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US scientific societies condemn racism in the wake of George Floyd death

US scientific societies, universities and technology companies have reacted strongly to the death of African American George Floyd, who was killed on 25 May by a Minneapolis policeman. Responding to Floyd’s death and other African Americans who have died at the hands of police, science-based organizations have condemned injustice, systemic racism and lack of opportunity for minority members in science and the broader community. Yet some have criticized the society statements as coming too little, too late, and without the support of positive action to counter the abuses.

Floyd was arrested on 25 May suspected of carrying a counterfeit $20 bill. Handcuffed and lying face down on the street, a police officer pressed his knee to Floyd’s neck for almost nine minutes, killing him in the process. Following the death, protests and demonstrations were held across the US against systemic racism, excessive use of police force and lack of accountability for police officers.

Racism persists because many of us have refused to see it
Megan Donahue

In a letter to the membership of the National Society of Black Physicists (NSBP), president and Brown University physicist Stephon Alexander noted that racism “poisons law enforcement and can poison the scientific enterprise”. Alexander added that the loss of innocent lives “at the hand of those who are supposed to protect lives deepens our fear and isolation” and encouraged donations to the NSBP, which has supported black physics students and professionals for four decades.

Among the scientific organizations to have added their voice in support of the black community is the American Physical Society (APS). It said in a statement that while systemic racism and racial injustice persist around the world, it was “especially concerned for colleagues of colour and their families”.

APS’s current president-elect and former NSBP president James Gates told Physics World that the society felt it important to issue a statement because “the attitudes are as toxic to democracy and science as poison to a body”. He added that the APS values diversity, equity, inclusion, and respect and that they will work “to take actions that support these values”.

Taking action

However, Fermilab and University of Chicago astrophysicist Brian Nord questioned the APS’s response. “On what planet does APS think that it has convinced Black people of any commitment to justice,” he said on Twitter. “Will there be a letter discussing any real action? No suggestions about concrete things people can do right now?” he asked in other Tweets.

Some admit that the scientific community must take some responsibility for continuing racial problems. “Racism persists because many of us have refused to see it,” astrophysicist Megan Donahue from Michigan State University, who is also president of the American Astronomical Society, said in a statement. “Dispersed across the world, many of us isolated at home, we can barely comprehend the tragedies unfolding across the country and the world, but we know that the trauma of these tragedies will be felt most acutely by the marginalized.”

Several organizations have, however, begun specific efforts to help remedy the situation. The American Meteorological Society, for example, has created a “culture and inclusion cabinet”. AMS president Mary Glackin, who is also a vice-president of The Weather Company, noted in a statement that the society “acknowledges the pain our Black and African American community members are experiencing and hope our solidarity relieves a part of the weight of that path”. Sudip Parikh, chief executive of the American Association for the Advancement of Science, meanwhile, has called for the association to “recommit to systemic change and such relevant principles as ensuring diversity, equity and inclusion”.

Why we need to keep talking about equality in physics

Universities and companies have also joined in the calls to change. Cornell University president Martha Pollack says that her university will “address this scourge of racism directly in our educational programmes, in our research and in our engagement and related activities”. Meanwhile, medical-device company Boston Scientific has pledged to “increase talks with employee resource groups around the world and ask employees to act when they experience or witness intolerance, mistreatment or bias”.

Scientists have also started to promote their own ideas. Sarafina Nance, a graduate student in theoretical astrophysics at the University of California, Berkeley, has compiled some anti-racism resources. And in an article in Forbes, astrophysicist and science writer Ethan Siegel suggests steps that academics can take to “play a major role in transforming science and academia into a safer, more inclusive environment.” Those include recognizing that black students face challenges beyond those that other students face; actively creating a welcoming, supportive environment; and learning how to be inclusive oneself rather than putting the onus on black colleagues.

Why the SpaceX/NASA launch is so important, how to be a successful physics YouTuber

On Saturday 30 May space enthusiasts around the world held their breath as the first commercially built rocket to carry people into orbit lifted off from Florida. On board were two American astronauts heading for the International Space Station – and this joint mission involving NASA and SpaceX has thus far been a success.

