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Airborne viruses could be protected by phase transitions in droplets and aerosols

Phase transitions within protein-rich aerosols and droplets may protect viruses at low humidity levels, which could explain why respiratory diseases such as COVID-19 can often spread efficiently in dry air. That is the conclusion of Ryan Davis of Trinity University in Texas and colleagues, who have observed a structural transition in aerosols that occurs as humidity falls.

Respiratory pathogens spread between hosts in either micrometre-scale aerosols – which remain suspended in air currents like cigarette smoke – or in larger droplets, which slowly fall to the ground under gravity. Both are emitted by infected hosts coughing, talking, singing or simply breathing. They are subsequently inhaled by new hosts.

The humidity (more accurately, the relative humidity) in the respiratory system is typically 100%, so as soon as a particle is emitted its surrounding humidity is usually lower. Exposure to drier air might be expected to destroy viruses adapted to the warm, moist atmosphere of the lungs, but this is not always the case.

Most viruses’ viabilities in exhaled particles – including those of influenza and the Sars-CoV-2 virus that causes COVID-19 – vary with humidity in a curious U-shape. At close to 100% humidity, the viruses can survive for relatively long times, whereas at intermediate humidity their lifetimes are shorter. This is because in drier air water evaporates faster from the outside of an aerosol particle, leaving it more concentrated in non-volatile components such as sodium chloride. When these components become too concentrated, they disinfect the particle. However, after dropping to a minimum at 50-80% humidity, the viabilities of most viruses begin to increase as humidity decreases further. The reasons for this are not entirely clear.

Protective shall?

Previously, researchers have proposed that it could be due to efflorescence, in which the inorganic content of the particle crystallizes, encapsulating the virus in a protective shell. As the water is driven off, this manifests as a sharp decrease in the particle mass.

In the new research Davis and colleagues studied aerosols and droplets composed of model respiratory compounds (salt and protein) in growth media, which are organic–inorganic mixtures used in studies of pathogen survival. They showed that efflorescence was suppressed, sometimes to humidity levels as low as 35%. However, when they tried to merge levitated particles together, they found many of them behaved as solids or semi-solids at much higher humidity, with the firmness of the particles gradually – and unexpectedly – increasing as the humidity fell.

The researchers believe, therefore, that they were observing glass transitions due to cross-linking of the organic molecules in the growth media. “Glass transitions happen over a broad range,” explains Davis. “And when you have a glass transition, molecular motion kind of stops. That’s one reason why we think a glass transition could cause long virus survival times – because whatever inactivation process happens is going to be slowed down.”

Complex, elongated shapes

In a growth medium that contained calcium ions, however, the particles coalesced fully at humidity levels above 53%, below which they formed complex, elongated shapes. When the researchers looked at these under a microscope, they found that the particles had separated into liquid and solid fractions. They attribute this to a phase transition, in which the calcium crosslinks the proteins in the solution to form a gel.

“You can have what’s called a critical gel concentration fairly abruptly,” says Davis. “The proteins and the viruses likely do migrate together and partition into the organic phase where that organic can form a rigid protective layer.” An important subtlety is that small aerosols are likely to reach a protective state in seconds after emission as evaporation will occur quickly, whereas larger droplets may have been sterilized by the time it forms.

Droplets created by speech could contribute to COVID-19 spread, new study suggests

The researchers conclude that the organic content of the encapsulating particle is probably crucial to viruses’ viability at any given humidity. This organic content will depend upon where in the respiratory tract the particle was produced, which in turn will depend on the disease and how far it has progressed in a specific patient. “The next step would be to systematically vary different aspects of the droplet composition and the virus involved to try to understand better what the mechanism of viral deactivation is,” says Davis.

Biological aerosol expert Peter Raynor of the University of Minnesota in the US says “I think it’s an important [study], but there have been important [studies] before this and there are going to need to be important [studies] after this to give us a complete picture of how droplet composition is linked to survivability.” He adds, “Potentially an important outcome of this line of research is making sure we properly humidify buildings in the winter when otherwise there would be dry air, not only for human comfort but also to keep viruses in their most fragile state.”

