Bionic Plants Perform Better
Kyle Maxey posted on March 18, 2014 |
Plants infused with nanoparticles photosynthesize better and have the ability to detect explosives. ...
plant, biology, nano, nanoparticles, sensor, bomb, While it might seem ripped straight from the pages of a sci-fi novel, researchers have used vascular infusion to turn Arabidopsis thaliana, a small flowering plant, into a bionic super machine.

“Plants are very attractive as a technology platform,” says Michael Strano, MIT professor and leader of the research team. “They repair themselves, they’re environmentally stable outside, they survive in harsh environments, and they provide their own power source and water distribution.”

Building on those strengths, researchers applied a carbon nanotube solution to the underside of the Arabidopsis’ leaf where the plant’s stomata quickly absorbed the fluid. Once absorbed by the plant the nanotubes quickly migrated to its chloroplast and began boosting photosynthetic production. In fact, when measured, the nanotube infused Arabidopsis demonstrated a 30 percent increase in photosynthetic electron flow.

While that bionic upgrade is pretty impressive, MIT researchers also found that by introducing carbon nanotubes to the Arabidopsis’ leaves the plant could be transformed into a sensor able to detect TNT, hydrogen peroxide and nitric oxide, an environmental pollutant.

According to Juan Pablo Giraldo, a PhD candidate working on the project, “We could someday use these carbon nanotubes to make sensors that detect in real time, at the single-particle level, free radicals or signaling molecules that are at very low-concentration and difficult to detect.”

With the field of synthetic biology still in its emerging stage, technologies like MIT’s bionic plant could mark the beginning of a completely new engineering paradigm. By leveraging nature’s already robust structures and systems, engineers might be able to create novel electrical and sensory systems that would be impossible to deploy and manufacture by traditional methods.

Image Courtesy of MIT

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