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Localized Surface Plasmon Resonance-Mediated Charge Trapping/Detrapping for Core-Shell Nanorod-Based Optical Memory

Li Zhou, Su-Ting Han, Shiwei Shu

  • 1Department of Physics and Materials Science, City University of Hong Kong , Hong Kong, China.

ACS Applied Materials & Interfaces
|September 12, 2017
PubMed
Summary
This summary is machine-generated.

Researchers developed organic optical memory devices using gold-silver core-shell nanorods. These devices offer dual functionality for light sensing and data storage, advancing Internet of Things (IoT) applications.

Keywords:
Au@Ag nanorodsLSPRmultilevel data storageorganic memoryphototunable

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Optoelectronics

Background:

  • Moore's Law drives miniaturization, requiring versatile single devices for the Internet of Things (IoT).
  • Existing devices often lack integrated light sensing and data storage capabilities.

Purpose of the Study:

  • To propose and investigate organic optical memory devices with dual optoelectronic functionality.
  • To explore the use of gold-silver (Au@Ag) core-shell nanorods (NRs) for enhanced memory performance.

Main Methods:

  • Fabrication of Au@Ag core-shell nanorods with controlled morphology, size, and concentration.
  • Systematic study of phototunable memory behavior by varying silver shell thickness.
  • Utilizing localized surface plasmon resonance (LSPR) simulations to understand device mechanisms.

Main Results:

  • Demonstrated a large memory window of up to 19.7 V in the Au@Ag NRs-based memory device.
  • Achieved phototunable memory properties and multilevel data storage assisted by light.
  • Experimental and simulation results confirmed LSPR as the origin of the phototunable memory effect.

Conclusions:

  • Au@Ag core-shell NRs enable high-performance organic optical memory devices with dual functionality.
  • The phototunable memory property offers a new strategy for advanced optoelectronic applications.
  • These findings contribute to the development of next-generation IoT devices.