Effect of the spectrometer slit width and charge‐coupled device detector on Raman intensities

2021 ◽  
Author(s):  
Ryan S. Jakubek
Keyword(s):  
Slit Width ◽  
Charge Coupled Device ◽  
Raman Intensities ◽  
Spectrometer Slit

The Influence of Slit-Width on the Shape and Intensity of Infra-Red Absorption Bands

1951 ◽  
Vol 4 (2) ◽  
pp. 172
Author(s):  
JB Willis
Keyword(s):  
Experimental Data ◽  
Half Width ◽  
Slit Width ◽  
Absorption Bands ◽  
Infra Red ◽  
Spectrometer Slit

Making certain assumptions as to the shape of infra-red absorption bands and the shape of the slit function of the monochromator, expressions are obtained for the dependence on spectrometer slit-width of the intensity and half-width of absorption bands. Experimental data to confirm the accuracy of these deductions are presented.

Temperature Effect on Spectrometer Slit Width and Photomultiplier Sensitivity

1968 ◽  
Vol 39 (7) ◽  
pp. 1039-1043 ◽  
Author(s):  
A. Ozolins ◽  
W. C. Lineberger ◽  
F. E. Niles
Keyword(s):  
Temperature Effect ◽  
Slit Width ◽  
Spectrometer Slit

Microphotometric Errors for Photographically Recorded Spectral Lines of Nonuniform Half-Width

1978 ◽  
Vol 32 (5) ◽  
pp. 433-444 ◽  
Author(s):  
L. C. McGonagle ◽  
J. A. Holcombe
Keyword(s):  
Line Width ◽  
Half Width ◽  
Slit Width ◽  
Spectral Lines ◽  
Average Error ◽  
Spatially Resolved ◽  
Source Line ◽  
Line Widths ◽  
Spectrometer Slit ◽  
The Impact

Various microphotometric (or densitometric) techniques for generating quantitative intensity information from photographically recorded spectral lines of time or spatially resolved sources are discussed. The impact of various parameters on the accuracy of quantitative densitometry is presented. These parameters include line widths of the calibration spectrum, source line broadening, microphotometer scan slit width and the optical density of the photographic image. Nonrandom errors associated with the use of various microphotometer slit widths for spectral lines of nonuniform half-width are presented. Spectral lines which are uniform and exhibit slit width or diffraction limited resolution can be scanned with any size microphotometer slit width as long as the calibration curve is prepared using the same scan slit width. The use of microphotometer slit widths narrower than the line width produce H and D curves with maximal γ and increased accuracy in the final intensity value. A density-to-intensity conversion accuracy with a 6% average error was determined for SA-1 plates. For sources whose line widths are larger than the spectrometer bandpass, minimal errors are generated by using a narrow line source for calibration and scanning this spectrum with a slit width less than the line width. Scanning of the broadened line of interest is accomplished using a scan slit width equal to approximately twice the spectrometer slit width. Under these conditions an average error of approximately 11% was determined experimentally for SA-1 plates.

Effects of Sampling Parameters on Principal Components Analysis of Raman Line Images

1996 ◽  
Vol 50 (6) ◽  
pp. 708-714 ◽  
Author(s):  
Charlene A. Hayden ◽  
Michael D. Morris
Keyword(s):  
Principal Components Analysis ◽  
Spectral Data ◽  
Principal Components ◽  
Slit Width ◽  
Data Sets ◽  
Polystyrene Spheres ◽  
Components Analysis ◽  
Scanned Images ◽  
The Individual ◽  
Spectrometer Slit

Raman images of the distribution of materials in a sample prepared from 10-μm-diameter polystyrene spheres embedded in epoxy were reconstructed from sets of line-scanned images, with the use of univariate and multivariate processing of the spectral data. Multiple sets of microscopic Raman spectral line images were acquired by using line-focused illumination with a cylindrical lens, a motorized translation stage to move the sample perpendicular to the illumination line, and a holographic imaging spectrograph equipped with a 2D charge-coupled device (CCD) detector. Repeat sets of data were obtained at different spectrometer slit width settings and different magnification. The raw spectral data were processed by using both a simple univariate method (single-band integration) and a more sophisticated multivariate method [principal components analysis (PCA) with eigenvector rotation] to generate 2D Raman images representing spatial distribution of the individual polymeric constituents. The repeat data sets were compared to ascertain the effects of the sampling parameters on the PCA method. The results indicated that spectrometer slit width and magnification affect the sampling depth and spatial resolution, but have little effect on the PCA. Moreover, digital sampling (i.e., number of PCA wavelength variables) could be significantly reduced with little or no degradation of the PCA-generated images, particularly if key bands were represented.