The research is described in Proceedings of the National Academy of Sciences.

How entropy might increase backwards in time – as well as forwards

We live life forward as time flows from past to future, and believe that any closed system, like a box of particles, follows an “arrow of time” into the future as the system’s entropy grows. This seems paradoxical, since a video of a single particle in motion looks equally valid running forwards or backwards. The video does not distinguish past from future because Newtonian mechanics is unchanged under reversed time. But statistical mechanics shows that a large group of particles is highly likely to irreversibly tend towards greater disorder. As a measure of disorder, entropy is considered to show the universal forward march of time. In contrast, The Janus Point: a New Theory of Time, by physicist and science writer Julian Barbour, presents a different approach that leads to a time-symmetric universe.

Barbour’s views on the subject benefit from a personal situation that allows him to develop his ideas more freely than most researchers. He earned a PhD in general relativity from the University of Cologne in 1968 but he is not an academic. Instead, working alone or in collaboration from his home near Oxford, he has over decades produced research and review papers about dynamics and time, and two books: The Discovery of Dynamics (1989) and The End of Time (1999).

His latest effort, The Janus Point, first discusses the 19th-century origins of thermodynamics and entropy in the work of Sadi Carnot, Lord Kelvin and Rudolf Clausius. This yielded the powerful three laws, prompting Einstein to call thermodynamics “the only physical theory of universal content which I am convinced that, within the framework of applicability of its basic concepts, will never be overthrown”. The second law introduces entropy, a concept that Clausius was the first to explore, then named in an 1865 paper that contained the sweeping statement: “the entropy of the universe tends to a maximum”; that is, entropy points inexorably to the heat death of the universe when it reaches thermal equilibrium.

Barbour notes, however, that thermodynamics began with Carnot’s study of steam engines. These operate by confining steam in cylinders with pistons, making it natural to model thermal and statistical behaviour with ideal gas molecules in a box. Now though, writes Barbour, to consider the entire expanding universe we should change the “framework of applicability” by using an unbounded model. He represents the universe by multiple masses mutually interacting in free space through Newtonian mechanics and gravitation, the famous N-body problem. In 1772 Joseph-Louis Lagrange showed that for N = 3 and under certain conditions, the system passes through a minimum size just once as it evolves. Since gravitation is invariant under time reversal, so is this behaviour (or any other, for all values of N.)

The three-body system provides a simple introduction to Barbour’s ideas, but in 2014 he made a more general N-body analysis with Tim Koslowski at the National Autonomous University of Mexico and Flavio Mercati at the University of Naples, Italy, in their paper “Identification of a gravitational arrow of time” (Phys. Rev. Lett. 113 181101). The article shows that, in a computer simulation with N = 1000, nearly every starting configuration reached a minimum size, then began growing again. Notably, the form of the configuration evolved with time from a structured arrangement with clusters of bodies to a uniform distribution at the minimum size, then again developed clusters as it grew.

This behaviour represents two streams of time. Each begins at the minimum point, and tracks an expanding configuration as it forms clusters (or galaxies), although not with identical futures, due to fluctuations. Barbour dubbed the minimal state the “Janus point” after the Roman god of transitions, portrayed as two faces gazing in opposite directions. The Janus point is perhaps a kind of Big Bang, but it lies in the middle of the universe’s development. We exist on one side of this point and follow its gravitational arrow of time into the future. We can also look back to the Janus point but not beyond it, just as with the Big Bang, but we now know that the time stream on the far side gives the universe overall symmetry in time.

My brief summary is only a glimpse into Barbour’s ideas. The book further explains the Janus point and its important corollary, the rise of cosmic structure (in Barbour’s phrase, “shape complexity”) as the universe evolves. This, he believes, makes his proposal more scientifically and philosophically acceptable than a scenario where the universe descends from the special initial Big Bang condition of low entropy (high order) into growing disorder and final heat death.

