Self-powered biosensors could monitor your health

Self-powered biosensors could monitor your health

Technology News |
By eeNews Europe

1) (a) Structure of the double-grating-patterned organic
photovoltaic film. (b) The OPV wrapped over a spatula
rod and pulled by tweezers.

Their paper “Self-powered ultra-flexible electronics via nano-grating-patterned organic photovoltaics” published in Nature emphasizes on a novel development, a high-throughput room-temperature moulding process to form nano-gratings on the photovoltaic cell’s charge transporting layers. Designed at a 760nm periodicity, the nano-gratings are reported to substantially increase the efficiency of the 3µm-thin organic photovoltaics, yielding a power-conversion efficiency up to 10.5% which for the ultralight-weight device translated into a high power-per-weight value (11.46W/g).

The nano-grating also reduced the light angle dependency of the cell’s output voltage. The cells fared well under repetitive compression tests, withstanding wrinkling at a radius as low as 3µm.

Schematic of a double-grating-patterned OPV
integrated with an OECT.

As proof of a wearable biological sensing application, the researchers co-designed the conformable and light-weight solar cells with organic electrochemical transistors (OECTs) to create a self-powered cardiac sensor.

The self-powered
integrated biosensor
attached to a finger.

In this scheme, the potential difference between a gel electrode on the chest and the OECT channel on a fingertip acts as the gate bias, affecting the PEDOT:PSS channel conductance. The device had a responsivity above 1kHz under physiological conditions, enabling the recording of clear biological signal curves under ambient light.

The paper reports a peak intensity of the cardiac signal at 0.47µA, with a signal-to-noise ratio of 40.02 decibels for cardiac signal detection. These new findings open the way to the integration of ultra-flexible organic power sources with functional electronic devices for the precise, sensitive and continuous data acquisition of biological signals without external power connections, conclude the authors.


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