Imaging-Based Lensless Polarization-Sensitive Fluid Stream Analyzer for Automated, Label-Free, and Cost-Effective Microplastic Classification

Abstract

The presence of microplastics in the environment is of significant concern, yet the exact extent of this pollution remains largely unknown. The ocean is of particular interest as the monitoring of microplastics presents a challenge in that in situ fluid stream solutions are not readily available and traditional sampling methods are labor-intensive and costly. This study introduces an imaging-based lensless polarization-sensitive fluid stream analyzer (FSA) for automated, label-free, and cost-effective detection and classification of microplastics. The FSA incorporates digital in-line holography and birefringence computation, enabling quantitative polarization-sensitive imaging and machine-learning-based activities including sample classification. Birefringent textures of synthetic polymers are investigated owing to their optical anisotropy. A microplastic classifier is developed for the FSA and integrated to form an end-to-end workflow capable of sampling fluid streams and determining marine and microplastic particle presence. Cultures of two phytoplankton species form a simplified marine environment for FSA evaluation. The device is tested in a two-class configuration for marine microorganisms and microplastics, as well as a five-class configuration for marine microorganisms and four individual microplastic types (polyethylene, polyethylene terephthalate, polypropylene, and polystyrene). The results demonstrate high classification accuracy, supported by experiments in the simulated marine environment that validate the proposed implementation's efficacy.