Any reader willing to engage with Barbour’s ideas will come away enlightened

Barbour’s clear examples and evocative metaphors will help non-physicists follow his detailed arguments, and he lightens the science with apropos quotes from Shakespeare and others. Still, much of the exposition is dense for general readers, whereas cosmologists may well be unconvinced by Barbour’s quantum and relativistic extensions of his classical theory. But any reader willing to engage with Barbour’s ideas will come away enlightened.

A clue to evaluating the book comes from its epigraph “The universe is made of stories, not of atoms,” from the American poet Muriel Rukeyser. She believed that science has much in common with poetry, so perhaps she meant that humanity needs origin stories to understand its place in the cosmos. The narratives that come from science are unique in being supported by theory and evidence. In that spirit, Julian Barbour is telling us a new scientific story about time. Could it prove more meaningful than the one based on entropy? Only time will tell.

2020 Bodley Head 400pp £20hb

Deep neural networks track eye movements during MRI scans

Our eyes are considered windows to the soul. For scientists and physicians, the eyes provide access to memories, cognition and even neurological dysfunction. What our eyes fixate on, and how we maintain our gaze, may be diagnostic of impaired working memories, indicative of amnesia or even signal Parkinson’s disease.

The gold standard of modern human neuroimaging is functional MRI (fMRI), which uses strong magnetic fields to measure changes in blood flow, and therefore brain activity. The technique is noninvasive – not requiring any injections, ionizing radiation or surgery. Monitoring eye movement during imaging could add valuable information to fMRI studies and clinical routines alike. However, the magnetic environment imposes restrictions on equipment brought into the scanner, making eye tracking difficult.

MR-compatible camera-based eye trackers, such as the EyeLink 1000 Plus, can set research labs back around $40,000. As such, only 10% of fMRI studies published in the last two years employed eye tracking, and only half of these used the eye tracking to help interpret their results.

To address this low utilization of eye tracking, researchers at the Kavli Institute for Systems Neuroscience and the Max Planck Institute for Human Cognitive and Brain Sciences developed DeepMReye, a convolutional neural network that uses the MR signal from the eyes for eye tracking, without the need for a camera.

In six independent 3T-MRI datasets, their machine-learning algorithm learned to detect patterns in the MRI signal indicative of gaze position, and then to decode or reconstruct the corresponding viewing behaviour in data the algorithm had never seen before. Critically, this means that DeepMReye can perform eye tracking even in existing fMRI datasets, making it possible to address new research questions using a large and immediately available data resource. The team describe DeepMReye in Nature Neuroscience.

Markus Frey and Matthias Nau — The team behind DeepMReye: Markus Frey (left) and Matthias Nau. (Courtesy: Matthias Nau)

Human eyes have difficulty extracting signals from noise in massive datasets – finding Waldo isn’t always easy for everyone. But machine-learning algorithms can tease out patterns from inscrutable tangles of complex data. Joint-first-authors Markus Frey and NIH neuroscientist Matthias Nau instructed their model to extract generalizable patterns from the eyeballs using dimensionality reduction techniques, and then to interpret these patterns in a large number of existing MRI datasets.

Here is how it works. When the eyes move, the MRI signal undergoes noticeable variations. To visualize these variations, the team first extracted the eyeball voxels and plotted the normalized signal intensity of those voxels as a function of gaze position. This made it clear that gaze position does indeed affect the eyeball MRI signal a lot.

The researchers then input the eyeball voxels into a convolutional neural network, which selects the relevant features before whittling down the input feature size into more manageable chunks for the underlying processors. The dimensionality-reduced input data then serve as the basis to train fully connected layers, or decoders, to reconstruct gaze positions.

The researchers examined the efficacy of their machine-learning algorithm by comparing DeepMReye data with results from a camera-based eye tracker. With 268 existing participants’ datasets loaded into the CNN, 90 with camera-based eye tracking, the scientists could confirm the high accuracy of their model and tune it accordingly.

The team applied the technique to fMRI datasets from participants performing various visual-related tasks, during which they either maintained fixation or executed pursuit or free-viewing tasks. The ability to apply this algorithm universally, requiring only the MRI information, enables the researchers to extract value from massive datasets that already exist.

