Research Topic

Perovskite-based Synaptic Devices and Memristors

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


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

22 May 2021 Abstract
19 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

22 May 2021 Abstract
19 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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