Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
First Hardware Demonstration of Fully Integrated Hafnia-based Multimodal Neuromorphic Computing Platform
- Authors
- Park, Eun Chan; Song, Minsuk; Kim, Jangsaeng; Lee, Jongwoo; Koo, Ryun-Han; Im, Jiseong; Shin, Wonjun; Kwon, Daewoong
- Issue Date
- Jan-2026
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Citation
- 2025 IEEE International Electron Devices Meeting (IEDM), pp 1 - 4
- Pages
- 4
- Indexed
- SCOPUS
- Start Page
- 1
- End Page
- 4
- ISSN
- 0163-1918
2156-017X
- Abstract
- We demonstrate for the first time a hafnia-based multimodal neuromorphic computing (HMNC) platform via co-integration of volatile and nonvolatile FeTFTs. Material-device co-optimization of the FeTFTs enables diverse functionalities for multimodal data processing. Full hardware demonstration achieves robust performance for multimodal MNIST data (88%) and emotion/sentiment recognition (66%), offering a scalable and energy-efficient neuromorphic solution.
- Files in This Item
- Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Related Researcher
- Kwon, Daewoong
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)