Scientists in the US have developed a new type of photovoltaic battery that runs on the energy given off by nuclear waste. The battery uses a scintillator crystal to transform the intense gamma rays from radioisotopes into electricity and can produce more than a microwatt of power. According to its developers at Ohio State University and the University of Toledo, it could be used to power microelectronic devices such as microchips.

The idea of a nuclear waste battery is not new. Indeed, Raymond Cao, the Ohio State nuclear engineer who led the new research effort, points out that the first experiments in this field date back to the early 1950s. These studies, he explains, used a 50 milli-Curie ⁹⁰Sr-⁹⁰Y source to produce electricity via the electron-voltaic effect in p-n junction devices.

However, the maximum power output of these devices was just 0.8 μW, and their power conversion efficiency (PCE) was an abysmal 0.4 %. Since then, the PCE of nuclear voltaic batteries has remained low, typically in the 1–3% range, and even the most promising devices have produced, at best, a few hundred nanowatts of power.

Exploiting the nuclear photovoltaic effect

Cao is confident that his team’s work will change this. “Our yet-to-be-optimized battery has already produced 1.5 μW,” he says, “and there is much room for improvement.”

To achieve this benchmark, Cao and colleagues focused on a different physical process called the nuclear photovoltaic effect. This effect captures the energy from highly-penetrating gamma rays indirectly, by coupling a photovoltaic solar cell to a scintillator crystal that emits visible light when it absorbs radiation. This radiation can come from several possible sources, including nuclear power plants, storage facilities for spent nuclear fuel, space- and submarine-based nuclear reactors or, really, anyplace that happens to have large amounts of gamma ray-producing radioisotopes on hand.

The scintillator crystal Cao and colleagues used is gadolinium aluminium garnet (GAGG), and they attached it to a solar cell made from polycrystalline CdTe. The resulting device measures around 2 x 2 x 1 cm, and they tested it using intense gamma rays emitted by two different radioactive sources, ¹³⁷Cs and ⁶⁰Co, that produced 1.5 kRad/h and 10 kRad/h, respectively. ¹³⁷Cs is the most common fission product found in spent nuclear fuel, while ⁶⁰Co is an activation product.

Enough power for a microsensor

The Ohio-Toledo team found that the maximum power output of their battery was around 288 nW with the ¹³⁷Cs source. Using the ⁶⁰Co irradiator boosted this to 1.5 μW. “The greater the radiation intensity, the more light is produced, resulting in increased electricity generation,” Cao explains.

The higher figure is already enough to power a microsensor, he says, and he and his colleagues aim to scale the system up to milliwatts in future efforts. However, they acknowledge that doing so presents several challenges. Scaling up the technology will be expensive, and gamma radiation gradually damages both the scintillator and the solar cell. To overcome the latter problem, Cao says they will need to replace the materials in their battery with new ones. “We are interested in finding alternative scintillator and solar cell materials that are more radiation-hard,” he tells Physics World.

The researchers are optimistic, though, arguing that optimized nuclear photovoltaic batteries could be a viable option for harvesting ambient radiation that would otherwise be wasted. They report their work in Optical Materials X.

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Baseball season just started, and everyone’s talking about these crazy new bats. Will they change the game?

The nervous system is often considered the body’s wiring, sending electrical signals to communicate needs and hazards between different parts of the body. However, researchers at the University of Massachusetts at Amherst have now also measured bioelectronic signals propagating from cultured epithelial cells, as they respond to a critical injury.

“Cells are pretty amazing in terms of how they are making collective decisions, because it seems like there is no centre, like a brain,” says researcher Sunmin Yu, who likens epithelial cells to ants in the way that they gather information and solve problems. Alongside lab leader Steve Granick, Yu reports this latest finding in Proceedings of the National Academy of Sciences, suggesting a means for the communication between cells that enables them to coordinate with each other.

While neurons function by bioelectric signals, and punctuated rhythmic bioelectrical signals allow heart muscle cells to keep the heart pumping blood throughout our body, when it comes to intercell signals for any other type of cell, the most common hypothesis is the exchange of chemical cues. Yu, however, had noted from previous work by other groups that the process of “extruding” wounded epithelial cells to get rid of them involved increased expression of the relevant proteins at some distance from the wound itself.

