Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach
Deterministic Lateral Displacement (DLD) has been widely utilized for the high-throughput and efficient separation of microspheres, cells, exosomes, and proteins, playing a crucial role in size-based particle separation. The high performance of DLD devices in various tasks relies on optimal design....
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Engineering Applications of Computational Fluid Mechanics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2453633 |
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