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Home » Page 413

Quantum material ‘learns’ like a living creature

Quantum materials known as Mott insulators can “learn” to respond to external stimuli in a way that mimics animal behaviour, say researchers at Rutgers University in the US. The discovery of behaviours such as habituation and sensitization in these non-living systems could lead to new algorithms for artificial intelligence (AI).

Neuromorphic, or brain-inspired, computers aim to mimic the neural systems of living species at the physical level of neurons (brain nerve cells) and synapses (the connections between neurons). Each of the 100 billion neurons in the human brain, for example, receives electrical inputs from some of its neighbours and then “fires” an electrical output to others when the sum of the inputs exceeds a certain threshold. This process, also known as “spiking”, can be reproduced in nanoscale devices such as spintronic oscillators. As well as being potentially much faster and energy efficient than conventional computers, devices based on these neuromorphic principles might be able to learn how to perform new tasks without being directly programmed to accomplish them.

Mimicking non-associative learning

In the new work, researchers led by Subhasish Mandal in the Department of Physics and Astronomy at Rutgers focused on nickel oxide, which is a typical example of a Mott insulating material. When they monitored how the material’s electrical conductivity changes as the concentration of its atomic defects is reversibly modulated using external stimuli such as oxygen, ozone and light, they found that it mimics non-associative learning. This type of learning is one of the most fundamental ways in which living organisms learn, and it helps animals adapt continuously to changing situations.

Another intriguing finding from the study is that when the researchers exposed the nickel oxide to rapidly changing oxygen concentrations or different light intensities, the material was unable to respond fully, and instead remained in an unstable state with its electrical conductivity fluctuating little. When they later introduced additional atomic defects into the sample using a harsher stimulus, ozone, the material’s electrical conductivity fluctuated faster, only to slow down again.

Universal learning characteristics

Mandal says that the team’s results demonstrate universal learning characteristics such as habituation and sensitization that are generally found in living species. He also suggests that the characteristics they unearthed could inspire new algorithms for unsupervised learning in neural networks and AI, much as the collective motion of birds or fish has done in the past. “The growing field of AI requires hardware that can host adaptive memory properties beyond what is used in today’s computers,” he says. “We find that nickel oxide insulators, which historically have been restricted to academic pursuits, might be interesting candidates to be tested in the future for brain-inspired computers and robotics.”

Beyond nickel oxide, the researchers say that similar effects could be found in other correlated materials that have defects susceptible to modulation using external stimuli. They now plan to further explore the learning behaviour of nickel oxide devices under electric fields in test chips.

The team reports its work in PNAS.

Quantum start-up targets single photons, perovskite pioneers bag Rank Prize

Our first guest in this episode of the Physics World Weekly podcast is the physicist Carmen Palacios-Berraquero, who is chief executive of Nu Quantum. The UK-based company spun-out from the from the University of Cambridge in 2018 and Palacios-Berraquero explains how the firm’s single-photon sources and detectors are used in quantum technologies.

Also in this episode are Akihiro Kojima and Mike Lee, who are two of seven winners of the 2022 Rank Prize for Optoelectronics – which has been given “For the discovery and development of all-solid-state perovskite semiconductor solar cells”. Kojima and Lee talk about the potential that perovskites have for creating high-performance solar cells and also chat about where their careers have taken them since they did their award-winning work.

Special relativity keeps digital identities secure

The laws of physics have been helping to keep sensitive information secret for well over a decade, with banks and other organizations using quantum cryptography to carry out very secure communications. But new research shows that special relativity can also be exploited to guarantee secrecy.

Scientists in Canada and Switzerland have shown that someone can prove their identity without having to provide a personal identification number (PIN) or other information that could potentially be stolen by hackers. They did so using two devices made from off-the-shelf electronics to carry out what is known as a zero-knowledge proof – finding that they could answer each of a series of questions designed to root out imposters in less time than it takes for light to travel between the two devices.

Anyone withdrawing money from a cash machine may think that their PIN ensures the transaction’s security. In reality, however, the PIN itself is vulnerable to fraudsters – who, either by planting a fake machine or tampering with an existing one, can capture the code and use it to remove money from a bank account.

