Time‐Domain Content‐Addressable Memory Based on Single Ambipolar Ferroelectric Memcapacitor for High‐Density and Highly‐Precise Distance Function Computation

Abstract Single ambipolar ferroelectric memcapacitor‐based time‐domain (TD) content‐addressable memory (CAM) is proposed and experimentally demonstrated. The proposed TD CAM design effectively resolves the critical challenges of limited integration density and computational reliability in conventional ferroelectric memcapacitor‐based capacitive CAMs. The band‐reject‐filter‐shaped and symmetric capacitance‐voltage characteristics with high dynamic range of a gated p‐i‐n diode‐structured ferroelectric memcapacitor are leveraged. This CAM performs dual‐edge search operations, where the Hamming distance (HD) between entry and query vectors is computed based on the modulation of the variable capacitance of cells. The propagation delay of the TD CAM output signal is linearly correlated with the computed HD, enabling improved search accuracy and sensing margin. The error‐free classification of previously unseen classes in a five‐way one‐shot learning task indicates the feasibility of the proposed TD CAM as an associative memory within memory‐augmented neural networks toward real‐world implementations. Moreover, modeling results confirm that the proposed operation scheme maintains robustness against process variations and interconnect parasitics in massive arrays of highly scaled devices. Overall, the proposed TD CAM array offers exceptional compactness, linearity, and in‐memory search reliability, considerably outperforming the conventional ferroelectric CAMs for HD computation.

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Publication Details

Journal
Advanced Electronic Materials
Published
2025-10-13
DOI
https://doi.org/10.1002/aelm.202500421
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Time‐Domain Content‐Addressable Memory Based on Single Ambipolar Ferroelectric Memcapacitor for High‐Density and Highly‐Precise Distance Function Computation

Woo Young Choi, Jae Seung Woo, Minjeong Ryu, Sung In Cho et al.
Advanced Electronic Materials
Advanced Memory and Neural Computing
article

Time‐Domain Content‐Addressable Memory Based on Single Ambipolar Ferroelectric Memcapacitor for High‐Density and Highly‐Precise Distance Function Computation

Woo Young Choi, Jae Seung Woo, Minjeong Ryu, Sung In Cho, Yeonwoo Kim, J Jeon
article en

Abstract

Abstract Single ambipolar ferroelectric memcapacitor‐based time‐domain (TD) content‐addressable memory (CAM) is proposed and experimentally demonstrated. The proposed TD CAM design effectively resolves the critical challenges of limited integration density and computational reliability in conventional ferroelectric memcapacitor‐based capacitive CAMs. The band‐reject‐filter‐shaped and symmetric capacitance‐voltage characteristics with high dynamic range of a gated p‐i‐n diode‐structured ferroelectric memcapacitor are leveraged. This CAM performs dual‐edge search operations, where the Hamming distance (HD) between entry and query vectors is computed based on the modulation of the variable capacitance of cells. The propagation delay of the TD CAM output signal is linearly correlated with the computed HD, enabling improved search accuracy and sensing margin. The error‐free classification of previously unseen classes in a five‐way one‐shot learning task indicates the feasibility of the proposed TD CAM as an associative memory within memory‐augmented neural networks toward real‐world implementations. Moreover, modeling results confirm that the proposed operation scheme maintains robustness against process variations and interconnect parasitics in massive arrays of highly scaled devices. Overall, the proposed TD CAM array offers exceptional compactness, linearity, and in‐memory search reliability, considerably outperforming the conventional ferroelectric CAMs for HD computation.

Advanced Electronic MaterialsVol. 11(20)
Seoul National University (KR), Sogang University (KR)
Seoul National University, Ministry of Science and ICT, South Korea, Samsung
Openalex Percentile: Top 71%
Advanced Memory and Neural Computing
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