In this episode of the Physics World Weekly podcast, aeronautical engineer Steve Bullock and space enthusiast Andrew Glester explain why this launch is an important milestone and what it means for the future of space travel.

Video offers a unique opportunity for physicists to present complex ideas in a way that is accessible to a wide range of people. In this episode, the theoretical physicist and YouTuber Sabine Hossenfelder talks about her YouTube channel “Science without the gobbledygook” – and gives some top tips about how to make physics videos for a general audience, including some advice about using a green screen.

Machine learning teases out differences in high-pressure ice phases

Although nearly all ice found on Earth has a hexagonal structure, at least 17 types of ice are known to exist, each with a different molecular arrangement. Most of these novel variants, however, require high pressures and controlled temperature environments to form, making them difficult to study directly. A team of researchers in China has now used a first-principles neural network potential technique to discriminate between several high-pressure water phases. Their findings add to our understanding of the proton transfer mechanisms involved when these phases melt and could prove important for planetary science as well as fundamental physics and chemistry.

Water is unique in forming a wide variety of different crystalline and amorphous ice structures. Its unusual behaviour in the frozen state stems in part from the weak intermolecular bonds between its two hydrogen atoms, which are separated by a single atom of oxygen.

One of the most-studied alternative forms of ice is known as ice VII. This exotic body-centred cubic (bcc) crystal phase is also known as “hot ice”, and it can form at ambient temperatures under pressures above 3 GPa (about 30 000 times atmospheric pressure at sea level). Ice in this form has been theorized to exist in cold subduction zones within the Earth’s crust, and on Saturn’s icy moon Titan.

phasediagram — The phase diagram of H₂O. Courtesy: Xin-Zheng Li

Another novel ice phase, known as superionic ice or ice XVIII, exists at even higher temperatures and pressures of 1000 kelvin and 40 GPa. This form of frozen water contains liquid-like hydrogen ions – that is, protons – that quickly diffuse through a solid lattice of oxygen atoms. Superionic ice could make up a large fraction of the interiors of the planets Uranus and Neptune, with the fast-diffusing protons helping to generate the strong and complex magnetic fields characteristic of these “ice giant” planets.

Ice VII to superionic ice

In 2005, researchers confirmed experimentally that ice VII can transform into superionic ice at around 47 GPa and 1000 K. They also suggested that the transformation takes place via a “dynamic” form of ice VII in which the protons are more disordered than in conventional ice VII, while still being more localized than they are in superionic ice. This transition, however, proved difficult to simulate using traditional ab initio calculations and force field molecular modelling methods. This is because ab initio methods are normally restricted to short time periods and relatively small supercell simulations, whilst force field-based techniques cannot address the chemical bond breaking associated with proton diffusion in dynamic ice VII.

Xin-Zheng Li of Peking University in Beijing and colleagues believe they have now overcome this problem by applying an alternative modelling technique based on neural network potentials. Their model used a popular deep-learning package (the DeePMD-kit) to create large-scale simulations that are as accurate as density-functional theory (DFT) calculations and require about the same amount of computing time and power.

The results of these simulations enabled the researchers to explore the nature of high-pressure water phases at an atomic level. They found that dynamic features, such as the diffusive motion of hydrogen and oxygen atoms, are indispensable for distinguishing between several subtle and “non-trivial” ice phases.

Detailed phase diagram

In dynamic ice VII, for example, Li’s team identified two subtle phases, which they dubbed dynamic ice VII T and dynamic ice VII R. The former incorporates local motion and transversal transfer of protons while the latter also accounts for their rotational transfer. They also interpreted the superionic phase as involving the non-trivial melting of ice VII at pressures above 40 GPa.

