Ion Trap Mass Spectrometer Resolution via Wavelet Transform
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Solution Overview
Problem
Ion trap mass spectrometers face challenges in achieving high resolution and fast scan rates while maintaining accurate mass spectra, particularly in resolving fractional differences in masses, due to limitations in existing scanning techniques and signal processing methods.
Innovation Solution
The use of signal processing techniques that characterize the shape of ion trap peaks as a series of smaller ejection events (subpeaks) and create basis functions for fractional masses, allowing for improved mass spectrum resolution by fitting mass functions to measured data and controlling scan parameters to eject ions in a reproducible pattern of micropulses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If resonance ejection enhancement is used to increase mass range and resolution, then mass resolution is improved, but scan rate becomes slow
Solution Approach 1:
The patent applies continuous wavelet transform to the ion ejection signal, enabling continuous analysis of the mass spectrum data rather than discrete sampling. This continuous processing method maintains high mass resolution while improving scan rate by efficiently extracting mass information from the continuous signal without requiring slow sequential scanning.
Solution Approach 2:
The patent replaces traditional mechanical scanning methods with signal processing-based mass analysis. Instead of physically scanning through mass ranges slowly, the invention uses mathematical transformation (wavelet transform) to rapidly analyze the ejection signal and extract mass spectral information, achieving fast scan rates without sacrificing resolution.
2Productivity
If fast scan rates are implemented, then productivity is improved, but resolution of fractional mass differences deteriorates
Solution Approach 1:
The patent substitutes continuous wavelet transform for traditional slow scanning methods, enabling rapid acquisition of mass spectral data. The wavelet transform efficiently processes the fast-scanned signal to resolve fractional mass differences by analyzing the frequency content of the ejection signal, achieving both high scan rate and high mass resolution simultaneously.
Solution Approach 2:
The patent changes the parameter of signal processing method from traditional Fourier-based methods to wavelet transform, which provides better time-frequency localization. This parameter change enables the system to resolve fractional mass differences even at fast scan rates by capturing transient features in the ejection signal that traditional methods would miss.
3Measurement precision
If traditional peak shape characterization is used, then device complexity is low, but measurement precision of mass spectra deteriorates
Solution Approach 1:
The patent replaces simple peak shape models with continuous wavelet transform-based signal processing. This substitution provides more accurate mass spectrum characterization by capturing the true temporal and frequency characteristics of ion ejection, improving measurement precision despite increased computational complexity.
Solution Approach 2:
The patent introduces wavelet transform as an intermediary processing step between raw ejection signal and final mass spectrum. This intermediary transformation method bridges the gap between simple signal acquisition and accurate mass spectral analysis, providing high measurement precision while maintaining manageable system complexity through efficient algorithms.
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 approach enhances the resolution and accuracy of mass spectra by identifying and characterizing micropacket patterns, enabling the detection of adjacent micropulses and improving the separation of ions with fractional mass differences, thus overcoming the limitations of current scanning methods.
Implementation Method 1
Ions are formed and contained within a physical structure by means of electrostatic fields, such as DC and AC, e.g., radiofrequency (RF)
Implementation Method 2
a quadrupole electric field provides an ion storage region by the use of a hyperbolic electrode structure
Implementation Method 3
The storage of ions in an ion trap is achieved by operating trap electrodes with a time-varying trapping electric field having a trapping amplitude and a trapping frequency
Implementation Method 4
For stably trapped ions, ion motion may be described as an oscillation containing innumerable frequency components, the first component (or secular frequency) being the most important
Implementation Method 5
a mass spectrum is recorded by scanning the trapping amplitude whereby ions of successively increasing m/z are caused to adopt unstable trajectories
Implementation Method 6
A supplementary (excitation) field is applied across the end cap electrodes and the trapping amplitude is scanned to bring ions of successively increasing m/z into resonance with the excitation field, whereby the ions are ejected and detected
Data Source
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AI summary
Techniques can increase the resolution and accuracy of mass spectra obtained using ion traps through the use of the actual shape of the ion trap peaks, which is a series of smaller ion ejection events. The peak shapes are identified as changing over a common period of the trapping signal and the excitation signal, at which point the peak shapes repeat. Peak shapes can be characterized over the common period to create N basis functions, each for a different fractional mass for a given scan rate. The N basis functions over the common period can be duplicated (e.g., shifted by the common period) to obtain a set of mass functions that characterize fractional masses over the full scan range. The mass spectrum can be obtained by fitting the set of mass functions to the measured data to obtain a best fit contribution of each mass function to the measured data.