Analysis method for individual particle shape and chemical composition classification of atmospheric samples using SEM-EDS automatic analyzer

The use of a platinum-coated polycarbonate filter with SEM-EDS and AI training addresses the challenges of analyzing ultrafine dust, enabling efficient classification and source identification of fine dust particles.

KR102992923B1Active Publication Date: 2026-07-21KOREA INST OF SCI & TECH
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Patent Information

Application Number
KR1020240195564
Authority / Receiving Office
KR · KR
Patent Type
Patents
Current Assignee / Owner
Filing Date
2024-12-24
Publication Date
2026-07-21
Estimated Expiration
2044-12-24

AI Technical Summary

Technical Problem

Conventional methods for analyzing individual fine dust particles are labor-intensive and difficult to apply universally for statistical analysis, especially for ultrafine dust like PM2.5, and existing SEM-EDS analysis faces challenges with fibrous filters and diverse compound compositions.

Method used

A method involving a polycarbonate filter coated with platinum for capturing atmospheric samples, combined with SEM-EDS analysis and artificial intelligence training, to classify particle shapes and compositions, using unsupervised learning and manifold learning to identify trends.

Benefits of technology

Enables efficient classification of particle sources by distinguishing contamination sources through automated analysis, reducing the time required to identify pollution origins and providing statistical analysis of large quantities of particles.

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Abstract

This specification provides a method for classifying the shape and chemical composition of individual particles in fine dust atmospheric samples using SEM-EDS automated analysis.
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Citation Information

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