“Our thought process was to inquire about the mechanism by which information could be transmitted over the necessary long distance,” says Yu. She realised that common molecular signalling mechanisms, such as extracellular signal-regulated kinase 1/2 (ERK), which has a speed of around 1 mm/s, would be rather slow as a potential conduit.

Epithelial signals measure up

Yu and Granick grew a layer of epithelial cells on a microelectrode array (MEA). While other approaches to measuring electrical activity in cultured cells exist, an MEA has the advantage of combining electrical sensitivity with a long range, enabling the researchers to collect both temporal and spatial information on electrical activity. They then “wounded” the cells by exposing them to an intense focused laser beam.

Following the wound, the researchers observed electrical potential changes with comparable amplitudes and similar shapes to those observed in neurons, but over much longer periods of time. “The signal propagation speed we measured is about 1000 times slower than neurons and 10 times faster than ERK,” says Yu, expressing great interest in whether the “high-pitch speaking” neurons and heart tissue cells communicate with these “low-pitch speaking” epithelial cells, and if so, how.

The researchers noted an apparent threshold in the amplitude of the generated signal required for it to propagate. But for those that met this threshold, propagation of the electric signals spanned regions up to 600 µm for as long as measurements could be recorded, which was 5 h. Given the mechanical forces generated during “cell extrusion”, the researchers hypothesized the likely role of mechanosensitive proteins in generating the signals. Sure enough, inhibiting the mechanosensitive ion channels shut down the generation of electrical signals.

Yu and Granick highlight previous suggestions that electrical potentials in epithelial cells may be important for regulating the coordinated changes that take place during embryogenesis and regeneration, as well as being implicated in cancer. However, this is the first observation of such electrical potentials being generated and propagating across epithelial tissue.

“Yu and Granick have discovered a remarkable new form of electrical signalling emitted by wounded epithelial cells – cells traditionally viewed as electrically passive,” says Seth Fraden, whose lab at Brandeis University in Massachusetts in the US investigates a range of soft matter topics but was not involved in this research.

Fraden adds that it raises an “intriguing” question: “What is the signal’s target? In light of recent findings by Nathan Belliveau and colleagues, identifying the protein Galvanin as a specific electric-field sensor in immune cells, a compelling hypothesis emerges: epithelial cells send these electric signals as distress calls and immune cells – nature’s healers – receive them to rapidly locate and respond to tissue injuries. Such insights may have profound implications for developing novel regenerative therapies and bioelectric devices aimed at accelerating wound healing.”

Adam Ezra Cohen, whose team at Harvard University in the US focuses on innovative technology for probing molecules and cells, and who was not directly involved in this research, also finds the research “intriguing” but raises numerous questions: “What are the underlying membrane voltage dynamics?  What are the molecular mechanisms that drive these spikes? Do similar things happen in intact tissues or live animals?” he asks, adding that techniques such as patch clamp electrophysiology and voltage imaging could address these questions.

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I was unprepared for the Roger Penrose that I met in The Impossible Man. As a PhD student training in relativity and quantum gravity at the Perimeter Institute for Theoretical Physics in Waterloo, Canada, I once got to sit next to Penrose. Unsure of what to say to the man whose ideas about black-hole singularities are arguably why I took an interest in becoming a physicist, I asked him how he had come up with the idea for the space-time diagrams now known as “Penrose diagrams”.

Penrose explained to me that he simply couldn’t make sense of space-time without them, that was all. He spoke in kind terms, something I wasn’t quite used to. I was more familiar with people reacting as if my questions were stupid or impertinent. What I felt from Penrose – who eventually shared the 2020 Nobel Prize for Physics with Reinhard Genzel and Andrea Ghez for his work on singularities – was humility and generosity.

The Penrose of The Impossible Man isn’t so much humble as oblivious and, in my reading, quite spoiled

In hindsight, I wonder if I overread him, or if, having been around too many brusque theoretical physicists, my bar as a PhD student was simply too low. The Penrose of The Impossible Man isn’t so much humble as oblivious and, in my reading, quite spoiled. As a teenager he was especially good at taking care of his sister and her friends, generous with his time and thoughtfulness. But it ends there.

As we learn in this biography – written by the Canadian journalist Patchen Barss – one of those young friends, Judith Daniels, later became the object of Penrose’s affection when he was a distinguished faculty member at the University of Oxford in his 40s. A significant fraction of the book is centred on Penrose’s relationship with Daniels, whom he became reacquainted with in the early 1970s when she was an undergraduate studying mathematics at John Cass College in London.