Further, unlike MR-compatible eye-tracking cameras, DeepMReye accurately tracks gaze positions even when the eyes are closed, opening new possibilities for resting-state fMRI studies, or even studies of participants in rapid eye movement (REM) sleep. The algorithm could also be used to perform eye tracking in people with blindness, who traditionally have often been excluded from such research because cameras could not be calibrated accordingly. DeepMReye doesn’t need to know whether the patient is blind or not – the algorithm works on all individuals.

Scientists and doctors believe that eye tracking could prove invaluable for research, helping to inform studies exploring our visual or oculomotor systems. For example, pairing neuroimaging maps of whole-brain activity with precise measurements of eye movements from eye trackers can help researchers learn more about Alzheimer’s disease and other neural disorders.

Spread the word: The team provides documentation on DeepMReye (logo pictured above) to stimulate and encourage eye tracking in research studies. (Courtesy: Matthias Nau & Markus Frey)

What began as a weekend project is now an open source code downloadable on the researchers’ GitHub page. But when will eye-tracking become the gold-standard in fMRI research? Further advances could lead to better modelling, which becomes a robust readout of our behaviours. Since our eyes express our thoughts, goals and memories, this is yet another example of how artificial intelligence can help to replace expensive hardware with free software for the benefit of all. Ultimately, the research conducted with this new tool could help us understand better who we are.

The James Webb Space Telescope launches astronomy into a new era

After decades in the making, the James Webb Space Telescope (JWST) finally launched on 25 December 2021, ushering in a new era for astronomy. On Monday the $10bn mission reached its destination, the L2 Lagrange point 1.5 million kilometres from Earth, where it will remain in orbit throughout the mission.

In this episode of the Physics World Stories podcast, Andrew Glester meets JWST scientists to recall their experiences of the mission launch and the telescope’s journey so far. Now, the researchers are looking ahead with excitement to the science programme, which gets under way in June or July.

Jonathan Gardner, the JWST’s deputy senior project scientist, describes the fierce competition among astronomers to win time to use the state-of-the-art telescope. Gardner’s own research in deep surveys will benefit as the JWST can peer back to some of the first galaxies to form after the Big Bang.

Joining Gardner on the podcast is Stefanie Milam, the JWST’s deputy project scientist for planetary science. Milam describes how the telescope will explore the watery moons of Europa and Enceladus within our solar system, as well as investigating the atmospheres of exoplanets in search of intriguing chemical signals.

Find out more about the JWST mission in this feature article by Keith Cooper, originally published in the January issue of Physics World.

Twisted light from semiconducting nanohelices could speed drug discovery

Researchers in the UK and the US have discovered a novel photonic effect that could make it far easier for chemists to assess the chirality of new drug candidates. Led by Ventsislav Valev at the University of Bath, the team achieved the result after synthesizing semiconductor nanohelices that emit intense, twisted blue light along a single direction when illuminated with red light. Their findings could be key to maintaining the rapid pace of modern drug discovery.

Today, drug development techniques are highly automated. Using AI algorithms, robotic chemists can produce millions of mixtures in a single process, creating vast libraries of chemical compounds. To determine whether any of these chemicals may be promising drug candidates, these systems must analyse tiny volumes of them in quick succession. This currently involves the use of microplates containing thousands of wells – each with a volume as small as a cubic millilitre and filled with a unique chemical sample.

Such minuscule sizes create a problem for the latest analytical techniques, especially when assessing the chirality of molecules within a sample – a key measurement for drug analysis. Currently, the optical techniques required to determine chirality require volumes up to 1000 times larger than modern microplate wells. This is a particularly pressing problem, since although some chiral molecules may have identical chemical formulae to their opposite-handed counterparts, their structures can make them ineffective, or even actively harmful to patients when used in drugs.

