Filament Engineering of Two-Dimensional h-BN for a Self-Power Mechano-Nociceptor System.

The switching variability caused by intrinsic stochasticity of the ionic/atomic motions during the conductive filaments (CFs) formation process largely limits the applications of diffusive memristors (DMs), including artificial neurons, neuromorphic computing and artificial sensory systems. In this study, a DM device with improved device uniformity based on well-crystallized two-dimensional (2D) h-BN, which can restrict the CFs formation from three to two dimensions due to the high migration barrier of Ag+ between h-BN interlayer, is developed. The BN-DM has potential arrayable feature with high device yield of 88%, which can be applied for building a reservoir computing system for digital pattern recognition with high accuracy rate of 96%, and used as an artificial nociceptor to sense the external noxious stimuli and mimic the important biological nociceptor properties. By connecting the BN-DM to a self-made triboelectric nanogenerator (TENG), a self-power mechano-nociceptor system, which can successfully mimic the important nociceptor features of "threshold", "relaxation" and "allodynia" is designed.

Reconfigurable 2D WSe2 -Based Memtransistor for Mimicking Homosynaptic and Heterosynaptic Plasticity.

The mimicking of both homosynaptic and heterosynaptic plasticity using a high-performance synaptic device is important for developing human-brain-like neuromorphic computing systems to overcome the ever-increasing challenges caused by the conventional von Neumann architecture. However, the commonly used synaptic devices (e.g., memristors and transistors) require an extra modulate terminal to mimic heterosynaptic plasticity, and their capability of synaptic plasticity simulation is limited by the low weight adjustability. In this study, a WSe2 -based memtransistor for mimicking both homosynaptic and heterosynaptic plasticity is fabricated. By applying spikes on either the drain or gate terminal, the memtransistor can mimic common homosynaptic plasticity, including spiking rate dependent plasticity, paired pulse facilitation/depression, synaptic potentiation/depression, and filtering. Benefitting from the multi-terminal input and high adjustability, the resistance state number and linearity of the memtransistor can be improved by optimizing the conditions of the two inputs. Moreover, the device can successfully mimic heterosynaptic plasticity without introducing an extra terminal and can simultaneously offer versatile reconfigurability of excitatory and inhibitory plasticity. These highly adjustable and reconfigurable characteristics offer memtransistors more freedom of choice for tuning synaptic weight, optimizing circuit design, and building artificial neuromorphic computing systems.

Stacked Two-Dimensional MXene Composites for an Energy-Efficient Memory and Digital Comparator.

Two-dimensional MXene has enormous potential for application in industry and academia owing to its surface hydrophilicity and excellent electrochemical properties. However, the application of MXene in optoelectronic memory and logical computing is still facing challenges. In this study, an optoelectronic resistive random access memory (RRAM) based on silver nanoparticles (Ag NPs)@MXene-TiO2 nanosheets (AMT) was prepared through a low-cost and facile hydrothermal oxidation process. The fabricated device exhibited a typical bipolar switching behavior and controllable SET voltage. Furthermore, we successfully demonstrated a 4-bit in-memory digital comparator with AMT RRAMs, which can replace five logic gates in a traditional approach. The AMT-based digital comparator may open the door for future integrated functions and applications in optoelectronic data storage and simplify the complex logic operations.