Monitoring of Chemical Speciation of DEA – CO2 – Water System by Raman Spectroscopy

2015 ◽  
Vol 1113 ◽  
pp. 358-363 ◽  
Author(s):  
Muhammad Zubair Shahid ◽  
Humbul Suleman ◽  
Adulhalim Shah Maulud ◽  
Mohammad Azmi Bustam Khalil ◽  
Zakaria Man
Keyword(s):  
Raman Spectroscopy ◽  
Water System ◽  
Chemical Species ◽  
Principal Component Regression ◽  
Principal Component ◽  
Carbon Dioxide Separation ◽  
Key Factor ◽  
Kinetics Of ◽  
Respective Characteristic ◽  
Good Agreement

Carbon dioxide separation has gained immense importance since its detrimental effects towards our environment has been realized. Commercially, CO2has been captured by absorption in alkanolamines such as diethanolamine (DEA), since many years. The thermodynamics and kinetics of the process is a key factor towards its efficiency and significantly depends on its qualitative and quantitative speciation. In this work, the analysis of speciation for CO2loaded aqueous DEA has been performed by Raman spectroscopy. Experimentally determined CO2loading data and modified Kent Eisenberg equation was used to quantify the chemical species present. The speciation results were fitted with the respective characteristic Raman peaks of (CO3-, HCO3-, DEACOO-, DEA, DEA+, CO2) by Principal Component Regression (PCR). The fitted results showed good agreement with thermodynamically predicted chemical species.

Determination of Chemical Species in MDEA – Carbon Dioxide – Water System by Raman Spectroscopy

2015 ◽  
Vol 1113 ◽  
pp. 261-266 ◽  
Author(s):  
Humbul Suleman ◽  
Muhammad Zubair Shahid ◽  
Abdulhalim Shah Maulud ◽  
Zakaria Man ◽  
Mohammad Azmi Bustam Khalil
Keyword(s):  
Carbon Dioxide ◽  
Raman Spectroscopy ◽  
Chemical Speciation ◽  
Water System ◽  
Chemical Species ◽  
Principal Component Regression ◽  
Principal Component ◽  
Carbon Dioxide Absorption

Alkanolamines based carbon dioxide absorption from flue gases remains the most industrially implemented technique. The effective design of absorbers and associated equipment requires robust thermodynamic and kinetic models thus, instigating research efforts in chemical speciation and characterization of CO2loaded alkanolamine solutions. In this study, the potential of Raman spectroscopy has been investigated to determine the in situ chemical speciation in MDEA – CO2– Water system. The Raman spectra have been fitted to thermodynamic values using principal component regression. Results are in good agreement for carbonate, bicarbonate, MDEA and protonated MDEA chemical species.

Use of Multivariate Analysis to Determine Temperature from Low-Resolution Infrared Spectra of Carbon Dioxide

2000 ◽  
Vol 54 (2) ◽  
pp. 197-201 ◽  
Author(s):  
Michael P. Szczepanski ◽  
Augustus W. Fountain
Keyword(s):  
Carbon Dioxide ◽  
Chemical Species ◽  
Principal Component Regression ◽  
Principal Component ◽  
Industrial Applications ◽  
Low Resolution ◽  
Band Shape ◽  
Temperature Spectra ◽  
Plume Temperature ◽  
Industrial Monitoring

The remote optical monitoring of gaseous contaminants is important for both military and industrial applications. An important parameter for quantifying chemical species and for predicting plume dynamics is the temperature. While in some industrial monitoring situations it may be practical to independently measure the temperature of stack emissions, for compliance monitoring and military chemical reconnaissance a remote optical means of estimating gas plume temperature is required. It was noticed that the band shape of low-resolution spectra of carbon dioxide in equilibrium with an exhaust plume was very sensitive to temperature. Spectra of carbon dioxide were acquired under controlled laboratory conditions in 5° increments from 20 to 200 °C. Various multivariate models were used to predict the temperature. It was found that partial least-squares (PLS) was unable to effectively model the simultaneous changes in amplitude and bandwidth with temperature. However, principal component regression (PCR) was found to be well correlated with temperature and allowed cross-validated prediction within 4% error.

