In-situ Crystal Imaging for High-Aspect-Ratio Particle Analysis
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Solution Overview
Problem
Conventional methods for determining the particle size distribution of high-aspect-ratio crystals, such as laser diffraction and laser backscattering, are inadequate due to orientation-dependent measurements and limitations in handling high solids concentrations, leading to inaccurate results and the need for invasive sampling.
Innovation Solution
The development of image analysis systems that can segment and analyze low-quality images of high-aspect-ratio crystals, using techniques like Burns direction analysis to locate linear features, determine co-linearity, and extract statistical information about orientation and shape, enabling reliable in situ monitoring and control of crystallization processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser diffraction is used to determine particle size distribution, then the measurement can be performed on suspended crystal particles, but the results are inaccurate for high-aspect-ratio crystals due to orientation-dependent diffraction patterns and spherical particle assumptions
Solution Approach 1:
The patent replaces laser diffraction (optical measurement based on spherical assumptions) with in-situ imaging technology that directly captures crystal morphology. The imaging system uses digital cameras and image analysis algorithms to measure crystal length, width, and aspect ratio without assuming spherical geometry, thereby achieving accurate measurement of high-aspect-ratio crystals while maintaining on-line capability
Solution Approach 2:
The patent changes the measurement parameters from diffraction pattern analysis (which assumes spherical particles) to direct image-based dimensional measurement. By capturing actual crystal images and analyzing their geometric parameters (length, width, aspect ratio) directly, the system adapts to measure high-aspect-ratio crystals accurately without being constrained by spherical particle models
2Productivity
If laser diffraction is used for in situ measurements, then on-line monitoring is possible, but insufficient light passes through high solids concentration samples to be recorded
Solution Approach 1:
The patent substitutes laser diffraction (which requires light transmission through the sample) with reflective imaging technology. The imaging system uses lights positioned around the reactor and cameras to capture reflected light from crystal surfaces, enabling on-line monitoring of high solids concentration slurries where transmitted light would be insufficient
3Measurement precision
If conventional imaging systems are used to size high-aspect-ratio crystals, then size and shape information can be extracted, but invasive sampling is required which is inconvenient and potentially hazardous
Solution Approach 1:
The patent implements in-situ imaging capability directly within the crystallization reactor before sampling is needed. By installing transparent windows on the reactor and positioning imaging devices to view the crystal slurry in real-time, the system eliminates the need for invasive sampling while providing continuous size and shape measurement data
Solution Approach 2:
The patent introduces transparent reactor windows and optical pathways as intermediaries that allow light and imaging signals to pass through the reactor wall without requiring physical contact with or removal of the crystal slurry. This intermediary approach enables non-invasive measurement while maintaining the integrity and safety of the crystallization process
Data Source
AI summary
An image of high-aspect-ratio objects is analyzed to locate linear features within the image. The gradient direction for each pixel is determined, and connected pixels having similar gradient directions are grouped into line support regions. A linear feature is determined for each line support region. The linear features are analyzed to identify those that are co-linear. The linear features are then analyzed to find groups that are parallel and that sufficiently overlap. Additional sets of linear features that intersect the identified group are combined into that group. The line support regions of the grouped linear features are analyzed to determine representative orientation and/or dimensional information, which is analyzed to determine statistical information about a plurality of the objects. This information is used to monitor or control one or more processes associated with the objects, to reject the objects or a structure or device comprising the objects, or the like.


