Design of Inorganic Material for Brain-like Computing
In this blog, I will discuss the Design of Inorganic Material for Brain-like Computing. Imagine a computer that can think like you do or even understand you. While this future may not be here yet, it’s one step closer. Scientists and engineers have discovered a material that mimics neural signals responsible for transmitting information within the human brain.
Material That Changes with Temperature or Electrical Stimulus
We are getting closer to a reality where materials change with temperature or an electrical stimulus. The team studied β’-CuxV2O5, a chameleon-like material that changes in response to temperature or an electrical stimulus. They discovered how copper ions move inside the material, and how this movement causes electrons to shift and transform the material.
The research showed that copper ion movement is key to an electrical conductivity change. This change can be used to create electrical spikes, similar to how neurons function in the cerebral nervous system. This is a significant step in the Design of Inorganic Material for Brain-like Computing.
Natural Material
“Nature has given us materials with the appropriate behavior to mimic brain-like information processing. However, the materials studied so far had limitations,”
“The importance of this work is to show that we can design inorganic materials with improved neuromorphic properties. As we learn more, these materials will improve, opening up new paths for technological advancements in computing.”
Computer Mimicry of the Brain
A computer designed to mimic the brain’s neural networks produces similar results to the best brain-simulation supercomputer software used for neural-signaling research.
Movement of Copper Ions
A small movement of copper ions causes a significant change in conductance throughout the material. This movement transforms the material from an insulator to a conductor in response to temperature, voltage, or current changes. There’s a large gap between the brain’s energy consumption and today’s supercomputers. Neuromorphic (brain-inspired) computing lets us explore how close we can get to the brain’s energy efficiency using electronics.”
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