scholarly journals Multivariate Method Based on Raman Spectroscopy for Quantification of Dipyrone in Oral Solutions

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luciana Lopes Guimarães ◽  
Letícia Parada Moreira ◽  
Bárbara Faria Lourenço ◽  
Walber Toma ◽  
Renato Amaro Zângaro ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Quality Control ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quantitative Model ◽  
Calibration Model ◽  
Analytical Methodology ◽  
Figures Of Merit ◽  
Model Based ◽  
Raman Probe

This work employed a quantitative model based on Raman spectroscopy and principal component regression (RS/PCR) to quantify the active ingredient dipyrone (metamizole) in commercially available formulations as an analytical methodology for quality control in the pharmaceutical industry. Raman spectra were collected using a dispersive Raman spectrometer (830 nm, 250 mW excitation, and 20 s exposure time) coupled to a Raman probe. Solutions of dipyrone diluted in water in the range of 80 to 120% of the concentration of commercial formulations (500 mg/mL) were used to develop a calibration model based on PCR to obtain the figures of merit for class I validation from the Brazilian Sanitary Surveillance Agency (ANVISA, RE no. 899/2003). This spectral model was then used to predict the concentration of dipyrone in commercial formulations from distinct brands with 500 mg/mL. A prediction error of 6.5 mg/mL (1.3%) was found for this PCR model using the diluted samples. Commercial formulations had predicted concentrations with a difference below 5.0% compared to the label concentration, indicating the applicability of Raman spectroscopy for quality control in the final product.

Nonlinear Optimization Algorithm for Multivariate Optical Element Design

2002 ◽  
Vol 56 (4) ◽  
pp. 477-487 ◽  
Author(s):  
Olusola O. Soyemi ◽  
Frederick G. Haibach ◽  
Paul J. Gemperline ◽  
Michael L. Myrick
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Algorithm ◽  
Optical Computing ◽  
Chemical Species ◽  
Principal Component Regression ◽  
Principal Component ◽  
Optical Element ◽  
Optical Elements ◽  
Design Algorithm ◽  
Nonlinear Optimization Algorithm

A new algorithm for the design of optical computing filters for chemical analysis, otherwise known as multivariate optical elements (MOEs), is described. The approach is based on the nonlinear optimization of the MOE layer thicknesses to minimize the standard error in sample prediction for the chemical species of interest using a modified version of the Gauss–Newton nonlinear optimization algorithm. The design algorithm can either be initialized with random layer thicknesses or with layer thicknesses derived from spectral matching of a multivariate principal component regression (PCR) vector for the constituent of interest. The algorithm has been successfully tested by using it to design various MOEs for the determination of Bismarck Brown dye in a binary mixture of Crystal Violet and Bismarck Brown.

scholarly journals Chemometrics-Assisted Monitoring in Raman Spectroscopy for the Biodegradation Process of an Aqueous Polyfluoroalkyl Ether from a Fire-Fighting Foam in an Environmental Matrix

2019 ◽  
Author(s):  
Mario Marchetti ◽  
Marc Offroy ◽  
Ferroudja Abdat ◽  
Philippe Branchu ◽  
Patrice Bourson ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Fire Fighting ◽  
Least Square ◽  
Experimental Procedure ◽  
Raman Spectroscopic ◽  
Spectroscopic Monitoring ◽  
In Fire ◽  
Kinetics Of

Surfactants based on polyfluoroalky ethers are commonly used in fire-fighting foams on airport platforms, including for training sessions. Because of their persistence into the environment, their toxicity and their bioaccumulation, abnormal amounts can be found in ground and surface water following operations of airport platforms. As many other anthropogenic organic compounds, some concerns raised about their biodegradation. That is why the OECD 301 F protocol was implemented to appreciate the oxygen consumption during the biodegradation of a commercial fire-fighting foam. However, a Raman spectroscopic monitoring of the process was also attached to this experimental procedure to evaluate to what extent a polyfluoroalkyl ether disappeared from the environmental matrix. The relevance of our approach is to use chemometrics, including the Principal Component Analysis (PCA) and the Partial Least Square (PLS), in order to monitor the kinetics of the biodegradation reaction of one fire-fighting foam, Tridol S3B, containing a polyfluoroalkyl ether. This study provided a better appreciation of the partial biodegradation of some polyfluoroalkyl ethers by coupling Raman spectroscopy and chemometrics. This will ultimately facilitates the design of a future purification and remediation devices for the airport platforms.

