Mass Spectrometer Hazardous Substance Monitoring
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Solution Overview
Problem
Current methods for monitoring hazardous substances in water samples are inefficient, often leading to delayed detection or omission, especially in environmental water, due to the complexity of samples and the difficulty in frequent testing, which can result in missed detections or late countermeasures.
Innovation Solution
A specific substance monitoring system utilizing a mass spectrometer capable of MSn analysis, including a sample collector, mass spectrometry controller, judgment section, abnormal peak locator, MSn analysis controller, and substance identifier, which automates the sampling and analysis process, uses AI for image recognition to quickly identify hazardous substances by comparing mass spectra to a database and performing MS2 and MS3 analyses for accurate identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional LC or GC analysis is used to separate compounds in environmental water, then some separation is achieved, but hazardous substances cannot be completely separated from other compounds and detection is delayed
Solution Approach 1:
The mass spectrum is segmented into multiple stages: first-stage mass spectrum for initial screening, second-stage mass spectrum for detailed analysis of abnormal peaks. This segmentation allows rapid identification of hazardous substances by focusing analysis only on suspicious peaks rather than analyzing all peaks comprehensively, thereby improving detection accuracy while reducing detection time.
Solution Approach 2:
The system transitions from two-dimensional analysis (retention time and mass-to-charge ratio) to three-dimensional analysis by incorporating peak intensity comparison with learned normal spectra. This additional dimension enables more precise identification of hazardous substances by detecting deviations in peak intensities that indicate contamination, even when retention times and mass spectra alone are insufficient for definitive identification.
2Measurement precision
If manual peak location and analysis is performed by operators, then detailed examination is possible, but the task is extremely cumbersome and may cause overlooking of hazardous substances
Solution Approach 1:
The system performs self-service by automatically learning normal mass spectrum patterns from historical data and autonomously identifying abnormal peaks that indicate hazardous substance contamination. The automated peak location and analysis functions eliminate the need for manual operator intervention in examining mass spectra, thereby maintaining high detection accuracy while dramatically reducing operator burden and the risk of human error.
Solution Approach 2:
The system incorporates feedback mechanisms where mass spectra from analyzed samples are used to update and refine the learned normal spectrum database. This continuous feedback loop enables the system to adapt to varying environmental conditions and improve its ability to detect hazardous substances over time, maintaining high detection accuracy without requiring manual recalibration or operator expertise.
3Speed
If frequent sampling and analysis is conducted to detect sudden hazardous substance contamination, then detection speed is improved, but the complexity and burden of manual operation increases
Solution Approach 1:
The system performs self-service by automatically executing the complete analysis workflow including sample intake, mass spectrum acquisition, abnormal peak detection, and hazardous substance identification. This automation enables frequent sampling and analysis without proportionally increasing operational complexity, as the system autonomously manages all analytical steps without requiring manual intervention for each sample.
Solution Approach 2:
The system performs preliminary actions by pre-learning normal mass spectrum patterns from historical data before actual monitoring begins. This preliminary preparation enables rapid comparison and identification of abnormal peaks during frequent sampling, allowing the system to maintain high detection speed while minimizing the complexity of real-time analysis operations.
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
This system enables frequent and accurate detection of hazardous substances in water samples without overburdening operators, allowing for prompt alerts and countermeasures, such as discontinuing water supply, by automating the sampling and analysis process and using advanced mass spectrometry techniques.
Implementation Method 1
a mass spectrometry execution controller for performing a mass spectrometric analysis by the mass spectrometer for the sample collected by the sample collector, to acquire a mass spectrum for the sample
Implementation Method 2
an MSn analysis execution controller for performing an MSn analysis by the mass spectrometer for the sample collected with the sample collector
Data Source
AI summary
A sample introduction unit 2 regularly collects a sample from a sample passage 1. A measurement unit 3 performs an LC/MS analysis for the collected sample. A spectrum matching judgment section 42 performs image recognition referring to mass spectra in a normal condition accumulated in a normal spectrum database 44, to determine whether a measured mass spectrum is in a normal condition. If the mass spectrum is non-normal, an abnormal peak locator 45 locates a peak which should not be detected in the normal condition, and an MSn analysis with the located peak selected as the target is performed in the measurement unit 3 under an MSn analysis execution commander 46. An identification processor 47 performs substance identification by a library search based on an acquired MSn spectrum. Upon successful identification, an alert commander 49 issues an alert. Thus, the system can automatically monitor hazardous substances with high accuracy.