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Real-time Gas Mixture Analysis Using Mid-infrared Membrane Microcavities Tiening Jin, Junchao Zhou, Zelun Wang, Ricardo GutierrezOsuna, Charles Ahn, wonjun hwang, Ken Park, and Pao Tai Lin Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b03599 • Publication Date (Web): 06 Mar 2018 Downloaded from http://pubs.acs.org on March 7, 2018

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Analytical Chemistry

Real-time Gas Mixture Analysis Using Mid-infrared Membrane Microcavities Tiening Jin,ab Junchao Zhou,ab Zelun Wang,c Ricardo Gutierrez-Osuna,cd Charles Ahn,e Wonjun Hwang,e Ken Park,e and Pao Tai Linabd* a. Department of Electrical and Computer Engineering, b. Department of Materials Science and Engineering, c. Department of Computer Science and Engineering, and d. Center for Remote Health Technologies and Systems, Texas A&M University, College Station, Texas 77843, United States. e. Crucialtec Co., LTD, Gyeonggi-do, South Korea. ABSTRACT: Real-time gas analysis on-a-chip was demonstrated using a mid-infrared (mid-IR) microcavity. Optical apertures for the microcavity were made of ultrathin silicate membranes embedded in a silicon chip using the complementary metal-oxidesemiconductor (CMOS) process. Fourier transform infrared spectroscopy (FTIR) shows that the silicate membrane is transparent in the range 2.5 - 6.0 µm, a region that overlaps with multiple characteristic gas absorption lines and therefore enables gas detection applications. A test station integrating a mid-IR tunable laser, a micro-gas delivery system, and a mid-IR camera was assembled to evaluate the gas detection performance. CH4, CO2, and N2O were selected as analytes due to their strong absorption bands at λ = 3.25 - 3.50 µm, 4.20 - 4.35 µm, and 4.40 - 4.65 µm, which correspond to C-H, C-O, and O-N stretching, respectively. A short response time of subsecond and high accuracy of gas identification were achieved. Therefore, our chip-scale mid-IR sensor provides a new platform for an in-situ, remote, and embedded gas monitoring system.

Gas or chemical vapor sensing have attracted significant attention due to their broad applications such as early stage disease detection, environmental hazard monitoring, oil and gas production, and explosive and drug detection.1-6 Various sensing devices have been developed based on catalytic, electrochemical, thermal, ultrasonic, semiconductor and infrared sensors.7-12 However, these sensors tend to be bulky and have high energy consumption, which makes them impractical for wearable or on-site gas detection applications. Through improvements fabrication technologies it is now possible to build miniature analytical instruments that can potentially replace their counterpart bulky instruments such as benchtop gas chromatographs (GC) and mass spectrometers. Though micro gas chromatographs (MGCs) can accurately identify the composition of a gas mixture, the analysis process can take minutes to effectively separate different gases.13-19 Furthermore, MGCs need to be heated up frequently (to 150 oC or higher) to prevent condensation of the gas compounds inside the device. The heating process not only consumes considerable energy, but also causes instability in gas analysis due to thermal crosstalk. Solid-state sensors based on metal-oxide semiconductors (MOS) have shown a high sensitivity and fast response times. However, MOS sensors have poor selectivity and are prone to interference from background gases such ozone, water, and volatile organic compounds (VOCs). This is a major limitation for gas monitoring applications. Therefore, it is critical to find new sensing platforms that can achieve real-time gas detection at the chip-scale, while retaining high specificity and CMOS compatibility for large volume manufacturing.

A promising approach to achieve in-situ and multiple gas detection is mid-IR spectroscopy. Mid-IR is a spectral regime between wavelengths λ = 2.5 µm and 20 µm that overlaps with characteristic absorptions of various molecules, including CO2, CH4, NO, HCN, SO2, and VOCs. As such, mid-IR spectra provide both detection specificity and sensitivity for accurate and in-parallel gas identification.20-27 Not surprisingly, gas tracing through mid-IR lasers and detection techniques has been widely applied in the oil industry, as well as in environmental monitoring.28-32 Presently, however, acquiring infrared absorption spectra requires Fourier transform infrared spectroscopy (FTIR) or diffraction grating monochromators, benchtop instruments that are not suitable for portable or remote gas measurements. Fortunately, recent work in mid-IR planar photonics has showed that real-time detection on-a-chip is possible. Devices like pedestal waveguides, micro-ring resonators, and opto nanofluidics have been shown to allow recognition of multiple chemicals by analyzing the spectrum from their waveguide modes.33-37 However, these devices require delicate optical alignment to efficiently couple external mid-IR light into a micron scale waveguide. In addition, waveguide-based chemical detection rely on absorption of the evanescent field, which is relatively weak compared to the waveguide light, and therefore reduces signal-to-nose ratio and the overall sensor sensitivity. To address these limitations, we propose an embedded gas sensor based on mid-IR microcavities to achieve real-time, small footprint, and energy-efficient gas detection. The microcavity consists of ultrathin silicate membranes embedded within a Si chip, enabling integration with other microelectronics for wireless communication and processing. To evalu-

