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Enhancing Accuracy In 3D Defocusing Particle Tracking Using 3D-Printed Ramp

Zhengwei Chen, Baoxuan Tao, Steven T. Wereley

Purdue University, West Lafayette, United States


Three-dimensional defocusing particle tracking velocimetry (3D DPTV) is an emerging tool for investigating fluid motion within microfluidic devices, where observation is typically limited to a single direction. This technique enables the reconstruction of 3D flow fields by analyzing the defocused particle images. The accuracy of 3D DPTV significantly relies on the collection of a proper calibration image stack containing particle images with precisely known defocus distances. One major challenge is to insert a microscale calibration target inside the microfluidic devices due to the small length scales of microfluidic devices. While the alternative approaches such as using tilted glass slides or conducting z-scans of particles fixed at the bottom wall, face several limitations. Here, we present the application of a two-photon polymerization (2PP) based method to manufacture a microscale reference ramp as the calibration target. We demonstrate the fabrication of a precise reference ramp structure that spans the desired calibration range to enhance accuracy in 3D defocusing particle tracking. We experimentally and computationally compare the result with the commonly employed methods to obtain the calibration image stack. The performance of the 2PP-based calibration ramps is compared with the z-scanning method using the General Particle tracking (GPTV). The results demonstrate that the z-scanning method underestimates the defocused distances compared to the ground truth provided by the ramp approach, with the error increasing as the defocused distance grows. The integration of microscale calibration targets using 2PP fabrication method offers a significant advancement in the reliability and accuracy of 3D DPTV measurements in microfluidic systems. By enabling precise, device-specific calibration, this approach can enhance the fidelity of flow field reconstructions, benefiting a wide range of microfluidic applications that rely on detailed velocity field information.

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