According to Li, the transition from ice VII to superionic ice can be understood as occurring when oxygen and hydrogen atoms simultaneously escape from the crystal sites in ice VII at moderate pressures just as the solid structure suddenly breaks down. At higher pressures (above 40 GPa), the hydrogen atoms melt first, followed by the oxygen atoms.

Based on these results, the researchers have drawn up a detailed phase diagram (see image above), which they say will be useful for understanding how water behaves under high pressures. “The method to detail this diagram could be extended to other materials – even those that are thought to be relatively well understood,” Li tells Physics World.

The research is detailed in Chinese Physics Letters, which is published by IOPP.

Neutron stars may contain free quarks

A long-standing debate about what lies at the heart of neutron stars might soon be cleared up, if a new analysis reconciling observational data and theory is vindicated. The latest research, carried out by physicists in Europe and the US, concludes that massive neutron stars are likely to have free quarks in their core rather than being entirely composed of neutrons and other non-fundamental particles. If such extremely dense cores exist, the researchers say that their presence may leave telltale traces in gravitational-wave data from merging neutron stars.

Quarks are normally confined inside protons and neutrons, but they can exist as individual particles if the energy density is high enough. Scientists know this because researchers working on experiments at the CERN laboratory in Switzerland and the Brookhaven National Laboratory in the US have collided heavy ions to generate what is known as a quark-gluon plasma – a “soup” of free quarks and strong force-carrying gluons that is thought to have existed for a few milliseconds after the Big Bang.

It is possible that quarks could also break free from their confined states within the cores of neutron stars. These extremely dense objects form when giant stars collapse and shed most of their material in a supernova explosion. Physicists are confident that neutron stars contain a variety of elements in their outer layers and individual neutrons further in. But they are not sure what exists in the core, and whether neutrons remain intact or break down into their constituent quarks and gluons.

Although energy densities in the core are comparable to those generated by heavy-ion collisions, the “quark matter” that would be produced is quite different from the quark-gluon plasma recreated in laboratories – cooler, but far more dense. Unfortunately, the computational scheme used to simulate quark-gluon plasma, known as lattice quantum chromodynamics (lattice QCD), is unable to model the cold, matter-heavy interiors of neutron stars.

Model-independent analysis

To get around this problem, Eemeli Annala of the University of Helsinki in Finland and colleagues carried out a model-independent analysis of astrophysical data and theoretical calculations. In a paper published in Nature Physics, they point out that nuclear theory can describe fairly precisely how the pressure experienced by protons, neutrons and other quark-containing hadrons varies with energy density in the relatively un-dense environment of a neutron star’s crust. Similarly, they say, QCD can be used to calculate this pressure variation – known as an equation of state – at very high densities.

The real challenge is to work out what goes on between these two extremes, since it is here that neutron-star cores lie. Annala and colleagues took the approach of plotting the variation of a vast ensemble of functions used to represent a neutron star’s equation of state across the full range of energy densities. They tried to be as unbiased as possible in selecting the functions, varying only the maximum speed of sound through the neutron-star matter and anchoring the plots using two empirical constraints: that neutron stars weigh as much as 1.97 solar masses; and that the tidal distortion of a 1.4-solar mass neutron star matches observed values.

The researchers found that their modelled equations of state agreed fairly well with those of standard hadronic theory for lower-mass neutron stars – confirming, they say, that the gravitational fields in these bodies are not high enough to rip neutrons and protons apart. In the most massive neutron stars, however, they found very little agreement between the two sets of modelled data. As such, they conclude that quark cores in massive neutron stars should be considered “the standard scenario, not an exotic alternative”.

As group member Aleksi Kurkela of the CERN laboratory in Switzerland explains, the very few points that do agree would require sound to zip through neutron stars at velocities of at least 90% the speed of light. But he argues that this is very unlikely, simply because scientists know of no physical system that could support such speeds. “Having matter with such a high speed of sound would be truly remarkable,” he says.

Indeed, Kurkela adds that more typical speeds imply that the quark cores are relatively large. By stipulating that sound waves travel no quicker than about half the speed of light, he and his colleagues predict that a 24-km diameter neutron star would have a quark core some 13 km across.

