IR laser induced meniscus evaporation from a microchannel

Xu, Qing-Yun; Chen, Rong; Wang, Hong; Zhu, Xun; Liu, Qiang; He, Xiao‐Ting

doi:10.1016/j.ces.2015.03.011

Cited by 9 publications

(2 citation statements)

References 27 publications

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“…Control of the local temperature of the menisci was demonstrated multiple times using integrated microfabricated heaters (e.g., Figure ), surface acoustic waves, or photothermal effects induced by an IR laser . For capillary-driven microfluidic systems, localized cooling of the inlet reservoirs close to the dew point was also conversely used to limit evaporation and the unavoidable change of concentration of the dissolved analytes, notably for miniaturized immunoassays involving submicroliter volumes, as shown in Figure A. , Importantly, the fine control of heat transfer at the microfluidic scale, associated with the use of materials with high thermal conductivity (e.g., glass/silicon chips as in Figure ), opens up the possibility to tune evaporation-driven pumping with short response times, down to ∼1 s …”

Section: Microfluidic Passive Pumpingmentioning

confidence: 99%

“…Control of the local temperature of the menisci was demonstrated multiple times using integrated microfabricated heaters 81 (e.g., Figure 6), surface acoustic waves, 93 or photothermal effects induced by an IR laser. 94 For capillary-driven microfluidic systems, localized cooling of the inlet reservoirs close to the dew point was also conversely used to limit evaporation and the unavoidable change of concentration of the dissolved analytes, notably for miniaturized immunoassays involving submicroliter volumes, as shown in Figure 7A. 84,89 Importantly, the fine control of heat transfer at the microfluidic scale, associated with the use of materials with high thermal conductivity (e.g., glass/silicon chips as in Figure 6), opens up the possibility to tune evaporation-driven pumping with short response times, down to ∼1 s. 82 Forced convection at the air/liquid interface was also reported multiple times using, for instance, air directly flowing in a microchannel at a distance of the meniscus fixed by the design of the microfluidic network, 81 an air fan for menisci trapped at the outlets of the chip, 83 or even localized nitrogen flows to control and maintain a steady flow rate once the mechanical balance is reached in a capillary pump.…”

Section: Microfluidic Passive Pumpingmentioning

confidence: 99%

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Microfluidic Evaporation, Pervaporation, and Osmosis: From Passive Pumping to Solute Concentration

2021

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Evaporation, pervaporation, and forward osmosis are processes leading to a mass transfer of solvent across an interface: gas/liquid for evaporation and solid/liquid (membrane) for pervaporation and osmosis. This Review provides comprehensive insight into the use of these processes at the microfluidic scales for applications ranging from passive pumping to the screening of phase diagrams and micromaterials engineering. Indeed, for a fixed interface relative to the microfluidic chip, these processes passively induce flows driven only by gradients of chemical potential. As a consequence, these passive-transport phenomena lead to an accumulation of solutes that cannot cross the interface and thus concentrate solutions in the microfluidic chip up to high concentration regimes, possibly up to solidification. The purpose of this Review is to provide a unified description of these processes and associated microfluidic applications to highlight the differences and similarities between these three passive-transport phenomena.

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Section: Microfluidic Passive Pumpingmentioning

confidence: 99%

Section: Microfluidic Passive Pumpingmentioning

confidence: 99%

Microfluidic Evaporation, Pervaporation, and Osmosis: From Passive Pumping to Solute Concentration

2021

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Experimental methods in chemical engineering: Data processing and data usage in decision‐making

Thibault

Chioua

McKay³

et al. 2023

Can J Chem Eng

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Industrial facilities collect large volumes of data, store them according to prescribed protocols, and then interpret them for process decision‐making. Several sources and types of error contaminate these data for various reasons, but especially because they come from unreliable or unpredictable instruments. Data (or signal) processing corrects measurement errors to improve fidelity. Here, we highlight decision‐making applications and signal processing methods. To fully appreciate the state‐of‐the‐art, we interviewed plant data experts and software developers in the pulp and paper industry to examine how they apply signal processing methods in the context of decision‐making, including the value of process data, how these data are used, and the major barriers that prevent plants from using data. Process experts clean data thoroughly with basic approaches compared to the advanced techniques available in the recent literature. The interviews demonstrate that decisions in industry are primarily based on steady‐state process operating data. Challenges and barriers that prevent the use of process data to their full potential relate to resource limitations (people, time, and money), an entrenched culture, and access to recent technology. In practice, experts consider, implicitly or explicitly, data that represent the process operating under steady‐state conditions. A plant model that represents steady‐state operations is easier to interpret, is presented in a form that is usable by plant operators, and in this way, better enables decision‐making.

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