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Thomas says that the 3-D-structured particles have potential to become ultrafast, ultrasensitive biosensors. They’re sensitive because they have plenty of surface area to which DNA or other biotags can attach. With conventional solid microarrays and particles, biotags only adorn the probe’s surface. In contrast, biotags can attach inside the latticework particles, increasing the number of target molecules that bind to a particle, and therefore producing a more intense fluorescent signal. “The particle, of course, is transparent, so if the fluorescence is occurring in the center of the particle, it’s still visible outside,” says Thomas. He adds that he and his team have demonstrated about a 10-fold signal boost so far, and he predicts that they will optimize the lattice to yield at least a 10,000-fold signal boost.

Commercialization of MIT’s microfluidic particle biosensors is by no means around the corner. But several companies have expressed interest in the system, and collaborations are under way to test it on real-world samples from genetic tests. The MIT researchers’ goal is to launch a startup or have licensing agreements in place within two years. Patents are in the works covering the microfluidic process for making particles, its application for making biosensor arrays, and the new phase-mask-enhanced system for structured particles.

Looking beyond biosensors, Thomas envisions applications that dynamically exploit the particles’ mechanical properties. Particles with narrow scaffolding, for example, should be capable of squashing down to squeeze into tight spaces, much as fresh red blood cells squeeze into the tightest capillaries. He also imagines that the latticework particles could beget tunable sieves for handling and sorting much smaller nanoparticles by using polymers that swell and seal up the lattice in response to external conditions such as acidity. “If you were trying to choke off transport of virus particles, for example, this would work nicely,” says Thomas. “That’s one of our dreams.”

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Credit: Ji-Hyun Jang, MIT

Tagged: Computing, Materials, MIT, materials, nanoparticles

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