Liquid Crystals as Multifunctional Interfaces for Trapping and Characterizing Microplastics

TL;DR

This study demonstrates that liquid crystal interfaces can effectively trap, differentiate, and characterize microplastics like PE and PS using aggregation patterns and machine learning, offering a new approach for environmental microplastic analysis.

Contribution

The paper introduces a novel method combining liquid crystal interfaces with machine learning for accurate microplastic identification and characterization.

Findings

PE and PS microparticles exhibit distinct aggregation patterns at LC interfaces.

SDS surfactant modifies aggregation behavior, aiding differentiation.

Deep learning models classify PE vs PS with over 99% accuracy.

Abstract

Identifying and removing microplastics (MPs) from the environment is a global challenge. This study explores how the colloidal fraction of common MPs behave at aqueous interfaces of liquid crystal (LC) films. We observed polyethylene (PE) and polystyrene (PS) microparticles to be captured at the LC interface and exhibit distinct two-dimensional aggregation patterns. The addition of low concentrations of surfactant (sodium dodecylsulfate (SDS)) was found to further amplify the differences in PS/PE aggregation patterns, with PS changing from a linear chain-like morphology to a singly dispersed state with increasing SDS concentration and PE forming dense clusters at all SDS concentrations. Statistical characterization of assembly patterns using fractal geometric theory-based machine learning and a deep learning image recognition model yielded highly accurate classification of PE vs PS (>99%). Additionally, by performing feature importance analysis on our deep learning model, dense, multi-branched assemblies were confirmed to be unique features of PE relative to PS. To obtain additional insight into the origin of these key features, we performed microscopic characterization of LC ordering at the microparticle surfaces. These observations led us to predict that both microparticle types should generate LC-mediated interactions (due to elastic strain) with a dipolar symmetry, a prediction consistent with the observed interfacial organization of PS but not PE. We conclude that the non-equilibrium organization of the PE microparticles arises from their polycrystalline nature, which leads to rough particle surfaces and weakened LC elastic interactions and enhanced capillary forces. Overall, our results highlight the potential utility of LC interfaces for surface-sensitive characterization of colloidal MPs.