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Published on October 18th, 2017 | By: April Gocha, PhD

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Video: Perovskites that forget could enable materials that learn

Published on October 18th, 2017 | By: April Gocha, PhD

[Image above] Credit: Argonne National Laboratory; YouTube

 

 

Scientifically speaking, the past week has been weird.

 

First, I read about how scientists made a discovery that brings us a step closer towards developing invisible materials.

 

Then came headlines about astronomers finding half of the missing matter in the universe (was anyone else unaware it was missing?).

 

Plus, former Blink-182 guitarist Tom DeLonge announced that he’s formed a consortium of scientists and engineers that is going to pursue so-called exotic science, including a transportation vehicle that reduces “current travel limits of distance and time.” 

 

And then things got weird.

 

For instance, scientists have demonstrated entanglement swapping at a record long distance of 103 km of optical fiber. Entanglement is weird science, even for scientists—Einstein himself called entanglement “spooky action at a distance.”

 

As if entanglement wasn’t strange enough on its own, another team of researchers just reported that even more atoms can be entangled in a quantum relationship than previously thought—reportedly 16 million atoms can be entangled in a 1-cm crystal.

 

Then this week, scientists announced that they’ve observed the collision of two neutron stars, a massive element-forming event that occurred some 130 million years ago. The material that makes up neutron stars is incredibly dense—one teaspoon of the stuff weighs as much as Mt. Everest.

 

And back here on earth, researchers at Argonne National Lab now report that they’re working on a material that, like the human brain, can learn and forget. The electronic material, a quantum perovskite, adaptively responds to repeated stimuli.

 

Inspired by how the human brain forgets to make way for new information storage and becomes desensitized to repeated stimuli, the quantum perovskite can forget when repeatedly exposed to a persistent stimulus, allowing the material to learn and adapt.

Credit: Argonne National Laboratory; YouTube

 

“When scientists add or remove a proton (H+) from the perovskite (SmNiO3 (SNO)) lattice, the material’s atomic structure expands or contracts dramatically to accommodate it in a process called ‘lattice breathing,’” Badri Narayanan, an Argonne assistant material scientist and co-author of the study, says in an Argonne press release. “The material’s electronic properties also evolve with this process.”

 

Repeatedly adding and removing a proton eventually makes the material calm down, reducing its lattice breathing. The material becomes desensitized, altering its electronic properties as it does so.

 

“This behavior allows the material to be effectively programmed, like a computer, by the proton doping. Essentially, a scientist could insert or remove protons to control whether or not the perovskite would allow a current,” according to the release.

 

The idea is that such adaptive materials could be used for complex computational models and learning machines, which could have abilities for facial recognition and reasoning, for example.

 

“These simulations, which quite closely match the experimental results, are inspiring whole new algorithms to train neural networks to learn,” says Argonne postdoctoral scholar Mathew Cherukara.

 

The open-access paper, published in Nature Communications, is “Habituation based synaptic plasticity and organismic learning in a quantum perovskite” (DOI: 10.1038/s41467-017-00248-6).

 

 

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