Avi Cagan
Arizona State University
8 Papers
61 Citations
Avi Cagan is an academic researcher from Arizona State University. The author has contributed to research in topics: Chemistry & Hexamethylene triperoxide diamine. The author has an hindex of 6, co-authored 8 publications.
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Papers
A Hybrid Nanosensor for TNT Vapor Detection
Alvaro Diaz Aguilar,Erica Forzani,Matthew J. Leright,Francis Tsow,Avi Cagan,Rodrigo Alejandro Iglesias,Larry A. Nagahara,Islamshah Amlani,Raymond K. Tsui,Nongjian Tao +9 more
TL;DR: A hybrid nanosensor based on the electrochemical reduction of TNT and the interaction of the reduction products with conducting polymer nanojunctions in an ionic liquid that provides a selective, fast, and sensitive detection of TNT.
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Highly sensitive electrochemical detection of trace liquid peroxide explosives at a Prussian-blue ‘artificial-peroxidase’ modified electrode
TL;DR: A highly sensitive electrochemical assay of the peroxide-based explosives triacetone triperoxide (TATP) and hexamethylene tri peroxide diamine at a Prussian-blue modified electrode is reported and offers nanomolar detection limits following a short (15 s) irradiation times.
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Integrated explosive preconcentrator and electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor
Karel Cizek,Chad Prior,Chongdee Thammakhet,Michal Galik,Kevin L. Linker,Ray Tsui,Avi Cagan,John Wake,Jeffrey T. La Belle,Joseph Wang +9 more
TL;DR: An integrated explosive-preconcentration/electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor is reported on and the integrated device was successfully demonstrated using a sample of solid TNT located upstream of the preconcentrator.
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"One-step" simplified electrochemical sensing of TATP based on its acid treatment.
TL;DR: By greatly simplifying the analytical procedure, such an acid-operated "artificial peroxidase" electrocatalytic transducer holds great promise for designing "one-step", user-friendly, miniaturized, cost-effective devices for field screening of peroxide explosives.
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Least-squares based feature extraction and sensor fusion for explosive detection
Narayan Kovvali,Chad Prior,Karel Cizek,Michal Galik,Alvaro Diaz,Erica Forzani,Avi Cagan,Joseph Wang,Nongjian Tao,Douglas Cochran,Andreas Spanias,Ray Tsui +11 more
- 14 Mar 2010
TL;DR: An explosive detection approach based on multi-modal sensing and sensor data fusion using a least-squares feature extraction technique to isolate explosive signatures in data collected using electrochemical and polymer nanojunction sensors is developed.
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