ABSTRACT
Two-dimensional (2D) transition-metal dichalcogenides (TMDs) materials, such as molybdenum disulfide (MoS2), stand out due to their atomically thin layered structure and exceptional electrical properties. Consequently, they could potentially become one of the main materials for future integrated high-performance logic circuits. However, the local back-gate-based MoS2 transistors on a silicon substrate can lead to the degradation of electrical characteristics. This degradation is caused by the abnormal effect of gate sidewalls, leading to non-uniform field controllability. Therefore, the buried-gate-based MoS2 transistors where the gate electrodes are embedded into the silicon substrate are fabricated. The several device parameters such as field-effect mobility, on/off current ratio, and breakdown voltage of gate dielectric are dramatically enhanced by field-effect mobility (from 0.166 to 1.08 cm2/V·s), on/off current ratio (from 4.90 × 105 to 1.52 × 107), and breakdown voltage (from 15.73 to 27.48 V) compared with a local back-gate-based MoS2 transistor, respectively. Integrated logic circuits, including inverters, NAND, NOR, AND, and OR gates, were successfully fabricated by 2-inch wafer-scale through the integration of a buried-gate MoS2 transistor array.
ABSTRACT
Wearable electronic devices with next-generation biocompatible, mechanical, ultraflexible, and portable sensors are a fast-growing technology. Hardware systems enabling artificial neural networks while consuming low power and processing massive in situ personal data are essential for adaptive wearable neuromorphic edging computing. Herein, the development of an ultraflexible artificial-synaptic array device with concrete-mechanical cyclic endurance consisting of a novel heterostructure with an all-solid-state 2D MoS2 channel and LiSiOx (lithium silicate) is demonstrated. Enabled by the sequential fabrication process of all layers, by excluding the transfer process, artificial van der Waals devices combined with the 2D-MoS2 channel and LiSiOx solid electrolyte exhibit excellent neuromorphic synaptic characteristics with a nonlinearity of 0.55 and asymmetry ratio of 0.22. Based on the excellent flexibility of colorless polyimide substrates and thin-layered structures, the fabricated flexible neuromorphic synaptic devices exhibit superior long-term potentiation and long-term depression cyclic endurance performance, even when bent over 700 times or on curved surfaces with a diameter of 10 mm. Thus, a high classification accuracy of 95% is achieved without any noticeable performance degradation in the Modified National Institute of Standards and Technology. These results are promising for the development of personalized wearable artificial neural systems in the future.
ABSTRACT
High-precision artificial synaptic devices compatible with existing CMOS technology are essential for realizing robust neuromorphic hardware systems with reliable parallel analogue computation beyond the von Neumann serial digital computing architecture. However, critical issues related to reliability and variability, such as nonlinearity and asymmetric weight updates, have been great challenges in the implementation of artificial synaptic devices in practical neuromorphic hardware systems. Herein, a robust three-terminal two-dimensional (2D) MoS2 artificial synaptic device combined with a lithium silicate (LSO) solid-state electrolyte thin film is proposed. The rationally designed synaptic device exhibits excellent linearity and symmetry upon electrical potentiation and depression, benefiting from the reversible intercalation of Li ions into the MoS2 channel. In particular, extremely low cycle-to-cycle variations (3.01%) during long-term potentiation and depression processes over 500 pulses are achieved, causing statistical analogue discrete states. Thus, a high classification accuracy of 96.77% (close to the software baseline of 98%) is demonstrated in the Modified National Institute of Standards and Technology (MNIST) simulations. These results provide a future perspective for robust synaptic device architecture of lithium solid-state electrolytes stacked with 2D van der Waals layered channels for high-precision analogue neuromorphic computing systems.
