Porous crystalline materials for memories and neuromorphic computing systems

G Ding, JY Zhao, K Zhou, Q Zheng, ST Han… - Chemical Society …, 2023 - pubs.rsc.org
Porous crystalline materials usually include metal–organic frameworks (MOFs), covalent
organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites …

Resistive random access memory (RRAM): an overview of materials, switching mechanism, performance, multilevel cell (MLC) storage, modeling, and applications

F Zahoor, TZ Azni Zulkifli, FA Khanday - Nanoscale research letters, 2020 - Springer
In this manuscript, recent progress in the area of resistive random access memory (RRAM)
technology which is considered one of the most standout emerging memory technologies …

A comprehensive review on emerging artificial neuromorphic devices

J Zhu, T Zhang, Y Yang, R Huang - Applied Physics Reviews, 2020 - pubs.aip.org
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

Nanostructured perovskites for nonvolatile memory devices

Q Liu, S Gao, L Xu, W Yue, C Zhang, H Kan… - Chemical Society …, 2022 - pubs.rsc.org
Perovskite materials have driven tremendous advances in constructing electronic devices
owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties …

Designing crystallization in phase-change materials for universal memory and neuro-inspired computing

W Zhang, R Mazzarello, M Wuttig, E Ma - Nature Reviews Materials, 2019 - nature.com
The global demand for data storage and processing has increased exponentially in recent
decades. To respond to this demand, research efforts have been devoted to the …

Memristor modeling: challenges in theories, simulations, and device variability

L Gao, Q Ren, J Sun, ST Han, Y Zhou - Journal of Materials Chemistry …, 2021 - pubs.rsc.org
This article presents a review of the current development and challenges in memristor
modeling. We review the mechanisms of memristive devices based on various …

Hardware implementation of memristor-based artificial neural networks

F Aguirre, A Sebastian, M Le Gallo, W Song… - Nature …, 2024 - nature.com
Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …

Floquet engineering of quantum materials

T Oka, S Kitamura - Annual Review of Condensed Matter …, 2019 - annualreviews.org
Floquet engineering, the control of quantum systems using periodic driving, is an old
concept in condensed matter physics dating back to ideas such as the inverse Faraday …

Electronic synapses made of layered two-dimensional materials

Y Shi, X Liang, B Yuan, V Chen, H Li, F Hui, Z Yu… - Nature …, 2018 - nature.com
Neuromorphic computing systems, which use electronic synapses and neurons, could
overcome the energy and throughput limitations of today's computing architectures …

Ferroelectric analog synaptic transistors

MK Kim, JS Lee - Nano letters, 2019 - ACS Publications
Neuromorphic computing is a promising alternative to conventional computing systems as it
could enable parallel computation and adaptive learning process. However, the …