With the goal of developing molecular neuromorphic computing technology

Artificial intelligence and machine learning have the potential to revolutionize today’s workplace, but their development is hampered by the fact that the current state of the art in electronics is not up to par.

In a move to develop devices that can mimic how neurons work in the brain, researchers at the Indian Institute of Science, Bengaluru (IISc) have developed neuromorphic devices using organic materials that have not been used before. This is what her work has been aiming for since 2014.

Organic materials were considered the worst of all material types in the manufacture of computer components because they were fragile and unstable. “We chose this genre as our horse of the race because we felt that if there were a way to solve these performance issues, the functionalities we could extract from these materials could blow up anything else that exists says Sreetosh Goswami from the Center for Nanoscience and Engineering (CeNSE), IISc.

He and his collaborators have published significant work in this field since 2017 natural materials, nature nanotechnology, Advanced Materials and Nature, proving that organic materials can compute reliably and in some respects even outperform inorganic materials. “The molecular system (transition metal complexes of azoaromatic ligands) is an idea of ​​my father, Prof. Sreebrata Goswami,” says Dr. Sreetosh Goswami in an email The Hindu.

The plastic brain

The human brain that inspired the researchers’ work, in the words of Sreebrata Goswami, who is now at CeNSE, IISc, “far exceeds any artificial electronic analogue in terms of its ability to learn, perceive and make decisions”. Its remarkable performance consumes only 20 watts of power in a space of 1260 cc. Some of the desirable properties it exhibits include connectivity and reconfigurability.

“The neurons in the brain operate on the edge of chaos with a highly non-linear feedback mechanism. We are looking for materials that can capture such properties, an elusive goal…” explains Prof. Sreebrata Goswami.

Many functionalities

Molecular materials are characterized by interactions between molecules and ions, which then present a multidimensional landscape of parameter space that can be tinkered with to develop appropriate functionalities. The question they asked in a recent article Advanced Materials was whether they could manipulate these many-body interactions to achieve plasticity and reconfigurability in the devices. To do this, they measured the current-voltage curves as a function of temperature over a wide range. You could capture functionalities that include bipolar, unipolar, non-volatile, and volatile memristors.

In Dr. In Sreetosh Goswami’s words, this is an “insane amount of variability” to describe which the group had to design a mathematical space that allows for nearly every possible characteristic variation desirable in neuromorphic devices. “The same device could be operated in both analog and digital regimes simply by tuning the activation energy,” says Dr. Sreetosh Goswami.

To make it work

The challenge was that when making low-temperature measurements in molecular memristors, the switching responses were quenched or flattened out as the temperature was lowered. “We could make it work because our molecular devices are robust and the switching mechanisms have a thermodynamic component that still occurs when the device is cooled,” says Santi Prasad Rath, post-doc at CeNSE, IISc and the first author of the article published in Advanced Materials.

dr Sreetosh Goswami says: “We are quite confident that we will be able to develop a functional neuromorphic platform based on our metal complexes, which could be the world’s first molecular neuromorphic technology.”