Ultrasensitive bacterial sensing using a disposable all-in-one amperometric platform with self-noise cancellation.

The early detection of very low bacterial concentrations is key to minimize the healthcare and safety issues associated with microbial infections, food poisoning or water pollution. In amperometric integrated circuits for electrochemical sensors, flicker noise is still the main bottleneck to achieve ultrasensitive detection with small footprint, cost-effective and ultra-low power instrumentation. Current strategies rely on autozeroing or chopper stabilization causing negative impacts on chip size and power consumption. This work presents a 27-µW potentiostatic-amperometric Delta-Sigma modulator able to cancel its own flicker noise and provide a 4-fold improvement in the limit of detection. The 2.3-mm2 all-in-one CMOS integrated circuit is glued to an inkjet-printed electrochemical sensor. Measurements show that the limit of detection is 15 pArms, the extended dynamic range reaches 110 dB and linearity is R2 = 0.998. The disposable device is able to detect, in less than 1h, live bacterial concentrations as low as 102 CFU/mL from a 50-µL droplet sample, which is equivalent to 5 microorganisms.

Novel transducers for high-channel-count neuroelectronic recording interfaces.

Neuroelectronic interfaces with the nervous system are an essential technology in state-of-the-art neuroscience research aiming to uncover the fundamental working mechanisms of the brain. Progress towards increased spatio-temporal resolution has been tightly linked to the advance of microelectronics technology and novel materials. Translation of these technologies to neuroscience has resulted in multichannel neural probes and acquisition systems enabling the recording of brain signals using thousands of channels. This review provides an overview of state-of-the-art neuroelectronic technologies, with emphasis on recording site architectures which enable the implementation of addressable arrays for high-channel-count neural interfaces. In this field, active transduction mechanisms are gaining importance fueled by novel materials, as they facilitate the implementation of high density addressable arrays.

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. The 1024-channel ROIC has been fabricated in a standard 1.8-V 0.18- µm CMOS technology with 0.012 mm 2 and 36 µ W per channel. An automated methodology for the in-situ calibration of each GFET sensor is also proposed. Experimental ROIC tests are reported using a custom FPGA-based µECoG headstage with 16×32 and 32×32 GFET probes in saline solution and agar substrate. Compared to state-of-art neural ROICs, this work achieves the largest scalability in hybrid platforms and it allows the recording of infra-slow neural signals.

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. Herein, we present the concept of frequency-division multiplexing (FDM) of neural signals by graphene sensors. We demonstrate the high performance of graphene transistors as mixers to perform amplitude modulation (AM) of neural signals in situ, which is used to transmit multiple signals through a shared metal line. This technology eliminates the need for switches, remarkably simplifying the technical complexity of state-of-the-art multiplexed neural probes. Besides, the scalability of FDM graphene neural probes has been thoroughly evaluated and their sensitivity demonstrated in vivo. Using this technology, we envision a new generation of high-count conformal neural probes for high bandwidth brain machine interfaces.

One-Step Route to Iron Oxide Hollow Nanocuboids by Cluster Condensation: Implementation in Water Remediation Technology.

The fabrication procedure of hollow iron oxide nanoparticles with a large surface to volume ratio by a single-step gas condensation process at ambient temperature is presented. Fe clusters formed during the sputtering process are progressively transformed into hollow cuboids with oxide shells by the Kirkendall mechanism at the expense of oxygen captured inside the deposition chamber. TEM and Raman spectroscopy techniques point to magnetite as the main component of the nanocuboids; however, the magnetic behavior exhibited by the samples suggests the presence of FeO as well. In addition, these particles showed strong stability after several months of exposure to ambient conditions, making them of potential interest in diverse technological applications. In particular, these hierarchical hollow particles turned out to be very efficient for both As(III) and As(V) absorption (326 and 190 mg/g, respectively), thus making them of strong interest for drinking water remediation.