The development of novel hardware devices and computational substrates is rapidly emerging to support the need for temporal/sequential data processing, real-time computing, or pattern recognition. We are facing a shift from neuromorphic hardware based on standard microelectronics processes and digital components toward materials and physical substrates with complex electrical behavior that mimic natural neuronal networks. The development of hardware-based data processing, instead of software-based computing, requires a novel class of neuromorphic devices based on the fabrication, characterization, and integration of inorganic and organic materials, and exploiting various physical mechanisms. Theoretical studies have addressed the potentially disruptive nature of a neuromorphic approach based on novel hardware, however, the experimental investigation of neuromorphic materials is still in its infancy.
The overall goal of this Research Topic is to identify and address the fundamental aspects and the technological opportunities of novel hardware systems embedding in their structure the capabilities of neural networks. Different classes of materials will be considered such as oxides, 2D systems, organic materials, ferroelectric or magnetic materials, nanostructured and nanocomposite systems, bringing in (exploiting) different electronic and ionic conduction regimes and various resistive switching mechanisms, also today named memristive devices. Technological challenges, such as the downscaling of the devices, the integration of different materials and devices with standard electronic hardware, and the upscaling of novel fabrication approaches will be highlighted. Multidisciplinary approaches aiming at the development of new physical concepts and bio-inspired paradigms will receive particular attention.
The aim of this Research Topic is the cross-fertilization between the material science community and the neuroscience and neuromorphic engineering communities. We welcome any type of contribution (Original Research manuscripts, Reviews, Perspectives) on novel device concepts and systems for brain-inspired computation and data processing based on a large variety of materials, such as (list not exhaustive):
• phase change and materials
• charge trapping
• valence change, electrochemical and thermochemical systems
• ferroelectric materials
• magnetic materials
• Mott metal-insulator materials
• organic materials
• nanoparticle/nanowire assembled systems
• percolating networks
• bio-inspired materials
The development of novel hardware devices and computational substrates is rapidly emerging to support the need for temporal/sequential data processing, real-time computing, or pattern recognition. We are facing a shift from neuromorphic hardware based on standard microelectronics processes and digital components toward materials and physical substrates with complex electrical behavior that mimic natural neuronal networks. The development of hardware-based data processing, instead of software-based computing, requires a novel class of neuromorphic devices based on the fabrication, characterization, and integration of inorganic and organic materials, and exploiting various physical mechanisms. Theoretical studies have addressed the potentially disruptive nature of a neuromorphic approach based on novel hardware, however, the experimental investigation of neuromorphic materials is still in its infancy.
The overall goal of this Research Topic is to identify and address the fundamental aspects and the technological opportunities of novel hardware systems embedding in their structure the capabilities of neural networks. Different classes of materials will be considered such as oxides, 2D systems, organic materials, ferroelectric or magnetic materials, nanostructured and nanocomposite systems, bringing in (exploiting) different electronic and ionic conduction regimes and various resistive switching mechanisms, also today named memristive devices. Technological challenges, such as the downscaling of the devices, the integration of different materials and devices with standard electronic hardware, and the upscaling of novel fabrication approaches will be highlighted. Multidisciplinary approaches aiming at the development of new physical concepts and bio-inspired paradigms will receive particular attention.
The aim of this Research Topic is the cross-fertilization between the material science community and the neuroscience and neuromorphic engineering communities. We welcome any type of contribution (Original Research manuscripts, Reviews, Perspectives) on novel device concepts and systems for brain-inspired computation and data processing based on a large variety of materials, such as (list not exhaustive):
• phase change and materials
• charge trapping
• valence change, electrochemical and thermochemical systems
• ferroelectric materials
• magnetic materials
• Mott metal-insulator materials
• organic materials
• nanoparticle/nanowire assembled systems
• percolating networks
• bio-inspired materials
