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Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Autonomous Microsensors for Chemical Analysis
PI: Alexander Mamishev
Department of Electrical Engineering
University of Washington, Seattlemamishev@ee.washington.edu
http://www.ee.washington.edu/research/seal
Sensors
, Ene
rgy,
and Automation Laboratory
SE A L
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Outline
Motivation Theoretical background System overview
Smart tubing External sensors Internal sensors In-line sensors
Cost considerations Conclusions
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Motivation
Continuous process monitoring and control for microreactorsBefore, during, and after reactionFeedforward and feedback controlAuto-calibration of sensors through
multi-point measurements Miniaturization of sensor arrays Cost-reduction of sensing systems
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Physics of Dielectrics
The figure depicts an idealized view of dielectric phenomena. A variety of physical mechanisms contribute to the polarization of the material. Each mechanism has a characteristic frequency above which its contribution vanishes. Therefore dielectric spectra will generally appear as decreasing functions of frequency.
Innerelectrons
Outer electrons
Freeelectrons
Boundions
Freeions
Multipoles
Response Resonance Resonance Relaxation Relaxation Relaxation Relaxation
Type Atomic polarizatio
n
Atomic polarization
Space charge polarization
Orientation polarization
Space charge polarization
Orientation polarization
Resonance Frequency
~1019 Hz ~1014 Hz ~10-1 Hz ~108 Hz ~10-1 Hz ~108 Hz
The table shows the different physical mechanisms and their typical characteristic frequencies.
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Multipoles
The concept of multipoles is used to describe the distribution of charges (and, consequently, distribution of space potential) in complex molecules. Multiple color peaks in the figure on the right indicate equivalent multiple charge concentrations with the associated radii larger then those of outer electrons. Naturally, such structures have slower response to alternating electric field excitation.Practical example: Organic materials contain long molecular chains that have specific relaxation times. Detection of associated peaks may allow identification of molecular structure (in a limited subset of suspect materials).
This color map show the distribution of space potential in n-pentane (alkaline).
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Nature of dielectric signatures
• Dielectric signatures are characterized by smooth variation rather than narrowband features.
• Best selectivity will be obtained by measuring with relatively few data points over a large a frequency range.
• Measurements below about 1 Hz are impractical for a real time system because measurement time becomes too long (proportional to period).
• For selectivity, the method should be combined with other techniques.
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Dielectrometry
M easurecapacitancesand conductances
C alib ra tion-basedsensing
D iffe ren tia lsensing
C om puted istribu tionof d ie lectricproperties
C om puted istribu tionof physica lp roperties
Im aging
Faster S low er
* , tan
th icknesssurface texturetem pera turedegree o f curem oistureporositydensityconcentrationpercolationstructura l in tegrityaging sta tuscontam ination .......
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Sensor Embodiments
Micro-
reactor
Smart tubing
External sensor
Internal sensor In-line
sensor
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Smart tubing: spectroscopy and imaging
• Concentration• Composition• Reaction stage• Micro-particle size• Viscosity
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Smart tubing: differential measurements
• Flow uniformity• Auto-calibration• Residual
contamination
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Macroworld example of “smart tubing”
Metal pipe section replaced with custom made plastic pipe fitted with an dielectric spectroscopy sensor
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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External sensors
• Non-destructive, one-sided access• Non-uniform field energy distribution• Non-uniform measurement sensitivity – allows
correction for barrier effects
Flexib le substra te
B ackp lane
1l2l
3l
E lectrodes
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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The Ideal Internal Sensor
Wireless Self-powered Non-invasive Can withstand harsh environments Explosion proof Inexpensive
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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WISP system
RFIDReader
power
WISP
ID
ComputingPower
Harvesting
ID
Sensing
sensor Data
No battery!
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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PCB version of the WISP
Completed fully function WISP
Ready for applications Still working on range
and antenna design
Generations of Power Harvesters and WISPs
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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In-line sensor on NeSSI Platform
Initial tests will be focused on detection of water in oil, and mixtures of alcohols
Allows for high material feed rates due to non-contact sensor design
Offers non-destructive, inline testing of material
Uses data acquisition hardware previously developed in SEAL
Integration of a microfabricated sensor with a NeSSI block for fluid measurement
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Test Wafers Back form Fab
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Reaction Monitoring Example
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Cost considerations “Headquarter” labs routinely install analytical
instrumentation in the price range of $50K to $200K High-end dielectric spectroscopy equipment falls in
this range (Agilent, Solartron, Novocontrol) Small plants and micro-reactors cannot support
this level of investment Dielectric spectroscopy equipment in the range $5K -
$10K would be adequate Commerciallization of system developed in SEAL is
currently supported by the NSF STTR grant in partnership with Kraft (we could use additional partners)
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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mini-DiSPEC
Small, low-cost, portable, dielectric spectroscopy system
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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LabView Screenshot
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Conclusions: Sensor Miniaturization
Dielectric spectroscopy sensors are positioned for installation throughout the micro-reactor platform
Measurements range from sophisticated dielectric spectroscopy (instrumentation cost about $15K per channel) to simple single frequency units (instrumentation cost below $1K per channel) Inexpensive and mature technology available for
mass fabrication at MEMS level Small and disposable
Sensors, Energy, and Automation Laboratory (SEAL), University of Washington, Seattle
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Acknowledgements
Presented research work includes results from projects sponsored by:
National Science Foundation Center for Processing Analytical Chemistry Kraft
Key contributing graduate students: Xiaobei Li, Kishore Sundara-Rajan, Gabriel
Rowe, Abhinav Mathur
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