Confirmation still needed

The researchers reckon that their predictions could be put to the test. Shock waves reflecting off the edge of a very dense quark-matter core could, they argue, leave an imprint in the gravitational waves generated when neutron stars merge.

However, not everyone is convinced. James Lattimer, an astrophysicist at Stony Brook University in the US, thinks it likely that quark matter exists inside massive neutron stars. But he maintains that the study relies on too much interpolation – some two orders of magnitude in energy density – to draw firm conclusions. He also notes that the physical conditions assumed by the authors to yield quark-matter cores have been shown by other researchers to produce cores containing only hadronic matter.

Laura Paulucci, an astrophysicist at the Federal University of ABC in Brazil, largely agrees. She argues that while the latest research indicates that quark cores are likely to exist, it falls short of providing direct evidence. “It is difficult to say how long it will take until we have a clearer picture and a definite answer,” she says. “I hope it is not long.”

AI-reconstructed medical images can’t be trusted

Image reconstruction — Images (x) including small structural perturbations (r, text and symbols) reconstructed with neural networks (Ell 50, DAGAN and MRI-VN) and state-of-the-art (SoA) methods. (Courtesy: *Proceedings of the National Academy of Sciences* 10.1073/pnas.1907377117)

Medical images reconstructed using artificial intelligence (AI) techniques are unreliable, according to recent research by an international team of mathematicians. The team found that deep learning tools that create high-quality images from short scan times produce multiple alterations and artefacts in the data that could affect diagnosis. These issues were found in multiple systems, suggesting the phenomenon will not be easy to fix.

Cutting medical scan time could reduce costs and allow more scans to be performed. To enable this, some researchers have developed AI systems that construct high-quality images from low-resolution scans. The medical imaging equipment samples fewer data points than would normally be required and the AI enhances these data to create a high-resolution image. The AI trains on previous datasets from high-quality images. This is a radical shift from classical reconstruction techniques based on mathematical theory, which do not learn or rely on previous data.

A study published in the Proceedings of the National Academy of Sciences, however, finds that these AI algorithms have serious instability issues. Small structural changes, such as the presence of a small tumour, may not be captured, while tiny, almost undetectable perturbations, like those created by patient movement, can lead to severe artefacts in the final image.

The team, led by Anders Hansen at the University of Cambridge, tested six different neural networks trained to create enhanced images from MRI or CT scans. The researchers fed the networks data designed to replicate three possible issues: tiny perturbations; small structural changes; and changes in the sampling rate compared with the data on which the AI was trained.

Tiny perturbations can be generated by factors such as the patient shifting, white noise-like issues from the scanner and small anatomic differences between people, the researchers say. Such issues created multiple different artefacts and instabilities in the AI systems.

“What we show is that a tiny perturbation that is so small that you can’t even see it with your eyes can suddenly make a change so that there is now a new thing that appears in the image, or something that is removed,” Hansen explains. “So, you can get false positives and false negatives.”

To test the ability of the systems to detect small structural changes the team added letters and symbols from playing cards to the images. One of the networks was able to reconstruct these details, but the other five presented issues ranging from blurring to almost complete removal of the changes.

Only one of the neural networks produced better images as the researchers increased the sampling rate of the scans. Another stagnated, with no improvement in quality, while in three, the reconstructions dropped in quality as the number of samples increased. The sixth AI system does not allow the sampling rate to be changed.

Hansen says that researchers need to start testing the stability of these systems. “What they will see on a large scale is that many of these AI systems are unstable,” he explains. The “big, big problem”, according to Hansen, is that there is no mathematical understanding of how these AI systems work. “They become a black box and if you don’t test these things properly you can have completely disastrous outcomes.”

Similar instabilities have also been highlighted in deep-learning tools that classify images. “You take a tiny little perturbation and the AI systems says the image of the cat is suddenly a fire truck,” Hansen explains. He says that you can now imagine a system where you use an unstable AI to classify a medical image that has been reconstructed by another unstable neural network. “You are now going to decide do you have cancer or not? The question is, would you like to try it?” he asks.

