Advances in perovskite-based neuromorphic computing devices.

Area of Science:

• Materials Science
• Computer Engineering
• Neuroscience

Background:

• Contemporary computing faces limitations due to the von Neumann bottleneck.
• Neuromorphic computing devices mimic the human brain's architecture and function.
• Perovskite materials are crucial for photosensitive layers in neuromorphic devices due to high light absorption and carrier mobility.

Purpose of the Study:

• To review the latest research on perovskite-based neuromorphic computing devices.
• To summarize different structures and application scenarios of these devices.
• To discuss current challenges and future prospects in perovskite-based neuromorphic computing.

Main Methods:

• Literature review of recent advancements in perovskite-based neuromorphic computing.
• Analysis of various perovskite material structures and their impact on device performance.
• Examination of diverse application scenarios for these neuromorphic devices.

Main Results:

• Perovskite materials show significant promise for developing efficient neuromorphic computing devices.
• Different perovskite structures offer unique advantages for specific applications.
• The review consolidates current knowledge on device performance and application potential.

Conclusions:

• Perovskite-based neuromorphic computing is a rapidly advancing field with potential to surpass conventional computing.
• Further research is needed to address existing challenges and optimize device performance.
• Future development holds promise for more sophisticated brain-inspired computing systems.