Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power integrated sensors, very little is known about their noise characterization when being operated in a liquid gate configuration. The noise characteristics in various regimes of their operation are important to select the most suitable conditions for signal-to-noise ratio (SNR) and power consumption. This work reports systematic DC, transient, and noise characterizations and models of a back-end of line (BEOL)-modified foundry-made ISFET used as pH sensor. The aim is to determine the sensor sensitivity and resolution to pH changes and to calibrate numerical and lumped element models, capable of supporting the interpretation of the experimental findings. The experimental sensitivity is approximately 40 mV/pH with a normalized resolution of 5 mpH per µm², in agreement with the literature state of the art. Differences in the drain current noise spectra between the ISFET and MOSFET configurations of the same device at low currents (weak inversion) suggest that the chemical noise produced by the random binding/unbinding of the H⁺ ions on the sensor surface is likely the dominant noise contribution in this regime. In contrast, at high currents (strong inversion), the two configurations provide similar drain noise levels suggesting that the noise originates in the underlying FET rather than in the sensing region.

We present an approach to simulate ion’s drift and diffusion in chemical sensors based on ion-selective-membranes (ISMs) in either ion-selective electrode structures or coupled to field-effect transistors. The model is used to analyze the sensitivity, selectivity, and transient response of ISMs in non-equilibrium conditions upon real-time concentration changes. Our simple implementation combines advanced features from semiconductor theory and analytical electrochemistry, such as the Schafetter-Gummel discretization scheme and Chang-Jaffé boundary conditions for ions at the interfaces, thus allowing to perform simulations beyond sensing. The results are in agreement with experimental transient responses reported in the literature. As relevant case studies, we examine the ISM preconditioning in miniaturized sensors and the electrostatic interaction between the FET channel and ISMs. In the first case, simulations reveal that calibration curves performed on incomplete ISM conditioning can lead to hysteretical responses when the ion affinity in the electrolyte and ISM is similar (e.g., with organic ions). In the second case, we find that the gate oxide field in contact with the ISM affects the device characteristics such that the ion concentrations not only change the FET threshold voltage but also the slope of its IV curve. This effect can be minimized by working in the subthreshold regime or using extended gates.

We propose a general methodology to calculate the individual sensitivity and the cross-sensitivities of potentiometric sensor devices (e.g., ion sensitive FETs (ISFETs), CHEMFETs) with an arbitrary number of non-interacting receptors binding to ionic species or analytes in the electrolyte. The surface charge generated at the (bare or functionalized) interface with the electrolyte is described by the Poisson equation coupled to a linear system of equations for each type of receptor, where the unknowns are the fractions of sites binding with a given ion/analyte. Our general model encompasses in a unique framework a few simple special cases so far separately reported in the literature and provides for them closed-form expressions of the average site occupation probability. Detailed procedural description of the usage and benefits of the model is shown for specific cases with concurring surface chemical reactions.

This paper firstly reports a general and powerful approach to evaluate the power spectral density (PSD) of the surface charge fluctuations, so-called “chemical noise”, from a generic set of reactions at the sensing surface of potentiometric sensors such as, for instance, Ion-Sensitive Field Effect Transistors (ISFETs). Starting from the master equation, the spectral noise signature of a reaction set is derived as a function of the reaction kinetic parameters and of the interface concentration of the ionic species. Secondly, we derive an equivalent surface admittance, whose thermal noise PSD produces a noise PSD equal to that of the surface charge fluctuations. We also show how to expand this surface admittance into stair-case RC networks, with a number of elementary cells equal to the number of surface reactions involved. This admittance can be included in circuit simulations coupled with a SPICE compact model of the underlying FET, to enable the physically based modelling of frequency dispersion and noise of the sensing layer when simulating the sensor and the read-out. Validation with existing models and literature results as well as new application examples are provided. The proposed methodology to compute the PSD from rate equations is amenable to use in different contexts where fluctuations are generated by random transitions between discrete states with given exchange rates.

We present and validate an equilibrium model based on the Poisson-Boltzmann equations that includes the main ingredients to simulate ion-sensitive membranes in the context of electrochemical potentiometric sensors with and without ionophores. With respect to phase boundary models, our model includes spatial resolution of the electrostatic potential and concentrations. The model enables the study of Nernstian and non-Nernstian equilibrium responses, helps improving the detection range and investigating selectivity and cross-sensitivity issues related to interferent ions in the sample solution. Therefore, the model is a useful support for the design of potentiometric microelectronic sensors and helps optimizing relevant membrane features such as ionic sites and ionophore concentration for best sensitivity and selectivity.

Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and of the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.