At the time Penrose was unhappily married to Joan, an American he’d met in 1958 when he was a postdoc at the University of Cambridge. In Barss’s telling, Penrose essentially forces Daniels into the position of muse. He writes her copious letters explaining his intellectual ideas and communicating his inability to get his work done without replies from her, which he expects to contain critical analyses of his scientific proposals.

The letters are numerous and obsessive, even when her replies are thin and distant. Eventually, Penrose also begins to request something more – affection and even love. He wants a relationship with her. Barss never exactly states that this was against Daniels’s will, but he offers readers sufficient details of her letters to Penrose that it’s hard to draw another conclusion.

Unanswered questions

Barss was able to read her letters because they had been returned to Penrose after Daniels’s death in 2005. Penrose, however, never re-examined any of them until Barss interviewed him for this biography. This raises a lot of questions that remain unanswered by the end of the book. In particular, why did Daniels continue to participate in a correspondence that was eventually thousands of pages long on Penrose’s side?

Judith Daniels was a significant figure in Penrose’s life, yet her death and memory seem to have been unremarkable to him for much of his later life

My theory is that Daniels felt she owed it to this great man of science. She also confesses at one point that she had a childhood crush on him. Her affection was real, even if not romantic; it is as if she was trapped in the dynamic. Penrose’s lack of curiosity about the letters after her death is also strange to me. Daniels was a significant figure in his life, yet her death and memory seem to have been unremarkable to him for much of his later life.

By the mid-1970s, when Daniels was finally able to separate herself from what was – on Penrose’s side – an extramarital emotional affair, Penrose went seeking new muses. They were always female students of mathematics and physics.

Just when it seems like we’ve met the worst of Penrose’s treatment of women, we’re told about his “physical aggression” toward his eventual ex-wife Joan and his partial abandonment of the three sons they had together. This is glossed over very quickly. And it turns out there is even more.

Penrose, like many of his contemporaries, primarily trained male students. Eventually he did take on one woman, Vanessa Thomas, who was a PhD student in his group at Oxford’s Mathematical Institute, where he’d moved in 1972.

Thomas never finished her PhD; Penrose pursued her romantically and that was the end of her doctorate. As scandalous as this is, I didn’t find the fact of the romance especially shocking because it is common enough in physics, even if it is increasingly frowned upon and, in my opinion, generally inappropriate. For better or worse, I can think of other examples of men in physics who fell in love with women advisees.

But in all the cases I know of, the woman has gone on to complete her degree either under his or someone else’s supervision. In these same cases, the age difference was usually about a decade. What happened with Thomas – who married Penrose in 1988 – seems like the worst-case scenario: a 40-year age difference and a budding star of mathematics, reduced to serving her husband’s career. Professional boundaries were not just transgressed, but obliterated.

Barss chooses not to offer much in the way of judgement about the impact that Penrose had on the women in science whom he made into muses and objects of romantic affection. The only exception is Ivette Fuentes, who was already a star theoretical physicist in her own right when Penrose first met her in 2012. Interview snippets with Fuentes reveal that the one time Penrose spoke of her as a muse, she rejected him and their friendship until he apologized.

No woman, it seems, had ever been able to hold him to the fire before. Fuentes does, however, describe how Penrose gave her an intellectual companion, something she’d previously been denied by the way the physics community is structured around insider “families” and pedigrees. It is interesting to read this in the context of Penrose’s own upbringing as landed gentry.

Gilded childhood

An intellectually precocious child growing up in 1930s England, Penrose is handed every resource for his intellectual potential to blossom. When he notices a specific pattern linking addition and multiplication, an older sibling is on hand to show him there’s a general rule from number theory that explains the pattern. The family at this point, we’re told, has a cook and a maid who doubles as a nanny. Even in a community of people from well-resourced backgrounds, Penrose stands out as an especially privileged example.

When the Second World War starts, his family readily secures safe passage to a comfortable home in Canada – a privilege related to their status as welcomed members of Britain’s upper class and one that was not afforded to many continental European Jewish families at the time (Penrose’s mother and therefore Penrose was Jewish by descent). Indeed, Canada admitted the fewest Jewish refugees of any Allied nation and famously denied entry to the St Louis, which was sent back to Europe, where a third of its 937 Jewish passengers were murdered in the Holocaust.

