Yuqin Deng, Zi Ye, Zhongshan Deng, Jie Hong, Huimin Zhang, Lin Gui
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引用次数: 0
Abstract
This work proposes a liquid-metal-based calorimetric micro-flow sensor within a polydimethylsiloxane (PDMS) chip. It can measure the flow rate of fluid in microscale channels, with a range as low as several microliters per minute. This in-chip sensor is proposed to solve the issue of detecting the flow rate in microfluidic systems. To make the sensor compatible with PDMS microfluidic chips, low-melting-point gallium-based alloy and bismuth-based (bi-based) alloy are used to make the micro heater and bi-metal thermocouples, for these alloys can be easily injected into a PDMS chip to form electrodes. To minimize heat resistance (or temperature difference) between fluid and the detecting ends of thermocouples, these ends are directly exposed to liquid in the flow channel with the help of a special reversible bonding technology. Thermocouples are connected in parallel to improve the sensor’s response. A novel method to bond and electrically connect the sensor to a PCB (print circuit board) is also elaborated. Since the calorimetric flow sensor is sensitive to heating power, fluid temperature and environment cooling, a dimensionless parameter less independent of these factors is deduced from heat transfer theory, and this idea is used in result processing to offset the bad effect. Experiments with pure water show that this sensor can be used to detect flow rates, with a resolution up to 4 µl/min/mV and a range of 12 µl/min in this case, and that at different heating powers, the thermal potential results vary significantly whereas the dimensionless results nearly keep the same. Present work indicates that this sensor has the potential to be integrated into a PDMS microfluidic system and to provide accurate and stable results if a dimensionless method is used in data processing.
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Journal of Micromechanics and Microengineering (JMM) primarily covers experimental work, however relevant modelling papers are considered where supported by experimental data.
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