JOURNAL ARTICLE

Resistive Switching of the Tetraindolyl Derivative in Ultrathin Films: A Potential Candidate for Nonvolatile Memory Applications

Abstract

Bipolar resistive switching using organic molecule is very promising for memory applications owing to their advantages, such as simple device structure, low manufacturing cost, stability, and flexibility. Herein we report Langmuir-Blodgett (LB) and spin-coated-film-based bipolar resistive switching devices using organic material 1,4-bis(di(1H-indol-3-yl)methyl)benzene (Indole1). The pressure-area per molecule isotherm (π-A), Brewster angle microscopy (BAM), atomic force microscopy (AFM), and scanning electron microscopy (SEM) were used to formulate an idea about the organization and morphology of the organic material onto thin films. On the basis of the device structure and measurement protocol, it is observed that the device made up of Indole1 shows nonvolatile resistive random access memory (RRAM) behavior with a very high memory window (∼106), data sustainability (5400 s), device yield (86.7%), and repeatability. The oxidation-reduction process and electric-field-driven conduction are the keys behind such switching behavior. Because of very good data retention, repeatability, stability, and a high device yield, the switching device designed using compound Indole1 may be a potential candidate for memory applications.

Keywords:
Materials science Resistive random-access memory Non-volatile memory Thin film Nanotechnology Optoelectronics Scanning electron microscope Yield (engineering) Electrode Chemistry Composite material

Metrics

30
Cited By
1.93
FWCI (Field Weighted Citation Impact)
63
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Photoreceptor and optogenetics research
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
Neural Networks and Reservoir Computing
Physical Sciences →  Computer Science →  Artificial Intelligence
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