Bin-Time Photon Distribution Analysis for Particle Characterization

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Solution Overview

Problem

Current fluorescence correlation spectroscopy (FCS) and photon counting histogram (PCH) methods are inadequate for comprehensive analysis of particles in systems with similar masses and diffusion coefficients, as they rely on reduced data sets and are time-consuming, making it difficult to analyze time-dependent behavior and partial concentrations of different species.

Innovation Solution

A method that uses bin-time dependent distribution functions to analyze the relative frequency of photon emissions, allowing for the determination of moments and torque functions from these distributions, enabling a more comprehensive characterization and quantification of particles by comparing measured data with a theoretical signal function.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If FCS method is used to quantify particles, then measurement speed is improved, but measurement precision deteriorates when particles have similar masses and diffusion coefficients

Engineering Contradiction:
Improvemeasurement speedVSAvoidparticle characterization precision
Core Design Contradiction:
ProductivityVSMeasurement precision

Solution Approach 1:

The patent combines FCS temporal autocorrelation analysis with PCH photon count rate histogram analysis into a unified evaluation method. By merging the time-dependent information from FCS with the brightness information from PCH, the method achieves both high measurement speed and high precision for characterizing particles with similar properties.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The patent transitions from analyzing only temporal fluctuations (single dimension) to simultaneously analyzing temporal behavior and photon count rate distributions (multiple dimensions). This dimensional expansion allows differentiation of particles with similar diffusion coefficients by incorporating brightness information as an additional analytical dimension.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Measurement precision

If PCH method is used to determine partial concentrations, then measurement precision is improved, but ability to analyze time-dependent behavior is lost

Engineering Contradiction:
Improvepartial concentration determination precisionVSAvoidtime-dependent information
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent merges PCH's precise concentration determination capability with FCS's time-dependent analysis capability. The unified method evaluates both the photon count rate histogram and the temporal autocorrelation function simultaneously, preserving time-dependent information while achieving high precision in partial concentration determination.

Inventive Principle:
Principle #5Merging (Combining)

3Measurement precision

If comprehensive analysis of multiple particle species is performed, then measurement precision is improved, but analysis time increases

Engineering Contradiction:
Improvemulti-species characterization precisionVSAvoidanalysis time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the analysis into distinct computational components: temporal autocorrelation calculation, photon count rate histogram generation, and combined fitting procedure. This segmentation allows efficient processing of multi-species systems by independently evaluating time-dependent and brightness-dependent characteristics before integrating the results.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent utilizes multiple parameters (diffusion coefficients, brightness values, partial concentrations) simultaneously in the unified evaluation model. By changing from single-parameter to multi-parameter analysis, the method achieves comprehensive multi-species characterization while maintaining efficiency through simultaneous rather than sequential determination of all parameters.

Inventive Principle:
Principle #35Parameter changes

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 provides a detailed analysis of particle behavior and concentrations, overcoming the limitations of existing methods by utilizing bin-time dependent analysis to extract comprehensive information from measurement data, facilitating the characterization and quantification of particles in complex systems.

Implementation Method 1

the photons emitted by particles in the excitation volume are transmitted via the confocal microscope optics imaged on a detector

Methodology Applied
Scientific EffectPhotoelectric Effect: Photoelectric Effect

Implementation Method 2

The particles are usually excited via an external light source, such as a laser, whereby the emission characteristics of the system with the particles can be determined by detecting the photons

Methodology Applied
Scientific EffectFluorescence: Fluorescence

Data Source

PatentEP3019852B1Method for identifying and quantifying emitting particles in systems
Publication Date: 2021.09.01 FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV
  • EP3019852B1 patent drawingFigure 1
  • EP3019852B1 patent drawingFigure 2
  • EP3019852B1 patent drawingFigure 3

AI summary

The invention relates to a method for quantifying emitting particles and for characterising the time-dependent behaviour of the particles. The number n of emissions of the particles in a measurement period that have been detected in a time interval having a predetermined interval width within the measurement period is ascertained, wherein the evaluation is performed particularly for a plurality of time intervals having the same interval width, with a distribution function p(n) for the number n of detected emissions being determined. For the interval width, different bin times τ are stipulated, and, for each bin time τ, the evaluation is performed and a distribution function pτ(n) is ascertained, wherein, for each bin time τ, moments m Mess i,τ for the distribution function pτ (n) are ascertained, from which bin-time-dependent moment functions m Mess i (τ) are presented. Comparison with a theoretical signal function comprising moments m sig i (τ) for a theoretical signal distribution P sig (n,τ) ascertains constants that characterise the particles in the system.