READ ME File For 'Dataset in support of the thesis 'Neuromorphic computing of SiC based memristor''

Dataset DOI: 10.5258/SOTON/D3323

ReadMe Author: Dongkai Guo, University of Southampton 0009-0001-3901-312X

This dataset supports the thesis entitled 
AWARDED BY: Univeristy of Southampton
DATE OF AWARD: 2024

DESCRIPTION OF THE DATA
[This should include a detailed description of the data, how it was collected/created, any specialist software needed to view the data]
This dataset is collected by author myself. The electric measurement data were collected by keysight B1500A. The surface scan photo was collected by AFM, while the topviews were photoed by optic microscope.
The composition and chemical bonds were measured with XPS equipment. The crystallinity of the films were measured by XRD equipment. The cross-section of device were photoed by TEM and SEM.\
The reservoir computing network was built with python and the training data was collected by myself.

This dataset contains:
The data and the photos used to present the characteristics of my SiC-based memristor in chapter 4, 5 and 6.



Date of data collection: 12/13/2024

Information about geographic location of data collection: Compus of university Southampton

Licence:
CC-BY


Related publication:
An ultra high-endurance memristor using back-end-of-line amorphous SiC
Reservoir computing using back-end-of-line SiC-based memristors
Back‐End‐of‐Line SiC‐Based Memristor for Resistive Memory and Artificial Synapse

Date that the file was created: 12, 2024