2D-Materials-Based Electronic Circuits (KAUST and TSMC)


A special edition article titled "Electronic Circuits made of 2D Materials" was just published by Dr. Mario Lanza, KAUST Associate Professor of Material Science and Engineering, and Iuliana Radu, corporate researcher at TSMC. This special issue covers 21 articles from leading subject matter experts, ranging from materials synthesis and their integration in micro/nano-electronic devices and c... » read more

Fabricating FeFET Devices with Silicon-Doped Hafnium Oxide As A Ferroelectric Layer


A new technical paper titled "Synergistic Approach of Interfacial Layer Engineering and READ-Voltage Optimization in HfO2-Based FeFETs for In-Memory-Computing Applications" was published by researchers at Fraunhofer IPMS, GlobalFoundries, and TU Bergakademie Freiberg. Abstract (partial) "This article reports an improvement in the performance of the hafnium oxide-based (HfO2) ferroelectric... » read more

L-FinFET Neuron For A Highly Scalable Capacitive Neural Network (KAIST)


A new technical paper titled "An Artificial Neuron with a Leaky Fin-Shaped Field-Effect Transistor for a Highly Scalable Capacitive Neural Network" was published by researchers at KAIST (Korea Advanced Institute of Science and Technology). “In commercialized flash memory, tunnelling oxide prevents the trapped charges from escaping for better memory ability. In our proposed FinFET neuron, t... » read more

Biocompatible Bilayer Graphene-Based Artificial Synaptic Transistors (BLAST) Capable of Mimicking Synaptic Behavior


This new technical paper titled "Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing" was published by researchers at The University of Texas at Austin and Sandia National Laboratories. Abstract "CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to para... » read more

Research Bits: Aug. 8


Speeding NVM encryption Researchers from North Carolina State University propose a way to speed up encryption and file system performance for non-volatile memory (NVM). “NVMs are an emerging technology that allows rapid access to the data, and retains data even when a system crashes or loses power,” said Amro Awad, an assistant professor of electrical and computer engineering at North C... » read more

3 Emerging Technologies: Memristors, Spintronics & 2D Materials


New technical paper titled "Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware" from researchers at University College London and University of Cambridge. Abstract "In a data-driven economy, virtually all industries benefit from advances in information technology—powerful computing systems are critically important for rapid technological pr... » read more

Neuromorphic Computing: Challenges, Opportunities Including Materials, Algorithms, Devices & Ethics


This new research paper titled "2022 roadmap on neuromorphic computing and engineering" is from numerous researchers at Technical University of Denmark, Instituto de Microelectrónica de Sevilla, CSIC, University of Seville, and many others. Partial Abstract: "The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the chall... » read more

Brain-Inspired Computing Device That Programs/RePrograms HW On Demand With Electrical Pulses


Multiple academic and government institutions jointly developed a new computer device that can "program and program computer hardware on demand through electrical pulses," according to this Argonne National Lab news release. The device's key materials are neodymium, nickel and oxygen and is referred to as a perovskite nickelate. This new research paper titled "Reconfigurable perovskite nicke... » read more

Technical Paper Round-Up: July 5


New technical papers added to Semiconductor Engineering’s library this week. [table id=36 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for... » read more

MEMprop: Gradient-based Learning To Train Fully Memristive SNNs


New technical paper titled "Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays" from IEEE researchers. Abstract "We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally arising voltage spikes. These spikes emitted by memristive dynamics are anal... » read more

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