Memory, the ability to store information accessibly, is crucial for both computers and human brains. However, the methods they use to process information are quite different. The human brain performs computations directly on stored data, while computers must transfer data between a memory unit and a central processing unit (CPU). This separation, known as the von Neumann bottleneck, leads to increased energy costs for computers. For over 50 years, researchers have explored the concept of a memristor (memory resistor), an electronic component capable of both computing and storing data, akin to a synapse. Aleksandra Radenovic of the Laboratory of Nanoscale Biology (LBEN) at EPFL’s School of Engineering aimed for something even more ambitious: a functional nanofluidic memristive device that relies on ions rather than electrons and their oppositely charged counterparts (holes). This approach more closely mimics the human brain’s information processing and is more energy-efficient.
“Memristors have already been used to build electronic neural networks, but our goal is to build a nanofluidic neural network that takes advantage of changes in ion concentrations, similar to living organisms,” says Radenovic. Théo Emmerich, a postdoctoral researcher at LBEN, adds, “We have fabricated a new nanofluidic device for memory applications that is significantly more scalable and much more performant than previous attempts. This has enabled us, for the very first time, to connect two such ‘artificial synapses’, paving the way for the design of brain-inspired liquid hardware.” This research was recently published in Nature Electronics.
Memristors can switch between two conductance states—on and off—by manipulating an applied voltage. While electronic memristors use electrons and holes to process digital information, LBEN’s memristor can leverage a variety of ions. For their study, the researchers immersed their device in an electrolyte water solution containing potassium ions, though other ions, such as sodium and calcium, could also be used. “We can tune the memory of our device by changing the ions we use, which affects how it switches from on to off, or how much memory it stores,” explains Emmerich.
The device was fabricated on a chip at EPFL’s Center of MicroNanoTechnology by creating a nanopore at the center of a silicon nitride membrane. The researchers added palladium and graphite layers to create nano-channels for ions. As a current flows through the chip, the ions percolate through the channels and converge at the pore, where their pressure creates a blister between the chip surface and the graphite. When the graphite layer is lifted by the blister, the device becomes more conductive, switching its memory state to ‘on’. The graphite layer remains lifted even without a current, allowing the device to ‘remember’ its previous state. A negative voltage puts the layers back into contact, resetting the memory to the ‘off’ state.
“Ion channels in the brain undergo structural changes inside a synapse, so this also mimics biology,” says Yunfei Teng, an LBEN PhD student who worked on fabricating the devices—dubbed highly asymmetric channels (HACs) in reference to the shape of the ion flow toward the central pores.
Nathan Ronceray, another LBEN PhD student, notes that observing the HAC’s memory action in real-time is a novel achievement in the field. “Because we were dealing with a completely new memory phenomenon, we built a microscope to watch it in action.”
By Impact Lab
