Electric-Field-Induced Metal Filament Formation in Cobalt-Based CBRAM Observed by TEM

Choi, Yeon-Joon; Bang, Suhyun; Kim, Tae-Hyeon; Hong, Kyungho; Kim, Sung-Joon; Kim, Sungjun; Park, Byung‐Gook; Choi, Woo Young

doi:10.1021/acsaelm.3c00034

Cited by 5 publications

(2 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They quantified the best-performing electrode material using the Gibbs free energy of formation which was found to have an optimal value slightly above 0 kJ mol −1 . Other factors like alloyed metal electrodes [ 38 ] and the effect of electromigration [ 39 ] have also been reported in recent literature.…”

Section: Resistive Switchingmentioning

confidence: 99%

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Udaya Mohanan

2024

Nanomaterials

View full text Add to dashboard Cite

Neuromorphic computing has emerged as an alternative computing paradigm to address the increasing computing needs for data-intensive applications. In this context, resistive random access memory (RRAM) devices have garnered immense interest among the neuromorphic research community due to their capability to emulate intricate neuronal behaviors. RRAM devices excel in terms of their compact size, fast switching capabilities, high ON/OFF ratio, and low energy consumption, among other advantages. This review focuses on the multifaceted aspects of RRAM devices and their application to brain-inspired computing. The review begins with a brief overview of the essential biological concepts that inspire the development of bio-mimetic computing architectures. It then discusses the various types of resistive switching behaviors observed in RRAM devices and the detailed physical mechanisms underlying their operation. Next, a comprehensive discussion on the diverse material choices adapted in recent literature has been carried out, with special emphasis on the benchmark results from recent research literature. Further, the review provides a holistic analysis of the emerging trends in neuromorphic applications, highlighting the state-of-the-art results utilizing RRAM devices. Commercial chip-level applications are given special emphasis in identifying some of the salient research results. Finally, the current challenges and future outlook of RRAM-based devices for neuromorphic research have been summarized. Thus, this review provides valuable understanding along with critical insights and up-to-date information on the latest findings from the field of resistive switching devices towards brain-inspired computing.

show abstract

Section: Resistive Switchingmentioning

confidence: 99%

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Udaya Mohanan

2024

Nanomaterials

View full text Add to dashboard Cite

show abstract

“…ITO has been extensively researched and widely used as transparent electrodes in solar cells because of its wide bandgap (3.98 eV). [24][25][26][27] Therefore, ITO was utilized in this study to ensure transparency. However, when used as a single layer, ITO cannot block light in the IR range.…”

mentioning

confidence: 99%

Light‐Wavelength‐Selective Transparent ITO/Ag/ITO/Ag/ITO Structure for Functional Energy Applications

Choi,

Lee,

Ghosh

et al. 2023

Solar RRL

View full text Add to dashboard Cite

Is it possible to achieve efficient energy control without it being visible? If it could, it would enable human to produce energy in a transparent manner and manage energy usage intelligently by reducing consumption through building and vehicle windows, and other structures. Herein, thin films are created that are highly transparent and can filter light by selecting specific wavelengths. The films consist of multiple layers of ITO/Ag/ITO/Ag/ITO (IAIAI) that are designed to reflect light selectively using the Bragg reflection effect. These films are able to block an average of 89.6% of near‐infrared light in the 800–1400 nm range, while maintaining a high optical transparency of 69.2% (±0.1%) at 550 nm with an excellent sheet resistance value of 1.06 Ω □−1. The IAIAI structure is also used as electrodes for transparent photovoltaic (TPV) devices, allowing for the collection of photogenerated carriers while ensuring overall optical transparency. ZnO/NiO‐based TPV devices using IAIAI films as transparent conducting electrodes are found to have a high open‐circuit voltage value of 271 mV with a short‐circuit current density value of 1.55 mA cm−2. Thus, the multifunctional IAIAI films offer a range of possibilities for transparent energy devices.

show abstract

Neuromorphic Nanoionics for Human–Machine Interaction: From Materials to Applications

Liu,

Sun,

et al. 2024

Advanced Materials

View full text Add to dashboard Cite

Human‐machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device‐based neuromorphic computing technologies and their pivotal role in shaping the next‐generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion‐gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.This article is protected by copyright. All rights reserved

show abstract

Electric-Field-Induced Metal Filament Formation in Cobalt-Based CBRAM Observed by TEM

Cited by 5 publications

References 64 publications

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations

Light‐Wavelength‐Selective Transparent ITO/Ag/ITO/Ag/ITO Structure for Functional Energy Applications

Neuromorphic Nanoionics for Human–Machine Interaction: From Materials to Applications

Contact Info

Product

Resources

About