Comprehensive Two-dimensional Gas Chromatography Time-of-flight Mass Spectrometry with Chemometric Analysis PDF Download
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Author: Amanda Elizabeth Moses Sinha
Publisher:
ISBN:
Category : Gas chromatography
Languages : en
Pages : 410
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Book Description
Author: Amanda Elizabeth Moses Sinha
Publisher:
ISBN:
Category : Gas chromatography
Languages : en
Pages : 410
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Book Description
Author: Brooke C. Reaser
Publisher:
ISBN:
Category :
Languages : en
Pages : 172
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Book Description
Gas chromatography is a powerful separation technique that alone, and when coupled with mass spectrometric detection, can provide detailed information regarding the chemical composition of complex mixtures. Advanced chemometric algorithms are often applied to the data generated from these gas chromatographic separations in order to glean additional meaningful information from large and complex data sets. This dissertation presents several research investigations conducted on the development, optimization, application and study of several chemometric algorithms applied to one- and two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (TOFMS). The two-dimensional mass cluster method and principal component analysis (PCA) were applied to a non-targeted investigation of the stable-isotope incorporation of metabolites present in the metabolome of the methylotrophic bacteria Methylobacterium extorquens AM1 using gas chromatography time-of-flight mass spectrometry (GC-TOFMS). The area under the curve (AUC) of receiver operating characteristic (ROC) curves were used as quantitative metrics for the optimization of the tile-based Fisher ratio method using diesel fuel spiked with native and non-native analytes using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC – TOFMS). This optimized algorithm was then applied to a process analytical chemistry (PAC) investigation into the source of catalyst yield reduction in an industrial polymerization plant. Finally, a GC-TOFMS simulation-based study determined the chemometric limit of resolution for deconvoluting analytes using multivariate curve resolution alternating least squares (MCR-ALS) and compared the results to expected theory surrounding the probability of peak overlap.
Author: Maximilian Karl Jennerwein
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author:
Publisher: Academic Press
ISBN: 0128137460
Category : Science
Languages : en
Pages : 332
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Book Description
Basic Multidimensional Gas Chromatography is aimed at the next generation of multidimensional gas chromatography users who will require basic training in the fundamentals of both GC and GCxGC. This book fills the current need for an inexpensive, straightforward guidebook to get new users started. It will help new users determine when to add or purchase a multidimensional system and teach them to optimize and maximize the capability of each system. Readers will also learn to select specific modes for each portion of a multidimensional analysis. This ideal resource is a concise, hard-hitting text that provides the facts needed to get users up and running. Provides a comprehensive and fundamental introduction to multidimensional gas chromatography Assists readers in determining when to add or purchase a multidimensional system Explains how a given system can be used to its maximum capacity and how users should choose specific modes for different portions of multidimensional analysis
Author: Lourdes Ramos
Publisher: Elsevier
ISBN: 008093269X
Category : Science
Languages : en
Pages : 324
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Book Description
The book reviews the basic concepts and highlights the most relevant advances and developments that have taken place in the field of comprehensive two dimensional gas chromatography (GC x GC) since its introduction in 1991. The several instrumental and technical approaches assayed and developed during these seventeen years and that have contributed to the development of this powerful separation technique and to its increasing application in many areas is explained and comprehensively illustrated through a number of chapters devoted these specific topics. More specialized aspects of the technique, including theoretical aspects, modelization of the chromatographic process, software developments, and alternative couplings is also covered. Finally, special attention is paid to data treatment, for both qualitative and quantitative analysis. This book will be a practical resource that will explain from basic to specialized concepts of GC x GC and will show the current state-of-the-art and discuss future trends of this technique. - Outlines basic concepts and principles of GCxGC technique for non-specialists to apply the technique to their research - Provides detailed descriptions of recent technical advances and serves as an instructional guide in latest applications in GCxGC - Sets the scene for possible future development and alternative new applications of technique
Author: Sarah Elizabeth Prebihalo
Publisher:
ISBN:
Category :
Languages : en
Pages : 151
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Book Description