Hansen believes that these reconstruction techniques do have potential, but there are things that machine learning will not be able to figure out. “What is absolutely crucial is to understand the limitations,” he explains.

Such techniques are not yet being used clinically. The team say that they created the tests as they do not want them to be approved by regulatory bodies unless they have been thoroughly tested.

White papers: Bruker Nano, Dectris and Park Systems

white papers from Bruker, Dektris and Park Systems — Innovation in action: (left to right) topography rendered in 3D view to study roughness (Courtesy: Bruker); Ligand binds at the dimer interface of trypanothione reductase (Courtesy: Dectris); AFM topography of a dehydrated collagen fibrils sample scanned using AutoScript (Courtesy: Park Systems).

This time we are featuring white papers from three firms: Bruker Nano, Dectris and Park Systems. You can access the content by following the link in the name of the relevant white paper.

Material properties

Bruker is showcasing two white papers. The first is on surface roughness, which is widely used in industry to validate manufacturing processes and guarantee the quality of products. Subjective judgements of quality, which you can obtain by looking at the surface of a product with your naked eye or feeling it with your finger, have steadily been replaced by unbiased metrics and well-defined formulas. In Advantages of Measuring Surface Roughness with White Light Interferometry, Samuel Lesko (Bruker Nano Surfaces and Metrology, Tucson, Arizona, US) reviews how surface roughness has evolved as a key manufacturing parameter.

Bruker’s other white paper concerns the viscoelastic properties of heterogeneous materials such as polymer composites, blends and multilayers. Making bulk measurements is routine, but it is harder if these materials are composites with nano-sized domains. Fortunately, atomic-force microscopy could provide the answer, as you can discover in Measuring Nanoscale Viscoelastic Properties with AFM-Based Nanoscale DMA by Bede Pittenger and Sergey Osechinskiy (Bruker Nano Surfaces, Santa Barbara, California, US), and Dalia Yablon (SurfaceChar, LLC).

Powerful detectors

Macromolecular crystallography is the most powerful method for determining the 3D structures of biological macromolecules. Most data are collected at large synchrotron facilities, but these days many crystal structures can be just as easily determined in the lab with detectors from companies such as Dectris. In Macromolecular Crystallography in the Laboratory, Andreas Förster shows how you can get publication-quality structures in the time it takes to send crystals to a synchrotron.

Meanwhile, in PILATUS3 CdTe Detector Technology and its Applications, Tilman Donath describes Dectris’s PILATUS3 CdTe detectors, which are the largest commercially available CdTe detectors for high-energy X-ray detection. He also explains how they are used not just for solving crystal structures, but in geology and materials science, too.

Microscopy matters

Atomic-force microscopes (AFMs), which image materials by probing them with the sharp tip attached to the end of a cantilever, have developed hugely since the first devices were built in the 1980s. But progress has been much more gradual in terms of how fast samples can be studied, with AFM users having to manually place samples on a stage. In Park SmartScan and AutoScript: Improving Operational Throughput and User Productivity, Gerald Pascual, Mina Hong, Byong Kim and Keibock Lee (Park Systems Inc., Santa Clara, California, US) describe the advantages of Park Systems’ large motorized stage, which lets users load large samples and also study small samples one at a time.

If you want to study the structure of biological cells, it is common to “fix” their structure in place before turning to microscopy. But how well do these techniques really conserve the cells’ essential chemical and physical characteristics? In Mechanical Properties of Live and Fixed Cells Measured by Atomic Force Microscopy and Scanning Ion Conductance Microscopy, Jake Kim, Moses Lee and Cathy Lee (Park Systems Corp., Suwon, Korea) show how different microscopy techniques can reveal quantitative differences.

