A New Look at Direct Compound Analysis Using Pyrolysis Mass Spectrometry

1983 ◽  
Vol 56 (5) ◽  
pp. 1031-1044 ◽  
Author(s):  
Jerry B. Pausch ◽  
Robert P. Lattimer ◽  
Henk L. C. Meuzklaar
Keyword(s):  
Mass Spectrometry ◽  
Mass Range ◽  
Molecular Ions ◽  
Volatile Components ◽  
Pyrolysis Mass Spectrometry ◽  
Organic Additives ◽  
Single Experiment ◽  
Pattern Recognition Techniques ◽  
Temperature Programmed ◽  
Future Work

Abstract For direct compound analysis, pyrolysis mass spectrometry offers renewed hope that the time-consuming and costly separations currently required can be bypassed, at least in part. Polymer blends and copolymers are readily identified along with certain additives. The ability to achieve this information quickly from a single experiment is a valuable improvement. However, more work needs to be done to identify curatives, oils, and higher molecular weight rubber chemicals in compounds. For example, the mass range scanned needs to be expanded to detect higher molecular ions. Temperature-programmed Py-MS may prove useful in separating the more volatile components (nonpolymeric oils and organic additives) for easier detection. Future work will also assess the quantitative potential of the technique. The success with experiments on CPVC materials using pattern recognition techniques opens up a new dimension for compound analysis. Besides being able to determine composition, selected information about reaction mechanisms, morphology, physical properties, or other important parameters may now be possible.

Identification of Rubber Additives by Field Desorption and Fast Atom Bombardment Mass Spectroscopy

1984 ◽  
Vol 57 (5) ◽  
pp. 1013-1022 ◽  
Author(s):  
Robert P. Lattimer ◽  
Robert E. Harris ◽  
Doyle B. Ross ◽  
Hugh E. Diem
Keyword(s):  
Molecular Weight ◽  
Mass Range ◽  
Molecular Ions ◽  
Organic Additives ◽  
Compound Identification ◽  
Mass Spectral ◽  
Rubber Compounds ◽  
General Answer ◽  
Background Ions ◽  
Normal Background

Abstract From the results presented here, it is clear that FD-MS and FAB-MS are very effective analytical methods for the identification of organic additives in extracts from rubber compounds. In the examples above, the molecular weight information provided by FD and FAB provided a nice complement to the IR data. In cases where IR could give only a general answer (i.e., a compound class), the mass spectral data provided a very specific compound identification. It is encouraging that all the samples examined gave useful spectra by both FD and FAB analysis. In most cases, the same information was obtained by both techniques. Certain compounds, however, were observed by FD but not by FAB (wax, oil, isocyanurate antioxidant). While FD provided only molecular weight information, FAB also provided fragmentation to aid in the confirmation of component assignments. Both the FD and FAB mass spectra were fairly complex for most of the extracts, but for different reasons. In FD, oil and wax oligomers gave many molecular ions over a wide mass range. FAB spectra, on the other hand, were somewhat cluttered due to the normal background ions produced by the sputtering process. With both techniques, however, the various components in some fairly complex mixtures were readily identified.

Use of Pyrolysis Mass Spectrometry with Supervised Learning for the Assessment of the Adulteration of Milk of Different Species

1997 ◽  
Vol 51 (8) ◽  
pp. 1144-1153 ◽  
Author(s):  
Royston Goodacre
Keyword(s):  
Mass Spectrometry ◽  
Supervised Learning ◽  
Bovine Milk ◽  
Back Propagation ◽  
Mass Range ◽  
Fat Content ◽  
Least Squares Regression ◽  
Back Propagation Algorithm ◽  
Pyrolysis Mass Spectrometry ◽  
Calibration Models

Binary mixtures of 0–20% cows' milk with ewes' milk, 0–20% cows' milk with goats' milk, and 0–5% cows' milk with goats' milk were subjected to pyrolysis mass spectrometry (PyMS). For analysis of the pyrolysis mass spectra so as to determine the percentage adulteration of either caprine or ovine milk with bovine milk, partial least-squares regression (PLS), principal components regression (PCR) and fully interconnected feed-forward artificial neural networks (ANNs) were studied. In the latter case, the weights were modified by using the standard back-propagation algorithm, and the nodes used a sigmoidal squashing function. It was found that each of the methods could be used to provide calibration models which gave excellent predictions for the percentage adulteration with cows' milk to <1% for samples, with an accuracy of ±0.5%, on which they had not been trained. Scaling the individual nodes on the input layer of ANNs significantly decreased the time taken for the ANNs to learn, compared with scaling across the whole mass range; however in one case this approach resulted in poor generalization for the estimates of percentage cows' milk in ewes' milk. To assess whether the calibration models had learned the differences between the milk species or the differences due to the different fat content of in each of the milk types, we also analyzed pure milk samples varying in fat content by PyMS. Cluster analysis showed unequivocally that the major variation between the different milk species was not due to variable fat content. Since any biological material can be pyrolyzed in this way, the combination of PyMS with supervised learning constitutes a rapid, powerful, and novel approach to the quantitative assessment of food adulteration generally.