Spectrophotometric Simultaneous Determination of Levamisole and Triclabendazole in Tablets by Principal Component Regression and Partial Least Squares Chemometric Methods

2008 ◽  
Vol 59 (2) ◽  
pp. 154-158 ◽  
Author(s):  
Gozde Pektas ◽  
Erdal Dinc ◽  
Dumitru Baleanu
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Addition ◽  
Chemometric Methods ◽  
Preliminary Separation ◽  
Absorbance Data ◽  
Good Agreement

Principal component regression (PCR) and partial least squares (PLS) chemometric methods were applied to the simultaneous quantitative analysis of levamisole (LVM) and triclabendazole (TCB) in tablets without using a preliminary separation, even in presence of the overlapping spectra of the above compounds. For both PCR and PLS, a concentration set containing 25 different mixtures of LVM and TCB in the linear concentration range was symmetrically prepared and then the absorbance values of the concentration set were measured at the wavelength set with Dl=0.1 nm in the spectral region of 225-322.3 nm. PCR and PLS calibrations were obtained by applying the PCR and PLS algorithms to the concentration set data (y-block) and their corresponding absorbance data (x-block). The validity of PCR and PLS chemometric methods was performed by using the independent synthetic mixtures and the standard addition technique. Then, these analytical methods were applied to the commercial tablets and a good agreement was obtained between experimental results provided by the application of the PCR and PLS to the synthetic and real samples.

Crosslinking of Gelatin in the Reaction with Formaldehyde: An FT-IR Spectroscopic Study

1996 ◽  
Vol 50 (10) ◽  
pp. 1314-1318 ◽  
Author(s):  
T. Salsa ◽  
M. E. Pina ◽  
J. J. C. Teixeira-Dias
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Potassium Bromide ◽  
Crosslinking Reaction ◽  
Spectral Changes ◽  
Principal Component Regression Analysis ◽  
Ft Ir ◽  
Ir Spectroscopic ◽  
Kinetics Of ◽  
Ft Ir Spectroscopy

The reaction of an aqueous solution of formaldehyde with gelatin dispersed in a potassium bromide pellet is monitored in real time by FT-IR spectroscopy. Principal component regression analysis of the spectra recorded at different times is carried out. On the whole, the latter results and the observed spectral changes are in agreement with a previously reported interpretation for the kinetics of the crosslinking reaction of gelatin with formaldehyde, according to which the reaction is initialized by the lysine–methylol formation and is subsequently followed by arginine–methylol, which, in turn, reacts with lysine–methylol to originate arginine–lysine crosslinks.

scholarly journals Chemometrics-Assisted Monitoring in Raman Spectroscopy for the Biodegradation Process of an Aqueous Polyfluoroalkyl Ether from a Fire-Fighting foam in an Environmental Matrix

Environments ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Mario Marchetti ◽  
Marc Offroy ◽  
Ferroudja Abdat ◽  
Philippe Branchu ◽  
Patrice Bourson ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Raman Spectroscopy ◽  
Principal Component ◽  
Fire Fighting ◽  
Experimental Procedure ◽  
Raman Spectroscopic ◽  
Spectroscopic Monitoring ◽  
Biodegradation Process ◽  
In Fire ◽  
Kinetics Of

