Thermodynamic model and Raman spectra of MgO–P2O5 glasses

AbstractThe structure of binary glasses xMgO·(1−x)P2O5 (x = 0.30, 0.35, 0.40, 0.45, 0.50, and 0.55) was studied by thermodynamic model (TDM) of Shakhmatkin and Vedishcheva (SV) and Raman spectroscopy. In the TDM, six following system components were considered: MgO (M), P2O5 (P), MgO·2P2O5 (MP2), MgO·P2O5 (MP), 2MgO·P2O5 (M2P), 3MgO·P2O5 (M3P). The principal component analysis (PCA) of experimental Raman spectra resulted in three independent components. The baseline subtracted and thermally corrected Raman spectra were analyzed by the multivariate curve analysis (MCR) for three components. The MCR resulted in the Raman spectra and relative abundance of each component. The experimental spectra were reproduced by the MCR on the level of 99.9%. Correlation analysis attributed the MCR components to M2P, MP, and MP2. Then the Malfait’s decomposition was performed based on the TDM-SV equilibrium molar amounts of system components (MP2, MP, and M2P) resulting in partial Raman spectra (PRS). Normalized MCR loadings coincide with normalized PRS. Adjusted scores were reproduced with good accuracy equilibrium molar amounts of system components.

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Structure and Raman spectra of binary barium phosphate glasses

Journal of Thermal Analysis and Calorimetry ◽

10.1007/s10973-020-09328-0 ◽

2020 ◽

Vol 142 (2) ◽

pp. 937-942

Author(s):

Branislav Hruška ◽

Rajesh Dagupati ◽

Mária Chromčíková ◽

Aleksandra Nowicka ◽

Jaroslava Michálková ◽

...

Keyword(s):

Phase Diagram ◽

Raman Spectroscopy ◽

Spectral Data ◽

Raman Spectra ◽

Thermodynamic Model ◽

Binary Phase Diagram ◽

Phosphate Glasses ◽

Curve Analysis ◽

System Components ◽

Glass Compositions

Abstract The structure of xBaO·(1 − x) P2O5 (x = 0.30, 0.35, 0.40, 0.45, and 0.50) glasses was studied by Raman spectroscopy and thermodynamic model Shakhmatkin and Vedishcheva (SVTDM). The seven system components (defined as stable crystalline phases of the BaO–P2O5 binary phase diagram) were considered in the SVTDM: BaO, P2O5, 4BaO·P2O5 (B4P), 3BaO·P2O5 (B3P), 2BaO·P2O5 (B2P), BaO·P2O5 (BP), and BaO·2 P2O5 (BP2). Only the equilibrium molar abundances of BP and BP2 were non-negligible in all studied glass compositions. Therefore, in the next step, multivariate curve analysis (MCR) of the baseline—subtracted, thermally—corrected experimental Raman spectra, was performed for two components (BP2 and BP). MCR resulted in the Raman spectra (loadings) and relative abundances (scores) of each considered component. The MCR method reproduced 98.93% of the spectral data variance. Then, the decomposition of Malfait was used. The perfect fit between the MCR loadings and the partial Raman spectra of BP2 and BP, obtained by Malfait’s decomposition, was found, confirming the validity of thermodynamic model.

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Heating Effects of Desi Ghee Using Raman Spectroscopy

Applied Spectroscopy ◽

10.1177/0003702818763331 ◽

2018 ◽

Vol 72 (6) ◽

pp. 833-846 ◽

Cited By ~ 6

Author(s):

Naveed Ahmad ◽

Muhammad Saleem ◽

Mushtaq Ahmed ◽

Shaukat Mahmood

Keyword(s):

Principal Component Analysis ◽

Raman Spectroscopy ◽

Raman Spectra ◽

Principal Component ◽

Nondestructive Technique ◽

Molecular Changes ◽

Spectral Bands ◽

Heating Effects ◽

Excitation Laser ◽

First Time

Raman spectroscopy as a fast and nondestructive technique has been used to investigate heating effects on Desi ghee during frying/cooking of food for the first time. A temperature in the range of 140–180℃ has been investigated within which Desi ghee can be used safely for cooking/frying without much alteration of its natural molecular composition. In addition, heating effects in case of reuse, heating for different times, and cooking inside pressure cookers are also presented. An excitation laser at 785 nm has been used to obtain Raman spectra and the range of 540–1800 cm−1 is found to contain prominent spectral bands. Prominent variations have been observed in the Raman bands of 560–770 cm−1, 790–1160 cm−1, and 1180–1285 cm−1 with the rise in temperature. The spectral variations have been verified using classifier principal component analysis. It has been found that Desi ghee can be reused if heated below 180℃ and it can be heated up to 30 min without any appreciable molecular changes if a controlled heating can be managed.

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Identification of new spectral signatures associated with dengue virus infected sera

10.31219/osf.io/98dn4 ◽

2017 ◽

Author(s):

Ayyaz Amin ◽

Nimrah Ghouri ◽

Safdar Ali

Keyword(s):