In Ontario, the Penrose children have a relatively idyllic experience. Throughout the rest of his childhood and his adult life, the path has been continuously smoothed for Penrose, either by his parents (who bought him multiple homes) or mentors and colleagues who believed in his genius. One is left wondering how many other people might have such a distinguished career if, from birth, they are handed everything on a silver platter and never required to take responsibility for anything.

To tell these and later stories, Barss relies heavily on interviews with Penrose. Access to their subject for any biographer is tricky. While it creates a real opportunity for the author, there is also the challenge of having a relationship with someone whose memories you need to question. Barss doesn’t really interrogate Penrose’s memory but seems to take them as gospel.

During the first half of the book, I wondered repeatedly if The Impossible Man is effectively a memoir told in the third person. Eventually, Barss does allow other voices to tell the story. Ultimately, though, this is firmly a book told from Penrose’s point of view. Even the inclusion of Daniels’s story was at least in part at Penrose’s behest.

I found myself wanting to hear more from the women in Penrose’s life. Penrose often saw himself following a current determined by these women. He came, for example, to believe his first wife had essentially trapped him in their relationship by falling for him.

Penrose never takes responsibility for any of his own actions towards the women in his life. So I wondered: how did they see it? What were their lives like? His ex-wife Joan (who died in 2019) and estranged wife Vanessa, who later became a mathematics teacher, both gave interviews for the book. But we learn little about their perspective on the man whose proclivities and career dominated their own lives.

One day there will be another biography of Penrose that will necessarily have distance from its subject because he will no longer be with us. The Impossible Man will be an important document for any future biographer, containing as it does such a close rendering of Penrose’s perspective on his own life.

The cost of genius

When it comes to describing Penrose’s contributions to mathematics and physics, the science writing, especially in the early pages, sings. Barss has a knack for writing up difficult ideas – whether it’s Penrose’s Nobel-prize-winning work on singularities or his attempt at quantum gravity, twistor theory. Overall, the luxurious prose makes the book highly readable.

Sometimes Barss indulges cosmic flourishes in a way that appears to reinforce Penrose’s perspective that the universe is happening to him rather than one over which he has any influence. In the end, I don’t know if we learn the cost of genius, but we certainly learn the cost of not recognizing that we are a part of the universe that has agency.

The final chapter is really Barss writing about himself and Penrose, and the conversations they have together. Penrose has macular degeneration now, so while both are on a visit to Perimeter in 2019, Barss reads some of his letters to Judith back to Penrose. Apparently, Penrose becomes quite emotional in a way that it seems no-one had ever seen – he weeps.

After that, he asks Barss to include the story about Judith. So, on some level, he knows he has erred.

The end of The Impossible Man is devastating. Barss describes how he eventually gains access to two of Penrose’s sons (three with Joan and one with Vanessa). In those interviews, he hears from children who have been traumatized by witnessing what they call “physical aggression” toward their mother. Even so, they both say they’d like to improve their relationship with their father.

Barss then asks a 92-year-old Penrose if he wants to patch things up with his family. His reply: “I feel my life is busy enough and if I get involved with them, it just distracts from other things.” As Barss concludes, Penrose is persistently unwilling to accept that in his life, he has been in the driver’s seat. He has had choices and doesn’t want to take responsibility for that. This, as much as Penrose’s intellectual interests and achievements, is the throughline of the text.

Penrose has shown that he doesn’t really care what others think, as long as he gets what he wants scientifically

The Penrose we meet at the end of The Impossible Man has shown that he doesn’t really care what others think, as long as he gets what he wants scientifically. It’s clear that Barss has a real affection for him, which makes his honesty about the Penrose he finds in the archives all the more remarkable. Perhaps motivated by generosity toward Penrose, Barss also lets the reader do a lot of the analysis.

I wonder, though, how many physicists who are steeped in this culture, and don’t concern themselves with gender equity issues, will miss how bad some of Penrose’s behaviour has been, as his colleagues at the time clearly did. The only documented objections to his behaviour seem more about him going off the deep end with his research into consciousness, cyclic theory and attacks on cosmic inflation.

As I worked on this review, I considered whether a different reviewer would have simply complained that the book has lots of stuff about Penrose’s personal messes that we don’t need to know. Maybe, to other readers, Penrose doesn’t come off quite as badly. For me, I prefer the hero I met in person rather than in the pages of this book. The Impossible Man is an important text, but it’s heartbreaking in the end.

