A rotational reference cell for high-accuracy real-time spectroscopic trace-gas sensing


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We demonstrate real-time drift correction of a quantum cascade laser based direct absorption trace-gas sensor using a rotating in-line reference cell. High accuracy and performance sufficient for long-term environmental monitoring has been demonstrated.


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  • Redundant phrases2 (electronics and optics) points which include the others
  • Get rid of multi-pass cells
  • Too much textSample – ambientZero (non-absorbing)3D exploded view of rotational cell
  • Combien this slide with previous using optimized dataStart with corrected and uncorrected then flip to red, green, and blue
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  • A rotational reference cell for high-accuracy real-time spectroscopic trace-gas sensing

    1. 1. CLEO/QELS June 12, 2012 A Rotational Reference Cell for High-accuracy Real-time Spectroscopic Trace-gas Sensing Clinton J. Smith, Wen Wang, and Gerard Wysocki Dept. of Electrical Engineering, Princeton University, Princeton, NJ 08544 pulse.princeton.edu
    2. 2. Project Goal & Outline The project goal: • Develop and implement a technique for real-time calibration of portable trace-gas sensors  Using a rotating in-line gas cell  Minimizes sources of drift in real time http://www.coas.oregonstate.edu/research/po/satellite.gif Outline • Key challenges to long-term sensor measurement stability • Conventional calibration methods • Overview of the rotational reference cell implementation • Experimental results • Conclusions and Future directions 2
    3. 3. Measurement Noise & Drift Reduce Sensitivity Measurement drift can be induced by many factors: • Fabry-Perot Fringing  Opto-mechanical instability Allan Deviation (sensitive to ambient temperature change)  Scattering • Electronics instability • Optical power fluctuation Averaging Time (sec) Recurring Calibration Required 3
    4. 4. Traditional Calibration Methods • Send beam to separate optical branch  Use separate reference cell  Subject to different parasitic I0 IDet,1 Ambient Detector 1 fringes • Multiple detectors Reference Cell  With different noise & drift IDet,2 Detector 2 • Single gas cell • Single detector • Cycle between reference and • sample gases  Maintenance challenge Lack of portability and autonomy Ambient Ref. Gas I0 Inlet Outlet IDet Detector 4
    5. 5. Suppress Drifts by Division of Background Signal Raw Spectra Scans Reference Path: Raw Scan with Spectral Fit I ref ( )  Tref I 0e  ( b ( ) Lb  ref ( ) La ) Corrected Reference Scan Background Corrected Reference Signal Tref , c ( )  Background Path: I zero ( )  Tzero I 0 e  b ( ) Lb I ref ( ) I zero ( )  Tref TZero e  ref ( ) La • Baseline and fringes are suppressed through division  Same process applies to the sample signal  Spectral fitting removes baseline but not fringes 6
    6. 6. Long-term Suppression of Drift Time Series of Uncorrected and Corrected Signals Allan Deviation of Uncorrected and Corrected Signals 1 ppmv 1sec, 1σ = 1.75 ppmv • Measure away from absorption line • •  Assess instrument stability 1 sec. 1σ sensitivity is 3.510-4 (1.75 ppmv) Sensitivity of 610-5 (0.3 ppmv) after 100 sec. averaging & sustained past 3000 sec. 7
    7. 7. Incomplete Correction of Absorption Peak Signal Time Series of Signals at the Peak and Away Allan Deviation of Signals at the Peak and Away 1 ppmv • Measured reference gas stability at and away from absorption peak • Long-term drift remains for on-line measurements • Full spectral fit of corrected reference also shows drift •  Improves 1 sec sensitivity ~2 to 210-4 (1 ppmv)  Uses full spectral information Background signal 4-5 reference signal  Difficult to suppress but can calibrate sample against reference 8
    8. 8. Baseline Drift & Error Correction Background-Corrected Scans at Different Experiment Times Scatter Plots Tsample,c(Tref,c) Before & After Baseline Correction • Baseline drift introduces error into single spectral point measurements •  Differences in reference & sample baseline also introduce error Use Sample-Reference regression + fundamental principles to correct  At 100% transmission the fit of Tsample,c(Tref,c) should intersect (1,1) coordinate  Scale spectra to meet this condition 9
    9. 9. Calibration Through Spectral Correlation Scatter Plots Tsample,c(Tref,c) Before & After Baseline Correction TS (t n )  mTR (t n )  y0 Baseline Corrected Transmissions TR (tn )  Tref , c (tn ) Bsim Bmeas TS (t n )   Tsample,c (t n ) Bsim,meas are simulated & measured baselines β is a modeled transmission correction factor • Use slope (m) of TS(TR) to calibrate sample concentration.  Slope is proportional to the ratio of analyte concentrations. [CO2 ]sample  m  [CO2 ]ref • Point-by-point spectral correlation of time domain data.  Uses all spectral data (like a spectral fit).  Frequency calibration not needed. 10
    10. 10. Single point, spectral fit, & spectral correlation Time Series Showing Effects of Calibration Allan Deviation Showing Effects of Calibration Drift reduction • Single point & spectral correlation calibration suppress drift • Full spectral fit shows ~6 % offset •  Consistent with sample and reference baseline differences  1.7 increase in 1s sensitivity (2.35 ppmv to 1.33 ppmv)  Drift remains Spectral correlation calibration has accuracy & precision of fit.  Same offset as fit  Removes baseline error without frequency calibration. 11
    11. 11. Conclusion and Future Work • A novel in-line drift suppression & calibration technique. • •  Uses a rotating in-line gas cell.  Provides real-time calibration. Divide the sample (reference) signals by the background spectrum.  Three sub-cells share the same optical interfaces.  Parasitic interference fringes are minimized. Spectral correlation calibration technique.  Maintains concentration retrieval accuracy.  Improves measurement precision.  Uses entire spectrum without wavelength calibration. Future Improvements • Address detector nonlinearity • Minimize background signal magnitude with solid optical waveguides  Calibration in a controlled atmosphere  Operation at the Brewster’s angle to further suppress fringes  Field deployment 12
    12. 12. Acknowledgements This work was sponsored in part by: The National Science Foundation’s MIRTHE Engineering Research Center An NSF MRI award #0723190 for the openPHOTONS systems An innovation award from The Keller Center for Innovation in Engineering Education National Science Foundation Grant No. 0903661 “Nanotechnology for Clean Energy IGERT” 13