Academic Journal
A Flexible Corn Starch‐Based Biomaterial Device Integrated with Capacitive‐Coupled Memristive Memory, Mechanical Stress Sensing, Synapse, and Logic Operation Functions
| Title: | A Flexible Corn Starch‐Based Biomaterial Device Integrated with Capacitive‐Coupled Memristive Memory, Mechanical Stress Sensing, Synapse, and Logic Operation Functions |
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| Authors: | Bai Sun, Yuanzheng Chen, Guangdong Zhou, Yongzan Zhou, Tao Guo, Shouhui Zhu, Shuangsuo Mao, Yong Zhao, Jinyou Shao, Yuning Li |
| Source: | Advanced Electronic Materials, Vol 9, Iss 3, Pp n/a-n/a (2023) |
| Publisher Information: | Wiley-VCH, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Electric apparatus and materials. Electric circuits. Electric networks LCC:Physics |
| Subject Terms: | artificial intelligence, biomaterials, capacitive‐coupled memristors, logic operation, mechanical stress sensors, synaptic performance, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4, Physics, QC1-999 |
| More Details: | Abstract Biomaterials‐based electronic devices (BEDs) have remarkable advantages such as biocompatibility and biodegradability, which are expected to have promising prospects in the development of green electronics such as wearable smart sensors and brain‐like synaptic devices. However, the development of BEDs is still in its infancy, and much work remains to be done before this technology can be widely used. Here, a novel corn starch‐based BED with a sandwiched structure of Ag/Corn starch:PVDF/ITO is developed, which has integrated multifunctional performance of capacitive‐coupled memristive memory, flexible mechanical stress sensing, synaptic application, and logic operation. Specifically, this device exhibits a wide memristive voltage operating range (1–16 V), a high bending response current (3.5–4.5 µA), long‐term durability synaptic performance, and logic operation capability. These advantageous characteristics endow this device has a good potential to be used in flexible wearable electronics and artificial intelligence. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2199-160X |
| Relation: | https://doaj.org/toc/2199-160X |
| DOI: | 10.1002/aelm.202201017 |
| Access URL: | https://doaj.org/article/8794e9ef6c1145cdb56fa49f4cd7f6bd |
| Accession Number: | edsdoj.8794e9ef6c1145cdb56fa49f4cd7f6bd |
| Database: | Directory of Open Access Journals |
| ISSN: | 2199160X |
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| DOI: | 10.1002/aelm.202201017 |
| Published in: | Advanced Electronic Materials |
| Language: | English |