Hertz Fellow Ken Suslick Developing Digital “Nose” for Sniffing Out Suicide Bombers

January 28, 2016
Jeremy Thomas
Livermore, Calif

In the wake of the terrorist attacks in Paris and a spate of ISIS-inspired suicide bombings and threats around the globe, the need for sniffing out the explosives used by potential terrorists is perhaps more crucial now than ever before.

Over the past 12 years, Hertz Fellow Ken Suslick, the Marvin T. Schmidt Professor of Chemistry at the University of Illinois at Urbana-Champaign (Urbana), has been developing technology that can detect a common primary explosive used by suicide bombers, triacetone triperoxide (TATP).

“It’s not a very safe explosive, but the primary advantage to a terrorist is that they can make it in one’s kitchen with ingredients that can be bought at any hardware store, combined with ingredients bought from any hair stylist,” Suslick said. “Actually, it is not easily detected by the usual nitro-explosive scanners found in airports.”

The detector contains an acid that breaks down emissions from solid TATP into its component parts, acetone and hydrogen peroxide. The hydrogen peroxide then reacts with an array of chemically responsive dyes that can indicate the presence of TATP, as well as millions of other chemical mixtures, like a digital litmus test.

“We refer to it as an optoelectronic nose,” Suslick said. “The changes in red, green, and blue of each of the dyes turn out to be a molecular fingerprint. The color difference map is unique to any odor or mixture of odorants at any given concentration.”

The technology is being made commercially available through a company Suslick co-founded in Mountain View, iSense Medical Corporation, and a prototype for a handheld detector is in development. In a paper published in Chemical Science in September, Suslick and his team detail a device able to detect a broad range of explosives at part-per-billion levels. See image below.

Image from paper published in Chemical Science. This image demonstrates the color difference maps of the sensor array to 16 military and homemade explosives, with the 40-element colorimetric sensor array showing signal-to-noise.

Using the technology, Suslick’s companies have demonstrated the ability to quickly detect and identify much more than just explosives, including toxic industrial chemicals, and blood infections. Moreover, they are using the technology to explore noninvasive ways to probe the body, such as diagnosing lung cancer from breath. Suslick said he is “rather enamored” with the idea of converting the input and output of the senses as a novel way to approach data manipulation and detection.

“As a species, humans are very visual creatures; which is actually relatively unusual among mammals,” Suslick said. “The technology that we have developed is a very effective way of converting olfactory-like stimuli into easily interpretable visual outputs. You can think of this as ‘smell-seeing,’ and it’s a quite general approach to what I refer to sometimes as an intentional synesthesia.”

Suslick has published more than 350 academic papers and is recognized as an expert in chemical sensing and the chemical and physical effects of ultrasound, including sonochemistry and sonoluminescence, a phenomena of light and heat produced by the collapse of bubbles in a liquid.

As he transitions to a research professorship, Suslick’s love for art (he is a collector as well as a sculptor) has spurred an interest in developing sensors to monitor artwork’s exposure to pollution, which he is working on in his university lab in collaboration with the Getty Museum and the Disney Animation Research Library.

“Artwork is even more sensitive to pollution than human beings,” Suslick said. “It’s a really interesting problem, and these disposable sensor arrays turn out to be a pretty effective way of monitoring what’s going on inside the sealed case of the artwork.”

Image from paper published in Chemical Science. This image demonstrates the color difference maps of the sensor array to 16 military and homemade explosives, with the 40-element colorimetric sensor array showing signal-to-noise.