Advanced memory technology : functional materials and devices.: functional materials and devices. Volume 1 (2023)

• Record Type: Book
• Further Information: Note: Edited by Ye Zhou.
• Editors: (Semiconductor engineer), Zhou, Ye
• Contents: Memory Technology: Developments, Fundamentals, and Future Trends;Biomemristors as the Next Generation Memory Devices;Organic Resistive Memories for Neuromorphic Electronics;Low Frequency 1/f-conductance Noise in Memristors;Electrical Bistability by Creating Internal Electrical Field and Its Application in Emerging Two Terminal Electronic Memory Devices;Memory Devices Based on Low-dimensional Materials;Development, Challenges, and Future Opportunities of Spintronic Memory Devices;Dual-gate Ferroelectric Field-effect Transistors: An Emerging Computational Memory for Advanced Logic Operations;Stochastic Emerging Resistive Memory for Unconventional Computing;Indium-gallium-zinc-oxide (IGZO) Based ReRAM: Material Overview, Latest Development and Technology Perspective;Emerging Memristive Artificial Neurons for Energy-efficient Neuromorphic Electronic System;Memory, Memristive, and Neuromorphic Devices Based on Two Dimensional Transition Metal Dichalcogenides;In-sensor Computing Based on Two-terminal Optoelectronic Memristors;Memory Devices and Artificial Synapses with 2D Materials;Polymer-based Transistor-type Memory and Artificial Synapse;Amorphous Oxide Semiconductor Memristors: Brain-inspired Computation;Working Dynamics in Low Dimensional Materials Based Neuromorphic Devices;Halide Perovskites for Neuromorphic Computing;Silicon Oxide Based CBRAM Memory and Neuromorphic Properties;Oxide Neuromorphic Transistors for Brain-like Computing;Sensing–Storage–Computing Integrated Devices Based on Carbon Nanomaterials;Resistive Switching Based Neuromorphic Devices for Artificial Neural Network;Silicon-based Heterostructures for Optoelectronic Synaptic Devices;Hybrid Devices for Neuromorphic Application;Algorithmic Optimisation for Memristive Deep Learning Accelerators;Memristive Devices for Neuromorphic and Deep Learning Applications.
• Publisher Details: Cambridge : Royal Society of Chemistry
• Publication Date: 2023
• Extent: 1 online resource (763 pages)
• Subjects: 004.5; Computer storage devices
• Languages: English
• ISBNs: 9781839169953
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.