Everyone

Vesa Ivanovic

Jelly Bean

A transparent bending-insensitive pressure sensor digital weight scale app measuring small normal pressures is essential to accurately evaluate external stimuli in curvilinear and dynamic surfaces such as natural tissues. Usually, sensitive and spatially accurate pressure sensors are achieved through conformal contact with the surface; however, this also makes them sensitive to mechanical deformation (bending). Indeed, when a soft object is pressed by another soft object, the normal pressure cannot be measured independently from the mechanical stress. Here, we show a pressure sensor that measures only the normal pressure, even under extreme bending conditions. To reduce the bending sensitivity, we use composite nanofibres of carbon nanotubes and graphene. Our simulations show that these fibres change their relative alignment to accommodate bending deformation, thus reducing the strain in individual fibres. Pressure sensitivity is maintained down to a bending radius of 80 μm. To test the suitability of our sensor for soft robotics and medical applications, we fabricated an integrated sensor matrix that is only 2 μm thick. We show real-time (response time of ∼20 ms), large-area, normal pressure monitoring under different, complex bending conditions.


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