Principal Component Analysis ◽

Raman Spectroscopy ◽

Discriminant Analysis ◽

Dengue Virus ◽

Linear Discriminant Analysis ◽

Raman Spectra ◽

Principal Component ◽

Component Analysis ◽

Optical Diagnosis ◽

Linear Discriminant

In a quest to use Raman spectroscopy as an optical diagnostic tool, we recorded Raman spectra of 32 dengue virus (DENV)-infected and 28 healthy sera samples in the near-infrared spectral range (540 to 1700 cm−1) using laser at 785 nm as the excitation source. We observed clear differences in the Raman spectra of DENV-infected sera as compared with those of healthy individuals. Here, as a result of our study, we report 12 unique Raman bands associated with DENV-infected sera that are not reported earlier. After applying analysis of variance and t-test (p < 0.05) on these 12 bands, six Raman bands at 630 (N-acetylglucosamine), 883 (in-plane bending (ring) of deoxyribose), 1218 (amide III–β conformation from C6H5–C stretching vibrations of tryptophan and phenylalanine), 1273 (amide–III), 1623 (tryptophan) and 1672 cm−1 (ceramide) were found only in the DENV-infected sera. The remaining six Raman bands at 716 (lipids), 780 (Uracil-based ring breathing mode), 828 (ring breathing tyrosine), 840 (α-anomers), 1101 (ν(C–N) of lipids and DNA) and 1150 cm−1(glycogen/carotenoids) were only found in healthy sera. Two types of classification models, principal component analysis and linear discriminant analysis, were employed to develop principal component analysis–linear discriminant analysis model that has provided diagnostic accuracy 96.50%, sensitivity 93.44%, and specificity 100%. This indicates that these 12 Raman bands have the potential to be used as biomarkers for optical diagnosis of DENV infection. This study provides a new insight for future research in the field of optical diagnosis using Raman spectroscopy.

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Multivariate Analysis of Micro-Raman Spectra of Thermoplastic Polyurethane Blends Using Principal Component Analysis and Principal Component Regression

Applied Spectroscopy ◽

10.1366/12-06588 ◽

2012 ◽

Vol 66 (11) ◽

pp. 1269-1278 ◽

Cited By ~ 14

Author(s):

Andrew Todd Weakley ◽

P.C. Temple Warwick ◽

Thomas E. Bitterwolf ◽

D. Eric Aston

Keyword(s):

Principal Component Analysis ◽

Multivariate Analysis ◽

Raman Spectra ◽

Thermoplastic Polyurethane ◽

Principal Component Regression ◽

Principal Component ◽

Component Analysis

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Simultaneous and rapid detection of polychlorinated phenols in water samples by surface-enhanced Raman spectroscopy combined with principal component analysis

Analytical and Bioanalytical Chemistry ◽

10.1007/s00216-022-03876-0 ◽

2022 ◽

Author(s):

Kun Ge ◽

Yonghui Li ◽

Qiyue Wu ◽

Ying Gu

Keyword(s):

Principal Component Analysis ◽

Raman Spectroscopy ◽

Water Samples ◽

Rapid Detection ◽

Principal Component ◽

Component Analysis ◽

Surface Enhanced Raman Spectroscopy ◽

Surface Enhanced ◽

Surface Enhanced Raman

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Principal component analysis of Raman spectra for TiO 2 nanoparticle characterization

Applied Surface Science ◽

10.1016/j.apsusc.2017.01.193 ◽

2017 ◽

Vol 417 ◽

pp. 93-103 ◽

Cited By ~ 41

Author(s):

Alina Georgiana Ilie ◽

Monica Scarisoareanu ◽

Ion Morjan ◽

Elena Dutu ◽

Maria Badiceanu ◽

...

Keyword(s):

Principal Component Analysis ◽

Raman Spectra ◽

Principal Component ◽

Component Analysis ◽

Nanoparticle Characterization

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Investigation of sport supplements quality by Raman spectroscopy and principal component analysis

Vibrational Spectroscopy ◽

10.1016/j.vibspec.2016.08.015 ◽

2016 ◽

Vol 87 ◽

pp. 1-7 ◽

Cited By ~ 8

Author(s):

Mariana R. Almeida ◽

Letícia P. de Souza ◽

Rodrigo S. Cesar ◽

Rafael A. Sousa ◽

Celly M.S. Izumi

Keyword(s):

Principal Component Analysis ◽

Raman Spectroscopy ◽

Principal Component ◽

Component Analysis ◽

Sport Supplements

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Raman Spectroscopy for Inverted Papilloma: A Proof-of-Concept Study

Otolaryngology ◽

10.1177/0194599818776640 ◽

2018 ◽

Vol 159 (3) ◽

pp. 587-589 ◽

Cited By ~ 1

Author(s):

Marco A. Mascarella ◽

Abdulaziz Alrasheed ◽

Naif Fnais ◽

Ophelie Gourgas ◽

Ghulam Jalani ◽

...

Keyword(s):

Principal Component Analysis ◽

Raman Spectroscopy ◽

Chronic Rhinosinusitis ◽

Principal Component ◽

Inverted Papilloma ◽

Proof Of Concept ◽

Linear Discriminant ◽

Acceptable Accuracy ◽

Sinonasal Mucosa ◽

Inverted Papillomas

Inverted papillomas are tumors of the sinonasal tract with a propensity to recur. Raman spectroscopy can potentially identify inverted papillomas from other tissue based on biochemical signatures. A pilot study comparing Raman spectroscopy to histopathology for 3 types of sinonasal tissue was performed. Spectral data of biopsies from patients with normal sinonasal mucosa, chronic rhinosinusitis, and inverted papillomas are compared to histopathology using principal component analysis and linear discriminant analysis after data preprocessing. A total of 18 normal, 15 chronic rhinosinusitis, and 18 inverted papilloma specimens were evaluated. The model distinguished normal sinonasal mucosa, chronic rhinosinusitis, and inverted papilloma tissue with an overall accuracy of 90.2% (95% confidence interval, 0.86-0.94). In conclusion, Raman spectroscopy can distinguish inverted papilloma, normal sinonasal mucosa, and chronically rhinosinusitis tissue with acceptable accuracy.

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