Mass Spectrum Generation via Adaptive Frequency Grid Optimization
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Solution Overview
Problem
Current Fourier Transform Mass Spectrometry methods face challenges in accurately resolving close characteristic frequencies, leading to errors in identifying ionic species and estimating their relative abundances due to overlapping peaks and limited frequency resolution.
Innovation Solution
A method that involves generating a second set of complex amplitudes with a finer frequency grid, optimized using an objective function and constraints on phase, to improve the resolution and accuracy of the mass spectrum, allowing for better separation of peaks and precise identification of ionic species.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete Fourier transform is used with standard frequency grid spacing, then the processing is computationally efficient, but the frequency resolution is insufficient leading to errors in identifying closely spaced characteristic frequencies
Solution Approach 1:
The patent changes the frequency grid spacing parameter from the standard uniform spacing (1/T) to a non-uniform spacing that provides finer resolution at frequencies of interest. This allows achieving better frequency resolution without proportionally increasing computational complexity across the entire spectrum.
Solution Approach 2:
The patent segments the frequency spectrum into different regions with different resolution requirements. By applying enhanced frequency sampling only in regions where closely spaced peaks need resolution, rather than uniformly across the entire spectrum, computational complexity is reduced while still achieving the needed measurement precision.
2Measurement precision
If zero-padding is applied to increase frequency sampling density, then the apparent resolution improves, but the actual resolving power does not increase and may introduce artifacts
Solution Approach 1:
The patent replaces the mechanical approach of zero-padding (artificially extending the time domain signal) with a mathematical approach of optimizing the frequency grid spacing and complex amplitude calculation. This substitution provides genuine resolution improvement through proper signal decomposition rather than artificial interpolation.
Solution Approach 2:
The patent employs an iterative optimization process where the frequency grid and complex amplitudes are adjusted based on feedback from the transient signal characteristics. This allows the system to converge on accurate peak positions and intensities without relying on zero-padding artifacts.
3Measurement precision
If the transient duration is increased to improve frequency resolution, then the separation between frequency bins decreases, but the measurement time increases
Solution Approach 1:
The patent changes the frequency grid spacing parameter to achieve finer effective bin separation without extending the transient duration. By using a non-uniform frequency grid with smaller spacing in critical regions, the method achieves better frequency resolution while maintaining the original measurement time.
4Measurement precision
If standard Fourier basis functions are used, then the decomposition is computationally straightforward, but overlapping peaks cannot be adequately resolved
Solution Approach 1:
The patent makes the frequency grid dynamic and adaptive rather than static and uniform. By allowing the frequency spacing to vary based on the spectral content and by iteratively optimizing the complex amplitudes, the decomposition process adapts to resolve overlapping peaks while managing computational 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 frequency resolution, reducing errors in peak identification and abundance estimation, particularly for closely spaced characteristic frequencies, and maintains the intensity integrity of peaks, improving the overall accuracy and fidelity of mass spectrometry results.
Implementation Method 1
ions are detected by an image current S(t) (also termed a continuous transient image current and herein referred to as the 'transient') induced on detection electrodes of the mass analyzer as the oscillating ions pass nearby
Implementation Method 2
The transient processing usually involves discrete Fourier transform (DFT), which decomposes the transient into a number of periodic functions (also termed Fourier basis functions)
Implementation Method 3
The frequency of oscillation of a coherent packet of ions is a function of the mass to charge (m/z) ratio of the ionic species and is referred to as the 'characteristic frequency' of an ionic species
Implementation Method 4
The trapping field can be provided by the combination of an electrostatic field and a magnetostatic field
Implementation Method 5
The trapping field can be provided by the combination of an electrostatic field and a magnetostatic field
Data Source
AI summary
A method of producing a mass spectrum from a time-varying transient signal detected in a mass spectrometer, the method comprising: performing a Fourier transform of the transient signal to produce a first set of complex amplitudes wherein each of the complex amplitudes corresponds to a respective frequency of a first set of frequencies; generating a second set of complex amplitudes, wherein each of the complex amplitudes corresponds to a respective frequency of a second set of frequencies with a minimum spacing less than the inverse of the duration of the transient signal; optimizing the second set of complex amplitudes to produce an improved second set; generating a mass spectrum from at least some of the improved second set of complex amplitudes; wherein optimizing the second set of complex amplitudes to produce an improved second set of complex amplitudes is based on an objective function subject to some phase constraints.