Comprehensive two-dimensional gas chromatography (GCxGC) coupled with time-of-flight mass spectrometry (TOFMS) is a powerful analytical technique capable of separating complex mixtures, providing valuable information about the chemical composition of samples. However, the inherent data density associated with three-dimensional data provides a unique challenge to analytical chemists. As a result, significant effort has been invested in utilizing advanced chemometrics to glean meaningful information about samples from large and complex data sets. Herein, this dissertation introduces several investigations conducted on optimizing separation conditions to be amenable to chemometric deconvolution algorithms as well as the development, study, and application of advanced chemometric techniques applied to GCxGC-TOFMS data. To begin, the metric trilinear deviation ratio (TDR) is utilized to study the impact of experimental parameters such as column selection and modulation period, PM, on the quantitative accuracy of parallel factor analysis (PARAFAC) deconvolution. TDR scales with increasing change in second dimension retention time, delta2tR, associated with pseudo-isothermal conditions on the second dimension, 2D, and quantitative accuracy decreases as TDR increases. Two column sets were utilized with varying film thickness on the first column, 1D, and each column set was studied using two PM for a total of 4 experiments. It was reported that using 1D columns with larger film thicknesses allows the analyst to employ a shorter PM, in turn lowering the delta2tR, leading to higher quantitative accuracy. Many GCxGC-TOFMS studies relate to identifying class distinguishing analytes and can be tedious when performed manually. Fortunately, the use of discovery-based chemometric tools such as principal component analysis (PCA) and Fisher ratio (F-ratio) analysis has increased in popularity as less time-intensive and automated techniques for untargeted analyses. To begin, this dissertation will investigate mass channel purity obtained via the tile-based F-ratio algorithm using diesel fuel spiked with non-native analytes using GCxGC-TOFMS. The F-ratio algorithm, considered a supervised discovery technique because class membership is known a priori, was first used to "discover" the spiked non-native analytes. Then, using a novel signal ratio (S-ratio) algorithm, the mass channel selectivity information output by the F-ratio method was studied using three statistical metrics: null distribution analysis, p-value, and lack-of-fit (LOF). The result of this investigation revealed that a mass channel has a high likelihood of being pure when its p-value and LOF are sufficiently low. Finally, F-ratio analysis was applied to a dataset including patients with an anterior cruciate ligament (ACL) injury to discover potential biomarkers of post-traumatic osteoarthritis (PTOA) post-injury. Standard F-ratios are calculated by the between class variance divided by the sum of the within-class variance, scaling up as the between class variance increases and the within-class variance remains sufficiently small. However, many biological studies involve significant biological variance (~30%) that may not be associated with disease state or injury severity, etc. Herein, the standard tile-based F-ratio algorithm was modified to use only the within-class variance associated with control samples. It was expected that the control class contained less within-class variance relative to the patient class, due to the expectation that some patient samples would be associated with increased severity of injury or the presence of coexisting conditions. Hit lists (metabolites discovered via F-ratio) from standard F-ratio and control-normalized F-ratio were studied and directly compared to establish a comprehensive metabolome of potential biomarkers for PTOA development post ACL injury. Reported in this dissertation is a discussion on the complementary nature of standard and control-normalized F-ratio, followed by demonstration of class distinguishing metabolites via PCA.
Author: Brian David Fitz
Publisher:
ISBN:
Category :
Languages : en
Pages : 164
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Book Description
Techniques to substantially increase peak capacity (number of peaks per separation window) and peak capacity production (number of peaks produced per unit time) for one and two-dimensional gas chromatography are demonstrated. First, instrumental advances related to sample introduction and column heating rate are discussed. Rapid sample introduction to the chromatographic system was achieved with a thermal injection device to deliver ultra-narrow peaks onto the GC column. When compared to standard sample introduction, thermal injection can provide peaks that are ~10 times narrower which gives rise to peak capacities an order of magnitude larger when compared to traditional GC practice. To further increase peak capacity and peak capacity production, a low thermal mass (LTM) GC system operated at a heating rate of 250 °C/min was applied with thermal injection to produce a separation with a peak capacity of ~300 in 1 minute. Additionally, thermal injection was applied to a comprehensive two-dimensional gas chromatographic system coupled to time-of-flight mass spectrometry (GC x GC - TOFMS) to produce a separation with a peak capacity of ~6,000 in 6 minutes, affording a peak capacity production rate of ~1,000 peaks/minute. Second, a novel algorithmic approach for processing GC-TOFMS data is presented which can increase the peak capacity and peak capacity production values even further. The algorithm relies on GC-TOFMS data that is sampled with sufficient data density (> 100 points/peak) to accurately measure analyte peak widths, W, and retention times, tR. Separation visualization is made possible by transforming the data from a signal versus time format to a peak width versus retention time format. This is achieved by measuring the W and tR of each m/z for each analyte in the separation, followed by plotting of the data (W vs. tR) in a two-dimensional format. Plotting the data in this fashion allows for the visualization of pure and interfered m/z of analytes. Coupled with chemometric analysis allows for the deconvolution of poorly-resolved analytes down to a resolution, Rs = 0.03. The peak capacity of a 7 minute GC-TOFMS separation was increased from ~400 to ~10,000 using this technique.