In the study, described in Nature Photonics, Valev’s team addressed this issue using a novel nanostructure, which mimics the self-assembling behaviours of biological proteins. Firstly, the researchers synthesized twisted ribbons of the semiconductor cadmium telluride – between 5 and 8 µm in length, and roughly 25 nm in width. Without any encouragement, these ribbons braided themselves together to form nanohelices, with chiralities that altered themselves to match those of molecules in their surrounding environments.

When the team illuminated the nanostructures with three different wavelengths of red light, they emitted blue light through the process of third-harmonic Mie scattering. This blue light, which twists like a corkscrew around its axis of travel, was emitted 10 times more strongly along the axes of the helices than in sideways directions, making it easy to collect and analyse. This means that when the helices are dispersed evenly throughout a chemical sample, they provide a highly effective way to measure its chirality indirectly.

Valev’s team calculated that this new type of photonic effect could enable chirality measurements within samples 100,000 times smaller than the wells used in current microplate designs. Since red and blue wavelengths are easily distinguished, the technique could enable chemists to rapidly screen the chiralities of vast numbers of compounds, including samples with complexities approaching those of biological tissues.

Selfishness for the greater good revealed in optimization of group dynamics

Simulation of particles — On the go: Time evolution of the positions of 14 particles, shown as red or yellow dots. (Courtesy: Alexandra Zampetaki/A Zampetaki *et al* *PNAS* e2111142118)

To increase their chances of survival, social organisms communicate in response to changes in resources, according to new research done in Germany. Scientists at the Max-Planck Institute for Extraterrestrial Physics, Heinrich-Heine-University and the Technical University of Darmstadt developed a general model describing groups of organisms or particles that move to produce or consume a certain resource and move collectively to improve their access to it. The team was led by led by physicist Hartmut Löwen and it reports its findings in the Proceedings of the National Academy of Sciences. As well as leading to a better understanding of social organisms, the research could help people who are designing systems of synthetic active particles.

In the Antarctic cold, emperor penguins must huddle up for warmth, but moving too closely together can cause them to overheat. Striking the delicate balance between the two states requires swarms of penguins to organize themselves in complex ways by balancing their attraction and repulsion. They are not alone – from bacteria seeking to optimize their surroundings’ oxygen concentration to foraging ants, groups of living organisms of different complexities show a great capacity for self-organization to achieve the greatest benefit for the collective.

Multiple attempts

Scientists have made multiple attempts to describe this behaviour by modelling individuals as particles with a field representing their external resource, for example, light intensity or oxygen concentration. A challenge is that these models are limited in their complexity. For example, the volume-filling models consider the effect of limited space in realistic situations. However, they describe the system of individuals in terms of optimizing the resource density instead of its field, which captures the more intricate way by which the resource changes in space.

The new model created by Löwen’s team describes the attempts of the individuals to optimize the resource field at their own position. Although both models lead to similar results in linear systems, in the non-linear regimes, the volume-filling models cannot capture the dynamic nature of the systems where the clusters of individuals continue changing, reaching different optimal relative positions or patterns.

Like atoms, the individuals are both attracted to and repulsed by their nearest neighbours, which normally leads to specific particle separations and the formation of packed structures. Yet, the researchers observed the formation of complex and aperiodic clusters of individuals. The nature of their model, using more sophisticated three-body interactions of high degrees of freedom, provides myriad solutions with multiple ways for the collective to reach their optimal state. This can be seen in the figure above, which shows the equilibrium positions of particles at different instances of time, with the background colours showing the value of the resource field. As time goes on (left to right), more particles reach a most favourable state (orange core) with a set of possible optimal positions (pink dashed lines) of higher density at the edges.

All for one or one for all

This is enabled by the existence of noise in the system, allowing individuals to go into the different configurations, true to the dynamic nature of living organisms. In fact, the patterns with high density on the outside really do resemble huddling behaviour in penguin colonies optimizing the temperature field.

In social models, one might expect that an individual must sacrifice for the greater good of the group, but here, having individuals acting only to maximize their personal access to resources, it still creates an optimized solution for the whole collective. The complex dependencies between the choices of the individuals and how they affect each other create what the researchers call an “invisible hand”, which helps the entire group reach its optimum state. In the case of limited resources or when the interests of the individuals are not aligned, there might be a different effect of the tension between selfishness and cooperation.

