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Title: Frequency-dependent synapse weight tuning in 1S1R with short-term plasticity TiOx-based exponential selector
Authors: Chee, Mun Yin
Dananjaya, Putu Andhita
Lim, Gerard Joseph
Du, Yuanmin
Lew, Wen Siang
Keywords: Science::Physics
Issue Date: 2022
Source: Chee, M. Y., Dananjaya, P. A., Lim, G. J., Du, Y. & Lew, W. S. (2022). Frequency-dependent synapse weight tuning in 1S1R with short-term plasticity TiOx-based exponential selector. ACS Applied Materials & Interfaces, 14(31), 35959-35968.
Project: I1801E0030 
Journal: ACS Applied Materials & Interfaces 
Abstract: Short-term plasticity (STP) is an important synaptic characteristic in the hardware implementation of artificial neural networks (ANN), as it enables the temporal information processing (TIP) capability. However, the STP feature is rather challenging to reproduce from a single non-volatile resistive random-access memory (RRAM) element, as it requires a certain degree of volatility. In this work, a Pt/TiOx/Pt exponential selector is introduced not only to suppress the sneak current, but also to enable the TIP feature in a one selector-one RRAM (1S1R) synaptic device. Our measurements reveal that the exponential selector exhibits the STP characteristic, while a Pt/HfOx/Ti RRAM enables the long-term memory capability of the synapse. Thereafter, we experimentally demonstrated pulse frequency-dependent multilevel switching in the 1S1R device, exhibiting the TIP capability of the developed 1S1R synapse. The observed STP of the selector is strongly influenced by the bottom metal-oxide interface, in which Ar plasma treatment on the bottom Pt electrode show the annihilation of the STP feature in the selector. A mechanism is thus proposed to explain the observed STP, using the local electric field enhancement induced at the metal-oxide interface coupled with the drift-diffusion model of mobile O2- and Ti3+ ions. This work therefore provides a reliable means of producing the STP feature in a 1S1R device, which demonstrates the TIP capability sought after in hardware-based ANN.
ISSN: 1944-8244
DOI: 10.1021/acsami.2c11016
Schools: School of Physical and Mathematical Sciences 
Rights: This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Applied Materials & Interfaces, copyright © 2022 American Chemical Society, after peer review and technical editing by the publisher. To access the final edited and published work see
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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