Author: Kelsey Leigh Berrier
Publisher:
ISBN:
Category :
Languages : en
Pages : 223
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Book Description
One- and two-dimensional gas chromatography coupled with mass spectrometry provides an enormous amount of quantitative data describing the chemical composition of complex samples. Besides quantification and identification of analytes, common analysis goals include classifying samples or predicting sample properties based upon the chemical information contained in the chromatographic data. The chemometric modeling techniques used to accomplish these goals often benefit from the removal of redundant or irrelevant chromatographic variables, which is achieved by feature selection. This dissertation presents several research studies detailing advances in and applications of feature selection applied to one- and two-dimensional gas chromatography with mass spectrometric detection. The two-dimensional mass cluster method was evaluated as a peak detection algorithm using simulations of gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS) data under varying sample and separation complexity. An unsupervised feature selection method based on variance thresholding was applied to simulated GC-MS chromatograms and a previously studied yeast metabolome dataset. A successful application of partial least squares (PLS) regression analysis to comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS) for the prediction of bulk physical properties of kerosene-based fuels is included to demonstrate a case where feature selection was not required. Finally, supervised feature selection was implemented on GCxGC-TOFMS data of rocket fuels to aid in the prediction of fuel thermal integrity by PLS.
Author: Eric Stauffer
Publisher: Academic Press
ISBN: 0080556264
Category : Law
Languages : en
Pages : 683
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Book Description
The study of fire debris analysis is vital to the function of all fire investigations, and, as such, Fire Debris Analysis is an essential resource for fire investigators. The present methods of analysis include the use of gas chromatography and gas chromatography-mass spectrometry, techniques which are well established and used by crime laboratories throughout the world. However, despite their universality, this is the first comprehensive resource that addresses their application to fire debris analysis.Fire Debris Analysis covers topics such as the physics and chemistry of fire and liquid fuels, the interpretation of data obtained from fire debris, and the future of the subject. Its cutting-edge material and experienced author team distinguishes this book as a quality reference that should be on the shelves of all crime laboratories. - Serves as a comprehensive guide to the science of fire debris analysis - Presents both basic and advanced concepts in an easily readable, logical sequence - Includes a full-color insert with figures that illustrate key concepts discussed in the text
Author: Christopher E. Freye
Publisher:
ISBN:
Category :
Languages : en
Pages : 320
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Book Description
A combination of four instrumental systems and five chemometric methods are shown to improve the efficiency and resolving power (i.e. peak capacity/ peak capacity production) of multi-dimensional gas chromatography (MDGC) as well as provide straightforward, easily interpretable chemical information. Implementation of a high speed pulse flow valve for two-dimensional gas chromatography (GC × GC) is shown to provide ultra-fast modulation with modulation periods (P[subscript]M) as short as 50 ms. Using a commercially available pulse flow valve, this injection technique performs a combination of vacancy chromatography and frontal analysis, whereby each pulse disturbance in the analyte concentration profile as it exits the first column (1D) results in data that is readily converted into a second separation (2D). A three-step process converts the raw data into a format analogous to a GC × GC separation, incorporating signal differentiation, baseline correction and conversion to a GC × GC chromatogram representation. For a P[subscript]M of 250 ms, the apparent peak width on the 2D, 2W[subscript]b, ranged from 12 to 45 ms producing a 2D peak capacity, 2n[subscript]c, of ~ 10, and the total peak capacity, n[subscript]c,2[subscript]D, was 4300 or a peak capacity production of 650 peaks/min. Next, the use of a high temperature diaphragm valve as a modulator for GC × GC facilitated