Lensless Microfluidic Particle Characterization via 2D Array Imaging
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Solution Overview
Problem
Current lensless microfluidic detection techniques face challenges in effectively characterizing particles in terms of size, shape, and distribution within heterogeneous fluid samples, particularly in industrial and pharmaceutical applications, where precise quality control and quality assurance are crucial.
Innovation Solution
A method involving a two-dimensional array detector to acquire images of particles as they flow through a microfluidic channel, applying particle characterization functions to categorize particles based on morphological characteristics, size, and statistical analysis, while using coherent scattering illumination and laser diffraction for further characterization, enabling real-time monitoring and dispersion metric extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If lensless microfluidic detection techniques are used to acquire microscopic images of suspended samples, then the device size is reduced and portability is improved, but the ability to effectively characterize particles in terms of size, shape, and distribution is insufficient
Solution Approach 1:
The patent combines lensless imaging with multiple characterization techniques including light scattering measurements and machine learning algorithms into a single integrated system. This merging allows the compact device to achieve comprehensive particle characterization capabilities that would normally require separate, larger instruments.
Solution Approach 2:
The patent introduces machine learning algorithms as an intermediary that processes the raw imaging data and extracts detailed particle characteristics. This computational mediator enables accurate size, shape, and distribution analysis from the simplified lensless images, bridging the gap between compact imaging and precise characterization.
2Measurement precision
If traditional imaging techniques with lenses are used, then particle characterization accuracy is improved, but device complexity and size increase
Solution Approach 1:
The patent extracts the lens component from the traditional imaging system, eliminating the complexity associated with lens alignment, focus adjustment, and lens-related aberrations. The lensless imaging approach uses direct projection geometry, removing the optical element that sources much of the system complexity while maintaining sufficient characterization capability through computational methods.
Solution Approach 2:
The patent replaces the mechanical-optical system (lenses, mirrors, complex optical paths) with a computational approach. Machine learning algorithms process the simplified lensless images to extract detailed particle characteristics, substituting computational complexity for mechanical-optical complexity.
3Loss of information
If multiple characterization techniques are applied simultaneously, then measurement comprehensiveness is improved, but processing time and computational load increase
Solution Approach 1:
The patent performs preliminary processing of the imaging data using machine learning algorithms that rapidly extract key particle features. This preliminary extraction of size, shape, and other characteristics from the lensless images allows subsequent analysis steps to work with pre-processed information, reducing overall processing time while maintaining comprehensive characterization.
Solution Approach 2:
The patent segments the characterization process into distinct computational stages: initial image processing, feature extraction via machine learning, and final analysis. This segmentation allows each stage to be optimized independently and enables parallel processing of multiple particles and parameters, reducing overall processing time while maintaining comprehensive data collection.
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 high-resolution imaging and real-time characterization of particles, enhancing quality control and assurance in industrial processes by accurately determining particle size, shape, and distribution, and enabling effective contaminant and counterfeit detection.
Implementation Method 1
acquire images of the particles as they flow past the two-dimensional array detector
Implementation Method 2
coherent scattering illumination
Implementation Method 3
laser diffraction step
Data Source
Figure 1
Figure 2A~2C
Figure 3
AI summary
The disclosure relates to methods and apparatus for detecting properties of heterogeneous samples, including detecting properties of particles or fluid droplets in industrial processes. Embodiments disclosed include a heterogeneous fluid sample characterization method, comprising: inserting a probe into a first of a plurality of heterogeneous fluid samples; drawing at least a first portion of the first sample into the probe and past a two-dimensional array detector; illuminating the first portion of the first sample as it is drawn past the two-dimensional array detector; acquiring at least a first image of the first portion of the first sample as it is drawn past the two- dimensional array detector; inserting the probe into a second of the plurality of heterogeneous samples; drawing at least a first portion of the second sample into the probe and past a two-dimensional array detector; illuminating the first portion of the second sample as it is drawn past the two-dimensional array detector in the fluid; and acquiring at least a first image of the first portion of the second sample as it is drawn past the two-dimensional array detector in the fluid.