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ENose's Polymer Sensors

ENose Substrates

Substrate chipSubstrate with polymer sensor

Each sensing chip is fabricated by depositing eight individual polymer-carbon composite sensing films on a ceramic substrate.

 

Sensor Resistance Data Plot

sensor graph

Each colored peak represents a response!This graph represents sensor response to one of the testing analytes. The sensor response is the ratio of the change in resistance to the baseline resistance. Response is generated on the 3rd Gen ENose.

 

Sensor size reference (~2.5cm)

substrate size

JPL ENose sensor substrates are 25-mm-wide ceramic base with eight screen-printed Pd-Au electrode sets. Polymer–carbon black composite films are deposited from solution on the electrodes. Heaters (thermistors) have been soldered to the back side of each substrate. Please read for more information: Polymer-Carbon Black Composite Sensors in an Electronic Nose For Air Quality Monitoring

ENose Spotlight

substrate

Click to watch Dr. Margaret A. Ryan explain the science behind the ENose

ENose's Molecular Modeling Research

molecule

Ball and Stick Models

The underlying objective of this work is to develop molecular models that accurately describe the polymer-carbon black composite films used in the ENose sensors and to gain a detailed understanding of polymer composite-analyte interactions. A combination of molecular simulation tools (molecular mechanics and dynamics) are used in this work.

 

carbon

Short Modeling Simulation Movie Clip!

Poly(4-vinylphenol) carbon black composite model

Molecular Modeling Technical Works and Links

Environmental Monitoring by Electronic Nose Sensors: A Molecular Modeling Study (Abstract, Electrical Chemical Society)

Correlating Polymer-Carbon Composite Sensor Response with Molecular Descriptors (J. Electrochem. Soc., Volume 153, Issue 11, pp. H209-H216 (2006))

Presentations

Molecular Modeling of Interactions in Electronic Nose Sensors for Environmental Monitoring in Aerospace Applications (American Institute of Chemical Engineers, Annual Meeting, Indianapolis, November 2002)

Book

Computational Methods for Sensor Material Selection (Out Now 2010!)

Computational Methods for Sensor Material Selection

Useful links for molecular modeling and simulations

Research

ChE Academic Research Groups
Technical Literature
Other resources

Computing Software

Schrodinger, Inc.
Accelrys Inc.
Other resources

Supercomputing Centers

National Center for Supercomputing Application
San Diego Supercompter Center
Pittsburgh Supercomputing Center
Cornell Theory Center

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