About this Research Topic
In the modern era of information technology, due to the rapid developments in Big Data, the Internet of Things, and Real-Time Analytics, massive amounts of data need to be efficiently stored and processed. However, conventional von Neumann architecture based computing hardware and memories have been approaching their limits under the current technologies and also required a lot of time as well as energy in transporting data between memory and process. Whereas the human brain can rapidly and precisely process myriads of information via highly parallel computation with ultralow power consumption. Inspired by brain functions, synaptic devices and memristors have been gained more attention recently for simultaneous in-memory data processing and storage. The complete realization of both the device functions requires a flexible regulation of conductance and appropriate retention of the active material with hysteresis effect due to electrical, optical, or chemical stimulation.
Presently, various materials such as semiconductors, metal oxides, organic materials, and halide perovskites have been used to fabricate synaptic and memristor devices. Organic-inorganic halide perovskite has emerged as an attractive material for a wide range of optoelectronic applications due to high absorption characteristics over a wide spectrum, long diffusion lengths, bandgap tenability. However various imperfections, high-density defects, and also halide ion migration in the perovskite film provides tunable charge trapping capability which makes it suitable for synaptic and memristor application. Furthermore, the perovskite-based devices consume a very low amount of energy per event, which is pretty close to the energy consumption of a biological synapse in a human brain.
This Research Topic aims to collect the most recent research developments on perovskite-based synaptic devices and memristors for neuromorphic computing applications. More specifically, it includes mostly perovskite-based materials, new device structures, fabrication techniques, device stability along different device circuits and systems. Furthermore, this collection will help further the realization of memristive hardware of non-Von-Neumann computing, which will help to overcome memory bottleneck using ultralow power consumption.
Some of the potential research themes of interest, but are not limited to:
• Perovskite-based optoelectronic synaptic devices
• Perovskite memristors and resistive switching devices
• Modeling of memristive materials and devices
• Growth and fabrication techniques of synaptic devices
• Perovskite-based hybrid superstructure
• Advanced characterizations for perovskite materials and optoelectronic devices
• Stability of perovskite memristors
• Energy Efficiency of Memristors and Synaptic devices
• Rational circuit design and hardware for Neuromorphic applications
Keywords: synaptic device, memristor, perovskite, neuromorphic applications, optoelectronic device, energy efficiency
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