Disk Triboelectric Nanogenerator-Based Nonvolatile Memory toward Smart Identification System

Jonghyeon Yun, Hyeonhee Roh, Jieun Choi, Dongyeop Gu, Daewon Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

With the rapid advancement of the Internet of things (IoT), security issues of the IoT are emerging because the wireless networks for conventional IoT are easily exposed to hacking. By storing the critical data in a physically separate space, these issues can be suppressed. The nonvolatile memory (NVM) is an attractive solution because the stored data are not erased even after turning off the power. However, the NVM consumes the power for operating and remaining data are exposed to attack. Hence, NVM with high security and low power operation is highly required for IoT platforms. Herein, a disk triboelectric nanogenerator-based NVM (DTNVM) is developed. The DTNVM can be operated with low power because the reading process of stored data is conducted with triboelectricity. Since the ternary system is adopted, 23 to 119 trits can be stored at the DTNVM by changing the sampling time. The identification information is stored at the DTNVM and 91.3% of consistency of the data with a range of 10% tolerance is recorded as result of the reading. Based on the result, the DTNVM is expected to be utilized in the near future as a next-generation NVM and for safe identification systems at the IoT.

Original languageEnglish
Article number2102536
JournalAdvanced Functional Materials
Volume31
Issue number28
DOIs
Publication statusPublished - 9 Jul 2021

Keywords

  • k-mean clustering
  • nonvolatile memory
  • security
  • smart electronics
  • triboelectric nanogenerators

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