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Full Description
Advanced memory technologies are impacting the information era, representing a vibrant research area of huge interest in the electronics industry. The demand for data storage, computing performance and energy efficiency is increasing exponentially and will exceed the capabilities of current information technologies.
Alternatives to traditional silicon technology and novel memory principles are expected to meet the need of modern data-intensive applications such as "big data" and artificial intelligence (AI). Functional materials or methodologies may find a key role in building novel, high speed and low power consumption computing and data storage systems.
This book covers functional materials and devices in the data storage areas, alongside electronic devices with new possibilities for future computing, from neuromorphic next generation AI to in-memory computing.
Summarizing different memory materials and devices to emphasize the future applications, graduate students and researchers can systematically learn and understand the design, materials characteristics, device operation principles, specialized device applications and mechanisms of the latest reported memory materials and devices.
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 Memories 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 Systems;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 Synapses;Amorphous Oxide Semiconductor Memristors: Brain-inspired Computation;Working Dynamics in Low-dimensional Material-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 Applications;Algorithmic Optimisation for Memristive Deep Learning Accelerators;Memristive Devices for Neuromorphic and Deep Learning Applications
