Multiple-perturbation two-dimensional (2D) correlation analysis for spectroscopic imaging data

2014 ◽  
Vol 1069 ◽  
pp. 176-182 ◽  
Author(s):  
Hideyuki Shinzawa ◽  
Kosuke Hashimoto ◽  
Hidetoshi Sato ◽  
Wataru Kanematsu ◽  
Isao Noda
Keyword(s):  
Correlation Analysis ◽  
Spectroscopic Imaging ◽  
Two Dimensional ◽  
Imaging Data ◽  
2D Correlation Analysis

New understanding on the reaction pathways of the polyacrylonitrile copolymer fiber pre-oxidation: online tracking by two-dimensional correlation FTIR spectroscopy

RSC Advances ◽  
2016 ◽  
Vol 6 (6) ◽  
pp. 4397-4409 ◽  
Author(s):  
Jing Zhao ◽  
Jihai Zhang ◽  
Tao Zhou ◽  
Xifei Liu ◽  
Qiang Yuan ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Ftir Spectroscopy ◽  
Reaction Pathways ◽  
Two Dimensional ◽  
Online Tracking ◽  
Polyacrylonitrile Copolymer ◽  
2D Correlation Analysis

FTIR spectroscopy in combination with scaling-MW2D and 2D correlation analysis is used to study the reaction pathways of polyacrylonitrile copolymer fibers pre-oxidation.

Two-Dimensional (2D) Correlation Analysis and the Search for Intermediates: A Strictly Mathematical Approach to an Important Mechanistic Question

ACS Catalysis ◽  
2015 ◽  
Vol 5 (6) ◽  
pp. 3588-3599 ◽  
Author(s):  
Qisong Xu ◽  
LiangFeng Guo ◽  
Tung Nguyen Dinh ◽  
Angie Cheong ◽  
Marc Garland
Keyword(s):  
Correlation Analysis ◽  
Mathematical Approach ◽  
Two Dimensional ◽  
2D Correlation Analysis

scholarly journals New Approach to Generalized Two-Dimensional Correlation Spectroscopy. 1: Combination of Principal Component Analysis and Two-Dimensional Correlation Spectroscopy

2002 ◽  
Vol 56 (12) ◽  
pp. 1562-1567 ◽  
Author(s):  
Young Mee Jung ◽  
Hyeon Suk Shin ◽  
Seung Bin Kim ◽  
Isao Noda
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Correlation Spectroscopy ◽  
Data Matrix ◽  
Two Dimensional ◽  
Noise Component ◽  
Reconstructed Data ◽  
2D Correlation Analysis

The direct combination of chemometrics and two-dimensional (2D) correlation spectroscopy is considered. The use of a reconstructed data matrix based on the significant scores and loading vectors obtained from the principal component analysis (PCA) of raw spectral data is proposed as a method to improve the data quality for 2D correlation analysis. The synthetic noisy spectra were analyzed to explore the novel possibility of the use of PCA-reconstructed spectra, which are highly noise suppressed. 2D correlation analysis of this reconstructed data matrix, instead of the raw data matrix, can significantly reduce the contribution of the noise component to the resulting 2D correlation spectra.

Multiple Perturbation Two-Dimensional Correlation Analysis of Cellulose by Attenuated Total Reflection Infrared Spectroscopy

2009 ◽  
Vol 63 (5) ◽  
pp. 501-506 ◽  
Author(s):  
Hideyuki Shinzawa ◽  
Shin-Ich Morita ◽  
Kimie Awa ◽  
Mariko Okada ◽  
Isao Noda ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Two Dimensional ◽  
Imaging Data ◽  
Analysis Scheme ◽  
Rate Of Evaporation ◽  
Crystallinity Changes ◽  
Grinding Time ◽  
Computational Form

An extension of the two-dimensional (2D) correlation analysis scheme for multi-dimensional perturbation is described. A simple computational form is provided to construct synchronous correlation and disrelation maps for the analysis of microscopic imaging data based on two independent perturbation variables. Sets of time-dependent attenuated total reflection infrared (ATR-IR) spectra of water and cellulose mixtures were collected during the evaporation of water from finely ground cellulose. The system exhibits complex behaviors in response to two independent perturbations, i.e., evaporation time and grinding time. Multiple perturbation 2D analysis reveals a specific difference in the rate of evaporation of water molecules when accompanied by crystallinity changes of cellulose. It identifies subtle differences in the volatility of water, which is related to the crystalline structure of cellulose.

