Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation
Abstract Organic memristors have emerged as leading candidates for “soft” biorealistic systems due to their intrinsic processability, biocompatibility, low power consumption, and low cost. They are highly compatible with wearable and flexible technologies, ultimately enabling seamlessly integrable biorealistic architectures, such as wearable in‐sensor computing systems. However, conventional organic memristors have notoriously been limited by low device yield and reliability, primarily due to the inherent semicrystallinity of mainstream conjugated (macro‐) molecules. In this context, utilizing a nonconjugated radical polymer can dramatically mitigate these issues by leveraging its intrinsic memristivity, amorphous nature, and the molecular tunability of the nonconjugated backbones. This work demonstrates a high‐yield and multifunctional organic memory device and a soft in‐sensor computing architecture based on a radical polymer. Specifically, this study achieves an on/off ratio of >10 6 , state retention of over 4 × 10 5 s, stable switching performance over 500 cycles, and remarkable flexibility, all with a very high yield (>95%) in an organic memristive array. Additionally, the polymer's intrinsic chemical sensitivity is leveraged for application in soft in‐sensor computing. This work presents a radical molecular engineering strategy to enhance the physical properties of organic memristive materials on demand, significantly broadening the scope of organic materials for next‐generation data processing technologies.
Authors
- Youngdo Jeong (ORCID: https://orcid.org/0000-0003-3514-9094)
- Sung Gap Im (ORCID: https://orcid.org/0000-0002-2802-6398)
- Byung Chul Jang (ORCID: https://orcid.org/0000-0002-2254-7918)
- H.J. Lee
- Seung‐Yeol Jeon (ORCID: https://orcid.org/0000-0001-7950-9050)
- Jaehyoung Ko (ORCID: https://orcid.org/0000-0002-2122-9328)
- Ji Eon Kwon (ORCID: https://orcid.org/0000-0001-5382-3690)
- Yongho Joo (ORCID: https://orcid.org/0000-0002-1149-9105)
- Dongseok Kwon (ORCID: https://orcid.org/0000-0001-7676-8938)
- Namju Kim
- Quynh H. Nguyen (ORCID: https://orcid.org/0000-0002-3881-5446)
- Sanghan Lee (ORCID: https://orcid.org/0000-0002-5807-864X)
- Seongeon Jin
- Daeun Kim (ORCID: https://orcid.org/0000-0002-9131-8764)
- Joohwan Eo
Institutions
- Seoul National University (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Kyungpook National University (KR)
- Gwangju Institute of Science and Technology (KR)
- Hanyang University (KR)
- Korea Institute of Science and Technology (KR)
- Korea University of Science and Technology (KR)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1002/adfm.202516603
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- Korea Institute of Science and Technology
- National Research Foundation of Korea