strained Si/SiGe MOSFET structures using Raman spectroscopy

2004 ◽  
Vol 95 (5) ◽  
pp. 340-344 ◽  
Author(s):  
P. Dobrosz ◽  
S. J. Bull ◽  
S. H. Olsen ◽  
A. G. O'Neill
Keyword(s):  
Raman Spectroscopy ◽  
Residual Strain ◽  
Strained Si

Submicron Simultaneous IR and Raman Spectroscopy (IR+Raman): Breakthrough Developments in Optical Photothermal IR (O-PTIR) Combined for Enhanced Failure Analysis

2019 ◽  
Author(s):  
Jay Anderson ◽  
Mustafa Kansiz ◽  
Michael Lo ◽  
Curtis Marcott
Keyword(s):  
Raman Spectroscopy ◽  
Failure Analysis ◽  
Data Quality ◽  
Raman Spectra ◽  
Spatial Resolution ◽  
Far Field ◽  
Field Mode ◽  
Microscopic Scale ◽  
Analytical Tools ◽  
Ir And Raman

Abstract Failure analysis of organics at the microscopic scale is an increasingly important requirement, with traditional analytical tools such as FTIR and Raman microscopy, having significant limitations in either spatial resolution or data quality. We introduce here a new method of obtaining Infrared microspectroscopic information, at the submicron level in reflection (far-field) mode, called Optical-Photothermal Infrared (O-PTIR) spectroscopy, that can also generate simultaneous Raman spectra, from the same spot, at the same time and with the same spatial resolution. This novel combination of these two correlative techniques can be considered to be complimentary and confirmatory, in which the IR confirms the Raman result and vice-versa, to yield more accurate and therefore more confident organic unknowns analysis.

scholarly journals Super-resolution time-resolved imaging using computational sensor fusion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Callenberg ◽  
A. Lyons ◽  
D. den Brok ◽  
A. Fatima ◽  
A. Turpin ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Single Photon ◽  
Super Resolution ◽  
Numerical Data ◽  
Data Cube ◽  
Fluorescence Lifetime Imaging ◽  
Time Resolved ◽  
Temporal Precision

AbstractImaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.

scholarly journals Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1944
Author(s):  
Xiaoming Liu ◽  
Menghua Wang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Ocean Color ◽  
Super Resolution ◽  
Inland Waters ◽  
Coastal Oceans ◽  
Chl A ◽  
Color Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

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