• 2024 Basic Books (US)/Atlantic Books (UK) 352pp $32/£25hb
• In 2015 Physics World’s Tushna Commissariat interviewed Roger Penrose about his career. You can watch the video below

 

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At a conference in 2014, bioengineer Jeffrey Fredberg of Harvard University presented pictures of asthma cells. To most people, the images would have been indistinguishable – they all showed tightly packed layers of cells from the airways of people with asthma. But as a physicist, Lisa Manning saw something no one else had spotted; she could tell, just by looking, that some of the model tissues were solid and some were fluid.

Animal tissues must be able to rearrange and flow but also switch to a state where they can withstand mechanical stress. However, whereas solid-liquid transitions are generally associated with a density change, many cellular systems, including asthma cells, can change from rigid to fluid-like at a constant packing density.

Many of a tissue’s properties depend on biochemical processes in its constituent cells, but some collective behaviours can be captured by mathematical models, which is the focus of Manning’s research. At the time, she was working with postdoctoral associate Dapeng Bi on a theory that a tissue’s rigidity depends on the shape of the cells, with cells in a rigid state touching more neighbouring cells than those in a fluid-like one. When she saw the pictures of the asthma cells she knew she was right. “That was a very cool moment,” she says.

Manning – now the William R Kenan, Jr Professor of Physics at Syracuse University in the US – began her research career in theoretical condensed-matter physics, completing a PhD at the University of California, Santa Barbara, in 2008. The thesis was on the mechanical properties of amorphous solids – materials that don’t have long-ranged order like a crystal but are nevertheless rigid. Amorphous solids include many plastics, soils and foods, but towards the end of her graduate studies, Manning started thinking about where else she could apply her work.

I was looking for a project where I could use some of the skills that I had been developing as a graduate student in an orthogonal way

“I was looking for a project where I could use some of the skills that I had been developing as a graduate student in an orthogonal way,” Manning recalls. Inspiration came from of a series of talks on tissue dynamics at the Kavli Institute for Theoretical Physics, where she recognized that the theories she had worked on could also apply to biological systems. “I thought it was amazing that you could apply physical principles to those systems,” she says.

The physics of life

Manning has been at Syracuse since completing a postdoc at Princeton University, and although she has many experimental collaborators, she is happy to still be a theorist. Whereas experimentalists in the biological sciences generally specialize in just one or two experimental models, she looks for “commonalities across a wide range of developmental systems”. That principle has led Manning to study everything from cancer to congenital disease and the development of embryos.

“In animal development, pretty universally one of the things that you must do is change from something that’s the shape of a ball of cells into something that is elongated,” says Manning, who working to understand how this happens. With collaborator Karen Kasza at Columbia University, she has demonstrated that rather than stretching as a solid, it’s energy efficient for embryos to change shape by undergoing a phase transition to a fluid, and many of their predictions have been confirmed in fruit fly embryo models.

More recently, Manning has been looking at how ideas from AI and machine learning can be applied to embryogenesis. Unlike most condensed-matter systems, tissues continuously tune individual interactions between cells, and it’s these localized forces that drive complex shape changes during embryonic development. Together with Andrea Liu of the University of Pennsylvania, Manning is now developing a framework that treats cell–cell interactions like weights in a neural network that can be adjusted to produce a desired outcome.

“I think you really need almost a new type of statistical physics that we don’t have yet to describe systems where you have these individually tunable degrees of freedom,” she says, “as opposed to systems where you have maybe one control parameter, like a temperature or a pressure.”

Developing the next generation

Manning’s transition to biophysics was spurred by an unexpected encounter with scientists outside her field. Between 2019 and 2023, she was director of the Bio-inspired Institute at Syracuse University, which supported similar opportunities for other researchers, including PhD students and postdocs. “As a graduate student, it’s a little easy to get focused on the one project that you know about, in the corner of the universe that your PhD is in,” she says.

As well as supporting science, one of the first things Manning spearheaded at the institute was a professional development programme for early-career researchers. “During our graduate schools, we’re typically mostly trained on how to do the academic stuff,” she says, “and then later in our careers, we’re expected to do a lot of other types of things like manage groups and manage funding.” To support their wider careers, participants in the programme build non-technical skills in areas such as project management, intellectual property and graphic design.