From mates to matter

The researchers hope that their work can be a stepping-stone for understanding complex phenomena at the intersection of biology, social sciences and physical systems of small particles. For example, the functions describing communicating organisms’ activities can also be applied to more sophisticated living systems.

Löwen and colleagues anticipate the use of similar models not only to describe the searching strategies of animals looking for food or mates, but even for helping to organize rescuers in disaster zones. In addition, the attractive-repulsive nature of the individuals in the model resembles that of charged colloids of nanoparticles. As such, similar models can be used to design systems of synthetic active particles that can be programmed to respond to external stimuli and move independently. These kinds of particles are promising for applications including chemical cleaning or drug delivery. The model can also be used beyond living systems to engineer artificial swarm intelligence, where the swarm can outsmart its individual members thanks to their unique communication.

Ultrathin flexible solar cells get an efficiency boost

Researchers have used materials known as transition metal dichalcogenides to make ultrathin, flexible solar cells with a power conversion efficiency (PCE) of 5.1% – a record for cells made from this type of material. Though this efficiency is far below that of standard silicon solar cells, the super-light nature of the new cells means they could be employed in mobile applications such as self-powered wearable devices and sensors as well as drones and lightweight electric vehicles.

Semiconducting transition metal dichalcogenides (TMDs) such as tungsten diselenide (WSe₂) show much promise for use in optoelectronics devices that need to efficiently absorb sunlight over a wide range of wavelengths. Because these materials are layered (two-dimensional), they can also be made into thin films for low-power electronic circuits and flexible displays, sensors and even flexible electronics that can be coated onto a variety of surfaces. This is why they are touted as a promising alternative to silicon, which despite being today’s most widely-used solar material is much too heavy, bulky and brittle for these applications.

The problem is that most TMD solar cells made so far have struggled to exceed PCEs of around 2%, compared to silicon’s PCE value of nearly 30%. One of the reasons for this is related to the way TMD cells are transferred onto flexible, supporting substrates during fabrication – a process that often damages the TMD layer, reducing its performance.

A team led by Alwin Daus (then at Stanford University in the US, and now a senior researcher at RWTH Aachen University, Germany) and Koosha Nassiri Nazif, a postdoctoral researcher at Stanford, got around this by devising a new method that allows the TMDs to be completely embedded in the substrate, thereby providing a flat surface for a transparent graphene (a sheet of carbon just one atom thick) top electrode. This, combined with a capping layer, makes the TMD solar cells more durable.

The new cells are less than six microns thick, lightweight, flexible, stable and robust for long periods of time, the team reports. They are also biocompatible since – unlike cells made from high-performing perovskites or lead sulphide quantum dots – they contain no toxic elements. Therefore, they could be used in wearable electronics that are worn next to the skin.

High power-to-weight ratio

As well as its PCE of 5.1% – a figure the team say could be increased to 27% with optimization – the new device also has a power-to-weight ratio 100 times greater than that of any other TMD solar cell developed to date. This ratio is important for mobile applications like drones and electric vehicles, explains Nassiri Nazif, co-lead author (with Daus) of a paper in Nature Communications describing the work. “What is more, the specific power – a measure of electrical power output per solar cell unit weight – of the prototype is 4.4 W/g, a figure that compares well with other established thin-film solar cells, such as CdTe, CIGS, III-V and silicon,” he tells Physics World. “Again, this value might be increased – by as much as 10 times – to reach 46 W/g.”

Looking forward, the Stanford team says it now aims to improve the optical and electronic design of the flexible WSe₂cells to increase their PCEs. One possible strategy could be to apply a thicker anti-reflection coating made of Molybdenum oxide (MoOx) to the TMD. Indeed, preliminary computer simulations have revealed that simply increasing the thickness of this coating to around 70 nm could boost the light absorption in the ultrathin WSe₂ to 80%.

