Two research breakthroughs are poised to accelerate the development of synthetic diamond-based quantum technology

Marilyn Monroe famously sang that diamonds are a girl's best friend, but they are also very popular with quantum scientists - with two new research breakthroughs poised to accelerate the development of synthetic diamond-based quantum technology, improve scalability, and dramatically reduce manufacturing costs.

While silicon is traditionally used for computer and mobile phone hardware, diamond has unique properties that make it particularly useful as a base for emerging quantum technologies such as quantum supercomputers, secure communications, and sensors.

However, there are two key problems; cost, and difficulty in fabricating the single-crystal diamond layer, which is smaller than one-millionth of a meter.

A research team from the ARC Centre of Excellence for Transformative Meta-Optics at the University of Technology Sydney (UTS) led by Professor Igor Aharonovich has just published two research papers Nanoscale and Advanced Quantum Technologies, that address these challenges. 

"For a diamond to be used in quantum applications, we need to precise engineer 'optical defects' in the diamond devices - cavities and waveguides - to control, manipulate and read out information in the form of qubits - the quantum version of classical computer bits," said Professor Aharonovich.

"It's akin to cutting holes or carving gullies in a super-thin sheet of diamond, to ensure light travels and bounces in the desired direction," he said.

To overcome the "etching" challenge, the researchers developed a new hard masking method, which uses a thin metallic tungsten layer to pattern the diamond nanostructure, enabling the creation of one-dimensional photonic crystal cavities.

"The use of tungsten as a hard mask addresses several drawbacks of diamond fabrication. It acts as a uniform restraining conductive layer to improve the viability of electron beam lithography at nanoscale resolution," said the lead author of a paper in Nanoscale, UTS Ph.D. candidate Blake Regan.

"It also allows the post-fabrication transfer of diamond devices onto the substrate of choice under ambient conditions. And the process can be further automated, to create modular components for diamond-based quantum photonic circuitry," he said.

The tungsten layer is 30nm wide - around 10,000 times thinner than a human hair - however, it enabled a diamond to etch of over 300nm, a record selectivity for diamond processing.

A further advantage is that removal of the tungsten mask does not require the use of hydrofluoric acid - one of the most dangerous acids currently in use - so this also significantly improves the safety and accessibility of the diamond nanofabrication process.

To address cost and improve scalability, the team further developed an innovative step to grow single-crystal diamond photonic structures with embedded quantum defects from a polycrystalline substrate.

"Our process relies on a lower-cost large polycrystalline diamond, which is available as large wafers, unlike the traditionally used high-quality single crystal diamond, which is limited to a few mm2," said UTS Ph.D. candidate Milad Nonahal, lead author of the study in Advanced Quantum Technologies.

"To the best of our knowledge, we offer the first evidence of the growth of a single crystal diamond structure from a polycrystalline material using a bottom-up approach - like growing flowers from seed," he added.

"Our method eliminates the need for expensive diamond materials and the use of ion implantation, which is key to accelerating the commercialization of diamond quantum hardware," said UTS Dr. Mehran Kianinia, a senior author on the second study.

Landslides occurring on land or underneath the sea - known as subaerial and submarine landslides respectively - can cause devastating tsunamis. They also pose other hazards such as severing submarine cables and pipelines.

Yet the mechanisms at play behind these landslides are less well understood, partly due to the multifaceted interactions taking place: a collapse of the seabed and/or the interaction between soil and water. Conventional approaches make it difficult to predict the behaviors of soil and seawater with high accuracy.

The researchers' breakthrough proposes a new hybrid simulation method that can express the complex interaction between soil structures - referred to as granular masses - and liquids.

"Our novel method couples together two computational methods that analyze the interactions of solids and liquids: the finite element method (FEM) along with the material point method (MEM)," said Kenjiro Terada, professor at Tohoku University's International Research Institute of Disaster Science and co-author of the study.

Using the newly created algorithm, the researchers were able to simulate a wave mimicking a submarine granular collapse and a wave induced by a subaerial slide over an inclined plane. To their delight, the simulations were in reasonable agreement with the numerical measurements.

Several numerical examples also revealed that the proposed method can be applied to other types of potentially dangerous natural events that involve the interaction of air, water, and solids.

Looking ahead, Terada and his team aim to improve the accuracy of their experimental measurements and apply it to larger-scale real data.

Better designed vaccines for insect-spread viruses like dengue and Zika are likely after researchers discovered models of immature flavivirus particles were originally misinterpreted.

Researchers from The University of Queensland and Monash University have now determined the first complete 3D molecular structure of the immature flavivirus, revealing an unexpected organization.

