Double-Floating-Gate van der Waals Transistor for High-Precision Synaptic Operations.

Two-dimensional materials and their heterostructures have thus far been identified as leading candidates for nanoelectronics owing to the near-atom thickness, superior electrostatic control, and adjustable device architecture. These characteristics are indeed advantageous for neuro-inspired computing hardware where precise programming is strongly required. However, its successful demonstration fully utilizing all of the given benefits remains to be further developed. Herein, we present van der Waals (vdW) integrated synaptic transistors with multistacked floating gates, which are reconfigured upon surface oxidation. When compared with a conventional device structure with a single floating gate, our double-floating-gate (DFG) device exhibits better nonvolatile memory performance, including a large memory window (>100 V), high on-off current ratio (∼107), relatively long retention time (>5000 s), and satisfactory cyclic endurance (>500 cycles), all of which can be attributed to its increased charge-storage capacity and spatial redistribution. This facilitates highly effective modulation of trapped charge density with a large dynamic range. Consequently, the DFG transistor exhibits an improved weight update profile in long-term potentiation/depression synaptic behavior for nearly ideal classification accuracies of up to 96.12% (MNIST) and 81.68% (Fashion-MNIST). Our work adds a powerful option to vdW-bonded device structures for highly efficient neuromorphic computing.

Filamentary and Interface-Type Memristors Based on Tantalum Oxide for Energy-Efficient Neuromorphic Hardware.

To implement artificial neural networks (ANNs) based on memristor devices, it is essential to secure the linearity and symmetry in weight update characteristics of the memristor, and reliability in the cycle-to-cycle and device-to-device variations. This study experimentally demonstrated and compared the filamentary and interface-type resistive switching (RS) behaviors of tantalum oxide (Ta2O5 and TaO2)-based devices grown by atomic layer deposition (ALD) to propose a suitable RS type in terms of reliability and weight update characteristics. Although Ta2O5 is a strong candidate for memristor, the filament-type RS behavior of Ta2O5 does not fit well with ANNs demanding analog memory characteristics. Therefore, this study newly designed an interface-type TaO2 memristor and compared it to a filament type of Ta2O5 memristor to secure the weight update characteristics and reliability. The TaO2-based interface-type memristor exhibited gradual RS characteristics and area dependency in both high- and low-resistance states. In addition, compared to the filamentary memristor, the RS behaviors of the TaO2-based interface-type device exhibited higher suitability for the neuromorphic, symmetric, and linear long-term potentiation (LTP) and long-term depression (LTD). These findings suggest better types of memristors for implementing ionic memristor-based ANNs among the two types of RS mechanisms.

Controlling resistive switching behavior in the solution processed SiO2-x device by the insertion of TiO2 nanoparticles.

The resistive switching behavior of the solution processed SiOx device was investigated by inserting TiO2 nanoparticles (NPs). Compared to the pristine SiOx device, the TiO2 NPs inserted SiOx (SiOx@TiO2 NPs) device achieves outstanding switching characteristics, namely a higher ratio of SET/RESET, lower operating voltages, improved cycle-to-cycle variability, faster switching speed, and multiple-RESET states. Density functional theory calculation (DFT) and circuit breaker simulation (CB) were used to detail the origin of the outstanding switching characteristic of the SiOx@TiO2 NPs. The improvement in resistive switching is mainly based on the difference in formation/rupture of the conductive path in the SiO2 and SiO2@TiO2 NPs devices. In particular, the reduction of resistance and lower switching voltage of TiO2 NPs control the formation and rupture of the conductive path to achieve more abrupt switching between SET/RESET with higher on/off ratio. This method of combined DFT calculation and CB offers a promising approach for high-performance non-volatile memory applications.

Spontaneous sparse learning for PCM-based memristor neural networks.

Neural networks trained by backpropagation have achieved tremendous successes on numerous intelligent tasks. However, naïve gradient-based training and updating methods on memristors impede applications due to intrinsic material properties. Here, we built a 39 nm 1 Gb phase change memory (PCM) memristor array and quantified the unique resistance drift effect. On this basis, spontaneous sparse learning (SSL) scheme that leverages the resistance drift to improve PCM-based memristor network training is developed. During training, SSL regards the drift effect as spontaneous consistency-based distillation process that reinforces the array weights at the high-resistance state continuously unless the gradient-based method switches them to low resistance. Experiments show that the SSL not only helps the convergence of network with better performance and sparsity controllability without additional computation in handwritten digit classification. This work promotes the learning algorithms with the intrinsic properties of memristor devices, opening a new direction for development of neuromorphic computing chips.

Characterization of Rotational Stacking Layers in Large-Area MoSe2 Film Grown by Molecular Beam Epitaxy and Interaction with Photon.

Transition metal dichalcogenides (TMDCs) are promising next-generation materials for optoelectronic devices because, at subnanometer thicknesses, they have a transparency, flexibility, and band gap in the near-infrared to visible light range. In this study, we examined continuous, large-area MoSe2 film, grown by molecular beam epitaxy on an amorphous SiO2/Si substrate, which facilitated direct device fabrication without exfoliation. Spectroscopic measurements were implemented to verify the formation of a homogeneous MoSe2 film by performing mapping on the micrometer scale and measurements at multiple positions. The crystalline structure of the film showed hexagonal (2H) rotationally stacked layers. The local strain at the grain boundaries was mapped using a geometric phase analysis, which showed a higher strain for a 30° twist angle compared to a 13° angle. Furthermore, the photon-matter interaction for the rotational stacking structures was investigated as a function of the number of layers using spectroscopic ellipsometry. The optical band gap for the grown MoSe2 was in the near-infrared range, 1.24-1.39 eV. As the film thickness increased, the band gap energy decreased. The atomically controlled thin MoSe2 showed promise for application to nanoelectronics, photodetectors, light emitting diodes, and valleytronics.

Filament Geometry Induced Bipolar, Complementary, and Unipolar Resistive Switching under the Same Set Current Compliance in Pt/SiOx/TiN.

The decidedly unusual co-occurrence of bipolar, complementary, and unipolar resistive switching (BRS, CRS, and URS, respectively) behavior under the same high set current compliance (set-CC) is discussed on the basis of filament geometry in a Pt/SiOx/TiN stack. Set-CC-dependent scaling behavior with relations Ireset ~ R0(-α) and Vreset ~ R0(-ß) differentiates BRS under low set-CC from other switching behaviors under high set-CC due to a low α and ß involving a narrow filamentary path. Because such co-occurrence is observed only in the case of a high α and ß involving a wide filamentary path, such a path can be classified into three different geometries according to switching behavior in detail. From the cyclic switching and a model simulation, we conclude that the reset of BRS originates from a narrower filamentary path near the top electrode than that of CRS due to the randomness of field-driven migration even under the same set-CC. Also, we conclude that URS originates from much narrower inversed conical filamentary path. Therefore, filament-geometry-dependent electric field and/or thermal effects can precisely describe the entire switching behaviors in this experiment.