This book will cover 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.
Advanced memory technologies are impacting the information era, representing a vibrant research area of huge electronic industry interest. 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.
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;SensingStorageComputing 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
Prof. Ye Zhou is a professor in the Institute for Advanced Study, Shenzhen University. His research interests include organic/inorganic semiconductors, surface and interface physics, nanostructured materials, and nano-scale devices for technological applications, such as logic circuits, data storage, photonics and sensors.
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