Quantum threat

Zero-knowledge proofs remove this vulnerability by convincing authentication software that a problem can be solved without having to reveal the underlying secret proof. This is currently done by using what are known as one-way functions, such as factoring a huge number into two huge prime numbers, which are assumed to be trivial to evaluate but very hard to solve. While this works very well today, quantum computers could someday solve such problems, raising doubts about the future security of this technique.

The latest research avoids this approach by using multiple physically distant “provers” to independently persuade one or more “verifiers”. This is similar to the police interrogation technique of interviewing several individuals in separate rooms at the same time to make it difficult for the individuals to lie collectively.

First proposed by scientists in the mid-1980s, this approach revolves around graphs – collections of interconnected nodes lying on a plane. The provers’ task is to convince the verifiers without providing proof that a graph with a certain set of nodes and connecting lines is “three-colourable”. This means that when each node can have just one of three colours, no two nodes of the same colour will be connected.

Provers and verifiers

The process involves two pairs of provers and verifiers, with the provers providing the graph and then answering a series of questions simultaneously from their respective verifiers. They can convince the verifiers that the graph is three-colourable only if they always respond with different answers when asked for the colour of nodes at opposite ends of a given line, while always agreeing on the colour of a common node at the intersection of two different lines.

The crucial condition underpinning the protocol is that each question and answer be completed in less time than it would take the two provers to communicate with one another – making them unable, when asked enough questions, to generate the “right” answers in the absence of a three-colourable graph. This time limit is determined by special relativity, which stipulates that no signal can travel faster than the speed of light.

Previous protocols could not meet this requirement over any reasonable distance as they required too much information to be communicated between each prover and verifier. But Claude Crépeau and colleagues at McGill University in Montreal have devised a new, more efficient protocol, which Hugo Zbinden and co-workers at the University of Geneva have now put into practice.

As they report in Nature, the researchers demonstrated their scheme using provers and verifiers made from field-programmable gate-arrays and other commercially available components. They performed two tests, showing that within about a second they could complete the roughly half a million rounds of questions needed to ensure a correct verdict. One test used GPS signals to synchronize the prover-verifier pairs over a distance of 390 m, while the other reduced the separation to just 60 m by employing an optical-fibre link.

Still too far

The researchers acknowledge that 60 m is still too far for many practical applications, but reckon that improved communication and chip technology could reduce the distance to around a metre. At that point, they say, a user could insert a pair of cards into ports on either side of a bank machine, having first activated them via thumbprint recognition. Convinced that the cards – or perhaps ultimately mobile phones – contain data from a three-colourable graph, the machine would then complete the transaction.

Gilles Brassard of the University of Montreal, who was not involved in the research, points out in an accompanying “News and views” article in Nature that fraudsters might in future try and breach security by using quantum entanglement – exploiting instantaneous correlations between devices to avoid the three-colour problem. As such, he argues, more research is needed “before these ideas can find their way to your local bank”.

Adrian Kent of the University of Cambridge in the UK agrees that further work is required – both to increase device speed and to guard against powerful quantum computers. But he nevertheless sees the research as “a significant step towards a practical real world application of relativistic cryptography” – adding that plausible future applications of the technology include electronic payments and voting.

Life beyond the Nobel: laureates tend to be serial risk-takers

You don’t win a Nobel prize by playing it safe. Indeed, physicists who win Nobel prizes often go on to gain additional notoriety for work that is very different from their prize-winning research. This video introduces the colourful careers of two such academics: Luis Walter Alvarez and Brian Josephson.

To discover the stories of other physics laureates take a look at the article ‘Life beyond the Nobel’, the cover story from the November issue of Physics World.

NVIDIA highlights healthcare AI innovations

Today, around 30% of all the world’s data is healthcare data, with hospitals generating 50 petabytes of data each year. And by 2025, healthcare data is predicted to be growing at the highest rate of any industry. As such, it comes as no surprise that graphics processing unit (GPU) specialist NVIDIA is developing a host of artificial intelligence (AI) technologies and tools designed to transform healthcare AI.

