Researchers from Indian institute of Technology, Bombay (IIT-B) develop High-sensitivity Gallium Nitride biosensors.
Harsha Mariam Shibu
credits: PhotoMIX Company from Pexels
Electrochemical biosensors are measuring equipment or devices that can produce electric current proportional to the concentration of specific molecules amongst many. They can also be used to detect cancers or any other diseases at the early stage, measure pollution, and can also detect food contamination. Gallium nitride (GaN) is a newer material in the semiconductor industry for producing high-density electronic circuits. This has become the most preferred material for control circuits in electric vehicles, thus enhancing the growth of GaN technology. As GaN transistors are much robust, sustain high voltages, and has the ability to switch faster, they can be used for high power and high-frequency application. These properties also allow them to sense even small changes in charge, thus making them a suitable candidate for electrochemical biosensors.
A GaN biosensor is mainly based on three-terminal nanodevice called bioHEMT (bio-high electron mobility transistor). It has two terminals, called source and drain, where both are connected by a current-carrying channel in the semiconductor material. The third terminal is called as gate, which controls the current flowing through the channel. A layer of bio recognition element is used to coat the gate and is then exposed to the analyte solution. The interaction between the analyte and detector molecules resulting in an electric charge that changes the gate voltage, thereby, changing the current through the transistor. The change in current is directly proportional to biomarker concentration and could therefore be used to measure it. “HEMTs make it possible to detect very minute changes in biomarker concentrations and could be used as early warning sensors to detect minute anomalies,” says Prof Siddharth Tallur, an author of the current study.
In the model which the researchers had created, they have derived a mathematical expression that calculates the current through the device based on the electrical and physical properties of the biosensor, the biomarker concentration and the voltage being applied at the gate. They followed a methodology which could be used for silicon devices. They also considered the charge layer at the interface while deriving this equation. To demonstrate this model, they used it to model the performance of a device in order to detect a molecule called prostate-specific antigen, the concentration of that antigen increases in the case of prostate cancer. For different molecular concentrations, the researchers calculated the current flowing through the device as the voltage at the gate varied.
The researchers tested their model against current values calculated using a computational model that takes into account the charge layer at the interface. The computational model does an independent analysis of this biosensor’s behaviour and calculates the value of the current through the device. The values calculated by the analytical model, being proposed by the designers are seen to be in good agreement with the values calculated by the computational method.
The researchers used their model to predict biosensor’s sensitivity, which is a measure of how much the current will change for a specific change in the target molecule concentration. A high value of sensitivity means that the biosensor can detect even a very small shift in concentration. They found that the sensitivity value predicted by their model is about 20% less than the value predicted by previous models that did not consider the effect of the charge layer at the interface. They also compared the sensitivity values empirically measured by other teams for a comparable setting with the sensitivity predicted using their model. They found out that the calculated sensitivity value showed a 10% deviation from the experimentally measured value.
We present a simple analytical formulation that will help designers optimise the device performance using just an equation. They don't need to use the expensive computational techniques to optimise the device design.- Prof Tallur
The researchers comment that the model could be extended to accurately estimate sensitivity for biosensors that can detect other types of cancer and various diseases characterized by early warning biomarkers. Gallium nitride devices could operate in very harsh conditions, such as highly corrosive and high-temperature environments and which in turn makes the GaN devices as an appealing choice for developing robust and reliable, high sensitivity environmental monitoring sensors with long life service, such as agricultural sensors for water quality monitoring, “With the growing adoption of GaN-based chips across various industries, the application space for GaN-based biosensors is expected to grow significantly in the coming years,” concludes Prof Tallur.