Thermo-Sensor Based on Peak Intensity Ratio of Photoluminescence from Cr Doped YAG Crystals

2006 ◽  
Author(s):  
Miki Kaneda ◽  
Kaoru Orihara ◽  
Hiroaki Aizawa ◽  
Tooru Katsumata ◽  
Shuji Komuro ◽  
...  
Keyword(s):  
Intensity Ratio ◽  
Peak Intensity Ratio ◽  
Peak Intensity

The distribution of BrKα/RbKα peak intensity ratio in human whole blood samples

1994 ◽  
Vol 42 (3) ◽  
pp. 231-241 ◽  
Author(s):  
C. Shenberg ◽  
S. Spiegel ◽  
S. Chaitchik ◽  
P. Jordan ◽  
M. Kitzis ◽  
...  
Keyword(s):  
Whole Blood ◽  
Intensity Ratio ◽  
Peak Intensity Ratio ◽  
Blood Samples ◽  
Human Whole Blood ◽  
Peak Intensity ◽  
Whole Blood Samples

High sensitivity X-ray analysis for a low accelerating voltage scanning electron microscope using a transition edge sensor

Microscopy ◽  
2020 ◽  
Vol 69 (5) ◽  
pp. 298-303
Author(s):  
Keiichi Tanaka ◽  
Akira Takano ◽  
Atsushi Nagata ◽  
Satoshi Nakayama ◽  
Kaname Takahashi ◽  
...  
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Intensity Ratio ◽  
Transition Edge Sensor ◽  
High Energy Resolution ◽  
Peak Intensity Ratio ◽  
X Ray ◽  
Peak Intensity ◽  
Transition Edge ◽  
Scanning Electron

Abstract A scanning electron microscope transition edge sensor has been developed to analyze the minor or trace constituents contained in a bulk sample and small particles on the sample under a low accelerating voltage (typically <3 keV). The low accelerating voltage enables to improve the spatial analysis resolution because the primary electron diffusion length is limited around the sample surface. The characteristic points of our transition edge sensor are 1) high-energy resolution at 7.2 eV@Al-Kα, 2) continuous operation by using a cryogen-free dilution refrigerator and 3) improvement of transmission efficiency at B-Kα by using thin X-ray film windows between the sample and detector (about 30 times better than our previous system). Our system could achieve a stabilization of the peak shift at Nd-Mα (978 eV) within 1 eV during an operation time of 27 000 s. The detection limits with B-Kα for detection times 600 and 27 000 s were 0.27 and 0.038 wt%, respectively. We investigated the peak separation ability by measuring the peak intensity ratio between the major constitute (silicon) and the minor constitute (tungsten) because the Si-Kα line differs from the W-Mα line by only 35 eV and a small W-Mα peak superimposed on the tail of the large Si-Kα peak. The peak intensity ratio (I(W-Mα)/I(Si-Kα)) was adjusted by the W particle area ratio compared with the Si substrate area. The transition edge sensor could clearly separate the Si-Kα and W-Mα lines even under a peak intensity ratio of 0.01.

Developing Micro-Raman Mass Spectrometry for Measuring Carbon Isotopic Composition of Carbon Dioxide

2007 ◽  
Vol 61 (7) ◽  
pp. 701-705 ◽  
Author(s):  
Masashi Arakawa ◽  
Junji Yamamoto ◽  
Hiroyuki Kagi
Keyword(s):  
Isotopic Composition ◽  
Intensity Ratio ◽  
High Spatial Resolution ◽  
Carbon Isotopic Composition ◽  
Peak Intensity Ratio ◽  
Factors Affecting ◽  
Isotopic Compositions ◽  
Carbon Isotopic ◽  
Peak Intensity ◽  
The Relationship

We investigated the applicability of micro-Raman spectroscopy for determining carbon isotopic compositions (13C/12C) of minute CO2 fluid inclusions in minerals. This method is nondestructive and has sufficiently high spatial resolution (1 μm) to measure each fluid inclusion independently. Raman spectra of CO2 fluid have 12CO2-origin peaks at about 1285 cm−1 and 1389 cm−1 (v12− and v12+) and a 13CO2-origin peak at about 1370 cm−1 (v13+). The relationship between carbon isotopic compositions and peak intensity ratios of v12+ and v13+ was calibrated. Considering several factors affecting the peak intensity ratio, the error in obtained carbon isotopic composition was 2% (20‰). The reproducibility of the intensity ratio under the same experimental environment was 0.5% (5‰). Within these error values, we can distinguish biogenic CO2 from abiogenic CO2.

scholarly journals Valley-to-peak intensity ratio thermometry based on the red upconversion emission of Er^3+

2016 ◽  
Vol 24 (12) ◽  
pp. 13244 ◽  
Author(s):  
Leipeng Li ◽  
Wei Xu ◽  
Longjiang Zheng ◽  
Feng Qin ◽  
Yuan Zhou ◽  
...  
Keyword(s):  
Intensity Ratio ◽  
Upconversion Emission ◽  
Peak Intensity Ratio ◽  
Peak Intensity

scholarly journals Identification of Lesional Tissues and Nonlesional Tissues in Early Gastric Cancer Endoscopic Submucosal Dissection Specimens Using a Fiber Optic Raman System

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhaohui Luan ◽  
Yusi Qin ◽  
Jianhua Dai ◽  
Hongbo Wu ◽  
Yao Chen ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Raman Spectrum ◽  
Early Gastric Cancer ◽  
Intensity Ratio ◽  
Fiber Optic ◽  
Energy Ratio ◽  
Peak Intensity Ratio ◽  
Peak Intensity ◽  
Integral Energy ◽  
Diagnostic Indicator

Aim. To identify lesional and nonlesional tissues from early gastric cancer (EGC) patients by Raman spectroscopy to build a diagnostic model and effectively diagnose EGC. Method. Specimens were collected by endoscopic submucosal dissection from 13 patients with EGC, and 55 sets of standard Raman spectral data (each integrated 10 times) were obtained using the fiber optic Raman system; there were 33 sets of lesional tissue data, including 18 sets of high-grade intraepithelial neoplasia (HGIN) data and 15 sets of adenocarcinoma data, and 22 sets of nonlesional tissue data. After the preprocessing steps, the average Raman spectrum was obtained. Results. The nonlesional tissues showed peaks at 891 cm-1, 1103 cm-1, 1417 cm-1, 1206 cm-1, 1234 cm-1, 1479 cm-1, 1560 cm-1, and 1678 cm-1. Compared with the peaks corresponding to nonlesional tissues, the peaks of the lesional tissues shifted by different magnitudes, and a new characteristic peak at 1324 cm-1 was observed. Comparing the peak intensity ratio and the integral energy ratio of the lesional tissues with those of the nonlesional tissues revealed a significant difference between the two groups (independent-samplest-test, P<0.05). Considering the peak intensity ratio of I1560 cm-1/I1103 cm-1 as a diagnostic indicator, the accuracy, sensitivity, and specificity of diagnosing EGC were 98.8%, 93.9%, and 91.9%, respectively. Considering the integral energy ratio (noncontinuous frequency band and continuous frequency band) as a diagnostic indicator, the accuracy, sensitivity, and specificity of diagnosing EGC were 99.2-99.6%, 93.9-97.0%, and 95.5%, respectively. Conclusions. The integral energy ratio of the Raman spectrum could be considered an effective indicator for the diagnosis of EGC.

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