TY - GEN
T1 - Understanding the Variability in GeAsTe Ovonic Threshold Switching Devices
AU - Hu, Z.
AU - Wang, G.
AU - Chai, Z.
AU - Zhang, W.
AU - Garbin, D.
AU - Degraeve, R.
AU - Clima, S.
AU - Ravsher, T.
AU - Fantini, A.
AU - Zhang, J. F.
AU - Belmonte, A.
AU - Kar, G. S.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Ovonic threshold switching (OTS) devices have recently demonstrated strong performance as selectors in high-density cross-point 1S1R emerging memory arrays to suppress the sneak current path and as selector-only-memory (SOM), with excellent Ion, Ion/Ioff nonlinearity, and endurance. However, a detailed variability study is still lacking, and understanding of the responsible mechanisms is limited. In this work, different cycle-to-cycle (C2C) Vth variability mechanisms in GeAsTe OTS are identified: (i) Defects that remain active at the off-state lead to the less than 0.2 V intrinsic small random variability (SRV); (ii) Defects activated at the on-state result in up to 1 V large pseudo-random variability (LPV). Novel techniques such as the fast frequency-domain noise analysis and the sequential variability analysis are developed to identify the SRV and LPV mechanisms and to characterize their statistical correlations with different defects. The observed single modal, bimodal and multimodal C2C Vth variability distributions can be explained by the combination of SRV and LPV at different pulse operation conditions. This work provides critical guidance for OTS variability optimization.
AB - Ovonic threshold switching (OTS) devices have recently demonstrated strong performance as selectors in high-density cross-point 1S1R emerging memory arrays to suppress the sneak current path and as selector-only-memory (SOM), with excellent Ion, Ion/Ioff nonlinearity, and endurance. However, a detailed variability study is still lacking, and understanding of the responsible mechanisms is limited. In this work, different cycle-to-cycle (C2C) Vth variability mechanisms in GeAsTe OTS are identified: (i) Defects that remain active at the off-state lead to the less than 0.2 V intrinsic small random variability (SRV); (ii) Defects activated at the on-state result in up to 1 V large pseudo-random variability (LPV). Novel techniques such as the fast frequency-domain noise analysis and the sequential variability analysis are developed to identify the SRV and LPV mechanisms and to characterize their statistical correlations with different defects. The observed single modal, bimodal and multimodal C2C Vth variability distributions can be explained by the combination of SRV and LPV at different pulse operation conditions. This work provides critical guidance for OTS variability optimization.
UR - https://www.scopus.com/pages/publications/86000032626
U2 - 10.1109/IEDM50854.2024.10873393
DO - 10.1109/IEDM50854.2024.10873393
M3 - 会议稿件
AN - SCOPUS:86000032626
T3 - Technical Digest - International Electron Devices Meeting, IEDM
BT - 2024 IEEE International Electron Devices Meeting, IEDM 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Electron Devices Meeting, IEDM 2024
Y2 - 7 December 2024 through 11 December 2024
ER -