LSPR Spectrometer Peak Wavelength Resolution via Adaptive Regularization

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Solution Overview

Problem

Localized surface plasmon resonance (LSPR) spectrometers face challenges in accurately determining the peak wavelength with high resolution due to noise in the peak wavelength signal, limiting their ability to analyze binding kinetics and chemical parameters effectively.

Innovation Solution

A method involving a mathematical model of the LSPR spectrometer system to estimate a parametric curve representing the absorbance/reflectance spectrum, with adaptive regularization algorithms to optimize parameters and reduce noise, achieving sub-pixel level peak wavelength resolution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional peak wavelength determination methods are used, then the measurement process is simple, but the peak wavelength resolution is coarse and noise in the signal is high

Engineering Contradiction:

Improvepeak wavelength resolutionVSAvoidcomplexity of mathematical modeling and optimization

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by using a mathematical model to estimate a parametric curve representing the absorbance/reflectance spectrum before actual measurement. This pre-established model framework enables subsequent precise parameter optimization to achieve sub-pixel level peak wavelength resolution (less than 5 pm) while systematically reducing noise in the peak wavelength signal.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements parameter changes by optimizing the parameters of the parametric curve through maximum likelihood estimation. This involves adjusting parameters such as peak position, width, and amplitude to maximize the likelihood that the curve represents the actual sensed spectrum, thereby achieving high-resolution peak wavelength determination with reduced noise.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If adaptive regularization algorithms are applied, then noise reduction is achieved, but computational complexity increases

Engineering Contradiction:

Improvenoise reduction in peak wavelength signalVSAvoidcomputational complexity of adaptive regularization

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies feedback through adaptive regularization algorithms that iteratively adjust the parametric curve parameters based on the measured spectrum data. The algorithm uses feedback from the data likelihood to refine parameter estimates and reduce noise, achieving reliable peak wavelength signals while managing computational complexity through efficient optimization strategies.

Inventive Principle:

Principle #23Feedback

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

The method significantly improves peak wavelength resolution to less than 5 pm, enabling more precise analysis of binding kinetics and chemical parameters, surpassing the coarse estimates of traditional methods.

Implementation Method 1

A localized surface plasmon resonance (LSPR) spectrometer is a chemical analysis spectrometer in which ligand protein molecules are immobilized onto nanoparticles such as gold nanoparticles. The molecule to be analyzed, known as the analyte, binds to the ligand, causing a shift in LSPR resonant frequency of the nanoparticle.

Methodology Applied

Scientific EffectLocalized surface plasmon resonance: Resonance

Implementation Method 2

using a mathematical model of the LSPR spectrometer system to estimate a parametric curve representing the absorbance/reflectance spectrum, and adjusting or optimizing the parameters of the parametric curve so as to increase the likelihood of the parametric curve representing the sensed spectrum

Methodology Applied

Scientific EffectMaximum likelihood estimation:

Implementation Method 3

Also described herein is a novel method to achieve LSPR peak wavelength signal noise reduction using an adaptive regularization algorithm.

Methodology Applied

Scientific EffectAdaptive regularization:

Data Source

PatentUS12078537B2System and method for finding the peak wavelength of the spectrum sensed by an LSPR spectrometer

Publication Date: 2024.09.03 NICOYA LIFESCI INC

AI summary

A system and method for fording the peak wavelength of the spectrum sensed by an LSPR spectrometer is described herein. The method comprises reading an image representing the reflected/absorbed spectrum, using a mathematical model of the LSPR spectrometer system to estimate a parametric curve representing the absorbance/reflectance spectrum, and adjusting or optimizing the parameters of the parametric curve so as to increase the likelihood of the parametric curve representing the sensed spectrum. Also described herein is a novel method to achieve LSPR peak wavelength signal noise reduction using an adaptive regularization algorithm.