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Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in…

Neural and Evolutionary Computing · Computer Science 2015-05-19 Gerard David Howard , Larry Bull , Ben de Lacy Costello , Andrew Adamatzky , Ella Gale

Magnetic random access memory that uses magnetic tunnel junction memory cells is a high performance, non-volatile memory technology that goes beyond traditional charge-based memories. Today its speed is limited by the high magnetization of…

Reconfigurable intelligent surfaces (RIS) have been actively researched as a potential technique for future wireless communications, which intelligently ameliorate the signal propagation environment. In the conventional design, each RIS…

Information Theory · Computer Science 2022-03-17 Qingchao Li , Mohammed El-Hajjar , Ibrahim Hemadeh , Arman Shojaeifard , Alain A. M. Mourad , Bruno Clerckx , Lajos Hanzo

Photonic Random-Access Memories (P-RAM) are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data links. Emerging Phase Change Materials (PCMs) have been showed…

The growing demand for artificial intelligence and complex computing has underscored the urgent need for advanced data storage technologies. Spin-orbit torque (SOT) has emerged as a leading candidate for high-speed, high-density magnetic…

I review the advancements of atomic scale nanoelectronics towards quantum neuromorphics. First, I summarize the key properties of elementary combinations of few neurons, namely long-- and short--term plasticity, spike-timing dependent…

Emerging Technologies · Computer Science 2016-09-21 Enrico Prati

We provide a perspective on soft metamaterials and biomatter with a special emphasis on future research directions at the interface between material intelligence and adaptation.

Soft Condensed Matter · Physics 2025-07-15 Colin Scheibner , Michel Fruchart , Vincenzo Vitelli

Deployable structures, essential across various engineering applications ranging from umbrellas to satellites, are evolving to include soft, morphable designs where geometry drives transformation. However, a major challenge for soft…

We report a bistable organic memory made of a single organic layer embedded between two electrodes, we compare to the organic/metal nanoparticle/organic tri-layers device [L.P. Ma, J. Liu, and Y. Yang, Appl. Phys. Lett. 80, 2997 (2002)]. We…

Materials Science · Physics 2015-06-24 Dominique Vuillaume , Kamal Lmimouni , Denis Tondelier , Christophe Fery , Gunther Haas

Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent…

Emerging Technologies · Computer Science 2020-09-15 Andrew Adamatzky , Anna Nikolaidou , Antoni Gandia , Alessandro Chiolerio , Mohammad Mahdi Dehshib

Atomically thin layered two-dimensional materials, including transition-metal dichacolgenide (TMDC) and black phosphorus (BP), (1) have been receiving much attention, because of their promising physical properties and potential applications…

Materials Science · Physics 2016-02-17 Qi Feng , Faguang Yan , Wengang Luo , Kaiyou Wang?

Reversible bipolar nano-switches that can be set and read electronically in a solid-state two-terminal device are very promising for applications. We have performed molecular-dynamics simulations that mimic systems with oxygen vacancies…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 S. E. Savel'ev , A. S. Alexandrov , A. M. Bratkovsky , R. Stanley Williams

Rigidity is an emergent property of materials - it is not a feature of individual components that comprise the structure, but instead arises from interactions between many constituent parts. Recently, it has been recognized that…

Soft Condensed Matter · Physics 2025-08-27 Kelly Aspinwall , Tyler Hain , M. Lisa Manning

Recently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs). However, these circuits are constrained by the…

The memristors are expected to be fundamental devices for neuromorphic systems and switching applications. For example, the device made of a sandwiched layer of poly(N-vinylcarbazole) and reduced graphene composite between asymmetric…

Metallic oxides encased within Metal-Insulator-Metal (MIM) structures can demonstrate both unipolar and bipolar switching mechanisms, rendering them the capability to exhibit a multitude of resistive states and ultimately function as memory…

Mesoscale and Nanoscale Physics · Physics 2012-06-14 Marcus Wu Shihong , Themistoklis Prodromakis , Iulia Salaoru , Christofer Toumazou

The object of this article is to review the development of ultrahigh-density, nanoscale data storage, i.e., nanostorage. As a fundamentally new type of storage system, the recording mechanisms of nanostorage may be completely different to…

Materials Science · Physics 2007-05-23 J. C. Li

Reconfigurable intelligent surfaces (RISs) have flexible and exceptional performance in manipulating electromagnetic waves and customizing wireless channels. These capabilities enable them to provide a plethora of valuable activity-related…

Signal Processing · Electrical Eng. & Systems 2023-11-15 Xinyu Li , Jian Wei You , Ze Gu , Qian Ma , Long Chen , Jingyuan Zhang , Shi Jin , Tie Jun Cui

We report on an experimental study of current induced switching in perpendicular magnetic random access memory (MRAM) cells with variable resistance-area products (RAs). Our results show that in addition to spin transfer torque (STT),…

Mesoscale and Nanoscale Physics · Physics 2019-05-08 Goran Mihajlovic , Neil Smith , Tiffany Santos , Jui-Lung Li , Michael Tran , Matthew Carey , Bruce D. Terris , Jordan A. Katine

A resistive memory network that has no crossover wiring is proposed to overcome the hardware limitations to size and functional complexity that is associated with conventional analogue neural networks. The proposed memory network is based…

Artificial Intelligence · Computer Science 2012-01-31 Alex Pappachen James , Sima Dimitrijev
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