AutoRE: Bayesian-Optimization-based Automatic Reliability Enhancement Tool for Flow-based Microfluidic Biochips
Siyuan Liang, Yushen Zhang, Mengchu Li, Tsun-Ming Tseng, Ulf Schlichtmann, Tsung-Yi Ho
Abstract
As an emerging platform for biochemical experiments, flow-based microfluidic biochips are currently suffering from malfunctions caused by manufacturing defects, thereby having low yield. While many related studies have been conducted and reliability quantification models have been published, layout optimization methods are yet lacking. In this paper, we propose AutoRE, the first tool to automatically enhance reliability by optimizing layouts. AutoRE varies the layout within a certain range without changing its topology, and adopts Bayesian optimization (BO) to identify the most reliable variant. Experimental results demonstrate that AutoRE can efficiently and effectively improve the reliability across all testcases by around 40% on average.
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