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ate the performance of the microcavity for gas sensing, we constructed a test platform with tunable mid-IR lights, multigas injectors, and mid-IR signal detectors, and performed experiments with gas mixtures of CH4, N2O, CO2 and N2 at various concentrations. As will be shown, our mid-IR microcavity is able to perform a real-time spectrum analysis as well as

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trace multiple gases in parallel by measuring the characteristic absorptions. EXPERIMENTAL SECTION

Figure 1 (a) Top and (b) cross-sectional schematics of the membrane microcavity. The center of the chip is the probe window while on the side are the apertures for gas injection and ejection. The top and the bottom membranes were bonded by a spacer layer that defined the microcavity height. (c) A diced chip sensor with a mid-IR microcavity embedded. A PDMS gas injector was attached to the chip sensor and connected to a gas tube. Figure 2. (a) Block diagram of the sensor testing platform. It has subsystems for gas mixture preparation, gas sample injection into the microcavity, gas identification, and real-time gas concentration measurement. (b) Experimental setup of the sensor testing subsystem. A probe mid-IR light emitted from the fiber passes through the membrane microcavity. The light signal is recorded by the mid-IR camera. The gas concentration inside the microcavity is constantly monitored by reading the attenuation of the probe light.

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Analytical Chemistry Structure of the microcavity gas sensor. Figure 1a and b show the design of the membrane microcavity. It has one optical window created in the chip center for IR absorption measurement, and two apertures for gas injection and ejection. The membrane is made by silicate, which is transparent from visible to mid-IR at λ = 6 µm. FTIR spectrum and the optical property of the membrane is illustrated in supplementary material S1. The broad spectral transparency of the microcavity overlaps with numerous characteristic gas absorptions such as CO, CO2, CH4, NO, and N2O, thus enabling real-time and nondestructive gas detection. The front and the back membranes were fused by an intermediate spacer layer that determines the height of the microcavity. Similar to a Fabry-Perot interferometer, the finesse F of the mid-IR microcavity can be resolved by the equation

√

, where R is the reflectivity of the

membrane surfaces. The finesse F approached to 313 when a reflectivity layer with R = 0.99 coated on both sides of the microcavity. Once the integration between the embedded microcavity and the Si chip was completed, a polydimethylsiloxane (PDMS) chamber was adhered to the front facet of the Si chip and connected to the external gas tube by a hypodermic needle, as illustrated in Figure 1c. The PDMS chamber is a miniaturized gas injector that allows the external gas to flow into the internal gas channels built inside the chip. During the gas characterization, the optical window of the microcavity is aligned with the mid-IR probe light. The detailed fabrication process of the mid-IR gas sensor is described in supplementary material S2. Gas sensing system setup. Figure 2a describes the main building blocks of the mid-IR gas sensing platform: gas mixing and delivery, chip-scale gas detection, and real time gas monitoring. The gas mixing and delivery subsystem consists of multiple mass flow controllers (MFC) to adjust the flow rates of individual gases (CH4, N2O, CO2 and N2), thus allowing us to precisely control the individual flow rates of the gas mixture constituents. The gas mixture is then delivered to the mid-IR microcavity inside the gas detection subsystem through a PDMS micro-injector made. The gas analysis platform is a real-time gas monitoring subsystem. It consists of a tunable laser and a mid-IR camera, between which the microcavity is placed. By aligning the laser wavelength with the absorption band of the target gas, the gas concentration can be constantly monitored by reading the intensity attenuation from the mid-IR. The measured concentration level can be fed back to the MCF controllers to adjust the flow rates until the gas mixture reaches the desired gas composition. Figure 2b illustrates the real-time gas monitoring platform, with a tunable pulse laser and a mid-IR camera. The wavelength from the pulse laser can be tuned from λ = 2.4 µm to λ = 3.8 µm with the laser linewidth of 3 cm-1. The laser has a 150 kHz pulse repetition rate, a 10 nano seconds pulse duration, and a 150 mW average power. Using a reflective lens, the laser light was coupled into the front facet of a fluoride fiber of 9 µm diameter core and 125 µm cladding. The light was then emitted from the back facet, which pointed toward the microcavity aperture to ensure the probe light fully passed through the microcavity. The output mid-IR signals were captured by a liquid-nitrogen-cooled InSb camera (640 x 512 pixels). For the gas mixing setup, N2O, CH4, CO2 and N2 gas cylinders were individually connected to MFCs. The flow