What I realized is that I did have implicit expectations that were based on my culture and background, and that they were distinct from those of some of my students

Manning’s senior role has also brought opportunities to build her own skills, with the COVID-19 pandemic in particular making her reflect and reevaluate how she approached mentorship. One of the appeals of academia is the freedom to explore independent research, but Manning began to see that her fear of micromanaging her students was sometimes creating confusion.

“What I realized is that I did have implicit expectations that were based on my culture and background, and that they were distinct from those of some of my students,” she says. “Because I didn’t name them, I was actually doing my students a disservice.” If she could give advice to her younger self, it would be that the best way to support early-career researchers as equals is to set clear expectations as soon as possible.

When Manning started at Syracuse, most of her students wanted to pursue research in academia, and she would often encourage them to think about other career options, such as  working in industry. However, now she thinks academia is perceived as the poorer choice. “Some students have really started to get this idea that academia is too challenging and it’s really hard and not at all great and not rewarding.”

Manning doesn’t want anyone to be put off pursuing their interests, and she feels a responsibility to be outspoken about why she loves her job. For her, the best thing about being a scientist is encapsulated by the moment with the asthma cells: “The thrill of discovering something is a joy,”  she says, “being for just a moment, the only person in the world that understands something new.”

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A new artificial intelligence/machine learning method rapidly and accurately characterizes binary neutron star mergers based on the gravitational wave signature they produce. Though the method has not yet been tested on new mergers happening “live”, it could enable astronomers to make quicker estimates of properties such as the location of mergers and the masses of the neutron stars. This information, in turn, could make it possible for telescopes to target and observe the electromagnetic signals that accompany such mergers.

When massive objects such as black holes and neutron stars collide and merge, they emit ripples in spacetime known as gravitational waves (GWs). In 2015 scientists on Earth began observing these ripples using kilometre-scale interferometers that measure the minuscule expansion and contraction of space–time that occurs when a gravitational wave passes through our planet. These interferometers are located in the US, Italy and Japan and are known collectively as the LVK observatories after their initials: the Laser Interferometer GW Observatory (LIGO), the Virgo GW Interferometer (Virgo) and the Kamioka GW Detector (KAGRA).

When two neutron stars in a binary pair merge, they emit electromagnetic waves as well as GWs. While both types of wave travel at the speed of light, certain poorly understood processes that occur within and around the merging pair cause the electromagnetic signal to be slightly delayed. This means that the LVK observatories can detect the GW signal coming from a binary neutron star (BNS) merger seconds, or even minutes, before its electromagnetic counterpart arrives. Being able to identify GWs quickly and accurately therefore increases the chances of detecting other signals from the same event.

This is no easy task, however. GW signals are long and complex, and the main technique currently used to interpret them, Bayesian inference, is slow. While faster alternatives exist, they often make algorithmic approximations that negatively affect their accuracy.

Trained with millions of GW simulations

Physicists led by Maximilian Dax of the Max Planck Institute for Intelligent Systems in Tübingen, Germany have now developed a machine learning (ML) framework that accurately characterizes and localizes BNS mergers within a second of a GW being detected, without resorting to such approximations. To do this, they trained a deep neural network model with millions of GW simulations.

Once trained, the neural network can take fresh GW data as input and predict corresponding properties of the merging BNSs – for example, their masses, locations and spins – based on its training dataset. Crucially, this neural network output includes a sky map. This map, Dax explains, provides a fast and accurate estimate for where the BNS is located.

The new work built on the group’s previous studies, which used ML systems to analyse GWs from binary black hole (BBH) mergers. “Fast inference is more important for BNS mergers, however,” Dax says, “to allow for quick searches for the aforementioned electromagnetic counterparts, which are not emitted by BBH mergers.”

The researchers, who report their work in Nature, hope their method will help astronomers to observe electromagnetic counterparts for BNS mergers more often and detect them earlier – that is, closer to when the merger occurs. Being able to do this could reveal important information on the underlying processes that occur during these events. “It could also serve as a blueprint for dealing with the increased GW signal duration that we will encounter in the next generation of GW detectors,” Dax says. “This could help address a critical challenge in future GW data analysis.”

So far, the team has focused on data from current GW detectors (LIGO and Virgo) and has only briefly explored next-generation ones. They now plan to apply their method to these new GW detectors in more depth.

