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 …
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
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 …
technology which is considered one of the most standout emerging memory technologies …
A comprehensive review on emerging artificial neuromorphic devices
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …
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 …
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
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 …
decades. To respond to this demand, research efforts have been devoted to the …
Memristor modeling: challenges in theories, simulations, and device variability
This article presents a review of the current development and challenges in memristor
modeling. We review the mechanisms of memristive devices based on various …
modeling. We review the mechanisms of memristive devices based on various …
Hardware implementation of memristor-based artificial neural networks
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 …
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 …
concept in condensed matter physics dating back to ideas such as the inverse Faraday …
Electronic synapses made of layered two-dimensional materials
Neuromorphic computing systems, which use electronic synapses and neurons, could
overcome the energy and throughput limitations of today's computing architectures …
overcome the energy and throughput limitations of today's computing architectures …
Ferroelectric analog synaptic transistors
Neuromorphic computing is a promising alternative to conventional computing systems as it
could enable parallel computation and adaptive learning process. However, the …
could enable parallel computation and adaptive learning process. However, the …