Materials that mimic axons promise more efficient computing

A team of researchers from Texas A&M University, Sandia National Laboratory in Livermore, and Stanford University are taking inspiration from the brain to design materials that can make computing more efficient. The new class of materials discovered is the first of its kind: it mimics the behavior of an axon, spontaneously propagating an electrical signal as it travels along a transmission line. These findings could be crucial to the future of computing and artificial intelligence.

This study is published in Nature.

Any electrical signal traveling through a metal conductor loses amplitude due to the metal’s natural resistance. Modern computer processing units (CPUs) and graphics processing units can contain about 50 kilometers of thin copper wires that move electrical signals around inside the chip. These losses add up quickly, requiring amplifiers to maintain the integrity of the pulse. These design constraints impact the performance of today’s densely interconnected chips.

To address this limitation, the researchers took inspiration from axons, a part of vertebrate nerve cells, or neurons, that can transmit electrical impulses outside the body of the nerve cell.

“Often we want to transmit a data signal from one location to another, more distant location,” said lead author Dr. Tim Brown, a postdoctoral researcher at Sandia National Lab and a former doctoral student in materials science and engineering at Texas A&M.

“For example, we might need to transmit an electrical impulse from the edge of a processor chip to transistors near its center. Even for the most conductive metals, resistance at room temperature continually dissipates transmitted signals. So we typically cut the transmission line and amplify the signal, which costs energy, time, and space. Biology does things differently: some signals in the brain are also transmitted over centimeter distances, but through axons made of much more resistive organic material, and without ever interrupting or amplifying the signals.”

According to Dr. Patrick Shamberger, associate professor in the Department of Materials Science and Engineering at Texas A&M University, axons are the highway of communication. They transmit signals from one neuron to a neighboring neuron. While neurons are responsible for processing signals, axons are like fiber optic cables that transmit signals from one neuron to its neighbor.

Much like the axonal model, the materials discovered in this study exist in a primed state, allowing them to spontaneously amplify a voltage pulse as it passes through the axon. The researchers exploited an electronic phase transition in lanthanum-cobalt oxide that makes it much more electrically conductive when heated. This property interacts with the small amounts of heat generated when a signal passes through the material, resulting in a positive feedback loop.

The result is a set of exotic behaviors not observed in ordinary passive electrical components (resistors, capacitors, inductors), including amplification of small disturbances, negative electrical resistances, and unusually large phase shifts in AC signals.

Shamberger says these materials are unique because they exist in a semi-stable “goldilocks state.” Electrical pulses don’t decay or exhibit thermal runaway or breakdown. Instead, the material naturally oscillates if it’s kept under constant current conditions. The researchers determined they could exploit this behavior to create spiking behavior and amplify a signal traveling along a transmission line.

“We are essentially exploiting internal instabilities in the material, which continue to strengthen an electronic pulse as it passes along the transmission line. Although this behavior was theoretically predicted by our co-author, Dr. Stan Williams, this is the first confirmation of its existence.”

These findings could prove pivotal to the future of computing, which is driving growing demand for energy. Data centers are expected to consume 8% of U.S. electricity by 2030, and artificial intelligence could significantly increase that demand. In the long term, this is a step toward understanding dynamic materials and using biological inspiration to promote more efficient computing.