Tag Archives: Brian Kiraly

Baby steps toward a quantum brain

My first quantum brain posting! (Well, I do have something that seems loosely related in a July 5, 2017 posting about quantum entanglement and machine learning and more. Also, I have lots of item on brainlike or neuromorphic computing.)

Getting to the latest news, a February 1, 2021 news item on Nanowerk announces research in to new intelligent materials that could lead to a ‘quantum brain’,

An intelligent material that learns by physically changing itself, similar to how the human brain works, could be the foundation of a completely new generation of computers. Radboud [university in the Netherlands] physicists working toward this so-called “quantum brain” have made an important step. They have demonstrated that they can pattern and interconnect a network of single atoms, and mimic the autonomous behaviour of neurons and synapses in a brain.

If I understand the difference between the work in 2017 and this latest work, it’s that in 2017 they were looking at quantum states and their possible effect on machine learning, while this work in 2021 is focused on a new material with some special characteristics.

A February 1, 2021 Radboud University press release (also on EurekAlert), which originated the news item, provides information on the case supporting the need for a quantum brain and some technical details about how it might be achieved,

Considering the growing global demand for computing capacity, more and more data centres are necessary, all of which leave an ever-expanding energy footprint. ‘It is clear that we have to find new strategies to store and process information in an energy efficient way’, says project leader Alexander Khajetoorians, Professor of Scanning Probe Microscopy at Radboud University.

‘This requires not only improvements to technology, but also fundamental research in game changing approaches. Our new idea of building a ‘quantum brain’ based on the quantum properties of materials could be the basis for a future solution for applications in artificial intelligence.’

Quantum brain

For artificial intelligence to work, a computer needs to be able to recognise patterns in the world and learn new ones. Today’s computers do this via machine learning software that controls the storage and processing of information on a separate computer hard drive. ‘Until now, this technology, which is based on a century-old paradigm, worked sufficiently. However, in the end, it is a very energy-inefficient process’, says co-author Bert Kappen, Professor of Neural networks and machine intelligence.

The physicists at Radboud University researched whether a piece of hardware could do the same, without the need of software. They discovered that by constructing a network of cobalt atoms on black phosphorus they were able to build a material that stores and processes information in similar ways to the brain, and, even more surprisingly, adapts itself.

Self-adapting atoms

In 2018, Khajetoorians and collaborators showed that it is possible to store information in the state of a single cobalt atom. By applying a voltage to the atom, they could induce “firing”, where the atom shuttles between a value of 0 and 1 randomly, much like one neuron. They have now discovered a way to create tailored ensembles of these atoms, and found that the firing behaviour of these ensembles mimics the behaviour of a brain-like model used in artificial intelligence.

In addition to observing the behaviour of spiking neurons, they were able to create the smallest synapse known to date. Unknowingly, they observed that these ensembles had an inherent adaptive property: their synapses changed their behaviour depending on what input they “saw”. ‘When stimulating the material over a longer period of time with a certain voltage, we were very surprised to see that the synapses actually changed. The material adapted its reaction based on the external stimuli that it received. It learned by itself’, says Khajetoorians.

Exploring and developing the quantum brain

The researchers now plan to scale up the system and build a larger network of atoms, as well as dive into new “quantum” materials that can be used. Also, they need to understand why the atom network behaves as it does. ‘We are at a state where we can start to relate fundamental physics to concepts in biology, like memory and learning’, says Khajetoorians.

If we could eventually construct a real machine from this material, we would be able to build self-learning computing devices that are more energy efficient and smaller than today’s computers. Yet, only when we understand how it works – and that is still a mystery – will we be able to tune its behaviour and start developing it into a technology. It is a very exciting time.’

Here is a charming image illustrating the reasons for a quantum brain,

Courtesy: Radboud University

Here’s a link to and a citation for the paper,

An atomic Boltzmann machine capable of self-adaption by Brian Kiraly, Elze J. Knol, Werner M. J. van Weerdenburg, Hilbert J. Kappen & Alexander A. Khajetoorians. Nature Nanotechnology (2021) DOI: https://doi.org/10.1038/s41565-020-00838-4 Published: 01 February 2021

This paper is behind a paywall.

A query into the existence of silicene

There’s some fascinating work on silicene at the Argonne National Laboratory which questions current scientific belief as per a July 25, 2014 news item on Nanowerk (Note: A link has been removed),

Sometimes, scientific findings can shake the foundations of what was once held to be true, causing us to step back and re-examine our basic assumptions.

A recent study (“Silicon Growth at the Two-Dimensional Limit on Ag(111)”) at the U.S. Department of Energy’s Argonne National Laboratory has called into question the existence of silicene, thought to be one of the world’s newest and hottest two-dimensional nanomaterials. The study may have great implications to a multi-billion dollar electronics industry that seeks to revolutionize technology at scales 80,000 times smaller than the human hair.

