Real-time identification method of microplastics based on single particle acoustophoretic behavior spectrum and application

By constructing a programmable multi-mode acoustic field to excite the characteristic dynamic behavior of microplastics, and combining acoustic behavior spectrum and machine learning model, the problems of weak detection capability and large optical interference of transparent microplastics in the existing technology are solved, and real-time, accurate identification and classification of microplastics are realized.

CN122108900APending Publication Date: 2026-05-29CHENGDU INSTITUTE OF BIOLOGY CHINESE ACADEMY OF SCIENCES
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHENGDU INSTITUTE OF BIOLOGY CHINESE ACADEMY OF SCIENCES
Filing Date
2026-02-10
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies cannot effectively detect transparent/semi-transparent microplastics, and optical imaging methods are easily affected by complex sample matrices, making it impossible to obtain real-time information on the physical properties of microplastics.

Method used

By constructing a programmable multi-mode sound field, the characteristic dynamic behavior of microplastics is stimulated. The size, shape and material of the particles are analyzed using the acoustic behavior spectrum, and real-time identification is achieved by combining machine learning models.

Benefits of technology

It enables non-destructive, high-throughput, real-time detection of transparent/semi-transparent microplastics, accurately distinguishes microplastics of different shapes and materials, has strong anti-interference capabilities, and is suitable for large-scale rapid screening of environmental water bodies.

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Abstract

The application specifically relates to a microplastic real-time identification method based on single-particle acoustic streaming behavior spectrum and application, and solves the technical problem that the characteristic dynamic behavior of particles in an acoustic field is not used for directly identifying and classifying the characteristics of particles in the prior art. By applying a programmable, multi-mode switching acoustic field, a single microplastic particle is excited to generate a characteristic dynamic behavior uniquely related to its size, shape, density and elastic modulus, and a high-speed sensor is used to collect a scattering light timing signal, and then a multi-dimensional behavior feature vector is extracted, and a microplastic is realized in real time by combining an artificial intelligence model. Label-free, high-throughput detection and classification. The application principle is innovative, and completely gets rid of the dependence on optical imaging, is especially suitable for and good at detecting transparent / semi-transparent microplastics, has strong anti-complex matrix interference capability, and provides a brand-new solution for on-site rapid screening of microplastics in environmental water bodies.
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