Flexible self-rectifying synapse array for energy-efficient edge multiplication in electrocardiogram diagnosis.

Edge computing devices, which generate, collect, process, and analyze data near the source, enhance the data processing efficiency and improve the responsiveness in real-time applications or unstable network environments. To be utilized in wearable and skin-attached electronics, these edge devices must be compact, energy efficient for use in low-power environments, and fabricable on soft substrates. Here, we propose a flexible memristive dot product engine (f-MDPE) designed for edge use and demonstrate its feasibility in a real-time electrocardiogram (ECG) monitoring system.

A Neuransistor with Excitatory and Inhibitory Neuronal Behaviors for Liquid State Machine.

A liquid state machine (LSM) is a spiking neural network model inspired by biological neural network dynamics designed to process time-varying inputs. In the LSM, maintaining a proper excitatory/inhibitory (E/I) balance among neurons is essential for ensuring network stability and generating rich temporal dynamics for accurate data processing. In this study, a "neuransistor" is proposed that implements the E/I neurons in a single device, allowing for the hardware implementation of the LSM.

Chiroferromagnetic Quantum Dots for Chiroptical Synapse (ChiropS).

Optoelectronic devices using circularly polarized light (CPL) offer enhanced sensitivity and specificity for efficient data processing. There is a growing demand for CPL sensing mediums with strong optical activity, stability and sensitivity, multiple transition bands, and environmental compatibility. Here, defect-engineered chiroferromagnetic quantum dots (CFQDs) are used as a new type of CPL sensing material.

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.

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.

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.

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.

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.

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.