SBIR Phase II: Sensory System for Autonomous Area-Wide Disease and Agriterror Detection and Reporting

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$500,000.00
Award Year:
2007
Program:
SBIR
Phase:
Phase II
Contract:
0725388
Award Id:
79647
Agency Tracking Number:
0539901
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
2060 CHICAGO AVE SUITE C2, 6745 HOLLISTER AVENUE, RIVERSIDE, CA, 92507
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
960774941
Principal Investigator:
Agenor Mafra-Neto
PhD
(951) 686-5008
president@iscatech.com
Business Contact:
Agenor Mafra-Neto
PhD
(951) 686-5008
president@iscatech.com
Research Institution:
n/a
Abstract
This SBIR Phase II research project will fabricate nanosensory arrays using the Micro-Electro-Mechanical Systems (MEMS) technique. This electrochemical polymerization of biomolecule-friendly conducting polymers was developed and successfully tested to build functional, highly reliable nanosensors. This research will address key technical challenges in automating the fabrication of antibody-functionalized conducting nanowires that are individually addressable and scalable to high-density biosensor arrays for the detection of Huanglongbing (HLB). The resultant nanosensory-arrays will form the base for the development of small, effective, inexpensive, field worthy, autonomous and automated pathogen detection devices. These units will permit the unattended processing of a large number of field samples, thus increasing the temporal and geographical density of data collection, providing superior pathogen and agri-terror detection. Current disease management techniques typically lack the data collection technologies needed to avert epidemics; diagnostic instruments are not amenable to unattended autonomous operation. Devices currently used are slow, expensive, bulky, and must interface with humans. Consequently, only few pathogen introductions are detected before causing widespread disease or epidemics. This research will increase the efficiency in detection of plant pathogens and agents of disease, allowing for preventative rather than crisis or remedial control actions. The development of this automated system can mitigate the estimated $300 billion loss due to agricultural pests.

* information listed above is at the time of submission.

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