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New data from the NOvA experiment at Fermilab in the US contain no evidence for so-called “sterile” neutrinos, in line with results from most – though not all – other neutrino detectors to date. As well as being consistent with previous experiments, the finding aligns with standard theoretical models of neutrino oscillation, in which three active types, or flavours, of neutrino convert into each other. The result also sets more stringent limits on how much an additional sterile type of neutrino could affect the others.

“The global picture on sterile neutrinos is still very murky, with a number of experiments reporting anomalous results that could be attributed to sterile neutrinos on one hand and a number of null results on the other,” says NOvA team member Adam Lister of the University of Wisconsin, Madison, US. “Generally, these anomalous results imply we should see large amounts of sterile-driven neutrino disappearance at NOvA, but this is not consistent with our observations.”

Neutrinos were first proposed in 1930 by Wolfgang Pauli as a way to account for missing energy and spin in the beta decay of nuclei. They were observed in the laboratory in 1956, and we now know that they come in (at least) three flavours: electron, muon and tau. We also know that these three flavours oscillate, changing from one to another as they travel through space, and that this oscillation means they are not massless (as was initially thought).

Significant discrepancies

Over the past few decades, physicists have used underground detectors to probe neutrino oscillation more deeply. A few of these detectors, including the LSND at Los Alamos National Laboratory, BEST in Russia, and Fermilab’s own MiniBooNE, have observed significant discrepancies between the number of neutrinos they detect and the number that mainstream theories predict.

One possible explanation for this excess, which appears in some extensions of the Standard Model of particle physics, is the existence of a fourth flavour of neutrino. Neutrinos of this “sterile” type do not interact with the other flavours via the weak nuclear force. Instead, they interact only via gravity.

Detecting sterile neutrinos would fundamentally change our understanding of particle physics. Indeed, some physicists think sterile neutrinos could be a candidate for dark matter – the mysterious substance that is thought to make up around 85% of the matter in the universe but has so far only made itself known through the gravitational force it exerts.

Near and far detectors

The NOvA experiment uses two liquid scintillator detectors to monitor a stream of neutrinos created by firing protons at a carbon target. The near detector is located at Fermilab, approximately 1 km from the target, while the far detector is 810 km away in northern Minnesota. In the new study, the team measured how many muon-type neutrinos survive the journey through the Earth’s crust from the near detector to the far one. The idea is that if fewer neutrinos survive than the conventional three-flavour oscillations picture predicts, some of them could have oscillated into sterile neutrinos.

The experimenters studied two different interactions between neutrinos and normal matter, says team member V Hewes of the University of Cincinnati, US. “We looked for both charged current muon neutrino and neutral current interactions, as a sterile neutrino would manifest differently in each,” Hewes explains. “We then compared our data across those samples in both detectors to simulations of neutrino oscillation models with and without the presence of a sterile neutrino.”

No excess of neutrinos seen

Writing in Physical Review Letters, the researchers state that they found no evidence of neutrinos oscillating into sterile neutrinos. What is more, introducing a fourth, sterile neutrino did not provide better agreement with the data than sticking with the standard model of three active neutrinos.

This result is in line with several previous experiments that looked for sterile neutrinos, including those performed at T2K, Daya Bay, RENO and MINOS+. However, Lister says it places much stricter constraints on active-sterile neutrino mixing than these earlier results. “We are really tightening the net on where sterile neutrinos could live, if they exist,” he tells Physics World.

The NOvA team now hopes to tighten the net further by reducing systematic uncertainties. “To that end, we are developing new data samples that will help us better understand the rate at which neutrinos interact with our detector and the composition of our beam,” says team member Adam Aurisano, also at the University of Cincinnati. “This will help us better distinguish between the potential imprint of sterile neutrinos and more mundane causes of differences between data and prediction.”

NOvA co-spokesperson Patricia Vahle, a physicist at the College of William & Mary in Virginia, US, sums up the results. “Neutrinos are full of surprises, so it is important to check when anomalies show up,” she says. “So far, we don’t see any signs of sterile neutrinos, but we still have some tricks up our sleeve to extend our reach.”

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A new study probing quantum phenomena in neurons as they transmit messages in the brain could provide fresh insight into how our brains function.

