A 1024-Channel 10-Bit 36- μW/ch CMOS ROIC for Multiplexed GFET-Only Sensor Arrays in Brain Mapping.

This paper presents a 1024-channel neural read-out integrated circuit (ROIC) for solution-gated GFET sensing probes in massive μECoG brain mapping. The proposed time-domain multiplexing of GFET-only arrays enables low-cost and scalable hybrid headstages. Low-power CMOS circuits are presented for the GFET analog frontend, including a CDS mechanism to improve preamplifier noise figures and 10-bit 10-kS/s A/D conversion.

Bias dependent variability of low-frequency noise in single-layer graphene FETs.

Low-frequency noise (LFN) variability in graphene transistors (GFETs) is for the first time researched in this work under both experimental and theoretical aspects. LFN from an adequate statistical sample of long-channel solution-gated single-layer GFETs is measured in a wide range of operating conditions while a physics-based analytical model is derived that accounts for the bias dependence of LFN variance with remarkable performance. LFN deviations in GFETs stem from the variations of the parameters of the physical mechanisms that generate LFN, which are the number of traps ( ) for the carrier number fluctuation effect (Δ) due to trapping/detrapping process and the Hooge parameter ( ) for the mobility fluctuations effect (Δ).

Switchless Multiplexing of Graphene Active Sensor Arrays for Brain Mapping.

Sensor arrays used to detect electrophysiological signals from the brain are paramount in neuroscience. However, the number of sensors that can be interfaced with macroscopic data acquisition systems currently limits their bandwidth. This bottleneck originates in the fact that, typically, sensors are addressed individually, requiring a connection for each of them.

Distortion-Free Sensing of Neural Activity Using Graphene Transistors.

Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented.

High-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors.

Recording infraslow brain signals (<0.1 Hz) with microelectrodes is severely hampered by current microelectrode materials, primarily due to limitations resulting from voltage drift and high electrode impedance. Hence, most recording systems include high-pass filters that solve saturation issues but come hand in hand with loss of physiological and pathological information.

Understanding the bias dependence of low frequency noise in single layer graphene FETs.

This letter investigates the bias-dependent low frequency noise of single layer graphene field-effect transistors. Noise measurements have been conducted with electrolyte-gated graphene transistors covering a wide range of gate and drain bias conditions for different channel lengths. A new analytical model that accounts for the propagation of the local noise sources in the channel to the terminal currents and voltages is proposed in this paper to investigate the noise bias dependence.

Quantum Size Effect in Organometal Halide Perovskite Nanoplatelets.

Organometal halide perovskites have recently emerged displaying a huge potential for not only photovoltaic, but also light emitting applications. Exploiting the optical properties of specifically tailored perovskite nanocrystals could greatly enhance the efficiency and functionality of applications based on this material. In this study, we investigate the quantum size effect in colloidal organometal halide perovskite nanoplatelets.