A discovery reveals that "brain-like computing" is possible at the molecular level

A breakthrough discovery by the University of Limerick in Ireland shows for the first time that unconventional brain-like computation is possible
at the smallest scale of atoms and molecules.

Researchers at the University of Limerick's Bernal Institute teamed up with an international team of scientists to create a new type of organic material that can learn
from past behavior.

A new study by the prestigious international journal Nature Materials reveals the discovery
of "dynamic molecular switches" that mimic synaptic behavior.

The study was co-led
by Damien Thompson, Professor of Molecular Modelling in UL's Department of Physics and Director of SSPC (Science Foundation Ireland Pharmaceutical Research Centre), sponsored by UL, and Christian Nijhuis, Center for Molecular and Brain-Inspired Nanosystems at the University of Twente, and Enrique del Barco at the University of Central Florida.

During the lockdown, the team developed a layer of molecules 2 nanometers thick, 50,000 times thinner than a hair, that remembers its history
as electrons pass through it.

Professor Thompson explains, "In molecular materials, switching probabilities and on/off state values are constantly changing, which provides a disruptive new option
for traditional silicon-based digital switches that can only be on or off.
”

The newly discovered dynamic organic switch shows all the mathematical logic functions required for deep learning, successfully simulating Pavlov's "call and respond" synaptic brain behavior
.

The researchers demonstrated the performance of the new materials through extensive experimental characterization and electrical measurements supported by multiscale modeling, from predictive modeling of molecular structures at the quantum level to analytical mathematical modeling
of electrical data.

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

They explain that since the electron transfer and proton coupling steps inside the material occur on very different timescales, the conversion can simulate synaptic neuronal connections, Pavlovian learning, and the plastic behavior of all logic gates of digital circuits, simply by varying the applied voltage and the duration
of the voltage pulse during synthesis.

Professor Thompson explains: "It was a great lockdown project where Chris, Enrique and I pushed each other through scaled meetings and a huge email process, bringing our team's combined skills in materials modeling, synthesis, and characterization to a point where
they could demonstrate these new brain-like computational properties.
"

"The scientific community has long known that silicon technology works quite differently than our brains, so we used new electronic materials based on soft molecules to simulate brain-like computing networks
.
"

The researchers explain that the method could in the future be applied to dynamic molecular systems driven by other stimuli, such as light, and coupled
to different types of dynamic covalent bonds.

This breakthrough unlocks a new range of adaptive and reconfigurable systems that create new opportunities for sustainable and green chemistry, from more efficient flow chemical production of pharmaceuticals and other value-added chemicals to the development of new organic materials
for high-density computing and storage in big data centers.

"This is just the beginning
.
We are already busy scaling up the next generation of smart molecular materials, enabling the development of sustainable alternative technologies to address major challenges in energy, environment and health," explains
Professor Thompson.

Professor Norelee Kennedy, UL Research Vice President, said: "Our researchers are constantly looking for new ways to
make more efficient and sustainable materials.
This latest discovery is very exciting, demonstrates the scope and ambition of our international collaboration, and demonstrates our world-leading ability
to encode useful properties into organic materials at UL.
" ”