Physics-Based Efficient Device Model for Fe-TFTs (Univ. of Florida)


A new technical paper titled "An efficient device model for ferroelectric thin-film transistors" was published by researchers at University of Florida. Abstract "Ferroelectric thin-film transistors (Fe-TFTs) have promising potential for flexible electronics, memory, and neuromorphic computing applications. Here, we report on a physics-based efficient device model for Fe-TFTs that effectivel... » read more

Survey of Energy Efficient PIM Processors


A new technical paper titled "Survey of Deep Learning Accelerators for Edge and Emerging Computing" was published by researchers at University of Dayton and the Air Force Research Laboratory. Abstract "The unprecedented progress in artificial intelligence (AI), particularly in deep learning algorithms with ubiquitous internet connected smart devices, has created a high demand for AI compu... » read more

Research Bits: May 28


Nanofluidic memristive neural networks Engineers from EPFL developed a functional nanofluidic memristive device that relies on ions, rather than electrons and holes, to compute and store data. “Memristors have already been used to build electronic neural networks, but our goal is to build a nanofluidic neural network that takes advantage of changes in ion concentrations, similar to living... » read more

Running More Efficient AI/ML Code With Neuromorphic Engines


Neuromorphic engineering is finally getting closer to market reality, propelled by the AI/ML-driven need for low-power, high-performance solutions. Whether current initiatives result in true neuromorphic devices, or whether devices will be inspired by neuromorphic concepts, remains to be seen. But academic and industry researchers continue to experiment in the hopes of achieving significant ... » read more

Research Bits: Mar. 19


Superconducting loops Researchers from University of California San Diego and University of California Riverside propose using superconducting loops to store and transmit information in a method similar to the human brain. “Our brains have this remarkable gift of associative memory, which we don't really understand,” said Robert C. Dynes, professor of physics at UC San Diego and preside... » read more

Analog Planar Memristor Device: Developing, Designing, and Manufacturing


A new technical paper titled "Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks" was published by researchers at Delft University of Technology and Khalifa University. Abstract: "Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation... » read more

Research Bits: December 5


Neuromorphic nanowires Researchers from UCLA and University of Sydney built an experimental computing system physically modeled after the biological brain. The device is composed of a tangled-up network of wires containing silver and selenium that were allowed to self-organize into a network of entangled nanowires on top of an array of 16 electrodes. The nanowire network physically reconfigure... » read more

Research Bits: Nov. 28


Switchable photodetector and neuromorphic vision sensor Researchers from the Institute of Metal Research at the Chinese Academy of Sciences built a device that can be switched between being a photodetector and neuromorphic vision sensor by adjusting the operating voltage. The trench-bridged GaN/Ga2O3/GaN heterojunction array device exhibits volatile and non-volatile photocurrents at low and hi... » read more

Research Bits: September 5


Layered TMD semiconductors Scientists from Tsinghua University investigated fabrication techniques for fabricating and engineering transition metal dichalcogenides (TMDs). By modulating TMDs with various methods, including phase engineering, defect engineering, doping, and alloying, the material class could provide a wide range of alternatives for high-quality layered semiconductors with st... » read more

Working With The NimbleAI Project To Push The Boundaries Of Neuromorphic Vision


At the end of 2022, the EU kicked off a cool project that aims to implement neuromorphic vision. But what is that? Let’s take a deeper look at the project and our contribution. First, if you are not familiar with Codasip Labs, I want to mention this briefly. Codasip Labs is in fact our innovation hub where we explore new technologies and try to contribute to the technology of the future. ... » read more

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