Information is processed by microprocessors in computers, data centers and smartphones by manipulating electrons passing through solid semiconductors. However, our brain has a specific mechanism as it processes information by controlling ions in a liquid medium. Scientists have long worked to create “ions” in an aqueous solution that mimics how the human brain processes information. Scientists believe that although ions in water move more slowly than electrons in semiconductors, the diversity of ionic species with different physical and chemical properties could be harnessed for richer and more diverse information processing.
Ionic transistors and diodes have so far only been created as individual components in laboratories; No one has ever managed to put numerous components together into a sophisticated circuit. However, research into ionic computing is still in its infancy. Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and DNA Script, a biotech startup, created an ion circuit using hundreds of ion transistors and performed a basic neural network arithmetic operation as the first step in making such groundbreaking research . The study was also published in the journal “Advanced Materials”, the chips mentioned are still in the prototype stage.
The researchers recently invented a method that was the basis for the novel ion transistor. The transistor consists of an aqueous solution of quinone molecules connected to two concentric ring electrodes and a porthole-shaped center disk electrode. The two ring electrodes electrochemically reduce and regulate the local pH around the center disc by generating and trapping hydrogen ions. When a voltage is applied, an electrochemical reaction causes an ion current to flow from the central disc into the water. Adjusting the local pH can increase or decrease the reaction rate, thereby increasing or decreasing the ionic current.
The next stage of their research was to design the pH-controlled ion transistor so that the disc current results from the addition of the disc voltage and an arithmetic “weight” parameter. This weight parameter represents the local pH gating of the transistor. The array of local pH values served as the weight matrix seen in neural networks. The transistors were arranged in a 16 x 16 array to extend the analog arithmetic multiplication of individual transistors to an analog matrix multiplication.
Matrix multiplication, the most common calculation in artificial intelligence neural networks, was used to analyze the ionic circuits. Based on an electrochemical machinery, the team’s ionic circuit performs matrix multiplication in water in an analogous manner. To perform matrix multiplication, microprocessors digitally manipulate electrons. The researchers emphasize that while electrochemical matrix multiplication in water may not be as fast or precise as digital microprocessors, it is attractive in its own right and has the potential to be energy efficient.
The ionic circuit also has the ability to speed up processes like DNA synthesis and others involved in brain networks. So far, only a few ionic species have been studied, including hydrogen and quinone ions. However, as more and more Ionic species are tried over time, information processing will only become more successful and diverse. The team speculates that neural networks could soon work on water-based ion circuits, which would be significantly slower but far 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 strives to harness the power of artificial intelligence for good.
Asif’s latest project is the development of an artificial intelligence media platform (Markechpost) that will revolutionize how people can find relevant news related to artificial intelligence, data science and machine learning.
Asif was featured by Onalytica in Who is 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 published by Onalytica (https://onalytica.com/blog/posts/interview-with-asif-razzaq/).