iontronic memristor

New “Iontronic Memristor” Could Revolutionize Brain-Like Computing Using Only Salt and Water

Scientists from the Netherlands and South Korea say they have made a significant leap towards artificially replicating the human brain by developing a device called the “iontronic memristor.” 

Researchers say this novel device, barely larger than a human hair, functions as an artificial synapse, mimicking the brain’s unique ability to process and share information. 

“The brain’s computing principles (neurons connected by synapses) and information carriers (ions in water) both differ fundamentally from those of conventional computers,” researchers wrote. “Building on this distinction, we present an aqueous memristor that emulates the brain’s short-term synaptic plasticity features through ion transport in water, mirroring the natural processes in the brain.” 

In their findings, recently published in the Proceedings of the National Academy of Sciences, researchers highlighted that the iontronic memristor marks a significant departure from earlier models designed to mimic the brain’s communication pathways. Moreover, the device uniquely emulates the dynamic processes of human synapses in real time, using only salt and water to closely replicate how neurons transmit information naturally.

This simplicity and fidelity to biological processes represent a significant advance in neuromorphic computing, which aims to recreate the efficiency and functionality of the human brain.

The Quest to Mimic the Human Brain

The human brain is an exceedingly efficient system, capable of performing complex computational tasks more efficiently than the most advanced modern supercomputers while consuming little energy. 

This impressive capability has driven scientists in the last few decades to try and develop neuromorphic systems that could revolutionize computing by significantly reducing power consumption and enhancing performance in tasks involving pattern recognition, learning, and real-time decision-making.

A fundamental component of neuromorphic engineering is a deep understanding of how the human brain operates at multiple levels, from individual neurons to complex circuits and overall architectural frameworks. 

It goes without saying that artificially replicating the brain’s methods of representing information, adapting to local changes, and evolving over time through synaptic plasticity is a formidable challenge.

Until recently, most attempts to develop brain-like computers have involved using solid materials. This fundamentally differs from how the brain naturally operates using only water and dissolved ions. 

How the Iontronic Memristor Works

In their findings, researchers explain that the iontronic memristor comprises a tapered microfluidic channel that houses a salt solution. When an electrical signal is applied, ions within the solution reposition themselves along the channel, altering their density and the device’s electrical conductivity. 

This change mimics the synaptic plasticity in human brains—where connections between neurons strengthen or weaken over time based on activity.

Unlike traditional electronic devices that use electrons or holes as information carriers and respond only to electrical signals, the iontronic memristor uses ions, replicating the electrical and chemical communication in biological systems. 

This feature enables it to mimic the more complex aspects of neuronal communication, potentially leading to more advanced and capable artificial intelligence systems.

“While artificial synapses capable of processing complex information already exist based on solid materials, we now show for the first time that this feat can also be accomplished using water and salt,” Tim Kamsma, a PhD candidate at Utrecht University and lead study author said in a statement. “We are effectively replicating neuronal behavior using a system that employs the same medium as the brain.” 

Potential Benefits of Replicating the Brain

Successfully emulating the brain’s superior natural processing capabilities would be transformative and open the door to developing highly advanced computing systems. 

These systems would feature machines that are much more adaptive and intelligent than the current generation of artificial intelligence, significantly boosting their capabilities and effectiveness. 

For example, developing neuromorphic technologies could lead to advanced neural networks that can better understand and interact with the world, greatly enhancing automation and machine learning systems’ efficiency and capabilities.

Moreover, the energy efficiency of brain-like computers could significantly reduce the environmental impact of large data centers and computing systems, which currently consume vast amounts of electricity and contribute to global warming.

Researchers emphasized the potential for the iontronic memristor to improve the energy efficiency of computing tasks, a critical consideration in an increasingly digital world. As the technology matures, it could pave the way for computers that think and process information like a human brain.

With the Iontronic Memristor, How Soon Will We Start Seeing Brain-Like Computers? 

While the development of the iontronic memristor is a promising step toward advanced neuromorphic computing, lead research author Kamsma highlighted that the technology is still in its infancy. 

So far, the device has demonstrated its theoretical potential and the ability to emulate simple brain-like functions. However, scaling up this novel method to the complexities of an entire human brain remains a significant challenge. 

Researchers suggest that the next steps in advancing the iontronic memristor technology involve several vital developments. This includes integrating multiple devices to create circuits that couple numerous channels, leveraging the available flexible fabrication methods. This integration is critical for scaling up the technology to more complex applications. 

Additionally, there is a focus on optimizing these devices to exhibit strong conductance modulation at lower voltages. Such improvements would align the device’s operating voltages closer to those naturally occurring in biological systems. These advancements are pivotal for developing more energy-efficient and biologically accurate brain-like computing systems.

Despite these remaining challenges, researchers hope their recent work will ultimately represent a significant step towards developing computing systems that may one day think and learn just like humans. 

“It represents a crucial advancement toward computers not only capable of mimicking the communication patterns of the human brain but also utilizing the same medium,” explained Kamsma. “Perhaps this will ultimately pave the way for computing systems that replicate the extraordinary capabilities of the human brain more faithfully.”

Tim McMillan is a retired law enforcement executive, investigative reporter and co-founder of The Debrief. His writing typically focuses on defense, national security, the Intelligence Community and topics related to psychology. You can follow Tim on Twitter: @LtTimMcMillan.  Tim can be reached by email: or through encrypted email: