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CC BY V4.0, Open Access
Thesis
MODELING AND ANALYTICAL STUDY OF NATURAL ORGANIC MEMRISTORS FOR NEUROMORPHIC COMPUTING
Washington State University
Master of Science (MS), Washington State University
05/2025
DOI:
https://doi.org/10.7273/000007425
Abstract
The need for faster and more energy-efficient chips is growing in the era of artificial intelligence. However, the conventional computing architecture suffers from the Von-Neumann bottleneck caused by the lag in data transfer between memory and processors. Neuromorphic computing systems offer an alternative to overcome this bottleneck. Similar to how neurons and synapses work in the human brain, this technology carries out memory and processing functions in the same cell, reducing the time required to transfer data between memory and processor. Memristive devices are promising candidates for implementing neuromorphic computing systems. In recent years, several materials for organic-based memristors have been under investigation, showing a promise for sustainability by reducing e-waste with environmentally friendly disposal. Honey, in particular, has been a viable dielectric thin-film for resistive switching, offering the benefits of being dissolvable and eco-friendly. However, the progress in advancing this technology is limited by a lack of understanding of the switching mechanism that dictates the device functionality. In particular, no physical model exists to explain the behavior of organic memristors. This paper proposes a physics-based numerical model to explain the I-V characteristics of an organic Ag/Honey/ITO memristor. Field-dependent filament nucleation and gap formation are used to describe the SET and RESET processes. To derive the temperature and field, carrier continuity and heat equations are self-consistently solved within an FEM solver. A 3D axisymmetric structure is constructed to perform the simulation. The primary conduction mechanism used in this work is phonon-assisted hopping. During the SET and RESET state, Gibb's free energy minimization determines the filament and gap evolution. The model
accurately accounts for the SET/RESET characteristics of the Honey memristor, providing insights into the resistive switching behavior from a thermodynamic point of view. The results will be beneficial in optimizing the device's performance and implementing it in a neuromorphic system.
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Details
- Title
- MODELING AND ANALYTICAL STUDY OF NATURAL ORGANIC MEMRISTORS FOR NEUROMORPHIC COMPUTING
- Creators
- Emdadul Huq Minhaj
- Contributors
- Feng Zhao (Chair)Tutku Karacolak (Committee Member)Hang Gao (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Engineering and Computer Science (VANC)
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Number of pages
- 75
- Identifiers
- 99901221251201842
- Language
- English
- Resource Type
- Thesis