We propose a general methodology to calculate the individual sensitivity and the cross-sensitivities of potentiometric sensor devices (e.g. 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 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.

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Understanding the biological-electrical transduction mechanisms is essential for reliable neural signal recording and feature extraction. As an alternative to state-of-the-art lumpedelement circuit models, here we adopt a multiscale-multiphysics finite-element modeling framework. The model couples ion transport with the Hodgkin-Huxley model and the readout circuit, and is used to investigate a few relevant case studies. This approach is amenable to explore ion transport in the extracellular medium otherwise invisible to circuit model analysis.

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 staircase 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.

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.