At NVIDIA GTC, an online GPU technology conference held earlier this week, the company announced new products that aim to change the way that AI powers medical devices. One highlight is the launch of Clara Holoscan, an AI computing platform for the healthcare industry.

“Recent advances in AI, physics machine learning, ray tracing and computing will revolutionize medical instruments,” said NVIDIA founder and CEO Jensen Huang, in his keynote address.

Clara Holoscan allows developers to build applications that process multimodality sensor data, run physics-based models, accelerate AI-based analysis and render high-quality graphics in real time. The new platform provides the infrastructure for end-to-end processing of streaming data from medical devices, seamlessly connecting such devices with edge servers in hospitals.

Most medical devices, from diagnostic imaging systems to surgical assistance instruments, have a workflow that starts with a sensor, incorporates data processing steps and then requires image visualization for human decision-making.

Powered by a new superfast robotics chip, NVIDIA AGX Orin, Clara Holoscan is designed to accelerate each phase of this data processing pipeline. Steps include: transmitting sensor data directly to the GPU; physics-based calculations or AI processing to transform these data into the image domain; image processing, such as segmentation or classification; data processing; and 3D visualization of the device data and resulting predictions.

Importantly, the platform allows developers to run low-latency streaming applications on devices, while exploiting data centre resources for more complex tasks. “Holoscan applications can be deployed fully in-instrument, in the hospital’s data centre or a mixture of both,” explained Huang. “This allows companies to develop applications that require more computing than is in the device or to upgrade the installed base of devices years after deployment.”

Speeding drug discovery

Another area in which AI could make a massive impact is drug discovery, a notoriously time-consuming and data-intensive process.

“Researchers are creating AI models that learn physics and make predictions that obey the laws of physics,” said Huang. “The application of machine learning to improve physics simulation has been growing incredibly.” And this combination of deep learning and physics-based simulation could transform the way that drugs are discovered.

NVIDIA Clara Discovery
Rapid predictions: Clara Discovery is powering start-up Entos’ machine learning approach for developing next-generation therapeutics. (Courtesy: NVIDIA)

Virtual drug screening involves finding a chemical that will bind to and inhibit the function of a protein in the disease pathway, using molecular dynamic simulations of the atomic forces between the chemical and the protein. Until recently, the 3D structure of a human protein was determined using X-ray crystallography and cryo-electron microscopy. But only 17% of roughly 25,000 human proteins had been decoded, limiting computer-aided drug discovery.

Earlier this year, however, researchers taught AI to predict the 3D shape of proteins from just their amino acid sequences, using DeepMind to decode over 20,000 human proteins overnight. Alongside, AI models are now able to learn the characteristics of known effective chemicals and use these to generate other potentially effective novel drugs.

“More potentially effective chemicals meet hundreds of thousands more protein structures, opening up a gigantic unexplored space of new opportunities,” said Huang. “The opportunity space has increased a million-fold, but this has created a massive molecular simulation bottleneck.”

Enter San Diego-based start-up Entos, a member of the NVIDIA Inception programme, which aims to use machine learning to revolutionize and accelerate drug discovery. Entos has created OrbNet, a physics machine learning architecture that provides a thousand-fold performance increase in molecular simulations. The company is advancing its work using NVIDIA Clara Discovery, a collection of AI tools, models and applications that enable such in silico drug discovery.

Entos focuses on identifying drug molecules that could deactivate proteins linked to certain forms of cancer. Huang shared an example simulation of a chemical reaction between a protein and a candidate drug. “This simulation took three hours on one GPU. Without the OrbNet physics machine learning, it would have taken over three months,” he pointed out.

“The future of drug discovery is computational end to end, modelling the disease pathway, the genes involved, the drug–target interactions and the off-target interactions,” said Huang. “With the confluence of million times acceleration, machine learning for protein and chemical structure prediction, and physics machine learning simulation approaches, we are witnessing the dawn of the biology revolution.”

Science takes centre stage at COP26

The importance of scientific evidence to the negotiations at the COP26 climate conference in Glasgow was given extra prominence yesterday (9 November) in what was billed as Science and Innovation Day. It saw several new initiatives unveiled at the two-week United Nations’ summit, focused on decarbonization and ways to adapt to climate threats.

