NMR Spectrum Alignment Using Reference Convolution Filters
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Solution Overview
Problem
Existing NMR systems struggle to align measurements across different NMR units due to variations in resolution, leading to inaccuracies and the introduction of significant errors through non-linear transformations.
Innovation Solution
A method involving filters based on NMR spectrum line shapes and convolution processes is applied to align NMR spectrums, followed by a machine learning model to generate consistent results across NMR units, while preserving integral values and updating filters as needed to maintain accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-linear transformations are used to transform low resolution NMR spectrums to higher resolution, then resolution is improved, but significant errors are introduced that prevent accurate alignment
Solution Approach 1:
The patent introduces an intermediary reference spectrum (from a known sample) that mediates the transformation between different NMR units' spectra. Instead of directly transforming one spectrum to another using non-linear methods, each spectrum is transformed relative to the reference spectrum through convolution with line shape functions, preserving accuracy while achieving alignment.
Solution Approach 2:
The patent changes the transformation approach from non-linear to linear convolution operations. By using convolution with line shape parameters (width, shape) instead of non-linear transformations, the system achieves resolution matching without introducing significant errors, thus maintaining both resolution improvement and alignment accuracy.
2Measurement precision
If different filters are used for each NMR unit to account for resolution differences, then alignment accuracy is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal reference spectrum that serves all NMR units in the network. This single reference spectrum enables all units to be aligned to a common standard, eliminating the need for complex pairwise filter management between units. The reference spectrum acts as a universal mediator that simplifies the system architecture while maintaining alignment accuracy.
Solution Approach 2:
The patent performs preliminary determination of line shape parameters and creation of the reference spectrum before actual NMR measurements. By pre-calculating the convolution filters based on reference measurements, the system avoids complex real-time filter determination during operation, reducing operational complexity while maintaining accuracy.
3Productivity
If a unified machine learning model is applied across all NMR units, then productivity and resource efficiency are improved, but adaptability to unit-specific variations decreases
Solution Approach 1:
The patent applies local quality adjustments by using unit-specific line shape parameters (convolution filters) derived from each NMR unit's characteristics. While the machine learning model is unified and applied globally, the preprocessing step incorporates local unit-specific properties through convolution with individually determined line shape functions, thus maintaining both efficiency and adaptability.
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 alignment of NMR spectrums, improves accuracy, reduces computational and memory requirements, and ensures reliable results by using a unified model across different NMR units, adapting to changes in resolution.
Implementation Method 1
Nuclear magnetic resonance (NMR) is a physical phenomenon in which nuclei in a strong constant magnetic field are perturbed by a weak oscillating magnetic field (in the near field) and respond by producing an electromagnetic signal with a frequency characteristic of the magnetic field at the nucleus
Data Source
AI summary
An NMR device that includes (i) a first fluid conduit that includes a measurement region and is configured to convey fluid, (ii) an NMR measurement unit that is configured to perform an NMR measurement of the fluid within the measurement region; wherein the NMR measurement unit comprises a permanent magnet; and (iii) a temperature control unit that is configured to thermally shield the permanent magnet, during the NMR measurement, from a temperature of the fluid within measurement region.