Thanks to their unique electromechanical and electrical properties, ferroelectrics are widely used in industry as actuators, sensors and capacitors. Researchers are also investigating them for use in modern communication technologies such as 5G or solar cells. In Stabilizing the Piezoresponse for Accurate and Crosstalk-free Ferroelectric Domain Characterization via Dual Frequency Resonance Tracking, Ilka Hermes (Park Systems Europe, Mannheim, Germany) and Romain Stomp (Zurich Instruments, Zurich, Switzerland) show how they imaged the ferroelectric domains of a bismuth-ferrite film with resonance-enhanced piezoelectric-force microscopy (PFM) on a Park Systems NX10 AFM with a Zurich Instruments HF2 Lock-In Amplifier.

Katsuhiko Sato: from inflation to science policy

Your first paper was with the physics Nobel laureate Hans Bethe. How did that come about?

Yes, it was my very first paper and was published in 1970 when I was still a graduate student at Kyoto University (Astronomy and Astrophysics 7 279). Bethe stayed in Kyoto for around four months and I was very fortunate to work with him at that time on the melting of nuclei in neutron stars. Bethe always explained things very kindly, using easy words. During this time I realized what a great physicist he was. It was a great start to my career.

You worked on the early universe next. What was interesting about this?

In 1979 I was invited to the Nordic Institute for Theoretical Atomic Physics in Copenhagen for a year to work on supernova explosions. At that time I was becoming more interested in cosmology, in particular what effects phase transitions had in the early universe. I found that cosmic expansion becomes exponential, and this is what we call inflation.

At the same time, physicists Alan Guth and Alexei Starobinsky independently came up with inflation and the theory had an immediate impact. What was it like watching the idea take hold?

It is very natural for scientists to come up with the same idea at the same time. Researchers read articles from around the world and from this, new ideas are born. What surprised me regarding inflation theory is that today many scientists are still working on new types of inflation. Alan Guth and I proposed inflation as a result of grand unified theories, but it was found there are some difficulties with this model. Now many types of inflation are proposed from various other points of view such as superstring theory. In that sense, the situation is a little complicated and confusing.

What did you think when you first heard that BICEP2 had detected signatures of inflation in the cosmic microwave background, only for it to be later disproved?

When I first heard the news, I was very pleased. I told Japanese newspaper and television reporters that this was a historic discovery. But when I learned that this important result for inflation theory had disappeared I was very sad. So now I’m greatly looking forward to a Japanese-led satellite mission called LiteBIRD, which has just been approved by the Japanese government. It involves people from NASA and the European Space Agency and will be 100 times more sensitive than BICEP2. This kind of co-operation is becoming stronger and stronger and is very important.

What surprised me is that many scientists are still working on new types of inflation

In the 1990s you switched into science administration, including two stints as president of the Physical Society of Japan. What attracted you to make this move?

Theoretical physicists usually make their contributions when they are young. I was getting old and felt that to continue making a contribution to science and Japanese society, I should move into science administration. At least then my research position could be used by an early-career scientist.

You’ve just stepped down as director of the Research Centre for Science Systems at the Japan Society for the Promotion of Science – a position you held since 2016. What does the research centre do?

Our primary mission is to advise the government on scientific research funding. Our secondary mission is to select scientists to review applications from researchers for competitive grants. There are approximately 100,000 applications each year and we have about 7000 reviewers. These are huge numbers. Although I stepped down as director at the end of March, I am staying on as a consultant.

Do you think the International Linear Collider (ILC) should be built in Japan?

I think the ILC should be built. Not only could the ILC produce large quantities of Higgs bosons, but the signal should be very clean. However, it is difficult for the ILC to be approved by the Japanese government as the total construction cost is estimated at more than 800 billion yen ($7bn). Of course, we will make many efforts to help the government understand the long-term scientific significance of this project.

How important is it that physicists communicate with the public to get their support for big projects like the ILC?

This is a very important role for scientists. Government support for science comes from people’s taxes so we must tell people about the results and achievements of science, and we must make it interesting. The Subaru Telescope in Hawaii is a good example. It has been very successful when communicating its results to the public and Japanese society has shown great support for this project.

