Particle Diffusometry for Nanoparticle Characterization
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Solution Overview
Problem
Current methods for characterizing nanoparticles, such as Dynamic Light Scattering, require prior knowledge of refractive index and fluid properties, and struggle to accurately determine surface modifications and biomolecule conjugation without fluorescent labels.
Innovation Solution
The method involves tracking Brownian motion of particles in a fluid using imaging techniques to calculate diffusion coefficients, allowing for characterization of nanoparticles and their surface modifications without needing foreknowledge of sample parameters, using particle diffusometry (PD) to determine diffusion coefficients and assess uniformity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Dynamic Light Scattering is used to characterize nanoparticles, then measurement capability is provided, but prior knowledge of refractive index and fluid properties is required which is not always available
Solution Approach 1:
The system performs self-calibration by using the nanoparticle sample itself as the calibration reference. The autofocus mechanism automatically adjusts to achieve sharp focus on nanoparticles in the sample, eliminating the need for external calibration standards or prior knowledge of sample properties such as refractive index and fluid characteristics.
2Measurement precision
If conventional techniques are used to determine surface modifications, then characterization is attempted, but accurate determination of biomolecule conjugation is difficult without fluorescent labels
Solution Approach 1:
The invention extracts and removes the fluorescent labeling step from the characterization process. By using autofocus-based optical measurement, the system directly detects surface modifications and biomolecule conjugation through changes in optical properties and focal position, eliminating the need for fluorescent labels and associated sample preparation complexity.
3Measurement precision
If traditional characterization methods are used, then nanoparticle properties can be measured, but the process requires larger volumes and longer times
Solution Approach 1:
The system implements a hierarchical measurement approach where multiple particles are simultaneously tracked within a single field of view. The autofocus mechanism operates at the system level to establish focal plane, while individual particle trajectories are analyzed in parallel, enabling high-throughput measurement of diffusion coefficients from small sample volumes in reduced time.
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
PD provides more accurate measurements of nanoparticle diffusion coefficients and uniformity, enabling characterization of biomolecule conjugation and size determination in smaller volumes and shorter times than conventional techniques, with statistical robustness and precision.
Implementation Method 1
tracking Brownian motion of particles suspended in a fluid
Implementation Method 2
determining the diffusion coefficient of the particles based on the average displacement of the particles
Data Source
AI summary
Methods and systems suitable for tracking Brownian motion of particles suspended in a fluid and determining the diffusion coefficient of the particles therefrom in order to characterize the particles, their synthesis, and/or their surface modifications. The methods include providing a sample having particles suspended in a fluid, obtaining and recording at least first and second images of the sample wherein the first image obtained at a first time and the second image subsequently obtained at a second time, determining the average displacement of the particles in an area of the first and second images during a time period between the first time and the second time based on the first and second images, and then determining a diffusion coefficient of the particles in the area of the first and second images based on the average displacement of the particles during the time period.