Hybrid ferroelectric-ionic memristive hardware for high scalability in-memory computing

) ratios with a storage capacity of 10 Gb. These results highlight the potential of this device as a hardware building block for scalable in-memory computing platforms.

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Publication Details

Journal
Nature Communications
Published
2026-05-21
DOI
https://doi.org/10.1038/s41467-026-72103-6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Hybrid ferroelectric-ionic memristive hardware for high scalability in-memory computing

Frances M. Ross, W. U. Jung, Youngchan Cho, Jiseong Im et al.
Nature Communications
Advanced Memory and Neural Computing
article

Hybrid ferroelectric-ionic memristive hardware for high scalability in-memory computing

Frances M. Ross, W. U. Jung, Youngchan Cho, Jiseong Im, Been Kwak, Hyunho Seok, Deok‐Hwang Kwon, Piush Behera, Feras Al-Dirini, Sojin Kim, Jinseok Hong, Jiwon You, Hwiin Ju, Jangsaeng Kim, Jeong-Han Kim, Wonjun Shin, Youngho Kang, Ryun-Han Koo, Yejin Hong, Kyunghwan Lee, Seung-Yong Lee, Qinyuan Xue, Daewon Ha, Jong-Ho Lee, Hyun-Min Kim, Daewoong Kwon, Suraj S. Cheema, Eugene Park, Dooyong Koh
article en

Abstract

) ratios with a storage capacity of 10 Gb. These results highlight the potential of this device as a hardware building block for scalable in-memory computing platforms.

Nature Communications
Seoul National University (KR), Incheon National University (KR), Sogang University (KR), Samsung (South Korea) (KR), Hanyang University (KR), Korea Institute of Science and Technology (KR), Massachusetts Institute of Technology (US), Sungkyunkwan University (KR)
Affordable and clean energy
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
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