Brain-like computation is possible on an atomic scale

A groundbreaking discovery at the University of Limerick has revealed for the first time that unconventional brain-like computation on the tiny scale of atoms and molecules is possible.

Researchers at the University of Limerick’s Bernal Institute have been working with an international team of scientists to create a new type of organic material that learns from its past behaviour.

The discovery of the ‘dynamic molecular switch’ that emulates synaptic behavior is revealed in a new study in the prestigious international journal Nature Materials.

The study was led by Damien Thompson, professor of molecular modeling in UL’s Department of Physics and director of SSPC, the Science Foundation Ireland’s Pharmaceuticals Research Center hosted by UL, together with Christian Nijhuis of the Center for Molecules and Brain-Inspired Nano Systems from the University of Twente and Enrique del Barco from the University of Central Florida.

Working during the lockdowns, the team developed a two-nanometer-thick layer of molecules, which is 50,000 times thinner than a strand of hair and remembers its history as electrons pass through it.

Professor Thompson explained that ‘the switching probability and the values ​​of the on/off states change continuously in the molecular material, which provides a disruptive new alternative to conventional silicon-based digital switches that can only be turned on or off.’

The recently discovered dynamic organic switch displays all the mathematical logic functions necessary for deep learning, successfully emulating the Pavlovian “call and response” brain-like synaptic behavior.

Researchers demonstrated the new material properties using extensive experimental characterization and electrical measurements supported by multiscale models ranging from predictive modeling of molecular structures at the quantum level to analytical mathematical modeling of electrical data.

To emulate the dynamic behavior of synapses at the molecular level, the researchers combined rapid electron transfer (similar to action potentials and rapid depolarization processes in biology) with slow diffusion-limited proton coupling (similar to the role of ions of biological calcium or neurotransmitters).

Since the electron transfer and proton pairing steps within the material occur on very different time scales, the transformation can emulate the plastic behavior of neuronal junctions of synapses, Pavlovian learning and all logic gates for digital circuits, simply by changing the applied voltage and the duration of voltage pulses during synthesis, they explained.

“This has been a big block project, with Chris, Enrique and I pushing each other through zoom meetings and mammoth email threads to bring our combined expertise in material modeling, synthesis and characterization to the point where we have could demonstrate these new computer brain-like properties,” explained Professor Thompson.

“The community has long known that silicon technology works completely different to how our brains work, and so we’ve been using new types of electronic materials based on soft molecules to emulate brain-like computer networks.”

The researchers explained that the method may in the future be applied to dynamic molecular systems driven by other stimuli such as light and coupled to different types of dynamic covalent bond formation.

This breakthrough opens up an entirely new range of adaptive and reconfigurable systems, creating new opportunities in sustainable and green chemistry, from the more efficient flow chemical production of pharmaceuticals and other value-added chemicals to the development of new organic materials for processing and memory-dense storage in large data centers.

‘This is just the beginning. We are already engaged in the expansion of this new generation of smart molecular materials, which is enabling the development of sustainable alternative technologies to address major energy, environmental and health challenges,’ explained Professor Thompson.

Professor Norelee Kennedy, vice president of research at UL, said: “Our researchers are continually finding new ways to make materials that are more effective and more sustainable. This latest discovery is very exciting, demonstrates the scope and ambition of our international collaborations, and showcases our world-leading ability at UL to encode useful properties in organic materials.”

reference: Wang Y, Zhang Q, Astier HPAG, et al. Dynamic molecular switches with hysteretic negative differential conductance that emulate synaptic behavior. Wet mother. 2022:1-9. doi: 10.1038/s41563-022-01402-2

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