Synaptic Device with Linear Weight Update Using Graded SiGe Body Capacitor-less 1T-DRAM

In this study, we propose an enhanced 1T-DRAM-based synaptic device structure aimed at improving conductance characteristics and linearity during potentiation and depression. While conventional 1T-DRAM based synaptic devices using a uniform SiGe body suffer from degraded linearity due to rapid hole saturation across the entire body region, our approach introduces a degraded SiGe body structure in which the body is divided into three sections with gradually decreasing Ge mole fractions (0.3, 0.2, and 0.1) from the source to the drain side. This gradient design enables more effective hole storage during potentiation and depression compared to a uniform SiGe body, alleviating abrupt saturation and thereby enhancing linearity. The proposed structure is evaluated in a multi-layer perceptron (MLP) simulation using NeuroSim, demonstrating increased classification accuracy with respect to training epochs.

Authors

Publication Details

Journal
JSTS Journal of Semiconductor Technology and Science
Published
2026-10-22
DOI
https://doi.org/10.5573/jsts.2026.26.5.374
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Synaptic Device with Linear Weight Update Using Graded SiGe Body Capacitor-less 1T-DRAM

Eungi Hwang, Younghoo Ro, Jun Lee, Garam Kim
JSTS Journal of Semiconductor Technology and Science
Advanced Memory and Neural Computing
article

Synaptic Device with Linear Weight Update Using Graded SiGe Body Capacitor-less 1T-DRAM

Eungi Hwang, Younghoo Ro, Jun Lee, Garam Kim
article en

Abstract

In this study, we propose an enhanced 1T-DRAM-based synaptic device structure aimed at improving conductance characteristics and linearity during potentiation and depression. While conventional 1T-DRAM based synaptic devices using a uniform SiGe body suffer from degraded linearity due to rapid hole saturation across the entire body region, our approach introduces a degraded SiGe body structure in which the body is divided into three sections with gradually decreasing Ge mole fractions (0.3, 0.2, and 0.1) from the source to the drain side. This gradient design enables more effective hole storage during potentiation and depression compared to a uniform SiGe body, alleviating abrupt saturation and thereby enhancing linearity. The proposed structure is evaluated in a multi-layer perceptron (MLP) simulation using NeuroSim, demonstrating increased classification accuracy with respect to training epochs.

JSTS Journal of Semiconductor Technology and ScienceVol. 26(5)
Openalex Percentile: Top 24%
Advanced Memory and Neural Computing
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