A July 24, 2014 Argonne National Laboratory news release by Justin H.S. Breaux , which originated the news item, describes both silicene and silicon in preparation for the discussion about whether or not silicene exists,

Silicene was proposed as a two-dimensional sheet of silicon atoms that can be created experimentally by super-heating silicon and evaporating atoms onto a silver platform. Silver is the platform of choice because it will not affect the silicon via chemical bonding nor should alloying occur due to its low solubility. During the heating process, as the silicon atoms fall onto the platform, researchers believed that they were arranging themselves in certain ways to create a single sheet of interlocking atoms.

Silicon, on the other hand, exists in three dimensions and is one of the most common elements on Earth. A metal, semiconductor and insulator, purified silicon is extremely stable and has become essential to the integrated circuits and transistors that run most of our computers.

Both silicene and silicon should react immediately with oxygen, but they react slightly differently. In the case of silicon, oxygen breaks some of the silicon bonds of the first one or two atomic layers to form a layer of silicon-oxygen. This, surprisingly, acts a chemical barrier to prevent the decay of the lower layers.

Because it consists of only one layer of silicon atoms, silicene must be handled in a vacuum. Exposure to any amount of oxygen would completely destroy the sample.

This difference is one of the keys to the researchers’ discovery. After depositing the atoms onto the silver platform, initial tests identified that alloy-like surface phases would form until bulk silicon layers, or “platelets” would precipitate out, which has been mistaken as two-dimensional silicene.

The news release next describes how the scientists solved the puzzle,

“Some of the bulk silicon platelets were more than one layer thick,” said Argonne scientist Nathan Guisinger of Argonne’s Center for Nanoscale Materials. “We determined that if we were dealing with multiple layers of silicon atoms, we could bring it out of our ultra-high vacuum chamber and bring it into air and do some other tests.”

“Everybody assumed the sample would immediately decay as soon as they pulled it out of the chamber,” added Northwestern University graduate student Brian Kiraly, one of the principal authors of the study. “We were the first to actually bring it out and perform major experiments outside of the vacuum.”

Each new series of experiments presented a new set of clues that this was, in fact, not silicene.

By examining and categorizing the top layers of the material, the researchers discovered silicon oxide, a sign of oxidation in the top layers. They were also surprised to find that particles from the silver platform alloyed with the silicon at significant depths.

“We found out that what previous researchers identified as silicene is really just a combination of the silicon and the silver,” said Northwestern graduate student Andrew Mannix.

For their final test, the researchers decided to probe the atomic signature of the material.

Materials are made up of systems of atoms that bond and vibrate in unique ways. Raman spectroscopy allows researchers to measure these bonds and vibrations. Housed within the Center for Nanoscale Materials, a DOE Office of Science User Facility, the spectroscope allows researchers to use light to “shift” the position of one atom in a crystal lattice, which in turn causes a shift in the position of its neighbors. Scientists define a material by measuring how strong or weak these bonds are in relation to the frequency at which the atoms vibrate.

The researchers noticed something oddly familiar when looking at the vibrational signatures and frequencies of their sample. Their sample did not exhibit characteristic vibrations of silicene, but it did match those of silicon.

“Having this many research groups and papers potentially be wrong does not happen often,” says Guisinger. “I hope our research helps guide future studies and convincingly demonstrates that silver is not a good platform if you are trying to grow silicene.”

Here’s an image illustrating the vibrational signatures of what scientists had believed to be silicene,

Argonne researchers investigating the properties of silicene (a one-atom thick sheet of silicon atoms) compared scanning tunneling microscope images of atomic silicon growth on silver and atomic silver growth on silicon. The study finds that both growth processes exhibit identical heights and shapes (a, g), indistinguishable honeycomb structures (c, e) and atomic periodicity (d, f). This suggests the growth of bulk silicon on silver, with a silver-induced surface reconstruction, rather than silicene. Courtesy: Argonne National Laboratory

Argonne researchers investigating the properties of silicene (a one-atom thick sheet of silicon atoms) compared scanning tunneling microscope images of atomic silicon growth on silver and atomic silver growth on silicon. The study finds that both growth processes exhibit identical heights and shapes (a, g), indistinguishable honeycomb structures (c, e) and atomic periodicity (d, f). This suggests the growth of bulk silicon on silver, with a silver-induced surface reconstruction, rather than silicene. Courtesy: Argonne National Laboratory

Here’s a link to and a citation for the paper,

Silicon Growth at the Two-Dimensional Limit on Ag(111) by Andrew J. Mannix, Brian Kiraly, Brandon L. Fisher, Mark C. Hersam, and Nathan P. Guisinger. ACS Nano, 2014, 8 (7), pp 7538–7547 DOI: 10.1021/nn503000w Publication Date (Web): July 5, 2014

Copyright © 2014 American Chemical Society

This paper is behind a paywall.

It will be interesting to note what kind of a response the Argonne researchers receive from the scientific community. As for ‘silicene’ items on this blog, there’s a Jan. 14, 2014 posting about work on silicene at the University of Twente (Netherlands). That research was instrumental in helping a student achieve a master’s degree.  While I can describe the Argonne research as fascinating, I imagine the student who got a master’s degree has a different adjective.