Are you confident that Japan’s rich history in physics will continue?

The Japanese science budget has been decreasing for a number of years, which has been challenging for Japan’s academic community. On the other hand, although government support for universities has been hurt by cuts, the money given directly to researchers through competitive grants is actually increasing. So it is not easy – scientists must make great efforts – but we should still have hope for Japanese science.

Image quality analysis for MR in radiotherapy using the MagphanRT system

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Watch now

MRI manufacturers have made great strides in reducing MR system distortion. Maintaining acceptable levels of distortion relies on properly controlling a long chain of conditions. A robust system of quality control for crucial imaging performance characteristics is critical for detecting significant deviations before they affect clinical operations. The Phantom Laboratory’s MagphanRT^® phantom design meets the specific QA needs for MR imagers in radiotherapy applications. MagphanRT’s modular configuration allows QA measurements over the wide fields of view found in radiotherapy applications.

This webinar presented by Richard Mallozzi will discuss:

The design and accompanying automated analysis of the phantom.
Setting up an automated QA system with the accompanying cloud-based Smári image analysis system.
Clinical experience and findings using the MagphanRT.

Want to learn more on this subject?

Watch now

Richard Mallozzi earned an AB in physics from Harvard University. He also gained a PhD in physics from the University of California at Berkeley in 1998, where he studied high-temperature superconductivity.

After graduating from UC Berkeley, Mallozzi joined GE Global Research as a magnetic resonance scientist, where he worked on diverse projects ranging from MRI acoustic noise reduction, interventional MRI, gradient and RF coil development, and applications of MRI to neuroimaging.

While at GE Global Research, Mallozzi collaborated with The Phantom Laboratory and GE scientist Daniel Blezek to develop the phantom and analysis technique that formed the basis of the control method.

Richard joined ONI Medical Systems in 2007, where he helped develop the first high-field (1.5 Tesla) commercial extremity MRI system. He then joined The Phantom Laboratory and Image Owl in 2014, where he works on a variety of physics and application issues pertinent to medical imaging. He co-designed the Magphan RT system and developed the automated analysis for the phantom.

Cyanobacteria and nanomaterials give solar cell a boost

Strategically designed nanomaterials have been used to optimize the performance of a solar cell that incorporates photosynthesizing cyanobacteria. The work was done by Jae Ryoun Youn, Young Seok Song and colleagues at Seoul National University and Dankook University in South Korea. What is especially impressive about their new technology is that it exploits a broad region of the solar spectrum while simultaneously boosting the photosynthetic activity of the cyanobacteria.

The Sun offers a supply of clean and renewable energy, but how to utilize this limitless yet decentralized energy source as efficiently and practically as possible is a significant engineering challenge. The Korean team is pursuing a biological solution to this problem in cyanobacteria, which are ancient organisms that carry out photosynthesis and respiration in almost every environment on Earth.

Optimized biophotovoltaic cell

The device, described in Nano Letters, achieved enhanced efficiency by employing three separate active materials, each covering different regions of the solar spectrum.

Zinc oxide nanorods are highly photoactive in the ultraviolet region, but the researchers extended this range to include visible light by coating the nanorods with another functional nanomaterial: gold nanoparticles. These exhibit localized surface plasmon resonance, a phenomenon capable of increasing the photoactivity of semiconductors through strong light absorption and scattering; and an enhanced local electromagnetic field at a specific frequency. Essentially, the gold nanoparticles act as tiny light-harvesting antennas.

By loading this hybrid nanostructure with cyanobacteria, the scientists made a third light-harvesting addition to the system and achieved a further boost in performance. Using electromagnetic field simulations and measurements, the authors showed that the zinc oxide nanorods scattered light across the spectral regions favoured by the cyanobacteria towards the organisms at the top of the photoanode. Furthermore this scattered light was amplified by the gold nanoparticles. They concluded that as well as harvesting light through interband transition and hot-electron injection, respectively, the zinc oxide nanorods and gold nanoparticles improved the power output of the cyanobacteria.

