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Scientists Develop Cutting-Edge Acoustic Fabric That Works Like A Mic

By Alexa Heah, 17 Mar 2022

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Image via MIT / Greg Hren

 

Engineers from the Massachusetts Institute of Technology (MIT) and the Rhode Island School of Design have created a brand-new “acoustic fabric” that mimics a microphone. 


While usual fabrics absorb sound, this one detects and produces it, converting sound waves in the air to mechanical vibrations, before turning them into electric signals that can be picked up by our ears. 


According to the researchers, all fabrics vibrate when exposed to sounds, though these vibrations are on a much smaller scale. 

 

Image via MIT / Greg Hren

 

In order to capture these nano-noises, they had to come up with a flexible fiber that could be woven into the fabric, which was designed from a “piezoelectrical” material that produces an electric signal when bent. 


The final product can impressively detect sounds ranging from a quiet room to loud traffic noise, and is able to determine the direction of sudden sounds, such as a clap. Plus, when tested, it generated an electric current proportional to the volume of the sound played. 

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“This shows that the performance of the fiber on the membrane is comparable to a handheld microphone,” said Grace Noel, co-author of the study. 

 

Image via MIT / Fink Lab

 

Not to mention, it’s practical, with the scientists taking care to weave the fibers with conventional yarns to produce a fabric that was ultimately lightweight and machine-washable.


“It feels almost like a lightweight jacket—lighter than denim, but heavier than a dress shirt,” explained fellow author, Elizabeth Meiklejohn.


Going forward, the possibilities seem limitless with what this new fabric can be turned into, with the team even suggesting it could be used to answer phone calls on the go. 


“In addition, this fabric can imperceptibly interface with the human skin, enabling wearers to monitor their heart and respiratory condition in a comfortable, continuous, real-time, and long-term manner,” said lead author Wei Yan.

 

 

 

[via MIT and CNET, cover images via MIT]

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