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Data Augmentation Empowering Simulation-Driven Design for Nanopore Based Single-Particle Sensing of Nanoplastics
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Scientists developed a faster way to design tiny sensors that can detect nanoplastics—microscopic plastic particles that are thousands of times smaller than the width of human hair. These improved sensors can identify different types and sizes of nanoplastics in water or other samples without using chemical labels. This technology could help us better monitor nanoplastic pollution in drinking water and food, which is important since these tiny particles can potentially harm human health when we consume them.
Nanopore-based single-particle electrochemical sensing offers the possibility to determine the size, charge, type, and shape of nanoplastics simultaneously in a label-free manner. However, the rational simulation-driven design of nanopore sensing interfaces is hampered by the high computational cost of generating sufficient current traces for single-particle identification and condition optimization. To solve this issue, two data-augmentation strategies are proposed to accelerate simulation-guided nanopore design. The first one is integrated with finite-element simulations to rapidly produce raw single-particle current traces for nanoplastics of prescribed size and charge, enabling multi-feature classification that mirrors experimental data analysis. The second interpolation-based augmentation is adopted to explore the resolving power of a given nanopore. Two performance indicators-the resolution of nanoplastics' size and charge discrimination-are defined and applied to optimize the conical nanopore angle and electrolyte concentration. The resulting system (150 nm tip diameter, 20° cone angle, and 0.005 M KCl) resolves minimum differences of 0.732 nm in size and 1.885 mC m-2 in charge at >90% accuracy, for nanoplastics of 100-110 nm and-0.005 to-0.0025 C m-2. Crucially, the obtained nanopore design strategy is validated experimentally, highlighting the promise of data augmentation empowered simulation-driven nanopore engineering for single-particle nanoplastics sensing.
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