Interfacial physics of field-effect biosensors

Abstract

Field-Effect Transistor-sensors (FET-sensors) are a class of pH and biomolecule sensors that can be produced at a low cost and with high sensitivity, as a result having potential for commercialisation and widespread use. The response of a FET-sensor is generated when the electric field at the sensor surface changes, thereby inducing a measurable change in current through the device. The electric field can be modified by pH or by binding of an analyte to the surface. The solid state counterpart, the Metal Oxide Semiconductor FET, has been extensively studied as it is the basis of modern electronics. FET-sensors are less well understood, mainly due to the inherent complexity introduced by the aqueous media present at the sensor surface. The FET-sensor surface is usually an oxide such as silica and its interaction with aqueous solution introduces many complex effects, such as ion-dynamics and pH dependent ionisation, which make these systems non-trivial to understand and predict. To-date, most models of FET-sensor response have relied upon mean-field assumptions which neglect the multi-scale nature of the system and even qualitative predictions of FET-sensor response remain challenging.

In the work presented here, the interfacial physics of FET-sensors were modelled using a variety of simulation techniques at different time- and length-scales. Acid-base surface charging reactions at the oxide surface of the sensor are an important part of FET-sensor response. Density Functional Theory (DFT) simulations revealed a new mechanism of surface charging and also showed that these reactions have no well-defined transition state which can be used to model their kinetics. A Kinetic Monte Carlo (KMC) model was validated that can be used describe the dynamics of surface-charging reactions on a device scale.

As FET-sensors operate by detecting changes in the interfacial electric field, the mean net charge density of surface-bound biomolecules is an important parameter in most models of BioFET response. Semi-empirical calculations were performed to estimate the net charge of two different biomolecular systems relevant to biosensing studies. The ion dynamics in the electrical double layer at the silicawater-biomolecule interface were investigated using classical Molecular Dynamics (MD) simulations, which suggested that, in contrast to commonly used net-charge arguments for FET-sensor response, the importance of water polarisation for FET-sensor response has been hitherto underestimated.

A quantitative analysis of data extracted from the FET-sensor literature was performed, comparing experimental biosensing data with pH-sensing data. This revealed some frequent problems related to reproducibility and comparability of experimental data in this field, and highlighted that optimisation of surface chemistry is an underappreciated component of sensor optimisation. Despite these limitations, BioFET research is a rapidly advancing field in which novel device design and operation methodologies are constantly being developed which increase the viability of BioFET devices for commercial use.

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Identifiers

ORCID for Nicolas Green: orcid.org/0000-0001-9230-4455

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