A Comparative Study of Ambipolar Material in Conventional and Access Region-Based Devices

Abstract

Neuromorphic devices utilizing atomically thin 2D materials show promise for large-scale computing by emulating biological neural networks. Floating gate transistors (FGTs) typically fall into two categories based on the selection of the semiconductor channel layer material. One category involves unipolar semiconductors that transmit only one type of majority carrier, while the second category consists of ambipolar semiconductors, tunable to switch the type of majority carrier. This flexibility enables devices to switch modes and respond to specific stimulation, such as molybdenum ditelluride (MoTe2), proven to be valid as a channel material [1]. Here, MoTe2, hexagonal boron nitride (h-BN), and graphene (Gr) were applied to construct the ambipolar FGT (AFGT). Additionally, access regions (ARs) were introduced in the AFGT to fabricate AR-based AFGT (AR-AFGT), altering the transmission mechanism of carriers in the channel layer compared with the AFGT device [2].2D van der Waal materials were stacked in the order of Gr/h-BN/MoTe2 to fabricate AFGTs with source/drain electrodes overlapping the Gr, serving as the floating gate (FG), with a channel length of about 2 µm. Gr/h-BN/MoTe2 AR-AFGTs were fabricated by placing ARs, which do not overlap with FG, in proximity to source/drain electrodes with a channel length of 10 µm. We measured and compared the transfer characteristic of AFGT and AR-AFGT devices. The AFGT exhibited obvious ambipolar behavior with dominant n-branch and p-branch. However, in the case of AR-AFGT, a significant n-branch portion was observed. These phenomena may arise from the AR increasing the distance from the electrode to the storage layer, indicating that MoTe2 acts as a unipolar material. Our study compared AFGT and AR-AFGT devices, highlighting their unique traits. While AFGT exhibited significant ambipolar behavior, AR-AFGT, influenced by the increased distance, displayed a distinct unipolar profile with an emphasis on the n-branch. The integration of AR stands out as a key factor for creating adaptable neuromorphic devices. References Wu, E., et al., Tunable and nonvolatile multibit data storage memory based on MoTe2/boron nitride/graphene heterostructures through contact engineering. Nanotechnology, 2020. 31(48): p. 485205. Sasaki, T., et al., Material and Device Structure Designs for 2D Memory Devices Based on the Floating Gate Voltage Trajectory. ACS Nano, 2021. 15(4): p. 6658-6668. Figure 1