Abstract

Emerging as an inevitable outcome of the big data era, long data are the massive amount of data that captures changes in the real world over a long period of time. In this context, recording and reading the data of a few terabytes in a single storage device repeatedly with a century-long unchanged baseline is in high demand. Here, we demonstrate the concept of optical long data memory with nanoplasmonic hybrid glass composites. Through the sintering-free incorporation of nanorods into the earth abundant hybrid glass composite, Young’s modulus is enhanced by one to two orders of magnitude. This discovery, enabling reshaping control of plasmonic nanoparticles of multiple-length allows for continuous multi-level recording and reading with a capacity over 10 terabytes with no appreciable change of the baseline over 600 years, which opens new opportunities for long data memory that affects the past and future.

Details

Title
High-capacity optical long data memory based on enhanced Young’s modulus in nanoplasmonic hybrid glass composites
Author
Zhang, Qiming 1 ; Xia, Zhilin 2 ; Yi-Bing, Cheng 3 ; Gu, Min 4 

 Laboratory of Artificial-Intelligence Nanophotonics and CUDOS, School of Science, Melbourne, VIC, Australia 
 Department of Materials Science and Engineering, Faculty of Engineering, Monash University, Clayton, VIC, Australia; School of Materials Science and Engineering, Wuhan University of Technology, Wuhan, Hubei, China 
 Department of Materials Science and Engineering, Faculty of Engineering, Monash University, Clayton, VIC, Australia; State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, Hubei, China 
 Laboratory of Artificial-Intelligence Nanophotonics and CUDOS, School of Science, Melbourne, VIC, Australia; Centre for Micro-Photonics, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC, Australia 
Pages
1-6
Publication year
2018
Publication date
Mar 2018
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2017036907
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.