一种基于偏振动态光散射的微粒形貌分析方法与系统
By combining polarization dynamic light scattering with neural networks and genetic algorithms, the problem of determining the proportion of spherical and rod-shaped particles in mixed samples was solved, enabling accurate acquisition of particle size information and improving analytical precision.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2024-01-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot accurately determine the particle size and volume percentage of spherical and rod-shaped particles when a mixed sample contains both.
A particle morphology analysis method based on polarization dynamic light scattering is adopted. By obtaining the autocorrelation functions of the vertical and horizontal polarization states of the particles under the scattering angle, a hybrid particle morphology inversion algorithm and neural network are used, combined with genetic algorithm and random vector function chain neural network, to invert and obtain the particle size information and volume ratio.
It enables the acquisition of accurate size information and volume ratio of spherical and rod-shaped particles, overcoming the limitation of existing technologies that cannot distinguish between spherical and rod-shaped particles, and improving the accuracy of analysis.
Smart Images
Figure CN117907165B_ABST