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Towards Artificial Intelligence Hardware With 3D Integrated Ferroelectric Transistors. [PDF]
SmallSeok H, Kim G, Son S, Choi H, Kim T.
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Transparent photovoltaic memory for neuromorphic device
Nanoscale, 2021Self-powered transparent photovoltaic (TPV) artificial eyes and memory device.
Priyanka Bhatnagar +5 more
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Neuromorphic computing with memristive devices
Science China Information Sciences, 2018Technology advances in the last a few decades have resulted in profound changes in our society, from workplaces to living rooms to how we socialize with each other. These changes in turn drive further technology developments, as the exponential growth of data demands ever increasing computing power.
Wen Ma, Mohammed Affan Zidan, Wei D. Lu
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Covalent Organic Frameworks for Neuromorphic Devices
The Journal of Physical Chemistry Letters, 2023Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices.
Kui Zhou +8 more
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Review of candidate devices for neuromorphic applications
ESSDERC 2019 - 49th European Solid-State Device Research Conference (ESSDERC), 2019Artificial intelligence technology has attracted much attention in recent years, and technological progress of this technology is anticipated with the development of semiconductor technology. This talk focuses on synaptic mimic devices to realize artificial intelligence with semiconductor memory technology.
Jong-Ho Lee 0002 +12 more
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Memristors and Memristive Devices for Neuromorphic Computing
2014Memristors are an important emerging technology for memory and neuromorphic computing applications. In this chapter, we review the fundamentals of the memistor framework developed by Leon Chuan nearly 40 years ago, and examine resistive switching phenomena as the quintessential example of physical memristive systems.
Patrick Sheridan, Wei Lu
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Ferroelectric Devices for Neuromorphic Computing
ECS Meeting Abstracts, 2022Neuromorphic computing inspired by the neural network systems of the human brain enables energy efficient computing for big-data processing. A neural network is formed by thousands or even millions of neurons which are connected by even a higher number of synapses. Neurons communicate with each other through the connected synapses.
Qing-Tai Zhao +5 more
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Proton Conducting Neuromorphic Materials and Devices
Chemical ReviewsNeuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine
Yifan Yuan +7 more
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Neuromorphic devices for electronic skin applications
Materials HorizonsThis paper illustrates future research directions for neuromorphic e-skin devices and their applications.
Chandrashekhar S. Patil +13 more
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Hybrid Devices for Neuromorphic Applications
2023The world always seeks new materials, devices and technologies for a better future, and thus researchers keep exploring the possibilities. Advanced memory technology also aims to make the world better, comfortable, accessible and explorable. In this direction, hybrid devices consisting of dissimilar materials stacked or fused together can be considered
Shobith M. Shanbogh +2 more
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