Electronic Sensor Technology 1 A New Type of Electronic Nose for Analyzing Malodor Introduction - Electronic Nose and Sensor Arrays Fast Chromatography as a Sensor Arrays Quantifiable Results - US EPA Validation VaporPrints TM Images and Pattern Recognition Breath and Common Mouthwash odors Other Useful VaporPrint TM Applications Summary and Conclusions Edward J. Staples, Ph.D. Electronic Sensor Technology 1077 Business Center Circle Newbury Park, California Ph: FAX: WebSite:
Electronic Sensor Technology 2 A New Type of Electronic Nose for Analyzing Malador A new type of Electronic Nose which simulates the human olfactory response with a 500 element array of nearly orthogonal sensors in 10 seconds is described in this paper. This electronic nose is the first to be validated by the US EPA with both volatiles as well as semi-volatile organic compounds. Application of this new technology to identify and quantify breath odors can identify specific analytes and their concentrations in breath. This new eNose contains a large number of orthogonal sensors, very detailed VaporPrint TM images which are used to identify complex odors and fragrances. With orthogonal 500 sensors, the olfactory response can be mapped into a visual image and this allows accurate pattern recognition by humans as well as computers. Unlike conventional sensor arrays this eNose speciates and quantifies the individual analytes present in breath. This paper will present results obtained from bacteria and other malodors associated with human diseases. In addition, VaporPrint TM images associated with common mouthwashes will be presented.
Electronic Sensor Technology 3 Electronic Noses (Sensor Arrays) Technical Approach –Sensor Arrays to mimic the human olfactory response –Visual Image –Pattern Recognition Specificity –Orthogonality –Sensor Separation –Meaningful Sensor Sequence or Order Ability to Calibrate –Sensitivity –Accuracy –Precision –Speed
Electronic Sensor Technology 4 Fast Gas Chromatography GC/SAW Electronic Nose with programmable sampling preconcentrator 10 Second Analysis Speed Volatile Compounds - ppb MDL Semi-Volatile Compounds - ppt MDL
Electronic Sensor Technology 5 Cal 1 in Air Cal 1 Air 0 o C SAW 30 second Sample Cal 2 Air 0 o C SAW 30 second Sample chloroform benzene toluene ethylbenzene 1,1,2,2 trichloroethane 1,2 DCE Carbon tetrachloride TCE PCE Xylene
Electronic Sensor Technology 6 Calibration Files for Air * 30 Second Sample 0 o C Detector
Electronic Sensor Technology 7 Water Calibration Cal 1 Water 0 o SAW 30 sec Sample Cal 2 Water 0 o SAW 30 sec Sample chloroform benzene toluene ethylbenzene 1,1,2,2 trichloroethane 1,2 DCE Carbon tetrachloride TCE PCE Xylene
Electronic Sensor Technology 8 Calibration Files for Water * 30 Second Sample 0 o C Detector
Electronic Sensor Technology 9 Minimum Detection Levels for Common VOC 30 second Sample of Vapor 0 o C SAW Detector
Electronic Sensor Technology 10 Chromatogram viewed as a serial polling of a sensor array Step 1 - Preconcentrate Step 2 - Desorb & Inject Step 3 - Observe elution of analytes from GC column
Electronic Sensor Technology 11 Display Formats and Vapor Signatures Frequency Pattern Derivative Pattern
Electronic Sensor Technology 12 VaporPrint TM Pattern Recognition Evaluation performed using Humans and Artificial Intelligence/Neural Net Software Result - Human perception is practically optimal at recognizing VaporPrint TM images. Example
Electronic Sensor Technology 13 Useful Attributes of an Electronic Nose Dental and Oral Characteristics –visual, sound, tactile –X-ray images – olfactory evaluation (quantitative) Electronic Nose –improves olfactory capabilities –transfers olfactory stimulus to visual pattern recognition Oldsmobile Alero Oldsmobile Aurora Example: Learning to recognize the olfactory image ‘that new car smell’
Electronic Sensor Technology 14 Volatile Organics Bacteria Odor Signatures Breath Odor Detection/Diagn ostics Gastrointestinal Salivary Treatment Animal studies Other –Medical Diagnosis –Early identification of Infectious disease –Biological agents –Body Odors Near Real Time (10 Seconds) Chromatography with an Electronic Nose
Electronic Sensor Technology 15 Now the Speed of a Sensor Array and the Performance of a Fast Gas Chromatograph SAW Sensor Vapor Signature Processed Vapor Signature US EPA Validated Chromatography Software Definable Sensor Arrays
Electronic Sensor Technology 16 VaporPrint TM Images of Mouthwash Odors Tom’s SpearmintTom’s PeppermintScope Peppermint Long’s MintScope mintLong’s Blue Mint Listerine Mint
Electronic Sensor Technology 17 Comparison of Mints Long’s Mint Listerine Cool Mint Long’s Blue Mint Quantitative Comparisons (Analyte by Analyte)
Electronic Sensor Technology 18 Long’s and Scope Mint Scope Peppermint Scope Mint Tom’s Peppermint Tom’s Spearmint Listerine Cool Mint Long’s Blue Mint
Electronic Sensor Technology 19 Tom’s Peppermint and Scope Mint
Electronic Sensor Technology 20 Scope Mint and Peppermint
Electronic Sensor Technology 21 Salmonella typhimurium Strep pneumonia Shigella flexneri Salmonella enteritidis Hemophilus influenza Enterococcus faecalis E. Coli O157E. Coli Staph aureus Pseudomonas aeruginosa Klebsiella pneumonia Candida albicans Cultures Prepared by: Department of Pathology and Laboratory Medicine, State Public Health Laboratory of Nevada VaporPrint TM of Infectious Bacteria Cultures
Electronic Sensor Technology 22 Dioxins OnionsGarlic CoffeeMushroomsAuto Exhaust Peanut Butter Cup PCB Aroclor 1260 US Currency Diesel Gasoline Kitt-Kat
Electronic Sensor Technology 23 Summary Flash Chromatography using Surface Acoustic Wave GC Detectors –Small, Solid State, low cost –no polymer coatings to degrade >> high stability 10 Second analysis time provides a fast and portable malodor analyzer Functional Electronic Nose –Serial Polling simulates 500 orthogonal Sensors in 10 Seconds –Minimal overlapping responses (co-elution) –EPA Methods Insure Accuracy & Precision Sensitivity –ppb for VOCs –ppt for Semi-VOC Save Money and Time with real time Quantitative Results in-situ See our web site :
Electronic Sensor Technology 24 Commercial Availability Benchtop Model for Mobile Labs