Researchers Develop New Sensor that Detects Very Weak Signals

Introducing noise to improve a weak signal is a common sensing phenomenon in the animal realm. However, it is unusual in the case of artificial sensors.

Artist’s depiction of a phenomenon called stochastic resonance. Researchers studied this technique to apply it to sensors to detect signals too faint to otherwise capture. Image Credit: Bessie Terrones, Penn State MRI.

Scientists from The Pennsylvania State University (Penn State) have now introduced a slight amount of background noise to improve extremely weak signals in a light source that is too dim to perceive.

Contrary to a majority of the sensors, where noise is a major issue that should be reduced, the researchers observed that introducing an exact amount of background noise can actually boost a signal that is too weak to be perceived by standard sensors—that is, to a level that can be detected.

While the researchers’ sensor, which is based on a 2D material known as molybdenum disulfide, is capable of detecting light, the same principle can also be applied to detect other types of signals. Since the sensor needs very limited space and energy when compared to the traditional sensors, it could be extensively adapted to the emerging Internet of Things (IoT).

Through IoT, tens of millions of sensors can be deployed to track conditions in factories and homes, and added to this, low energy needs would be a powerful bonus.

This phenomenon is something that is frequently seen in nature. For example, a paddlefish that lives in muddy waters cannot actually find its food, which is a phytoplankton called Daphnia, by sight.

Saptarshi Das, Assistant Professor of Engineering Science and Mechanics, The Pennsylvania State University

Das added, “The paddlefish has electroreceptors that can pick up very weak electric signal from the Daphnia at up to 50 meters. If you add a little bit of noise, it can find the Daphnia at 75 meters or even 100 meters. This ability adds to the evolutionary success of this animal.”

The jewel beetle is another fascinating example. This insect can sense a forest fire from a distance of 50 miles. By contrast, the most sophisticated infrared detector can detect only at a distance of 10 to 20 miles. This can be attributed to a phenomenon used by these animals, known as stochastic resonance.

Stochastic resonance is a phenomenon where a weak signal which is below the detection threshold of a sensor can be detected in the presence of a finite and appropriate amount of noise.

Akhil Dodda, Study Co-First Author and Graduate Student, Engineering Science and Mechanics, The Pennsylvania State University

The new article was recently published in the Nature Communications journal.

In their study, the team demonstrated the initial application of this method to spot a subthreshold photonic signal.

One potential application that is being contemplated is for troops in combat. Currently, army workers deployed to the field are already carrying very heavy equipment. Hence, it is not practical to add the bulky, power-hungry equipment needed to improve a subthreshold signal.

Moreover, the new method is also relevant to resource-limited surroundings or below the ocean in which individuals wish to track extremely weak signals. The method could even be used in volcanic sites or to track earthquakes in time to trigger an alarm.

Who would have thought that noise could play a constructive role in signal detection? We have challenged tradition to detect otherwise undetectable signals with miniscule energy consumption. This can open doors to a totally unexplored and ignored field of noise enhanced signal detection.

Aaryan Oberoi, Study Co-First Author and Graduate Student, Department of Engineering Science and Mechanics, The Pennsylvania State University

The next step for the researchers is to demonstrate the new method on a silicon photodiode, which would render the device highly scalable. According to Das, this concept can be used to improve any advanced sensor. The researchers have filed a provisional patent application with a complete patent to follow.

Other authors of the study are Tanushree H Choudhury, a graduate student of materials science and engineering, and Joan Redwing, a professor of materials science and engineering and electrical engineering, both from the Penn State.

The study was partly supported by the Air Force Office of Scientific Research.

Journal Reference:

Dodda, A., et al. (2020) Stochastic resonance in MoS2 photodetector. Nature Communications. doi.org/10.1038/s41467-020-18195-0.

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