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ACS News Service Weekly PressPac: Wed Jul 11 11:39:01 EDT 2018
Building a chemical weapons detector with Legos®
Nerve agents are scary stuff. They are among the most deadly substances on earth, yet can be odorless, tasteless and difficult to detect. But researchers now report in ACS Central Science that they have adapted building materials normally associated with children’s toys and a cell phone to help sense these compounds. The new method can sensitively detect these poisons, quantify the amount and distinguish between different classes present at contaminated sites.
Because nerve agents shut off enzymes that control the body’s nervous system function, death comes quickly — in minutes or even seconds. Thus, it’s important to detect these compounds quickly so that swift action can be taken. But in addition to taking too long, current methods require expensive instruments and are poorly suited for field use. Complicating matters, there are two main categories of nerve agents, requiring different decontamination protocols. Existing tools are not effective in differentiating between these classes, which is important because one is more toxic and less volatile than the other, leading to a greater potential for mass harm. Eric Anslyn, Edward M. Marcotte and colleagues sought to develop an instrumental set-up and method that addressed these issues and would be simple to use.
The researchers developed a cascade of reactions that amplify an optical signal that results from a byproduct of a decomposition reaction of the nerve agents. The resulting mixtures change their color and intensity of emission relative to the amount of chemical weapon present. This visual change of emission provides a sensitive test that can be read using common, inexpensive household and laboratory items. The simple design features a LEGO® box with a template to guide a smartphone’s placement on a stage, where the phone acts as the instrument’s camera. The only other necessary components are a UV/visible lamp and a standard 96-well test plate. Free software helps analyze the resulting image. To encourage wide adoption of their technology, the researchers uploaded their analytic code, image guides and a demonstration video to GitHub.
The authors acknowledge funding from the U.S. Department of Defense, the Howard Hughes Medical Institute and the W.M. Keck Foundation.
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