Skip to main content
padlock icon - secure page this page is secure

Ag/TiO2 NPs/TiO2 TF/Si Based Non-Volatile Memristor Device for Neuromorphic Computing Applications

Buy Article:

$106.51 + tax (Refund Policy)

Memristor device is a very promising emerging component for a revolution of the memory and computing applications in the recent years. It could be enhancing the field of artificial intelligence and helping the patients, suffering from various kinds of autism disorders, as well as in neuromorphic computing, neural networks, etc. This research article proposes fabricated non-volatile memristor device for neuromorphic computing applications. The demonstrate memory is based on Ag/TiO2 NPs/TiO2 TF/Si layers’ structure and achieves better conductivity and storage capacity, which could improve the performance of the neuromorphic computing as compared to conventional ones. The fabrication method of the proposed multi-layer memristor is examine with well precise techniques, which overcome the previous challenges. The surface morphology of the device is analysed by field emission gun scanning electron microscopy (FEGSEM) and Energy dispersive X-ray system. The rise time (Tr) of 2.5 s and fall time (Tf) of 3 s are demonstrated under ON/OFF white light illumination. While X-ray diffraction depicted that titanium dioxide nano particle, (TiO2 NPs) are crystalline in nature. Moreover, Photoluminescence and Raman analysis justify crystalline nature also and increasing oxygen vacancies concentration with the heating effect of TiO2 NPs. The electrical analysis reveals the driving mechanism under different sweeping voltages during SET and RESET resulting in low resistance state (‘ON’). Finally, capacitance-voltage characteristic of the proposed memory device shows excellent charge storage capacity within the dynamic range of operation.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Memristor Devices; Neuromorphic Computing; Titanium Dioxide Nano Particles (TiO2 NPs); Titanium Dioxide Thin Film (TiO2 TF)

Document Type: Research Article

Affiliations: 1: Department of Electronics and Communication Engineering, National Institute of Technology Goa, Goa 403401, India 2: Department of Nanoscience and Engineering, Centre for Nano Manufacturing, INJE University Gimhae, 50834, Republic of Korea

Publication date: November 1, 2018

More about this publication?
  • Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more