Mass Spectral Composition Estimation Under Ambient Ionization
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Solution Overview
Problem
Existing methods for inferring component composition in a sample face challenges due to the loss of information during dimension reduction and inconsistencies in ionization efficiency, making quantitative analysis difficult, especially with ambient desorption ionization methods.
Innovation Solution
A method involving non-negative matrix factorization (NMF) of mass spectra from thermal desorption and pyrolysis, combined with canonical correlation analysis to correct intensity distribution matrices, allowing for accurate inference of component ratios using a K-1 dimensional simplex and Euclidean distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HPLC-MS/MS method is used for component identification and quantification, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts only the essential spectral features (absorption peaks and their ratios) needed for component identification, separating these critical measurements from the complex HPLC-MS/MS system. This allows component analysis using simpler UV-Vis spectroscopy while maintaining identification accuracy through selective feature extraction and ratio calculation methods.
Solution Approach 2:
The patent creates a spectral library that stores characteristic absorption patterns of reference compounds. Instead of requiring complex instrumental analysis for each sample, the system copies and compares spectral fingerprints against this library, enabling accurate component identification through pattern matching rather than complex chemical analysis.
2Measurement precision
If HPLC-MS/MS method is used for component identification and quantification, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements automatic component identification and quantification through computer-based spectral analysis. The system automatically compares sample spectra against the reference library, calculates absorption ratios, and identifies components without requiring manual interpretation or complex operational procedures. This self-service approach simplifies operation while maintaining measurement precision.
3Device complexity
If conventional methods are used for component analysis, then device complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent replaces complex mechanical/chemical separation systems (HPLC) with optical measurement systems (UV-Vis spectroscopy) combined with computer-based spectral analysis. This substitution maintains component identification capability through absorption spectrum comparison while eliminating the need for complex separation instrumentation and reducing overall system complexity.
4Reliability
If comprehensive component analysis is performed, then reliability of content ratio estimation is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing a spectral library containing characteristic absorption patterns of reference compounds before actual sample analysis. During sample measurement, the system quickly compares spectra against this pre-prepared library and calculates absorption ratios, enabling rapid component identification and quantification without time-consuming separation procedures.
Solution Approach 2:
The patent focuses on measuring only the critical absorption peaks and their ratios that are sufficient for component identification and content ratio estimation. Rather than performing complete comprehensive analysis of all possible components, the system identifies and measures the essential spectral features needed for reliable estimation, reducing analysis time while maintaining accuracy for the components of interest.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise quantitative analysis of component ratios in unknown mixtures by correcting for noise and ionization inconsistencies, even without calibration samples, through sequential ionization and data matrix processing.
Implementation Method 1
a UV detector (16) to measure an absorption spectrum of the sample
Data Source
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AI summary
A method of the present invention is a method of inferring a content ratio of a component in a sample containing a component selected from K types, including: heating a sample set, ionizing resultant gas components sequentially, and observing mass spectra continuously; acquiring two-dimensional mass spectra of the respective samples from the mass spectra, and merging two or more of these spectra to acquire a data matrix; performing non-negative matrix factorization on the data matrix; correcting an intensity distribution matrix through analysis on canonical correlation between a base spectrum matrix and the data matrix; acquiring a feature vector from a corrected intensity distribution matrix and expressing the sample in vector space; defining a K-1 dimensional simplex and determining an end member; and inferring a content ratio of the component in the sample on the basis of the end member and the feature vector. It is possible to infer the composition of a component in an unknown mixture even from a mass spectrum acquired under an ambient condition.