However, the optimism was dented when a report released yesterday from Climate Action Tracker, which monitors the impact of national climate policies, found that current commitments will lead to global warming of at least 2.4 °C above pre-industrial levels. That is well above the Paris agreement, designed to keep warming as far below 2 °C as possible.

There was more bad news with today’s release of the first draft of the COP26 final statement. It has been widely criticised for its lack of ambition and enforceable commitments — despite growing evidence that restricting average global temperature rise to 1.5 °C will lead to far less catastrophic outcomes than warming of 2 °C or more.

“The target of 1.5 °C isn’t plucked from the air, it is an important evidence-based number and it’s a real possibility albeit one that is going to require unprecedented change,” said Sir Patrick Valance, the UK’s chief scientific adviser in Glasgow.

Deep decarbonization

Science and Innovation Day saw four new projects unveiled under the Mission Innovation programme, increasing the total to seven. Some 22 governments and the European Commission have already signed up to the new missions, which cover urban transitions, cutting industrial emissions, carbon-dioxide removal, and developing greener fuels and materials. In total, governments, corporations and research institutes have already invested $18bn in the programme, a figure projected to rise to $250bn by the end of the decade.

Meanwhile, the UK, India, Germany, Canada and the UAE have agreed to disclose the embodied carbon in major public construction projects by 2025, as part of the Industrial Deep Decarbonisation Initiative. These five nations have also committed to net zero steel and concrete by 2050 for major projects. Elsewhere more than 40 states, including China and the US, have agreed to act on annual updates from the Breakthrough Agenda — a programme launched last week to stimulate green alternatives in carbon-intensive sectors such as transport, energy and heavy industry. Politicians and business leaders have talked up “green hydrogen” as a key solution in these sectors.

Green smokescreens?

Science and Innovation Day also had a strong focus on adapting to climate threats. The UK Space Agency announced an additional £7m funding for projects that will help to track climate change and identify hazards. The UK Foreign, Commonwealth and Development Office launched its Adaptation Research Alliance, which brings together almost 100 organisations from 30 nations to increase the resilience of vulnerable communities. The UK announced an additional £48m funding towards the programme, mostly for African projects, although this is dwarfed by recent cuts to the UK’s foreign-aid budget from 0.7% to 0.5% of its gross national income (roughly £4–5bn annually).

Pasang Dolma Sherpa, executive director of the Center for Indigenous Peoples’ Research and Development, said yesterday that indigenous voices are still not being sufficiently incorporated into climate-adaptation proposals. “Indigenous people represent 5% of people in the world but they are safeguarding 80% of biodiversity in ecosystems,” she said. Sherpa, who also works with the International Union for Conservation of Nature, called on decision makers to treat indigenous knowledge as an equal to modern science when devising solutions to climate change.

Magnetic oxides for water oxidation: magnetization, pinning effect and pH dependence

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The slow kinetics of the oxygen evolution reaction (OER) limits the overall efficiency of water electrolysis for hydrogen production. As spin-dependent kinetics exist in triplet oxygen production, the spin alignment in active OER catalysts is critical for reducing the kinetic barriers in OER.

In this presentation, recent progress in investigating the OER on magnetic oxides is introduced as well as the finding of the spin pinning effect to make the spins in the most active oxyhydroxides more aligned for higher intrinsic OER activity. The control experiments were conducted to confirm the enhancement of OER under an external magnetic field. Some other factors that may affect the observed phenomenon are also discussed. The spin pinning effect is found at the interface of oxideFM/oxyhydroxide. The spin pinning effect can promote spin selective electron transfer on OER intermediates to generate oxygens with parallel spin alignment, which facilitates the production of triplet oxygen and increases the intrinsic activity of oxyhydroxide by ~1 order of magnitude. The spin polarization process in OER is sensitive to the existence of active oxygen ligand (O(-)) in oxyhydroxide. When the O(-) is created in the first deprotonation step under high pH, the spin polarization of ligand oxygens will be facilitated, which reduces the barrier for subsequent O-O coupling and promotes the triplet O2 turnover. Combining the above understanding and the magnetic domain evolution, why an external magnetic field can promote OER can be answered.