Figure 3. Absorption spectra of the microcavity filled with (a) CH4/N2 and (b) N2O/N2. The concentrations of gas mixtures were prepared at 0 %, 1 %, 5 %, 10 %, 25 %, and 50 %. CH4 has one strong absorption band at λ = 3.32 µm due to C-H stretching vibrational mode. N2O has two absorption bands at λ = 4.47 and 4.52 µm because of the N-O and N-N stretching vibrational modes, respectively. The simulated spectra of (c) 50 % CH4/N2 and (d) 50 % N2O/N2 using the HITRAN and PNNL database. The same characteristic absorption bands from C-H, N-O, and N-N vibrations were found in both the experiments and simulations.



ranges for N2O, CH4, and CO2 were regulated between 0 – 10 sccm, and N2 to 0 – 100 sccm. The accuracy of the flow rate was 1 % of its maximum flow range. MFCs were connected with chemically-resistant Teflon tubes, and connected to the PDMS gas injector, where the gas mixing took places. The MFCs can dynamically adjust the gas flow rates as well as rapidly prepare gas mixtures at desired gas concentrations. The gas sample inside the PDMS chamber was then injected into the mid-IR microcavity. RESULTS AND DISCUSSION Optical spectra of gas mixtures. High-resolution spectra from the gas filled microcavity were captured and analyzed by a FTIR instrument (Thermo Nicolet 380 FTIR spectrometer). It can measure the transmission spectrum from λ = 2 µm to 25 µm. The obtained spectra can be matched against various characteristic gas absorptions to estimate the composition of the gas sample inside the microcavity. Gas samples of CH4/N2 and N2O/N2 with concentrations at 0 %, 1 %, 5 %, 10 %, 25 %, and 50 %, were prepared and separately injected into the microcavity for spectral analysis. Figure 3a shows the absorption spectrum of CH4/N2 between λ = 3.15 µm and 3.45 µm, where a strong absorption band with a peak at 3.32 µm was observed. This corresponds to the C-H stretching vibrational mode.38, 39 As the CH4 concentration dropped from 50 % to 0 %, the characteristic C-H absorption decreased from 40 % to 0 %. Similar spectral results were found for the N2O/N2 gas mixtures; As shown in Figure 3b, two characteristic absorption bands appear between λ = 4.4 µm and 4.65 µm due to the N-O and N-N asymmetric stretching vibrational modes.40, 41 Absorption decreased from 55 % to 0 % as the N2O concentration was diluted from 50 % to 0 %, and a sensitivity better than 1% was achieved for CH4 and N2O detection. The simulated spectra based on the experimental conditions for 50 % CH4/N2 and 50 % N2O/N2 and using the HITRAN and PNNL database are added in Figure 3c and 3d. The simulated spectra revealed the same characteristic absorption bands as the measured results illustrated in Fig. 3a and 3b. The detection limit can reach better than 0.5 %. Next, to demonstrate the ability to trace multi-component gas mixtures, samples consisting of CH4, N2O, and CO2 with various composition ratios were prepared. Figure 4a shows the spectra of gas mixtures at CH4/N2O/CO2 ratios of 1:5:5, 3:5:5, 5:5:5, 7:5:5 and 9:5:5 as a result of increasing the gas flow rate of CH4, while keeping the N2O and CO2 flow constant. The absorption found at λ = 3.20 – 3.45 µm was assigned to CH4, and the absorption bands at λ = 4.20 µm - 4.35 µm and 4.4 µm - 4.65 µm belong to CO2 and N2O, respectively. The 3.32 µm absorption increased sharply when the mixture had a higher CH4 concentration. In comparison, Figure 4b and 4c show the spectra of gas mixtures when N2O or CO2 concentration varies while the other two gases remained the same. The composition ratios between the three gases were at 1:5:5, 3:5:5, 5:5:5, 7:5:5 and 9:5:5. The tendency of the spectrum changes revealed in Fig. 4b and 4c was similar to that of Fig. 4a, where the absorption bands at λ = 4.4 µm - 4.65 µm and 4.20 µm - 4.35 µm became stronger as the concentrations of N2O and CO2 increased. Hence, through the measurements of characteristic gas absorptions, our mid-IR chip-sensor is capable of accu-

rately identifying the gas constituents of a multi-component gas mixture as well as their concentrations. Real-time gas sensing. The sensor chip was placed in the real-time gas monitoring platform. The wavelength of the pulse laser was tuned to λ = 3.32 µm to align with the characteristic CH4 absorption, which enabled continuous CH4 tracing by reading the light intensity variation. Figure 5a shows the mid-IR fiber mode images captured after it passed through the microcavity. Before injecting CH4 into the cavity, a clear and bright mode was observed. In addition, no scattering and distortion were found, which indicates no organic or inorganic residue was remaining on the microcavity aperture during the fabrication. Once the cavity is filled with CH4, the fiber mode became dim. Evidently the intensity change of the fiber mode upon applying CH4 was attributed to its characteristic absorp-

