Memristors as electronic artificial synapses have attracted increasing attention in neuromorphic computing. Emulation of both "learning" and "forgetting" processes requires a bidirectional progressive adjustment of memristor conductance, which is a challenge for cutting-edge artificial intelligence. In this work, a memristor device with a structure of Ag/Zr 0.5 Hf 0.5 O 2 :graphene oxide quantum dots/Ag is presented with the feature of bidirectional progressive conductance tuning. The conductance of proposed memristor is adjusted through voltage pulse number, amplitude, and width. A series of voltage pulses with an amplitude of 0.6 V and a width of 30 ns is enough to modulate conductance. The impacts of pulses with different parameters on conductance modulation are investigated, and the potential relationship between pulse amplitude and energy is revealed. Furthermore, it is proved that the pulse with low energy can realize the almost linear conductance regulation, which is beneficial to improve the accuracy of pattern recognition. The bidirectional progressive conduction modulation mimics various plastic synapses, such as spike-timing-dependent plasticity and paired-pulse facilitation. This progressive conduction tuning mechanism might be attributed to the coexistence of tunneling effect and extrinsic electrochemical metallization effect. This work provides one way for memristor to attain attractive features such as bidirectional tuning, low-power consumption, and fast speed switching that is in urgent demand for further evolution of neuromorphic chips.

The development of the information age has made resistive random access memory (RRAM) a critical nanoscale memristor device (MD). However, due to the randomness of the area formed by the conductive filaments (CFs), the RRAM MD still suffers from a problem of insufficient reliability. In this study, the memristor of Ag/ ZrO 2 /WS 2 /Pt structure is proposed for the first time, and a layer of two-dimensional (2D) WS 2 nanosheets was inserted into the MD to form 2D material and oxide double-layer MD (2DOMD) to improve the reliability of single-layer devices. The results indicate that the electrochemical metallization memory cell exhibits a highly stable memristive switching and concentrated ON-and OFF-state voltage distribution, high speed (∼10 ns), and robust endurance (>10 9 cycles). This result is superior to MDs with a single-layer ZrO 2 or WS 2 film because two layers have different ion transport rates, thereby limiting the rupture/rejuvenation of CFs to the bilayer interface region, which can greatly reduce the randomness of CFs in MDs. Moreover, we used the handwritten recognition dataset (i.e., the Modified National Institute of Standards and Technology (MNIST) database) for neuromorphic simulations. Furthermore, biosynaptic functions and plasticity, including spike-timing-dependent plasticity and paired-pulse facilitation, have been successfully achieved. By incorporating 2D materials and oxides into a doublelayer MD, the practical application of RRAM MD can be significantly enhanced to facilitate the development of artificial synapses for brain-enhanced computing systems in the future.

Based on the fiber Bragg gratings (FBGs) and high nonlinear photonic crystal fiber (HN-PCF), a novel dual-wavelength erbium-doped fiber (EDF) laser is proposed and demonstrated. The experimental results show that, owing to the contributions of two degenerate four-wave mixings in the HN-PCF, the proposed fiber laser is great stable and two output signals are uniform at room temperature. With adjustment of the attenuator, our fiber laser can selectively realize one wavelength lasing.

No abstract

No abstract