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Zhichuan Xu is a professor in the School of Materials Science and Engineering, Nanyang Technological University (NTU). There he holds leadership appointments as deputy director of the CNYang Scholars Programme and Cluster Director of Materials for Energy and Catalysis, ERI@N. Prof. Xu’s research focuses on electrocatalysis and related materials. He serves as president of the ECS Singapore Section, and is a fellow of the Royal Society of Chemistry (FRSC) and member of the International Society of Electrochemistry ISE). Named a Clarivate Analytics Top 1% Global Highly Cited Researcher for the last four years (2018–2021), Prof. Xu was awarded the 2019 ISE Zhaowu Tian Prize for Energy Electrochemistry. He received his PhD from Lanzhou University, Institute of Physics at the Chinese Academy of Sciences in 2008 with a period as an exchange student in materials chemistry at Brown University (2005–2007). Prof. Xu worked as a research associate at the State University of New York at Binghamton from 2007–2009, followed by a postdoc at the Massachusetts Institute of Technology (2009–2012).

Quantum dot LEDs bend and fold like origami paper

A new ultrathin quantum dot light-emitting diode (QLED) that bends and creases like a piece of origami paper could be ideal for next-generation displays and foldable mobile phones. The device was made using laser etching, and researchers at the Institute of Basic Sciences in Korea say that the same technique could also be used to create QLED structures with complex 3D shapes that stand up to repeated folding.

Flexible light-emitting devices based on quantum dots and organic luminophores are at the heart of modern display technologies. Some devices made from these electroluminescent materials are now so thin – QLEDs, in particular, can be thinner than 5 microns – that they continue to operate despite being bent, folded or even rolled up. Researchers are now looking to go beyond these technologies and develop displays that can transform from 2D to 3D or vice versa. Such displays could be used in next-generation large-scale screens or miniaturized for use in mobile phones.

Origami technique cuts and folds

Origami is a simple and reliable way to convert 2D materials into 3D structures, and it has recently been applied in electronics to make a 3D photodetector array out of molybdenum diselenide. In that case, researchers converted an ultrathin 2D photodetector into a dome-shaped 3D pop-up structure.

In the latest work, which is described in Nature Electronics, a team led by Dae-Hyeong Kim and Taeghwan Hyeon of the Center for Nanoparticle Research at the IBS used a new type of laser patterning technique to form folding and cutting lines in conventional planar QLEDS. In the team’s fabrication process, the light-emitting layers of the material are protected from over-etching by a silver-based “etch-stop” layer deposited on the QLED surface. A pulsed, power-controlled carbon dioxide laser enables researchers to precisely control the depth of etching. Since the laser-etched part of the device is thinner than the surrounding area, the device folds easily along these etched lines.

Protected from external strain

Kim, Hyeon and colleagues succeeded in creating QLED architectures with bending radii of just 0.047 mm. Accordingly, the fold lines on the devices resemble sharp edges with no visible curves, allowing the devices to be folded into 3D structures in which the fold lines take on most of the applied deformation. The finished devices are thus protected from external strain and continue to emit light even after they are repeatedly folded 500 times.

The researchers used their foldable QLEDs to build a star-shaped passive matrix array displaying letters and numbers, as well as other 3D structures shaped like a pyramid, a cube, an aeroplane and even a butterfly. Kim notes that while the IBS team fabricated QLED arrays composed of 64 individual pixels, the same technique could be used to make more complex displays in the future.

The researchers now plan to develop deformable QLEDs that can take on various form factors for next-generation displays. In the longer term, Hyeon suggests that the new technique could be used to create electronic paper that folds as easily as the traditional kind. “Who knows when the day will come when electronic paper with a display unit can replace real paper?” he says.