Figure 4. Absorption spectra of the microcavity filled with CH4/CO2/N2O gas mixtures. The gas flow rate of (a) CH4, (b) 4 CO2, or (c) N2O changes while the rates for the other two remain the same. The ratios of the gas mixtures were 1:5:5, 3:5:5, 5:5:5, 7:5:5 and 9:5:5, respectively.

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Analytical Chemistry tion at λ = 3.32 µm. To evaluate the performance of real-time CH4 monitoring, pulses of CH4/N2 mixtures with concentrations of 100%, 50%, 25%, 10%, and 5% were injected into the cavity in sequence. Between the CH4/N2 pulses, N2 was injected for 30 s to purge the CH4 residue away from the microcavity. Figure 5b displays the transient intensity response from the probe mid-IR light, which shows an abrupt decrease in intensity whenever a CH4 pulse reached the cavity, and a recovery of the light intensity right after purging N2 into the microcavity.

To better quantify the relationship between the intensity change and the CH4/N2 compositions, Figure 5c shows the mid-IR intensities acquired at various CH4 concentrations, where a linear dependence between the intensity and the concentration was observed. This result shows that our chip sensor can accurately and continuously monitor the analyte concentration through mid-IR absorption measurements. Furthermore, to illustrate that our sensor has a fast response, discrete 5-sec N2 pulses were injected within a 10 sec period, while the CH4 flow rate remains constant. Shown in Figure 5d, the midIR intensity rapidly increases whenever a N2 pulse flows into the microcavity, and the N2 pulse stops followed by an instant intensity decrease. The short response time during the fast gas sampling attributes to the small volume of the sensor microcavity as well as the high sensitivity through the mid-IR detection, therefore allowing our chip sensor to perform gas monitoring in real time. CONCLUSIONS Real-time multi-gas monitoring was demonstrated using a mid-IR microcavity embedded chip sensor. The optical aperture of the microcavity consists of silicate membrane that is transparent at λ = 2.5 - 6.0 µm, enabling the sensor for broadband mid-IR absorption measurements. Through a CMOS fabrication process, the membrane was implanted in a Si chip. The internal micro gas channels were connected to an external gas delivery system through a miniaturized PDMS gas injector. The sensor performance was evaluated by a test platform assembled by subsystems for gas mixing and delivery, spectral analysis, and real-time monitoring. By measuring the characteristic C-H, C-O, and O-N absorptions at λ = 3.25 - 3.50 µm, 4.20 µm - 4.35 µm, and 4.40 - 4.65 µm, the gas sensor was able to detect CH4, CO2 and N2O and measure their concentrations in various gas mixtures. In addition, the gas sensor has a fast response time that was able to trace short gas pulses of less than 5 sec in duration. These results indicate that our chipscale mid-IR gas sensors is capable of in-situ, non-destructive, and multiple gas detection, and can be implemented for remote environmental monitoring and portable inspection of gas production plants.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI:XX.XXXX/acs.analchem.XXXXXX FTIR characterization of the membranes. Detailed fabrication processes of a microcavity (PDF)

AUTHOR INFORMATION Corresponding Author *[email protected]

ACKNOWLEDGEMENTS The authors gratefully acknowledge funding support provided by Crucialtec Co., LTD. Device fabrication and characterization Figure 5. (a) Fiber mode images after the light at λ = 3.32 µm is transmitted through the mid-IR microcavity. The mode intensity decreased when CH4 filled into the microcavity. (b) Realtime measurements of CH4/N2 gas concentration when decreased from 100%, 50%, 25%, 10%, to 5%. (c) Mid-IR intenACS Paragon sity at various CH4 concentrations. The light intensity decreasesPlus Environment as the CH4 concentrations increases. (d) Real-time CH4/N2 gas monitoring when its concentration changes at every 5 sec.

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were performed at AggieFab and Materials Characterization Facility (MCF) at Texas A&M University and the Center for Nanoscale Systems (CNS) at Harvard University.

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