Mass Spectrum Index Imaging for Polymer Distribution Analysis
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Solution Overview
Problem
Current methods fail to provide a comprehensive understanding of polymer distribution from a single mass image, and even when multiple mass images are analyzed, it is difficult to grasp the overall distribution of polymers.
Innovation Solution
An apparatus and method that compute indices representing characteristics of mass spectra across pixels, generating index distribution images to facilitate a holistic understanding of mass spectra, including number average molecular weight, weight average molecular weight, polydispersity, and other indices, allowing for more accurate evaluation and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single mass image is generated to represent polymer distribution, then the imaging process is simple and fast, but it cannot provide comprehensive understanding of overall polymer distribution
Solution Approach 1:
The patent segments the mass spectrum information by generating multiple mass images, each corresponding to a specific mass-to-charge ratio range. Instead of displaying a single comprehensive image that loses detail, the system divides the information into multiple targeted images that can be individually analyzed to understand overall polymer distribution characteristics.
Solution Approach 2:
The patent adds a new dimension to the analysis by introducing mass-to-charge ratio as an additional parameter. Rather than relying solely on spatial distribution in a single image, the system creates a multi-dimensional view where each mass image represents a specific mass range, enabling comprehensive understanding through dimensional expansion.
2Loss of information
If multiple mass images are generated to show different mass ranges, then comprehensive distribution information is obtained, but the complexity of analysis increases
Solution Approach 1:
The patent creates a universal analysis framework where the same processing and display methods can be applied to multiple mass images. Each mass image follows the same generation and interpretation protocol, allowing analysts to use a consistent approach across different mass ranges rather than learning multiple specialized techniques.
Solution Approach 2:
The patent applies local quality by optimizing each mass image for its specific mass range. Each image is tailored to highlight the characteristics of polymers within its designated mass-to-charge ratio range, providing localized detailed information that contributes to the overall understanding without requiring complex integrated analysis.
3Measurement precision
If mass spectra with different polymerization degrees are analyzed separately, then specific polymer characteristics are identified, but the overall polymer distribution becomes difficult to understand
Solution Approach 1:
The patent merges multiple separate mass spectrum analyses into a coordinated set of mass images. Each image maintains the precision needed for specific polymer characterization while being part of an integrated visual framework that enables easy comparison and understanding of overall distribution patterns across different polymerization degrees.
Data Source
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AI summary
An ion intensity array is computed for each mass spectrum forming a mass spectrum array (42). For each ion intensity array, a plurality of indices a ∼ e showing a plurality of characteristics of the mass spectrum as a whole are computed. Based on the plurality of indices, a plurality of index distribution images (46a ∼ 46e) are computed. A plurality of index distribution images (46a ∼ 46e) may alternatively be computed based on a mass image array generated from the mass spectrum array. The indices may comprise a number average molecular weight, a weight average molecular weight, a molecular-weight dispersity, a number average degree of polymerization, a weight average degree of polymerization, or a total ion amount.