GC-TOFMS Application: Comprehensive Analysis + Unknown Component Analysis of Vinyl Acetate Resins Using Pyrolysis GC-MS

  • Summary

MSTips No.243

Characteristic Component Extraction by Multiple Classification PCA and Component Identification by High Resolution MS -

General

Advances in mass spectrometry are enabling analysis of micro samples and unknown components that were not observable before. As the volume of information acquired from mass spectrometry increases, researchers are calling for simple techniques to analyze numerous components observed, and as a result, there is a rise in demand for comprehensive analytical techniques including multiple classification analysis.

In this work, we will introduce a new technique for non-target analysis, which combines comprehensive analysis using high resolution GC-TOFMS and unknown component analysis using soft ionization.

Method

As model samples, 6 commercial vinyl acetate resins (adhesives) were used. A gas chromatography time-of-flight mass spectrometer (GC-TOFMS) was used for measurement. Since emulsion samples including adhesives are difficult to analyze without preliminary treatment, the samples were subjected to pyrolysis.

The resulting data was analyzed by AnalyzePro (SpectralWorks) to compare multiple samples by PCA.

Table1. Mesurement Conditions

Py-GC-TOFMS conditions

System JMS-T200GC (JEOL)
Pyrolysis temp. 600°C
Ionization mode EI+: 70eV, 300μA
FI+: -10kV, 6mA (Carbotec 5μm)
GC column DB-5msUI (Agilent), 15m x 0.25mm, 0.25μm
Oven temp. 50°C (1min)→ 30°C/min→ 330°C (1.7min)
Inlet temperature 300°C
Inlet mode Split 100:1
He flow 1.0mL/min (Constant Flow)
m/z range m/z 35-650
Spectrum recording speed 0.1 sec
Software AnalyzerPro (SpectralWork)

Results

A total of 6 vinyl acetate resin samples were analyzed by pyrolysis GC-EI TOFMS (n=3), and the resulting data was subjected to PCA by AnalyzerPro. The PCA score plot (Figure 1) shows that sample E was clearly separated at the 1st principal component axis and sample B at the 2nd principal component axis, respectively. Components contributing to each principal component were easily detected in the loading plot.

Among the components contributing to the separation at the secondary principal component axis (positive side) , that is, characteristic components of sample B, the component at R.T. 4.55 min was analyzed in detail (data on the right side of Figure 2).

The NIST library search estimated that the component at R.T. 4.55 min was likely to be 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate (molecular weight 286) with a match factor of 813. However, the FI mass spectrum of this component detected a base peak at m/z 217, and as a result, the molecular weight estimated in NIST library search differed significantly from the molecular weight estimated from the results of FI ionization. While the chemical structure of 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate contains an esther group, FI ionization detected no ion that has an m/z equal to that. Esther group containing compounds are generally known to produce protonated molecules by FI ionization. Thus, it is likely that the component at R.T. 4.55 min is not the component estimated in NIST library search but is another component having a similar EI spectrum. Figure 3 shows the mass spectra of the component at R.T. 4.55 min acquired by EI and FI. Figure 4 shows the structural formula of 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate. After examining the EI and FI data in detail, it was estimated that the component at R.T. 4.55 min has the structure shown in Figure 5. None of the major libraries provided by NIST included a component equal to this structure.

PCA is an effective and efficient technique for the comprehensive analysis of GC-TOFMS data. Specifically, for multiple sample comparisons, use of score and loading plots makes it possible to examine the similarities between the samples and the characteristic components of each sample. Also, while the NIST library search is a powerful tool for identifying characteristic components of samples, combining NIST library searches with molecular weight information acquired by soft ionization such as FI makes it possible to identify components with a higher level of accuracy, preventing false identifications.

PCA score plot for Polyvinyl acetate samples.

Figure 1. PCA score plot of polyvinyl acetate samples

PCA loading plot for Polyvinyl acetate samples.

Figure 2. PCA loading plot of polyvinyl acetate samples

Figure 3. EI and FI mass spectra and exact mass analysis results for the unknown component (R.T. 4.55 min) in sample B

EI and FI mass spectra and accurate mass measurement results for the unknown component (R.T. 4.55 min) in the sample B.
Mass Formula Calculated
Mass
Mass
Error
[m Da]
DBE
217.178 C12 H25 O3 217.1798 -1.8 0.5
EI and FI mass spectra and accurate mass measurement results for the unknown component (R.T. 4.55 min) in the sample B.
Mass Formula Calculated
Mass
Mass
Error
[m Da]
DBE
43.0544 C3 H7 43.0542 0.2 0.5
56.0622 C4 H8 56.0621 0.1 1.0
71.0493 C4 H7 O 71.0491 0.2 1.5
83.0858 C6 H11 83.0855 0.3 1.5
89.0596 C4 H9 O2 89.0597 -0.1 0.5
98.1091 C7 H14 98.1090 0.1 1.0
111.1177 C8 H15 111.1168 0.9 1.5
143.1096 C8 H15 O2 143.1067 2.9 1.5
145.1246 C8 H17 O2 145.1223 2.3 0.5
173.1189 C9 H17 O3 173.1172 1.7 1.5
Estimated structure formula for the unknown component (R.T. 4.55 min) in the sample B.

Figure 4. Structural formula of 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate

Structure formula for 2,2,4-Trimethyl-1,3-pentanediol diisobutyrate

Figure 5. Estimated structural formula for the unknown component (R.T. 4.55 min) in sample B

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