Identification of Organic Components in Uncured Rubber Compounds Using Mass Spectrometry

1988 ◽  
Vol 61 (4) ◽  
pp. 639-657 ◽  
Author(s):  
R. P. Lattimer ◽  
R. E. Harris ◽  
C. K. Rhee ◽  
H-R. Schulten
Keyword(s):  
Mass Spectrometry ◽  
Organic Additive ◽  
Molecular Ions ◽  
Organic Additives ◽  
Additional Information ◽  
Filled Rubber ◽  
Rubber Compounds ◽  
Surface Desorption ◽  
Direct Thermal Desorption ◽  
Ionization Methods

Abstract Three carbon-black-filled rubber compounds of known composition were analyzed by mass spectrometry. Direct thermal desorption was used with three different methods of ionization (EI, CI, FI). In addition, the three rubbers were examined by FAB-MS (without liquid matrix) as a means for surface desorption/ionization. Extracts of the rubbers were also examined using two different solvents (acetone and acetonitrile). Each extract was examined directly by five methods of ionization (EI, CI, FI, FD, FAB). Of the various vaporization/ionization methods, it appears that FI/FD is the most efficient for identifying typical organic additives in rubber stocks. The analysis can be carried out using either the untreated rubber (FI mode) or else a solvent extract (FD mode). Molecular ions are dominant, which facilitates the characterization of the complex organic additive mixtures that are present in typical compounded rubbers. For samples in which the identity of FD/FI molecular ions is unclear, further analysis using other methods (EI, CI, FAB, MS/MS, GC/MS, LC/MS, high resolution) can be carried out to gain additional information. We conclude that FD and FI yield the most useful information in the shortest period of time. The main difference between the results of this study and those of the volcanizate study is with respect to the curatives. Intact accelerator molecules could readily be observed in the spectra from the uncured stocks, while only accelerator fragments could be observed from the vulcanizates.

Tandem Mass Spectrometry (MS/MS) for Analysis of Organic Additives in an Uncured Rubber Compound

1990 ◽  
Vol 63 (2) ◽  
pp. 298-307 ◽  
Author(s):  
R. P. Lattimer ◽  
H. Muenster ◽  
H. Budzikiewicz
Keyword(s):  
Mass Spectrometry ◽  
Direct Analysis ◽  
Molecular Ions ◽  
The Other ◽  
Ion Current ◽  
Diagnostic Tools ◽  
Ion Currents ◽  
Rubber Compound ◽  
Organic Additives ◽  
Other Hand

Abstract In this study, we examined the feasibility of obtaining MS/MS data for organic additives in an uncured rubber compound using several different ionization methods. EI-MS/MS worked well for those additives that gave intense molecular ions (M+·) via this mode of ionization. CI-MS/MS also worked quite well for most additives; the CI MH+ ion currents were generally quite intense and stable over a long period of time. Although fragmentation patterns for MH+ ions are different from those obtained from M+· ions, the fragments are still good diagnostic tools for identifying the original molecule. On the other hand, the FI- and FD-MS/MS analyses of these rubber samples were generally not very satisfactory. This was due to the fact that FI/FD ion currents were too weak and unstable to give daughter-ion spectra with good S/N. It may be concluded that the best way to detect and identify typical organic additives in a compounded rubber is to use a combination of EI- and CI-MS/MS. In this study, intact accelerators were successfully analyzed by MS/MS. The two accelerators in this particular rubber (OBTS and DPG) could be confirmed quite readily by daughter-ion analysis of their intense MH+ ions (CI-MS/MS). Daughter-ion analyses of M+· obtained by either EI, FI or FD modes were not very successful, however. In EI, the difficulty is that molecular ions are quite weak (or even absent) for typical rubber curatives. In FI and FD, on the other hand, a very large proportion of the ion current for accelerators resides in the molecular ion. The difficulty here is that the total ion current produced by FI or FD is rather low. The MS/MS approach has proven to be very useful for direct analysis of organic additives in rubber compounds. The principal advantage in using MS/MS is that more information is available from mixtures than can be obtained by direct analysis using conventional mass spectral methods. The MS/MS technique is also rapid experimentally compared to other techniques for mixture analysis such as GC/MS, LC/MS, or high resolution (AC-MS). Finally, since MS/MS involves two stages of mass analysis, it leads to a great reduction in the chemical noise associated with single-stage mass spectrometry. This leads to the facile confirmation of the presence (or absence) of specific components in a complex mixture.

Investigation of b-cyclodextrin peroxides’ thermal degradation by pyrolysis mass spectrometry

2016 ◽  
Vol 38 (4) ◽  
pp. 302-306
Author(s):  
V.V. Boyko ◽  
◽  
O.A. Radchenko ◽  
S.V. Riabov ◽  
S.I. Sinelnikov ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Thermal Degradation ◽  
Pyrolysis Mass Spectrometry

Investigation of titanium dioxide modified by the b-cyclodextrin-containing polymers applying pyrolysis mass spectrometry

2015 ◽  
Vol 37 (1) ◽  
pp. 54-59
Author(s):  
O.A. Opanasenko ◽  
◽  
S.V. Riabov ◽  
S.I. Sinelnikov ◽  
V.V. Boyko ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Titanium Dioxide ◽  
Pyrolysis Mass Spectrometry
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