Life beyond the Nobel: why physicists love to leave the herd

When Syukuro Manabe, Klaus Hasselmann and Giorgio Parisi received the time-honoured phone call from Stockholm last month telling them they had won the 2021 Nobel Prize for Physics, the trio surely knew their lives were going to change forever. Newer, rival awards might offer more money, but the Nobel prize is still the accolade that every physicist dreams of winning. Conferring prestige, kudos and honour, a Nobel immediately places the recipients in the pantheon of great physicists of the past. 

The ability and confidence to venture into new territory and question the status quo is often what led these scientists to do their Nobel-prize-winning work in the first place

The prize also gives the winners new freedoms. Unfettered by the need to “prove” themselves or continue on the treadmill of bringing in grants, equipment and students, Nobel laureates can branch out into new research directions. But tackling novel topics is usually second nature for Nobel laureates. In fact, the ability and confidence to venture into new territory and question the status quo is often what led them to their Nobel-prize-winning work in the first place. You don’t, after all, win a Nobel prize by playing safe.

For Andrea Ghez, who shared one half of the 2020 Nobel Prize for Physics with Reinhard Genzel for discovering a huge black hole lurking in the middle of the Milky Way, the award has already opened new doors. “I’m really excited to take on a more ambitious and riskier research agenda that would not have been possible otherwise,” Ghez told Physics World. She wants to explore how gravity works near supermassive black holes and how these exotic, but poorly understood, objects regulate the formation and evolution of galaxies.

No doubt, Ghez will do more great studies in astrophysics – the field in which she made her name. But there are lots of Nobel-prize-winners of the past who’ve gained notoriety for work beyond their Nobel endeavours. Some changed direction even before winning the prize, while for others the switch has been forced on them due to personal circumstances.

In the run-up to this year’s Nobel prize announcement, Physics World editors profiled Ghez and four more Nobel laureates – finding out what motivated these physicists to strike out in new directions. You can read all their profiles online:

Processed wood can be moulded into complex 3D structures

Researchers in the US have developed a new technique that allows wood to be shaped into complex 3D structures. Shaoliang Xiao, Bing Hu and colleagues at the University of Maryland, have shown how useful components can be made by breaking down the molecular structures of wood cell walls, and then moulding the material into desirable shapes. The approach could allow the manufacture of components that are normally made from plastics and metals, but with far lower environmental impacts.

Plastics and metals can be easily processed into lightweight structural components, with widely varying shapes and sizes. This property makes these materials particularly valuable for use in vehicles and buildings, where weight-saving measures are often vital for reducing costs and improving performance. Yet due to the environmental costs of producing metals and plastics, there is now a growing need for more sustainable alternatives.

As a mechanically strong, lightweight, and widely available resource, wood is now being studied as a potential replacement material. Since it is completely renewable, its production can be far more environmentally friendly than metals and plastics, provided it comes from sustainable sources.

Lignin inconvenience

But compared to these materials, wood is also far more difficult to mould into complex shapes. This inconvenience stems from lignin. This is a biopolymer that is a key component of the walls of wood cells, which typically have long, slender shapes running parallel to each other. Although lignin is essential to wood’s mechanical strength, it cannot easily change shape without breaking.

In their study, the researchers showed how the cell walls of wood can be engineered to overcome the challenges posed by lignin’s rigidity. To transport water and nutrients from their roots to their leaves, trees use several different types of wood cell: including “vessels”, which are around 100 micron in diameter, and narrower “fibres”. In the first part of their process, the researchers closed off these transport passages by removing around 55% of the lignin from their cell walls, and then air drying the material to remove any water.

Afterwards, the team re-swelled the wood using a “rapid water-shock” process – which selectively re-opened the vessels, while keeping the fibres closed. This technique produced distinctly wrinkled structures in the cell walls – with enough empty space to allow for compression, while also being able to support high levels of strain. This meant that the wood could be easily folded and moulded into different shapes, and then dried to fix its shape.

To demonstrate this, the researchers shaped flat sheets of hardwood into versatile 3D structures: including a honeycomb composite material, which they made by joining specially corrugated sheets. This structure was about six times stronger than the original wood – giving it a similar tensile strength to aluminium alloys, but with a far lower density. Based on their success, the team hopes their technique could soon expand the use of wood as an environmentally sustainable structural material.

The research is described in Science.

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