Surfactants based on polyfluoroalkyl ethers are commonly used in fire-fighting foams on airport platforms, including for training sessions. Because of their persistence into the environment, their toxicity and their bioaccumulation, abnormal amounts can be found in ground and surface water following the operations of airport platforms. As with many other anthropogenic, organic compounds, some concerns are raised about their biodegradation. That is why the Organization for Economic Co-operation and Development (OECD) 301 F protocol was implemented to monitor the oxygen consumption during the biodegradation of a commercial fire-fighting foam. However, a Raman spectroscopic monitoring of the process was also attached to this experimental procedure to evaluate to what extent a polyfluoroalkyl ether disappeared from the environmental matrix. Our approach relies on the use of chemometrics, such as Principal Component Analysis (PCA) and Partial Least Squares (PLS), in order to monitor the kinetics of the biodegradation reaction of one fire-fighting foam, Tridol S3B, containing a polyfluoroalkyl ether. This study provided a better appreciation of the partial biodegradation of some polyfluoroalkyl ethers by coupling Raman spectroscopy and chemometrics. This will ultimately facilitate the design of future purification and remediation devices for airport platforms.

scholarly journals Constrained regularization for noninvasive glucose sensing using Raman spectroscopy

2015 ◽  
Vol 08 (04) ◽  
pp. 1550022 ◽  
Author(s):  
Wei-Chuan Shih
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Calibration ◽  
Experimental Studies ◽  
Principal Component Regression ◽  
Principal Component ◽  
Glucose Sensing ◽  
Model Complexity ◽  
Calibration Model ◽  
Noise Rejection ◽  
Implicit Model

Multivariate calibration is an important tool for spectroscopic measurement of analyte concentrations. We present a detailed study of a hybrid multivariate calibration technique, constrained regularization (CR), and demonstrate its utility in noninvasive glucose sensing using Raman spectroscopy. Similar to partial least squares (PLS) and principal component regression (PCR), CR builds an implicit model and requires knowledge only of the concentrations of the analyte of interest. Calibration is treated as an inverse problem in which an optimal balance between model complexity and noise rejection is achieved. Prior information is included in the form of a spectroscopic constraint that can be obtained conveniently. When used with an appropriate constraint, CR provides a better calibration model compared to PLS in both numerical and experimental studies.

scholarly journals Bacillus thuringiensis Cells Selectively Captured by Phages and Identified by Surface Enhanced Raman Spectroscopy Technique

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 100
Author(s):  
Salvatore Almaviva ◽  
Antonio Palucci ◽  
Eleonora Aruffo ◽  
Alessandro Rufoloni ◽  
Antonia Lai
Keyword(s):  
Raman Spectroscopy ◽  
Bacillus Thuringiensis ◽  
Principal Component Regression ◽  
Principal Component ◽  
Surface Enhanced Raman Spectroscopy ◽  
Water Evaporation ◽  
Least Squares Regression ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Using Data

In this work, the results on the detection and identification of Bacillus thuringiensis (Bt) cells by using surface-enhanced Raman spectroscopy (SERS) are presented. Bt has been chosen as a harmless surrogate of the pathogen Bacillus anthracis (Ba) responsible for the deadly Anthrax disease, because of their genetic similarities. Drops of 200 μL of Bt suspensions, with concentrations 102 CFU/mL, 104 CFU/mL, 106 CFU/mL, were deposited on a SERS chip and sampled after water evaporation. To minimize the contribution to the SERS data given by naturally occurring interferents present in a real scenario, the SERS chip was functionalized with specific phage receptors BtCS33, that bind Bt (or Ba) cells to the SERS surface and allow to rinse the chip removing unwanted contaminants. Different chemometric approaches were applied to the SERS data to classify spectra from Bt-contaminated and uncontaminated areas of the chip: Principal Component Regression (PCR), Partial Least Squares Regression (PLSR) and Data Driven Soft Independent Modeling of Class Analogy (DD-SIMCA). The first two was tested and trained by using data from both contaminated and un-contaminated chips, the last was trained by using data from un-contaminated chips only and tested with all the available data. All of them were able to correctly classify the SERS spectra with great accuracy, the last being suitable for an automated recognition procedure.

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