Dark current and a sunny outlook

In addition to their environmentally friendly nature and self-healing ability, cyanobacteria have another trick up their microscopic sleeves when it comes to biophotovoltaics. The researchers demonstrated that their solar cell even produced photocurrent in the dark. This is because cyanobacteria can continue to break down stored carbon intermediates accrued during light periods. Given the cyclic nature of the energy provided by the Sun, this so-called “dark current” could help to reduce demand on energy storage systems.

In light of their results, the authors believe that this study paves the way for further development in the field of biophotovoltaics, enabling energy generation which is both efficient and sustainable.

Full details of the research are reported in Nano Letters.

Ammonia emissions can drive urban smog formation

Nitric acid and ammonia vapours can condense onto new aerosol particles and rapidly accelerate their growth, the CLOUD experiment (Cosmics Leaving Outdoor Droplets) at CERN has found. This may explain the smog that can engulf megacities on cold winter days, the researchers say, and provides evidence that tighter controls on ammonia emissions from vehicles and other sources are needed.

Winter urban smog occurs when pollution particles form and build up in cold air in and over the city that’s trapped under warmer air at higher altitudes. This temperature inversion suppresses convection, preventing the dispersal of the air pollution. But how these new particles continue to form has been a mystery, as theory suggests that they should be rapidly scavenged by the high concentration of pre-existing particles.

“When there is a winter smog episode, we’re seeing new particles continuously forming and these are making the clouds thicker and more opaque,” explains Jasper Kirkby, head of the CLOUD experiment. “It was not understood how these particles could form, because as soon as a small particle forms within a highly polluted environment it will collide with the pre-existing particles and basically be removed from creating new particles.”

The CLOUD experiment is able to replicate the atmosphere anywhere in the world in a special, ultra-clean chamber. It was designed to investigate the impact of cosmic rays on aerosol, cloud droplet and cloud formation, by taking advantage of CERN’s proton synchrotron, an adjustable source of cosmic rays. But it can be used to explore other atmospheric processes.

In the latest work, published in Nature, Kirkby and colleagues mimicked the range of atmospheric conditions typical of polluted megacities to investigate the role of ammonia and nitric acid in particle formation. They varied the temperature of the chamber from 20°C to −25°C, and adjusted the levels of sulphuric acid, ammonia and nitric acid, as well as aromatic precursors, to cover typical ranges of polluted megacities.

They found that at low temperatures, below about 5°C, nitric acid and ammonia vapours can condense onto freshly nucleated particles that are just a few nanometres in diameter. Due to the high abundance of these vapours, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. This speeds the particles through the so-called “valley of death”, where very small particles are most vulnerable to loss, in a few minutes.

Kirkby says that nitric acid and ammonia are volatile vapours that are continuously exchanging with particles in the atmosphere, “so they previously were thought to be playing just a passive role, adding a bit of mass to smog, but not really driving the processes”. He adds: “What we found is that they are actually key players and they are helping new particles form in highly polluted environments.”

Due to the strong temperature dependence, the researchers expect the conditions necessary for rapid particle growth to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and strong local sources of emissions such as traffic. Although the rapid growth may only last for a few minutes at a time, across an urban area this effect could still lead to the build-up of high concentrations of visible particles and dense smog.

The study also found that at temperatures below -15°C, ammonia and nitric acid can condense together and form their own ammonium nitrate particles – which then rapidly grow.

Global emissions of ammonia are dominated by farming. In cities, however, ammonia and nitric acid emissions are largely due to vehicles. Vehicle emissions of nitric acid, which derives from nitrogen oxides, are currently controlled. Ammonia emissions, however, are not. In fact, Kirkby says that such emissions are increasing in cities, as catalytic convertors on vehicles are creating ammonia.

According to Kirkby, the study results are significant for human health and urban pollution. “It has highlighted the importance of controlling ammonia inside urban environments,” he explains.

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