Post-Spectrometer Instrumentation for STEM

1990 ◽  
Vol 48 (2) ◽  
pp. 104-105
Author(s):  
D. McMullan ◽  
J.M. Rodenburg ◽  
W.T. Pike
Keyword(s):  
High Quality ◽  
Bright Field ◽  
Charge Coupled Device ◽  
Phosphor Screen ◽  
Diffraction Patterns ◽  
A Charge ◽  
Spectrometer Slit ◽  
Quadrupole Lenses ◽  
Dispersion Plane

A charge-coupled device (CCD) is being used for parallel recording on the EELS spectrometer of the V-G HB501 STEM in the Cavendish. Three quadrupole lenses are provided for focussing the EELS spectrum and, unlike in some other similar systems, the spectrometer slit has been retained. This was done so that the spectrometer could still be used for serial acquisition of EELS spectra and for energy-filtered imaging, although it would be preferable, and was envisaged as a later development, to have the first quadrupole positioned before the dispersion plane of the spectrometer; the slit would have been simulated by a suitably masked scintillator for the bright field detector.However it has proved advantageous to keep the slit so that microdiffraction patterns can be imaged through the spectrometer. The recording of high quality diffraction patterns in the HB501 STEM has not been straightforward: Grigson recording is far too slow, and although the standard microscope is provided with a phosphor screen and TV and film cameras, the speed and resolution are rather poor.

Quantitative energy-filtered tem imaging of interfaces

1996 ◽  
Vol 54 ◽  
pp. 542-543 ◽  
Author(s):  
J. Bentley ◽  
E. A. Kenik ◽  
K. Siangchaew ◽  
M. Libera
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Unit Volume ◽  
Core Loss ◽  
Mean Free Path ◽  
Slit Width ◽  
Elemental Mapping ◽  
Low Loss ◽  
Transmission Electron ◽  
Inelastic Mean Free Path

Quantitative elemental mapping by inner shell core-loss energy-filtered transmission electron microscopy (TEM) with a Gatan Imaging Filter (GIF) interfaced to a Philips CM30 TEM operated with a LaB6 filament at 300 kV has been applied to interfaces in a range of materials. Typically, 15s exposures, slit width Δ = 30 eV, TEM magnifications ∼2000 to 5000×, and probe currents ≥200 nA, were used. Net core-loss maps were produced by AE−r background extrapolation from two pre-edge windows. Zero-loss I0 (Δ ≈ 5 eV) and “total” intensity IT (unfiltered, no slit) images were used to produce maps of t/λ = ln(IT/I0), where λ is the total inelastic mean free path. Core-loss images were corrected for diffraction contrast by normalization with low-loss images recorded with the same slit width, and for changes in thickness by normalization with t/λ, maps. Such corrected images have intensities proportional to the concentration in atoms per unit volume. Jump-ratio images (post-edge divided by pre-edge) were also produced. Spectrum lines across planar interfaces were recorded with TEM illumination by operating the GIF in the spectroscopy mode with an area-selecting slit oriented normal to the energy-dispersion direction. Planar interfaces were oriented normal to the area-selecting slit with a specimen rotation holder.

A Simple Algorithm for Despiking Raman Spectra

2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes
Keyword(s):  
Moving Average ◽  
Simple Algorithm ◽  
Mathematical Concepts ◽  
Charge Coupled Device ◽  
Analytical Technique ◽  
Minimal Sample ◽  
Minimal Distortion ◽  
Molecular Specificity ◽  
Ccd Detectors ◽  
Average Filter

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>

A Simple Algorithm for Despiking Raman Spectra

2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes
Keyword(s):  
Moving Average ◽  
Simple Algorithm ◽  
Mathematical Concepts ◽  
Charge Coupled Device ◽  
Analytical Technique ◽  
Minimal Sample ◽  
Minimal Distortion ◽  
Molecular Specificity ◽  
Ccd Detectors ◽  
Average Filter

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>

Sign in / Sign up

Export Citation Format

Share Document