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Wearable human activity sensors developed in the past decade show a distinct trend of becoming thinner and more imperceptible while retaining their electrical qualities, with graphene e-tattoos, as the ultimate example. A persistent challenge in modern wearables, however, is signal degradation due to the distance between the sensor's recording site and the signal transmission medium. To address this, we propose here to directly utilize human skin as a signal transmission medium as well as using low-cost gel electrodes for rapid probing of 2D transistor-based wearables. We demonstrate that the hypodermis layer of the skin can effectively serve as an electrolyte, enabling electrical potential application to semiconducting films made from graphene and other 2D materials placed on top of the skin. Graphene transistor tattoos, when biased through the body, exhibit high charge carrier mobility (up to 6500 2V-1s-1), with MoS2 and PtSe2 transistors showing mobilities up to 30 cm2V-1s-1 and 1 cm2V-1s-1, respectively. Finally, by introducing a layer of Nafion to the device structure, we observed neuromorphic functionality, transforming these e-tattoos into neuromorphic bioelectronic devices controlled through the skin itself. The neuromorphic bioelectronic tattoos have the potential for developing self-aware and stand-alone smart wearables, crucial for understanding and improving overall human performance.

Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to digital systems. Though many devices have emerged as candidates for artificial neurons and artificial synapses, there have been few device candidates for artificial dendrites. In this work, we report on biocompatible graphene-based artificial dendrites (GrADs) that can implement dendritic processing. By using a dual side-gate configuration, current applied through a Nafion membrane can be used to control device conductance across a trilayer graphene channel, showing spatiotemporal responses of leaky recurrent, alpha, and gaussian dendritic potentials. The devices can be variably connected to enable higher order neuronal responses, and we show through data-driven spiking neural network classification simulations that overall spiking activity is reduced by up to 15% without accuracy loss while low frequency operation is stabilized. This positions the GrADs as strong candidates for energy efficient bio-interfaced spiking neural networks.

The combination of graphene with silicon in hybrid devices has attracted attention extensively over the last decade. Most of such devices were proposed for photonics and radiofrequency applications. In this work, we present a unique technology of graphene-on-silicon heterostructures and their properties as solution-gated transistors. The graphene-on-Silicon field-effect transistors (GoSFETs) were fabricated exploiting various conformations of drain-source regions doping and channel material dimensions. The fabricated devices were electrically characterized demonstrating hybrid behavior with features specific to both graphene and silicon. Although GoSFET's transconductance and carrier's mobility were found to be lower than in conventional silicon and graphene field-effect transistors (SiFETs and GFETs), it was demonstrated that the combination of both materials within the hybrid channel contribute uniquely to the charge carrier transport. A comprehensive physics-based compact modeling was specifically developed, showing excellent agreement with the experimental data. The model is employed to rationalize the observed hybrid behavior as the theoretical results from the electrostatics and the carrier transport under a drift-diffusion approach show that graphene acts as a shield for the silicon channel, giving rise to a non-uniform potential distribution along it, especially at the subthreshold region. This graphene screening effect is shown to strongly affect the device subthreshold swing when compared against a conventional SiFET due to a non-negligible diffusion current in this operation regime.

CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/m^2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.

Mycotoxins comprise a frequent type of toxins present in food and feed. The problem of mycotoxin contamination has been recently aggravated due to the increased complexity of the farm-to-fork chains, resulting in negative effects on human and animal health and, consequently, economics. The easy-to-use, on-site, on-demand, and rapid monitoring of mycotoxins in food/feed is highly desired. In this work, we report on an advanced mycotoxin biosensor based on an array of graphene field-effect transistors integrated on a single silicon chip. A specifically designed aptamer against Ochratoxin A (OTA) was used as a recognition element, where it was covalently attached to graphene surface via pyrenebutanoic acid, succinimidyl ester (PBASE) chemistry. Namely, an electric field stimulation was used to promote more efficient {\pi}-{\pi} stacking of PBASE to graphene. The specific G-rich aptamer strand suggest its {\pi}-{\pi} stacking on graphene in free-standing regime and reconfiguration in G-quadruplex during binding an OTA molecule. This realistic behavior of the aptamer is sensitive to the ionic strength of the analyte solution, demonstrating a 10-fold increase in sensitivity at low ionic strengths. The graphene-aptamer sensors reported here demonstrate fast assay with the lowest detection limit of 1.4 pM for OTA within a response time as low as 10 s, which is more than 30 times faster compared to any other reported aptamer-based methods for mycotoxin detection. The sensors hold comparable performance when operated in real-time within a complex matrix of wine without additional time-consuming pre-treatment.

This review provides a critical overview of current developments on nanoelectronic biochemical sensors based on graphene. Composed of a single layer of conjugated carbon atoms, graphene has outstanding high carrier mobility and low intrinsic electrical noise, but a chemically inert surface. Surface functionalization is therefore crucial to unravel graphene sensitivity and selectivity for the detection of targeted analytes. To achieve optimal performance of graphene transistors for biochemical sensing, the tuning of the graphene surface properties via surface functionalization and passivation is highlighted, as well as the tuning of its electrical operation by utilizing multifrequency ambipolar configuration and a high frequency measurement scheme to overcome the Debye screening to achieve low noise and highly sensitive detection. Potential applications and prospectives of ultrasensitive graphene electronic biochemical sensors ranging from environmental monitoring and food safety, healthcare and medical diagnosis, to life science research, are presented as well., Comment: 24 pages, 9 figures

Wearable bioelectronics with emphasis on the research and development of advanced person-oriented biomedical devices have attracted immense interest in the last decade. Scientists and clinicians find it essential to utilize skin-worn smart tattoos for on-demand and ambulatory monitoring of an individual's vital signs. Here we report on the development of novel ultrathin platinum-based two-dimensional dichalcogenide (Pt-TMDs) based electronic tattoos as advanced building blocks of future wearable bioelectronics. We made these ultrathin electronic tattoos out of large-scale synthesized platinum diselenide (PtSe2) and platinum ditelluride (PtTe2) layered materials and used them for monitoring human physiological vital signs, such as the electrical activity of the heart and the brain, muscle contractions, eye movements, and temperature. We show that both materials can be used for these applications; yet, PtTe2 was found to be the most suitable choice due to its metallic structure. In terms of sheet resistance, skin-contact, and electrochemical impedance, PtTe2 outperforms state-of-the-art gold and graphene electronic tattoos and performs on par with medical-grade Ag/AgCl gel electrodes. The PtTe2 tattoos show four times lower impedance and almost 100 times lower sheet resistance compared to monolayer graphene tattoos. One of the possible prompt implications of the work is perhaps in the development of advanced human-machine interfaces. To display the application, we built a multi-tattoo system that can easily distinguish eye movement and identify the direction of an individual's sight.