Multimode optical fibres make a hair-thin 3D imaging system

A new three-dimensional imaging system uses multimode optical fibres (MMFs) rather than traditional bulk optics, paving the way for applications in medical imaging. The system can scan a scene at a rate of nearly 23,000 points per second over depths of up to several metres beyond the end of a roughly 40 cm-long fibre. It can also record near real-time videos at frame rates of nearly 5 Hz, making it competitive with standard, camera-based fibre-optic endoscopes of the type routinely employed in biomedical research for diagnosing disease and in surgery.

As their name implies, MMFs are a type of optical fibre designed to carry multiple rays of light or light modes at the same time. Each of these rays or modes are reflected at slightly different angles inside the core of the optical fibre, which is usually made of glass and has a diameter in the 50–100 micron range for the light-carrying component. Because the modes tend to disperse as they travel down such fibres, MMFs are typically used to transmit light across relatively short distances. This makes them very different from single-mode fibres, which also contain a glass core (albeit a much smaller one, at less than 10 microns across) through which light can be transmitted at high speeds over longer distances with little modal dispersion.

High-speed wavefront shaping

Creating three-dimensional imaging platforms using MMFs has proved challenging since the optical signals are prone to scrambling, which distorts the resulting images – an effect known as aberration. A team led by Miles Padgett of the University of Glasgow, UK, together with colleagues in Germany and the Czech Republic, has now managed to control this effect thanks to a technique known as high-speed wavefront shaping, synchronized with a sub-nanosecond pulsed laser source to correct aberrations. This approach involves shaping the light fields entering the MMF using a digital micromirror device operating at 22.7 KHz.

The researchers then raster (that is, scan in a pattern of parallel lines) the pulsed laser source across the sample being imaged, delivering a single laser pulse to each of 4200 points in just 200 ms. A second fibre placed next to the illumination fibre then collects backscattered light. This collection fibre has a larger core diameter (500 mm) to increase the amount of light collected and thereby extend the working distance of an endoscope based on this technique, the researchers explain. Finally, the return signal from each image pixel is coupled directly to a device known as an avalanche photodiode and converted to a “time-of-flight histogram”, which is referenced to the time that the outgoing light pulse entered the illumination fibre.

Padgett and colleagues say that as well as biomedical imaging, their prototype time-of-flight-based 3D imaging system could have applications in remote inspection. Reporting their work in Science, they now plan to improve the system’s depth resolution to less than 1 mm and increase its image depth to more than 5 metres. “We also hope to reduce the time it takes to [perform] the fibre calibration,” Padgett tells Physics World.

Long-range quantum entanglement measured at last

Physicists have measured long-range quantum entanglement in special, topologically ordered phases of matter for the first time. This feat, which was achieved independently by two research groups using coupled superconducting circuits and arrays of atoms, could aid the development of robust memories for quantum computers.

When certain materials are cooled to extremely low temperatures, exotic phases of matter appear. These phases are very different from familiar states such as solids, liquids or gases, and the particles in them interact in ways that are dominated by quantum entanglement. This purely quantum-mechanical effect allows two or more particles to be more closely related than classical physics permits, and has numerous applications within quantum computing. In many cases, however, realizing these applications means entangling the particles over long distances within a material – a situation that, while predicted in theory, had never been measured in an experiment until now.

Topologically ordered states

In the latest work, researchers led by Frank Pollmann of the Technical University of Munich, Germany and Pedram Roushan of Google, together with a separate group led by Mikhail Lukin at Harvard University in the US, focused on phases that are topologically ordered, meaning that they retain certain essential properties even when locally deformed.

On the molecular scale, electrons in these special, topologically ordered states can only travel in one direction, meaning that they steer around imperfections or defects on the material’s surface without backscattering as they would in conventional materials. Another benefit is that in topological materials, a surface electron with a certain momentum cannot scatter into a state with opposite momentum because to do so it would have to flip its spin. Such states are thus said to be “topologically protected”, and they are considered desirable for reducing the error rate in quantum computing applications because they mitigate the effects of material defects that would otherwise destroy the quantum information (the spin state) carried by the electrons.

