Information is processed by microprocessors in computers, data centers and smartphones by manipulating electrons flowing through solid semiconductors. However, our brains have a distinct mechanism as they process information by controlling ions in a liquid medium. For a very long time, scientists have worked to create “ionics” in an aqueous solution that mimic the way the human brain processes information. Scientists believe that the variety of ionic species with different physical and chemical properties could be used for richer and more diverse information processing, despite the fact that ions in water move slower than electrons in water. semiconductors.
Ion transistors and diodes were created as individual components only in laboratories; no one has ever been able to combine many components to form a sophisticated circuit. The study of ion computing, however, is still in its infancy. Researchers from Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and DNA Script, a biotech start-up, created an ion circuit with hundreds of ion transistors and performed a fundamental neural network computational operation like first step towards producing such innovative research. The study was also published in the journal Advanced Materials, and the chips mentioned are still at the prototype stage.
Researchers recently invented a method that served as the basis for the new ion transistor. The transistor consists of an aqueous solution of quinone molecules connected to two concentric annular electrodes and a central electrode in the shape of a bull’s eye. The two ring electrodes electrochemically reduce and regulate the local pH around the central disk by creating and trapping hydrogen ions. An ion current flows from the central disk in the water due to an electrochemical reaction when a voltage is applied. By adjusting the local pH, the reaction rate can be accelerated or reduced, increasing or decreasing the ion current.
The next step in their research was to design the pH-triggered ion transistor so that the drive current results from adding the drive voltage and a “weight” parameter in arithmetic. This weight parameter represents the local pH gate of the transistor. The array of local pH values served as the weight matrix seen in the neural networks. The transistors were placed in a 16 x 16 array to extend the analog arithmetic multiplication of the individual transistors into an analog matrix multiplication.
Matrix multiplication, the most common computation in neural networks for artificial intelligence, has been used to analyze ion circuits. Based on electrochemical machines, the team’s ion circuit performs matrix multiplication in water analogically. To perform matrix multiplication, microprocessors digitally manipulate electrons. The researchers point out that while electrochemical matrix multiplication in water may not be as fast or accurate as digital microprocessors, it is attractive on its own and has the potential to be energy efficient.
The ion circuit also has the ability to speed up processes such as DNA synthesis and others involved in brain networks. Only a few ionic species, including hydrogen and quinone ions, have now been examined. However, as more and more ionic species are tried over time, information processing will only become more prosperous and diverse. The team speculates that neural networks could soon run on water-based ion circuits, which would be much slower but much more energy efficient.
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Asif Razzaq is an AI journalist and co-founder of Marktechpost, LLC. He is a visionary, entrepreneur and engineer who aspires to use the power of artificial intelligence for good.
Asif’s latest venture is the development of an artificial intelligence media platform (Marktechpost) that will revolutionize the way people can find relevant news related to artificial intelligence, data science and technology. machine learning.
Asif was featured by Onalytica in its ‘Who’s Who in AI? (Influential Voices & Brands)’ as one of the ‘Influential Journalists in AI’ (https://onalytica.com/wp-content/uploads/2021/09/Whos-Who-In-AI.pdf). His interview was also featured by Onalytica (https://onalytica.com/blog/posts/interview-with-asif-razzaq/).