separation temperatures up to 325 °C. Previous diaphragm valve technology limited use to 175 °C if the valve was mounted in the oven or to 265 °C if the valve was face mounted on the outside of the oven. A 44-component mixture was evaluated and the diaphragm valve created narrow, reproducible peaks on the 2D dimension leading to a peak capacity production of 300 peaks/min and had minimal retention time shifting on the 1D and 2D dimensions. In addition, the high temperature diaphragm valve was shown to increase the detection sensitivity by ~8 times compared to one-dimensional gas chromatography due to zone compression. Furthermore, the high temperature diaphragm valve was proven to be compatible with time-of-flight mass spectrometry (TOFMS). Finally a combination of the high temperature diaphragm valve and pulse flow valve yielded a three-dimensional gas chromatography system (GC3) that had a peak capacity production of 1000 peaks/min which is a ~5 times increase in efficiency compared to other GC3 systems. Investigation of novel chemometric techniques for the analysis of GC × GC is shown to be beneficial in extracting useful chemical information from complicated samples. Kerosene-based rocket fuels were analyzed via a GC × GC – FID system that implemented a high temperature diaphragm valve as a modulator. Using leave-one-out cross validation (LOOCV), the summed GC × GC – FID signal of three compound-class selective 2D regions (alkanes, cycloalkanes, and aromatics) was regressed against previously measured ASTM derived values. Additionally, a more detailed partial least squares (PLS) analysis was performed on compound classes (n-alkanes, iso-alkanes, mono-, di-, and tri-cycloalkanes, and aromatics) as well as the physical properties previously determined by ASTM methods (such as net heat of combustion, hydrogen content, density, kinematic viscosity, sustained boiling temperature and vapor rise temperature). The resulting models had low root mean square errors of cross validation (RMSECV) and had similar outcomes to previously reported results using a GC × GC – TOFMS. Using the information gained from the study, a more extensive study of predicting four physical properties (e.g., viscosity, heat of combustion, hydrogen content, and density) was undertaken using 74 different kerosene-based fuels. Highly reliable PLS models were developed that related chemical composition obtained via GC × GC – TOFMS to fuel properties obtained via ASTM methods. The PLS prediction of the four physical properties (e.g., viscosity, heat of combustion, hydrogen content, and density) had relatively low errors of RMSECV values of 0.0434, 38.1, 0.112, and 0.0037, respectively. Investigation of the linear regression vectors (LRVs) indicate the relationship between the chemical composition and physical properties enabling the chemical compositions of fuels to be altered to meet certain industrial specifications. Using a similar fuel set comprised of 36 kerosene-based fuels, the thermal stability was evaluated using a novel instrument, CRAFTI (Compact Rapid Assessment of Fuel Thermal Integrity). Using a chemometrics-based feature discovery algorithim, the chemical information obtained via GC × GC – TOFMS was correlated to the thermal integrity data. Certain forms of carbon that were deposited within the test article of the CRAFTI instrument were found to strongly correlate with increased backpressure and some of the more prevalent compounds were identified. Next, tile-based Fisher ratio (F-ratio) analysis was applied to tandem ionization time-of-flight mass spectrometry (TI – TOFMS) in order to enhance discovery-based analyses. A hard ionization energy (70 eV) and soft ionization energy (14 eV) were collected concurrently, and the discovery of 12 analytes spiked in diesel fuel was shown to be improved when the two ionization energies were used in tandem resulting in a higher discovery rate while also lowering the number of false positives. Using parallel factor analysis (PARAFAC) the analytes that were “discovered” were deconvoluted in order to obtain their identification via match values. Lastly, the limit of detection (LOD) and limit of quantification (LOQ) were improved by a novel integration method. Signal to noise (S/N) enhancement was theoretically studied using simulations and both the LOD and LOQ can be lowered by a factor of 3. When compared to the two-step, a commonly applied method for quantifying one-dimensional and two-dimensional, the integration method resulted in more accurate and precise measurements at low S/N.