Molecular self-healing mechanisms between C60-fullerene and anthracene unveiled by Raman and two-dimensional correlation spectroscopy

2016 ◽  
Vol 18 (27) ◽  
pp. 17973-17982 ◽  
Author(s):  
R. Geitner ◽  
J. Kötteritzsch ◽  
M. Siegmann ◽  
R. Fritzsch ◽  
T. W. Bocklitz ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Correlation Analysis ◽  
Correlation Spectroscopy ◽  
C60 Fullerene ◽  
Self Healing ◽  
Two Dimensional ◽  
Ft Raman Spectroscopy ◽  
2D Correlation Analysis ◽  
Ft Raman

C60-fullerene–anthracene self-healing copolymers were studied by time-, temperature- and concentration-dependent FT-Raman spectroscopy and advanced 2D correlation analysis.

New Approach to Avoid Erroneous Interpretation of Results Derived from Generalized Two-Dimensional Correlation Analysis for Applications in Catalysis

2005 ◽  
Vol 59 (8) ◽  
pp. 1060-1067 ◽  
Author(s):  
Peter Haider ◽  
Gary L. Haller ◽  
Lisa Pfefferle ◽  
Dragos Ciuparu
Keyword(s):  
Correlation Analysis ◽  
Surface Characterization ◽  
Oscillatory Behavior ◽  
Data Matrix ◽  
Spectral Features ◽  
Two Dimensional ◽  
New Approach ◽  
Set Up ◽  
Time Sequences ◽  
2D Correlation Analysis

Surface characterization and catalysis can significantly benefit from the application of generalized two-dimensional (2D) correlation analysis. This two-dimensional approach allows a better resolution of overlapping peaks, can reveal new features not readily observable in the raw spectra, gives clear evidence for spectral intensities that change as an effect of a perturbation applied to the system, and allows the establishment of time sequences for the changes occurring in different spectral features of interest for determining reaction intermediates and/or mechanisms. The interpretation of the synchronous and asynchronous plots was observed to lead to erroneous time sequences when spectral features change in a nonmonotonic way, such as a biphasic or oscillatory behavior, under the influence of a perturbation. We propose a new approach to the 2D correlation analysis to avoid misinterpretation of the results calculated in the asynchronous plot. Progressive correlation analysis (ProCorA) calculates the synchronous plot from the first two spectra of the data matrix and one spectrum is added at every step of the analysis. The sequence of changes can be set up from the progressive evolution of peaks in both the synchronous and asynchronous plots.

TWO-DIMENSIONAL CORRELATION ANALYSIS OF SUPERCONDUCTING YNi2B2C RAMAN SPECTRA

2005 ◽  
Vol 19 (01n03) ◽  
pp. 281-284 ◽  
Author(s):  
IN-SANG YANG ◽  
YOUNG MEE JUNG ◽  
SEUNG BIN KIM ◽  
M. V. KLEIN
Keyword(s):  
Correlation Analysis ◽  
Temperature Dependence ◽  
Raman Spectra ◽  
Superconducting State ◽  
Superconducting Gap ◽  
Two Dimensional ◽  
Temperature Changes ◽  
Phonon Peak ◽  
Two Peaks ◽  
2D Correlation Analysis

Two-dimensional (2D) correlation analysis is applied to the temperature dependence on the Raman spectra of superconducting YNi 2 B 2 C single crystal. 2D correlation analysis on the temperature dependence of the B 1g superconducting gap peak shows strong correlation with the Ni B 1g phonon peak near 200 cm -1. The analysis on the B 1g phonon peak itself shows that the peak is composed of essentially two peaks at 197 and 203 cm -1, and only the weight of the two peaks changes as the temperature changes. The result suggests that there are two distinctive environments of the Ni - B bonds in YNi 2 B 2 C system at the superconducting state.

On the Normalization Method in Two-Dimensional Correlation Spectra When Concentration is Used as a Perturbation Parameter

2003 ◽  
Vol 57 (2) ◽  
pp. 164-167 ◽  
Author(s):  
Z. W. Yu ◽  
I. Noda
Keyword(s):  
Correlation Analysis ◽  
Intensity Variation ◽  
Perturbation Parameter ◽  
Quantitative Information ◽  
Transformation Process ◽  
Normalization Method ◽  
Two Dimensional ◽  
Absorption Bands ◽  
Data Pretreatment ◽  
2D Correlation Analysis

Data pretreatment is of importance in two-dimensional (2D) correlation analysis when composition is used as a perturbation parameter. For composition-oriented studies, different normalization methods based on both external parameters (i.e., concentration) and internal parameters (i.e., absorbance from individual components) have been compared. It was found that when there is no overlapping between absorption bands of interest, no normalization is needed for data pretreatment. When overlapped bands must be used for 2D correlation analysis, the mean-centered normalization method could be used to obtain correct signs in synchronous spectra for a transformation process in the specific form of A → kC. The intensity of the 2D spectrum, however, may not accurately reflect quantitative information of the overall extent of spectral intensity variation observed during experiments.

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