A team of physicists have developed an ionic circuit, a processor based on the motions of charged atoms and molecules in an aqueous solution rather than electrons in a solid. The findings published in Advanced Materials on 23 August 2022 claim the technology might be the next development in brain-like computing since it is more similar to how the brain transmits information.
Ion transport—the movement of charged molecules known as ions across a liquid medium—is a critical component of signal transmission in the brain. Although scientists have found it incredibly difficult to duplicate the brain’s extraordinary processing capability, they have speculated that a comparable system—pushing ions through an aqueous solution—might be used for computing. This might offer some intriguing benefits despite being slower than traditional silicon-based computing.
For instance, ions can be produced from various molecules, each of which has unique characteristics that can be used in various ways. Similar technology is used in IonQ but instead of an aqueous solution, an electromagnetic field is used, a technology called trapped ion.
Their choice of an atom is influenced by the fact that the ions can retain their quantum state for a very long time. If ionic circuits is explored and found useful and scalable, quantum computing companies could them to build their devices.
But first, researchers must demonstrate that it is feasible, which is what Jung and his colleagues Han Sae Jung, Jun Wang, Henry Hinton, Maxime Fournier, Adrian Horgan, Xavier Godron, Robert Nicol, and Donhee Ham have been working on. Their first work was designing a working ionic transistor—a device that switches or enhances a signal. Their most recent development involved assembling many such transistors into an ionic circuit.
The ionic transistor runs electrochemically in a bare aqueous solution of quinones with no fluidic guides, channel materials, or ion-selective media. It has a central disk electrode encircled by a concentric pair of ring electrodes. In the quinone solution, a stream of hydrogen ions is produced when a voltage is applied to the center disk. The two ring electrodes simultaneously alter the pH of the solution to gate, varying the ionic current. To produce current, the transistor physically multiplies a “weight” parameter defined by the ring pair gating with the disk voltage.
However, matrix multiplication, a mathematical process involving many multiplications, is frequently used in neural networks. The researchers organized these electrochemically gated ionic transistors into a 16 x 16 array. This scalability is aided by CMOS electronics, which can combine a huge number of electrodes. They use physical or analog, multiply-accumulate (MAC) operations to show the value of an array-scale ionic circuit.
Though promising, Ionic circuits have obvious limitations. Since the 16 currents cannot be resolved independently when the MAC operations of the columns are performed in parallel, the MAC operations had to be performed column by column sequentially rather than concurrently. This slows down the already sluggish technology.
At the device level, the ionic transistor in its current form has a response time of 26 ms, a size scale of 10’s m, inner and outer ring diameters of 36 and 62 m, and uses as much as 11 nW for gating but is inferior to solid-state electronic transistors in integrated circuits.
Nonetheless, the team’s accomplishment is a step toward more complex ionic computing. The next step will be to inject more molecules into the system to see if this allows the circuit to process more complicated data. Ionics aims to complement electronics by offering novel characteristics like using various ionic charge carriers rather than competing with electronics.