According to the news, new computer chips made by modeling the neural network in our brain may be released in the next ten years, thanks to a new material developed. Here are the details…
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Scientists from the KTH Royal Institute of Technology and Stanford University in Stockholm have discovered that memory components made with a titanium carbide compound called MXene show extraordinary potential to complement classical transistor technology.
Electrochemical random access memory, or ECRAM, acts like a synaptic cell in an artificial network, providing a one-stop shop for data storage and processing. The findings, published in Advanced Functional Materials, suggest that MXenes could play a fundamental role in the development of neuromorphic computers that are closer to the human brain and are thousands or even hundreds of thousands of times more energy efficient than today’s conventional computers.
KTH Associate Professor and lead author Max Hamedi confirmed in a statement on the subject that the technology uses the same processes as cmos wafer assembly, integrating 2D material layers onto silicon, thus a true hybrid integration with back-of-the-line processes. He also said:
These new computers will be based on components that can have multiple states and perform in-memory computation. Therefore, we will be able to produce special-purpose computer blocks (within 5-10 years) where memory and transistors combine, making them at least 1000 times more energy efficient than the best computers we have for AI and simulation tasks today. The calculation even shows 1 million times energy efficiency for certain algorithms.
In addition, he said, slightly faster write speeds are seen than the other ECRAMs shown, meaning that if we scaled 2D ECRAMs to nano size, they could be as fast as transistors in today’s computers, which means they can be fused into our existing computers using the CMOS technology process.
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