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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

Memristor technology shows great promise for energy-efficient computing, yet it grapples with challenges like resistance drift and inherent variability. For filamentary Resistive RAM (ReRAM), one of the most investigated types of memristive…

In this work, a novel electrospun conductive polymer nanocomposite made of polycaprolactone with an exohedral complex made of multiwalled carbon nanotubes and fullerene C60 was prepared and characterized. The preparation was straightforward…

The present era has seen tremendous demands for low-cost electrochromic materials for visible-region multicolor display technology, paper-based, flexible, and wearable electronic devices, smart windows, and optoelectronic applications.…

Virtually all organic (opto)electronic devices rely on organic/inorganic interfaces with specific properties. These properties are, in turn, inextricably linked to the interface structure. Therefore, a change in structure can introduce a…

Materials Science · Physics 2022-04-21 Lukas Hörmann , Andreas Jeindl , Oliver T. Hofmann

The memristor can be used as non volatile memory (NVM) and for emulating neuron behavior. It has the ability to switch between low resistance $R_{on}$ and high resistance values $R_{off}$, and exhibit the synaptic dynamic behaviour such as…

Emerging Technologies · Computer Science 2018-09-28 Aidana Irmanova , Grant A. Ellis , Alex Pappachen James

The development of memristive device technologies has reached a level of maturity to enable the design of complex and large-scale hybrid memristive-CMOS neural processing systems. These systems offer promising solutions for implementing…

Emerging Technologies · Computer Science 2020-04-22 Elisabetta Chicca , Giacomo Indiveri

Shape memory structures are playing an important role in many cutting-edge intelligent fields. However, the existing technologies can only realize 4D printing of a single polymer or metal, which limits practical applications. Here, we…

Robotics · Computer Science 2023-12-25 Kewei Song , Chunfeng Xiong , Ze Zhang , Kunlin Wu , Weiyang Wan , Yifan Wang , Shinjiro Umezu , Hirotaka Sato

Spontaneous structural relaxation is intrinsic to glassy materials due to their metastable nature. For phase-change materials (PCMs), the resultant temporal change in electrical resistance seriously hamper in-memory computing (IMC)…

Spintronic devices based on antiferromagnetic (AFM) materials hold the promise of fast switching speeds and robustness against magnetic fields. Different device concepts have been predicted and experimentally demonstrated, such as…

Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to digital systems. Though many devices have emerged as candidates for…

Mesoscale and Nanoscale Physics · Physics 2023-10-05 Samuel Liu , Deji Akinwande , Dmitry Kireev , Jean Anne C. Incorvia

Colloidal magnetic particles embedded in an elastic polymer matrix constitute a smart material called ferrogel. It responds to an applied external magnetic field by changes in elastic properties, which can be exploited for various…

Soft Condensed Matter · Physics 2016-10-07 Peet Cremer , Hartmut Löwen , Andreas M. Menzel

On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential. While algorithmic…

Emerging Technologies · Computer Science 2019-10-09 M. E. Fouda , F. Kurdahi , A. Eltawil , E. Neftci

Electrical characteristics of a Co/TiO_x/Co resistive memory device, fabricated by two different methods are reported. In addition to crystalline TiO_2 layers fabricated via conventional atomic layer deposition (ALD), an alternative method…

Memristors have shown promising features for enhancing neuromorphic computing concepts and AI hardware accelerators. In this paper, we present a user-friendly software infrastructure that allows emulating a wide range of neuromorphic…

Neural and Evolutionary Computing · Computer Science 2022-07-19 Jinqi Huang , Spyros Stathopoulos , Alex Serb , Themis Prodromakis

Multifunctional capability, flexible design, rugged lightweight construction, and self-powered operation are desired attributes for electronics that directly interface with the human body or with advanced robotic systems. For these and…

Memristive systems emerge as strong candidates for the implementation of Resistive Random Access Memories (RRAM) and neuromorphic computing devices, as they can mimic the electrical analog behavior or biological synapses. In addition,…

Layered two-dimensional (2D) semiconductors have shown enhanced ion migration capabilities along their van der Waals (vdW) gaps and on their surfaces. This effect can be employed for resistive switching (RS) in devices for emerging…

Understanding the physical and chemical mechanisms occurring during the forming process and operation of an organic resistive memory device is a major issue for better performances. Various mechanisms were suggested in vertically stacked…

Heavy computational demands from artificial intelligence (AI) leads the research community to explore the design space for functional materials that can be used for high performance memory and neuromorphic computing hardware. Novel device…

Materials Science · Physics 2024-09-04 Xinye Li , Padma Srivari , Sayani Majumdar
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