Physical insight of random fluctuation in metal/IGZO Schottky barriers for low-variation contact optimal design.

The study aimed to investigate the impact of random fluctuations in Schottky barrier formation at polar interfaces between InGaZnO4 (IGZO) and different metals, particularly in the context of device miniaturization. The investigation revealed that different metals can establish various crystalline IGZO interfaces to achieve Ohmic contact, regardless of their work function. Additionally, the study suggests that introducing In doping at the amorphous IGZO interface can effectively reduce the Schottky barrier when in contact with Al metal. These findings provide theoretical guidance for the miniaturization of source-drain contacts in IGZO devices.

Transition from Schottky to ohmic contacts in the C31 and MoS2 van der Waals heterostructure.

The utilization of conventional metal contacts has restricted the industrial implementation of two-dimensional channel materials. To address this issue, we conducted first-principles calculations to investigate the interface properties of C31 and MoS2 contacts. An ohmic contact and a low van der Waals barrier were found in the C31/MoS2 heterostructure. Our findings provide a promising new contact metal material for two-dimensional nanodevices based on MoS2.

Quasi-Volatile MoS2 Barristor Memory for 1T Compact Neuron by Correlative Charges Trapping and Schottky Barrier Modulation.

Artificial neurons as the basic units of spiking neural network (SNN) have attracted increasing interest in energy-efficient neuromorphic computing. 2D transition metal dichalcogenide (TMD)-based devices have great potential for high-performance and low-power artificial neural devices, owing to their unique ion motion, interface engineering, and resistive switching behaviors. Although there are widespread applications of TMD-based artificial synapses in neural networks, TMD-based neurons are seldom reported due to the lack of bio-plausible multi-mechanisms to mimic leaking, integrating, and firing biological behaviors without external assistance. In this work, for the first time, a methodology is developed by introducing the hybrid effect of charge trapping (CT) and Schottky barrier (SB) in MoS2 FETs for barristor memory and one-transistor (1T) compact artificial neuron realization. By correlating the CT and SB processes, quasi-volatile and resistive switching behaviors are realized on the fabricated MoS2 FET and utilized to mimic the accumulating, leaking, and firing biological behaviors of neurons. Therefore, based on a single quasi-volatile CT-SB MoS2 barristor memory, a 1T compact neuron of the basic leaky-integral-and-fire (LIF) function is demonstrated without a peripheral circuit. Furthermore, a spiking neural network (SNN) based on the CT-SB MoS2 barristor neurons is simulated and implemented in pattern classification with high accuracy approaching 95.82%. This work provides a highly integrated and inherently low-energy implementation for neural networks.