Posted in | News | Nanofluidics | Graphene

Long-Term Memory Discovered in 2D Nanofluidic Channels

Researchers from the National Graphene Institute (NGI) at The University of Manchester and the École Normale Supérieure (ENS), Paris, illustrated the Hebbian learning in artificial nanochannels, where the channels exhibited short-and long-term memory.

Image Credit: The University of Manchester

Details of their study have been published in the journal Science.

Hebbian learning is a technical terminology created by Donald Hebb in 1949, illustrating the method of learning by repeatedly performing an action.

Hebbian learning is a well-established learning instrument. It is the method where people “get used” to performing an action. Comparable to what happens in neural networks, the scientists were able to illustrate the presence of memory in two-dimensional (2D) channels akin to atomic-scale tunnels with heights differing from numerous nanometers down to angstroms (10-10 m).

This was performed using simple salts (including table salt) liquefied in water flowing via nanochannels and by the application of voltage (<1 V) scans/pulses.

The study highlights the significance of the latest development of ultrathin nanochannels. Two versions of nanochannels were employed in this study. The “pristine channels” were from the Manchester team headed by Prof. Radha Boya, which are acquired by the assembly of 2D layers of MoS2.

These channels have minimal surface charge and are atomically even. Prof. Lyderic Bocquet’s team at ENS created the “activated channels;” these possess high surface charge and are acquired by electron beam etching of graphite.

A vital difference between solid-state and biological memories is that the former functions using electrons, while the latter possesses ionic flows central to their working. While solid-state silicon or metal oxide-based “memory devices” that can “learn” have long been created, this is a crucial first illustration of “learning” by basic ionic solutions and low voltages.

The memory effects in nanochannels could have future use in developing nanofluidic computers, logic circuits, and in mimicking biological neuron synapses with artificial nanochannels.

Lyderic Bocquet, Study Co-Lead Author and Professor, École Normale Supérieure

The study’s co-lead author Prof. Radha Boya added that “the nanochannels were able to memorize the previous voltage applied to them and their conductance depends on their history of the voltage application.”

This means the earlier voltage history can rise (potentiate in terms of synaptic activity) or drop (depress) the nanochannel’s conduction.

Dr. Abdulghani Ismail from the National Graphene Institute and the study’s co-first author said, “We were able to show two types of memory effects behind which there are two different mechanisms. The existence of each memory type would depend on the experimental conditions (channel type, salt type, salt concentration, etc.).”

The mechanism behind memory in ‘pristine MoS2 channels’ is the transformation of non-conductive ion couples to a conductive ion polyelectrolyte, whereas for ‘activated channels’ the adsorption/desorption of cations (the positive ions of the salt) on the channel’s wall led to the memory effect.

Paul Robin, Study Co-First Author, École Normale Supérieure

Dr. Theo Emmerich from ENS and the study’s co-first author also stated, “our nanofluidic memristor is more similar to the biological memory when compared to the solid-state memristors.”

This finding could have applications for the future, spanning from low-power nanofluidic computers to neuromorphic applications.

Journal Reference:

Robin, P., et al. (2022) Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels. Science.


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