The problem is that conventional techniques cannot be used to probe the long-range entanglement properties of topologically ordered phases – a prerequisite for using them in quantum error correction. Doing this requires fine control of the individual quantum constituents in a system as well as the entanglement interactions between them. Fortunately, such precise control has become possible in recent years thanks to new quantum computing devices.

Quantum simulators

Roushan and colleagues used one such device, Google’s Sycamore quantum processor, to probe the lowest-energy state of the so-called “toric” code – an example of a topologically ordered quantum phase that shows promise for quantum error correction. By executing short quantum programmes on Sycamore, which comprises a two-dimensional array of 31 coupled superconducting quantum devices, the researchers were able to measure long-range entanglement between phases. What is more, they showed that they could encode quantum information into the toric code, thus protecting it from quantum errors.

Lukin and colleagues, for their part, took a different approach to reach the same conclusion. Drawing on a theoretical proposal from a group led by Ashvin Vishwanath, their work involved a collection of 219 atoms that they arranged in a two-dimensional lattice using optical tweezers (devices that use a highly focused laser beam to generate forces that hold and move micron-sized objects in the beam’s trajectory). By controlling the interactions between adjacent atoms in this quantum simulator, the team encouraged the lattice to adopt a topologically ordered phase.

The Harvard researchers then tracked the long-range entanglements that developed between the atoms. In particular, they measured how the quantum correlations set themselves up on the spins of the atoms along a long meandering path that reflected the topological order of the quantum phases. The resulting structure is known as a quantum spin liquid, which despite its name is actually a solid magnetic material that cannot arrange its magnetic moments (or spins) into a regular and stable pattern. This behaviour contrasts with that of ordinary ferromagnets, in which all the spins point in the same direction, and antiferromagnets, in which the spins point in alternating directions.

The Harvard researchers, whose work is described in Science alongside that of the Google–Munich team, say they now plan to use their programmable quantum simulator to continue studying quantum spin liquids and how they can be exploited to create a more robust quantum memory. Members of the Google team, for their part, have written a preprint in which they propose an approach that might allow them to realize even more exotic states. “In particular, we show that even so called ‘non-abelian’ states can be prepared,” Pollmann tells Physics World. “The hope is that future hardware will allow for deeper circuits to implement the proposed protocols.”

Camel’s nose inspires humidity sensor, universe has 40 billion billion black holes, pondering the electron

Camels are adapted for life in arid environments and are therefore very good at finding sources of drinking water. Now, Weiguo Huang at the Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences and colleagues have developed a humidity sensor that is inspired by the structure and properties of the nose of a camel. They say that their device can detect changes in humidity in several environments including industrial exhausts and nearby to human skin.

Existing humidity sensors can be limited in their use. Some are sensitive but not durable – and others are the opposite. Another problem is that very sensitive detectors can be tricky to deploy outside because they are affected by sunlight – something that doesn’t bother camels in the least.

The noses of camels have narrow, scroll-like passages that contain mucus which absorbs water. The team created a porous polymer structure that mimics the high surface area of those passages. The mucus was replaced with moisture-attracting molecules called zwitterions, which act as a dielectric in a capacitor. Changes in humidity are detected as changes in capacitance.

Because the device can detect moisture emitted by human skin, the team reckons that it could be used to create touchless computer interfaces. The sensor is described in ACS Nano.

There are 40 billion billion black holes in the universe, according to new research done by Alex Sicilia at Italy’s Scuola Internazionale Superiore di Studi Avanzati and colleagues. This means that about 1% of the normal matter in the universe is bound up in black holes – something that the team says is a “remarkable amount”.

In the above video, colleague Lumen Boco explains how the team came up with that astonishing number. Much more about the research can be read in an open access paper in The Astrophysical Journal.

Finally, I really enjoyed the video below from the American Chemical Society about the electron. It is at a pretty basic level, but the presenter does a great job of explaining why our existence relies on the fermionic nature of electrons.

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