TY - GEN
T1 - Silicon Rich Silicon Nitride Microchannels to Determine Fluid Composition by Near Infrared Absorbance
AU - Sundararajan, Anneirudh
AU - Pericàs, Pep Canyelles
AU - Wiegerink, Remco J.
AU - Lotters, Joost C.
N1 - Funding Information:
The author is thankful to T.V.P Schut and the Optical Sciences (OS) department of the University of Twente for their support.
Funding Information:
This publication is part of the Perspectief program Synoptic Optics 2018 TTW with project number P17-24 project 6 which is (partly) financed by the Dutch Research Council (NWO). The author is thankful to T.V.P Schut and the Optical Sciences (OS) department of the University of Twente for their support.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The aim of multiparameter microfluidic sensors is to determine multiple physical and chemical properties of liquids and gases at a microscale on a same chip platform. Silicon-rich silicon nitride (SiRN) microfluidic channels fabricated with MEMS surface channel technology (SCT) are currently used in multiparameter sensors to detect physical parameters like mass flow rate, density, and pressure with high sensitivity. However, the current platform has limited information on sensing chemical parameters like fluid composition for mixtures of more than two different fluids when using traditional physical methods. The growing interest in integrating optics to microfluidic devices for such measurements has led to an attempt to integrate optics in the current multiparameter sensing platform. Here, we demonstrate absorbance measurements using the Beer-Lambert law for four different methanol in water mixtures in a microfluidic device fabricated with SiRN microchannels using coupled multimode optical fibers. We compare the measured transmission spectral response with the theoretical response of methanol-water mixtures. The absorbance measurements show the feasibility of integrating optical methods at near infrared wavelengths in the state-of-the-art multiparameter flow sensor technology platform.
AB - The aim of multiparameter microfluidic sensors is to determine multiple physical and chemical properties of liquids and gases at a microscale on a same chip platform. Silicon-rich silicon nitride (SiRN) microfluidic channels fabricated with MEMS surface channel technology (SCT) are currently used in multiparameter sensors to detect physical parameters like mass flow rate, density, and pressure with high sensitivity. However, the current platform has limited information on sensing chemical parameters like fluid composition for mixtures of more than two different fluids when using traditional physical methods. The growing interest in integrating optics to microfluidic devices for such measurements has led to an attempt to integrate optics in the current multiparameter sensing platform. Here, we demonstrate absorbance measurements using the Beer-Lambert law for four different methanol in water mixtures in a microfluidic device fabricated with SiRN microchannels using coupled multimode optical fibers. We compare the measured transmission spectral response with the theoretical response of methanol-water mixtures. The absorbance measurements show the feasibility of integrating optical methods at near infrared wavelengths in the state-of-the-art multiparameter flow sensor technology platform.
KW - Absorbance
KW - Flow sensors
KW - Microfluidic channel
KW - Multiparameter sensor
KW - Near infrared
KW - Optical fibers
KW - SiRN
KW - Spectral response
KW - Surface Channel Technology (SCT)
UR - http://www.scopus.com/inward/record.url?scp=85126392270&partnerID=8YFLogxK
U2 - 10.1109/MEMS51670.2022.9699647
DO - 10.1109/MEMS51670.2022.9699647
M3 - Conference contribution
AN - SCOPUS:85126392270
SN - 978-1-6654-0912-4
T3 - IEEE Symposium on Mass Storage Systems and Technologies
SP - 676
EP - 679
BT - 2022 IEEE 35th International Conference on Micro Electro Mechanical Systems Conference (MEMS)
PB - IEEE
CY - Piscataway, NJ
T2 - 35th IEEE International Conference on Micro Electro Mechanical Systems Conference, MEMS 2022
Y2 - 9 January 2022 through 13 January 2022
ER -