Memristive Monte Carlo DropConnect crossbar array enabled by device and algorithm co-design.

Device and algorithm co-design aims to develop energy-efficient hardware that directly implements complex algorithms and optimizes algorithms to match the hardware's characteristics. Specifically, neuromorphic computing algorithms are constantly growing in complexity, necessitating an ongoing search for hardware implementations capable of handling these intricate algorithms. Here, we present a memristive Monte Carlo DropConnect (MC-DC) crossbar array developed through a hardware algorithm co-design approach. To implement the MC-DC neural network, stochastic switching and analog memory characteristics are required, and we achieved them using Ag-based diffusive selectors and Ru-based electrochemical metalization (ECM) memristors, respectively. The devices were integrated with a one-selector one-memristor (1S1M) structure, and their well-matched operating voltages and currents enabled stochastic readout and deterministic analog programming. With the integrated hardware, we successfully demonstrated the MC-DC operation. Additionally, the selector allowed for the control of switching polarity, and by understanding this hardware characteristic, we were able to modify the algorithm to fit it and further improve the network performance.

Threshold Modulative Artificial GABAergic Nociceptor.

Gamma-aminobutyric acid (GABA) is a crucial inhibitory neurotransmitter of the central nervous system. It modifies the signal threshold of the nociceptor, allowing it to react to external stimuli in various circumstances. Thus, GABAergic behaviors are critical characteristics of adaptive behavior in life. Here, a threshold-modulative artificial GABAergic nociceptor is reported for the first time at a Pt/Ti/Nb2 O5- x /Al2 O3- y /Pt/Ti (top to bottom) of the double charge trapping structure. The Al2 O3- y layer contains deep defect states that function similarly to the GABA neurotransmitter in modulating the signal threshold. Meanwhile, the Nb2 O5- x layer traps volatile charges and produces nociceptive behaviors. The combined dynamics of the two layers readily offer threshold-modulative GABAergic nociceptive behaviors. Based on these GABAergic behaviors, a method of implementing hot- and cold-sensitive thermoreceptors is demonstrated and shows its potential applications in advanced sensory devices.

Retention Secured Nonlinear and Self-Rectifying Analog Charge Trap Memristor for Energy-Efficient Neuromorphic Hardware.

A memristive crossbar array (MCA) is an ideal platform for emerging memory and neuromorphic hardware due to its high bitwise density capability. A charge trap memristor (CTM) is an attractive candidate for the memristor cell of the MCA, because the embodied rectifying characteristic frees it from the sneak current issue. Although the potential of the CTM devices has been suggested, their practical viability needs to be further proved. Here, a Pt/Ta2 O5 /Nb2 O5- x /Al2 O3- y /Ti CTM stack exhibiting high retention and array-level uniformity is proposed, allowing a highly reliable selector-less MCA. It shows high self-rectifying and nonlinear current-voltage characteristics below 1 µA of programming current with a continuous analog switching behavior. Also, its retention is longer than 105 s at 150 °C, suggesting the device is highly stable for non-volatile analog applications. A plausible band diagram model is proposed based on the electronic spectroscopy results and conduction mechanism analysis. The self-rectifying and nonlinear characteristics allow reducing the on-chip training energy consumption by 71% for the MNIST dataset training task with an optimized programming scheme.

Untethered Soft Robotics with Fully Integrated Wireless Sensing and Actuating Systems for Somatosensory and Respiratory Functions.

There has been a great deal of interest in designing soft robots that can mimic a human system with haptic and proprioceptive functions. There is now a strong demand for soft robots that can sense their surroundings and functions in harsh environments. This is because the wireless sensing and actuating capabilities of these soft robots are very important for monitoring explosive gases in disaster areas and for moving through contaminated environments. To develop these wireless systems, complex electronic circuits must be integrated with various sensors and actuators. However, the conventional electronic circuits based on silicon are rigid and fragile, which can limit their reliable integration with soft robots for achieving continuous locomotion. In our study, we developed an untethered, soft robotic hand that mimics human fingers. The soft robotic fingers are composed of a thermally responsive elastomer composite that includes capsules of ethanol and liquid metals for its shape deformation through an electrothermal phase transition. And these soft actuators are integrated fully with flexible forms of heaters, with pressure, temperature, and hydrogen gas sensors, and wireless electronic circuits. Entire functions of this soft hand, including the gripping motion of soft robotic fingers and the real-time detections of tactile pressures, temperatures, and hydrogen gas concentrations, are monitored or controlled wirelessly using a smartphone. This wireless sensing and actuating system for somatosensory and respiratory functions of a soft robot provides a promising strategy for next-generation robotics.

Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays.

Recent advances in wearable electronics combined with wireless communications are essential to the realization of medical applications through health monitoring technologies. For example, a smart contact lens, which is capable of monitoring the physiological information of the eye and tear fluid, could provide real-time, noninvasive medical diagnostics. However, previous reports concerning the smart contact lens have indicated that opaque and brittle components have been used to enable the operation of the electronic device, and this could block the user's vision and potentially damage the eye. In addition, the use of expensive and bulky equipment to measure signals from the contact lens sensors could interfere with the user's external activities. Thus, we report an unconventional approach for the fabrication of a soft, smart contact lens in which glucose sensors, wireless power transfer circuits, and display pixels to visualize sensing signals in real time are fully integrated using transparent and stretchable nanostructures. The integration of this display into the smart lens eliminates the need for additional, bulky measurement equipment. This soft, smart contact lens can be transparent, providing a clear view by matching the refractive indices of its locally patterned areas. The resulting soft, smart contact lens provides real-time, wireless operation, and there are in vivo tests to monitor the glucose concentration in tears (suitable for determining the fasting glucose level in the tears of diabetic patients) and, simultaneously, to provide sensing results through the contact lens display.

Wearable, wireless gas sensors using highly stretchable and transparent structures of nanowires and graphene.

Herein, we report the fabrication of a highly stretchable, transparent gas sensor based on silver nanowire-graphene hybrid nanostructures. Due to its superb mechanical and optical characteristics, the fabricated sensor demonstrates outstanding and stable performances even under extreme mechanical deformation (stable until 20% of strain). The integration of a Bluetooth system or an inductive antenna enables the wireless operation of the sensor. In addition, the mechanical robustness of the materials allows the device to be transferred onto various nonplanar substrates, including a watch, a bicycle light, and the leaves of live plants, thereby achieving next-generation sensing electronics for the 'Internet of Things' area.