Analytical Instrument Documents

Currently, JASON SMILEQ supports the generation of two types of analytical reports based on quantitative analysis results. These reports offer comprehensive insights into the interpretation of quantitative data. This application note focuses on the impact of standard sample uncertainty, a key factor, and presents the results of a more detailed analysis of uncertainty factors conducted using the findings obtained in Part 1 and Part 2.

Currently, JASON SMILEQ supports the generation of two types of analytical reports based on quantitative analysis results. These reports offer comprehensive insights into the interpretation of quantitative data. This application note covers the following: Building on the findings from Part 1. Evaluation of Uncertainty Factors, it expands into variance analysis to provide a more detailed examination of uncertainty factors and their contributions. Furthermore, Part 3 leverages the insights from both Part 1 and Part 2 to present a deeper analysis of uncertainty factors.

Currently, JASON SMILEQ supports the generation of two types of analytical reports based on quantitative analysis results. These reports offer comprehensive insights into the interpretation of quantitative data. As part of the background, this application note provides an overview of the factors contributing to uncertainty and their significance in quantitative NMR analysis. The main focus lies in presenting an overview of SMILEQ reports and offering an in-depth explanation of the 'Uncertainty Report.' Parts 2 and 3 delve deeper into the findings presented in the Uncertainty Report, transitioning into variance analysis to examine uncertainties arising from factors not covered in the report. Additionally, these sections showcase examples illustrating the application of variance analysis and the evaluation of uncertainty factors.

Fatty acid methyl esters (FAMEs) are crucial for determining the fat content in food. Being environmentally friendly, they are also increasingly used as bio-diesel fuels. Many of the FAMEs are unsaturated with double bonds in the alkyl chains. As the number of double bonds increases (more unsaturation), the EI measurements tend to lack molecular ions. In this work, we measured a standard sample containing multiple FAMEs using EI and FI to detect their molecular ions. The resulting data was further examined by using msFineAnalysis to produce an integrated report for these compounds in which the library database search was combined with the molecular ion exact mass analysis to produce a qualitative identification of these compounds.

Electron ionization (EI) is a hard ionization method that is commonly used with gas chromatography mass spectrometry (GC-MS). The mass spectral fragmentation patterns produced by EI are used for library database searches to identify compounds. Conversely, soft ionization methods like field ionization (FI) tend to produce clear molecular ions with minimal fragmentation. When high-resolution MS is used with these ionization techniques, the accurate masses for the fragment ions produced by EI and the molecular ions produced by soft ionization provide an additional dimension of information for the analytes. Combining the exact mass information with the results of conventional library search can enhance the accuracy of identification compared to the use of library search alone.  In this work, we introduce the msFineAnalysis software and use it to automatically combine data acquired by GC/EI and GC/soft ionization for the qualitative analysis of coffee headspace.

In 2018, msFineAnalysis Ver.1 software was released in which data acquired by EI, soft ionization, and accurate mass measurements were automatically integrated to generate a qualitative report for samples measured by these techniques with GC-MS. Recently, msFineAnalysis Ver.2 was introduced as an enhanced version with additional features. In this work, we will describe the changes in Ver.2, which now includes chromatographic deconvolution, and present applications using the new features.

In 2018, we announced the msFineAnalysis software which was designed to automatically integrate two types of data acquired by EI and soft ionization. Recently, we developed msFineAnalysis Version 2, an enhanced version with additional features. msFineAnalysis Version 2 incorporates two new features: Chromatographic Deconvolution and Group Analysis. In this work, we use the group analysis capabilities of the software to evaluate the pyrolysis GC-MS results for a vinyl acetate resin.