Editorial: Focus on organic materials, bio-interfacing and processing in neuromorphic computing and artificial sensory applications

van de Burgt, Yoeri; Santoro, Francesca; Tee, Benjamin; Alibart, Fabien

doi:10.1088/2634-4386/ad06ca

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…2 Most of the neuromorphic functions accomplished thus far are based on the simulation of the electric pulse pattern using organic polymer devices. 3–5 However, an analog of biological synapses, and especially the modulation of a chemical synapse in a water-based medium, remains very demanding with these organic polymer-based devices. Traditional complementary metal oxide semiconductor (CMOS) technology has been successful in mimicking synaptic behavior but requires energy-intensive processes.…”

Section: Introductionmentioning

confidence: 99%

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Graphene oxide–DNA/graphene oxide–PDDA sandwiched membranes with neuromorphic function

Bong,

Grebenchuk,

Nikolaev

et al. 2024

Nanoscale Horiz.

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Section: Introductionmentioning

confidence: 99%

“…19 Water soluble polyelectrolytes usually use as a countercharge for the conjugated polyelectrolytes. 20–22 Natural polyelectrolyte coacervates 23 also tend to serve in neuromorphic devices owing to the dielectric layer formation. 3,24…”

Section: Introductionmentioning

confidence: 99%

Graphene oxide–DNA/graphene oxide–PDDA sandwiched membranes with neuromorphic function

Bong,

Grebenchuk,

Nikolaev

et al. 2024

Nanoscale Horiz.

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“…Neuromorphic photonics represents a cutting-edge, multidisciplinary realm at the confluence of artificial intelligence (AI), photonics, and neuroscience [1]. Its overarching goal is nothing short of a transformative evolution in computing, seamlessly uniting the foundational principles of neuromorphic computing with the swiftness and efficiency inherent in photonics [2]. This inventive paradigm employs light-based neurons and optical synapses to emulate the intricate behaviors of human brain cells closely, resulting in specialized hardware uniquely tailored for the domains of AI and machine learning [3].…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic Photonics Circuits: Contemporary Review

Kutluyarov,

Zakoyan,

Voronkov

et al. 2023

Nanomaterials

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Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain. Using optics and photonics principles, neuromorphic devices can execute intricate computations swiftly and with impressive energy efficiency. This innovation holds promise for advancing artificial intelligence and machine learning while addressing the limitations of traditional silicon-based computing. Neuromorphic photonics could herald a new era of computing that is more potent and draws inspiration from cognitive processes, leading to advancements in robotics, pattern recognition, and advanced data processing. This paper reviews the recent developments in neuromorphic photonic integrated circuits, applications, and current challenges.

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Artificial Neuron Based on the Bloch-Point Domain Wall in Ferromagnetic Nanowires

Sánchez,

Caso,

Aliev

2024

Materials

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Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state and the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits leak and refractory properties, the NW was placed in a homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of artificial neural networks (ANNs) based on reversible changes in the topology of magnetic NWs.

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Editorial: Focus on organic materials, bio-interfacing and processing in neuromorphic computing and artificial sensory applications

Cited by 3 publications

References 7 publications

Graphene oxide–DNA/graphene oxide–PDDA sandwiched membranes with neuromorphic function

Graphene oxide–DNA/graphene oxide–PDDA sandwiched membranes with neuromorphic function

Neuromorphic Photonics Circuits: Contemporary Review

Artificial Neuron Based on the Bloch-Point Domain Wall in Ferromagnetic Nanowires

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