UQ researcher Associate Professor Daniel Watterson said the team was studying the insect-specific Binjari virus when they made the discovery.

"We were using Australia's safe-to-handle Binjari virus, which we combine with more dangerous viral genes to make safer and more effective vaccines," Dr. Watterson said. 

"But when analyzing Binjari we could clearly see that the molecular structure we've all been working from since 2008 wasn't quite correct.

"Imagine trying to build a house when your blueprints are wrong - that's exactly what it's like when you're attempting to build effective vaccines and treatments and your molecular 'map' is not quite right."

The team used a technique known as cryogenic electron microscopy to image the virus, generating high-resolution data from Monash's Ramaciotti Centre for Cryo-Electron Microscopy facility.

With thousands of collected two-dimensional images of the virus, the researchers then combined them using a high-performance computing platform called 'MASSIVE' to construct a high-resolution 3D structure.

Monash's Associate Professor Fasséli Coulibaly, a co-leader of the study, said the revelation could lead to new and better vaccines for flaviviruses, which have a huge disease burden globally.

"Flaviviruses are globally distributed and the dengue virus alone infects around 400 million people annually," Dr. Coulibaly said.

"They cause a spectrum of potentially severe diseases including hepatitis, vascular shock syndrome, encephalitis, acute flaccid paralysis, congenital abnormalities, and fetal death.

"This structure defines the exact wiring of the immature virus before it becomes infectious, and we now have a better understanding of the levers and pulleys involved in viral assembly.

"This is a continuation of fundamental research by us and others and, without this hard-won basic knowledge, we wouldn't have the solid foundation needed to design tomorrow's treatments."

Energy constraints lead to novel ways of efficient, at-a-distance communication

When it fires, a neuron consumes significantly more energy than an equivalent computer operation. And yet, a network of coupled neurons can continuously learn, sense, and perform complex tasks at energy levels that are currently unattainable for even state-of-the-art processors.

What does a neuron do to save energy that a contemporary computer processing unit doesn't?

Supercomputer modeling by researchers at Washington University in St. Louis' McKelvey School of Engineering may provide an answer. Using simulated silicon "neurons," they found that energy constraints on a system, coupled with the intrinsic property neurons have to move to the lowest-energy configuration, leads to a dynamic, at-a-distance communication protocol that is both more robust and more energy-efficient than traditional computer processors. 

The research, from the lab of Shantanu Chakrabartty, the Clifford W. Murphy Professor in the Preston M. Green Department of Systems & Electrical Engineering, was published last month in the journal Frontiers in Neuroscience.

It's a case of doing more with less.

Ahana Gangopadhyay, a doctoral student in Chakrabartty's lab and a lead author on the paper, has been investigating computer models to study the energy constraints on silicon neurons -- artificially created neurons, connected by wires, that show the same dynamics and behavior as the neurons in our brains.

Like biological neurons, their silicon counterparts also depend on specific electrical conditions to fire, or spike. These spikes are the basis of neuronal communication, zipping back and forth, carrying information from neuron to neuron.

The researchers first looked at the energy constraints on a single neuron. Then a pair. Then, they added more. "We found there's a way to couple them where you can use some of these energy constraints, themselves, to create a virtual communication channel," Chakrabartty said.

A group of neurons operates under a common energy constraint. So, when a single neuron spikes, it necessarily affects the available energy -- not just for the neurons it's directly connected to, but for all others operating under the same energy constraint.

Spiking neurons thus create perturbations in the system, allowing each neuron to "know" which others are spiking, which are responding, and so on. It's as if the neurons were all embedded in a rubber sheet; a single ripple, caused by a spike, would affect them all. And like all physical processes, systems of silicon neurons tend to self-optimize to their least-energetic states while also being affected by the other neurons in the network.

These constraints come together to form a kind of secondary communication network, where additional information can be communicated through the dynamic but synchronized topology of spikes. It's like the rubber sheet vibrating in a synchronized rhythm in response to multiple spikes.

This topology carries with it information that is communicated, not just to the neurons that are physically connected, but to all neurons under the same energy constraint, including ones that are not physically connected.

Under the pressure of these constraints, Chakrabartty said, "They learn to form a network on the fly."

This makes for much more efficient communication than traditional computer processors, which lose most of their energy in the process of linear communication, where neuron A must first send a signal through B in order to communicate with C.

Using these silicon neurons for computer processors gives the best efficiency-to-processing speed tradeoff, Chakrabartty said. It will allow hardware designers to create systems to take advantage of this secondary network, computing not just linearly, but with the ability to perform additional computing on this secondary network of spikes.

The immediate next steps, however, are to create a simulator that can emulate billions of neurons. Then researchers will begin the process of building a physical chip.