In this project, described in the Computational and Structural Biotechnology Journal, theoretical physicist Partha Ghose from the Tagore Centre for Natural Sciences and Philosophy in India, together with theoretical neuroscientist Dimitris Pinotsis from City St George’s, University of London and the MillerLab of MIT, proved that established equations describing the classical physics of brain responses are mathematically equivalent to equations describing quantum mechanics. Ghose and Pinotsis then derived a Schrödinger-like equation specifically for neurons.

Our brains process information via a vast network containing many millions of neurons, which can each send and receive chemical and electrical signals. Information is transmitted by nerve impulses that pass from one neuron to the next, thanks to a flow of ions across the neuron’s cell membrane. This results in an experimentally detectable change in electrical potential difference across the membrane known as the “action potential” or “spike”.

When this potential passes a threshold value, the impulse is passed on. But below the threshold for a spike, a neuron’s action potential randomly fluctuates in a similar way to classical Brownian motion – the continuous random motion of tiny particles suspended in a fluid – due to interactions with its surroundings. This creates the so-called “neuronal noise” that the researchers investigated in this study.

Previously, “both physicists and neuroscientists have largely dismissed the relevance of standard quantum mechanics to neuronal processes, as quantum effects are thought to disappear at the large scale of neurons,” says Pinotsis. But some researchers studying quantum cognition hold an alternative to this prevailing view, explains Ghose.

“They have argued that quantum probability theory better explains certain cognitive effects observed in the social sciences than classical probability theory,” Ghose tells Physics World. “[But] most researchers in this field treat quantum formalism [the mathematical framework describing quantum behaviour] as a purely mathematical tool, without assuming any physical basis in quantum mechanics. I found this perspective rather perplexing and unsatisfactory, prompting me to explore a more rigorous foundation for quantum cognition – one that might be physically grounded.”

As such, Ghose and Pinotsis began their work by taking ideas from American mathematician Edward Nelson, who in 1966 derived the Schrödinger equation – which predicts the position and motion of particles in terms of a probability wave known as a wavefunction – using classical Brownian motion.

Firstly they proved that the variables in the classical equations for Brownian motion that describe the random neuronal noise seen in brain activity also obey quantum mechanical equations, deriving a Schrödinger-like equation for a single neuron. This equation describes neuronal noise by revealing the probability of a neuron having a particular value of membrane potential at a specific instant. Next, the researchers showed how the FitzHugh-Nagumo equations, which are widely used for modelling neuronal dynamics, could be re-written as a Schrödinger equation. Finally, they introduced a neuronal constant in these Schrödinger-like equations that is analogous to Planck’s constant (which defines the amount of energy in a quantum).

“I got excited when the mathematical proof showed that the FitzHugh-Nagumo equations are connected to quantum mechanics and the Schrödinger equation,” enthuses Pinotsis. “This suggested that quantum phenomena, including quantum entanglement, might survive at larger scales.”

“Penrose and Hameroff have suggested that quantum entanglement might be related to lack of consciousness, so this study could shed light on how anaesthetics work,” he explains, adding that their work might also connect oscillations seen in recordings of brain activity to quantum phenomena. “This is important because oscillations are considered to be markers of diseases: the brain oscillates differently in patients and controls and by measuring these oscillations we can tell whether a person is sick or not.”

Going forward, Ghose hopes that “neuroscientists will get interested in our work and help us design critical neuroscience experiments to test our theory”. Measuring the energy levels for neurons predicted in this study, and ultimately confirming the existence of a neuronal constant along with quantum effects including entanglement would, he says, “represent a big step forward in our understanding of brain function”.

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This episode of the Physics World Weekly podcast features Ileana Silvestre Patallo, a medical physicist at the UK’s National Physical Laboratory, and Ruth McLauchlan, consultant radiotherapy physicist at Imperial College Healthcare NHS Trust.

In a wide-ranging conversation with Physics World’s Tami Freeman, Patallo and McLauchlan explain how ionizing radiation such as X-rays and proton beams interact with our bodies and how radiation is being used to treat diseases including cancer.

• This episode was created in collaboration with IPEM, the Institute of Physics and Engineering in Medicine. IPEM owns the journal Physics in Medicine & Biology.

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Physics is weird. Especially when you’re dealing with moving reference frames.

In this episode of the Physics World Weekly podcast, we explore how computational physics is being used to develop new quantum materials; and we look at how ultrasound can help detect breast cancer.

Our first guest is Bhaskaran Muralidharan, who leads the Computational Nanoelectronics & Quantum Transport Group at the Indian Institute of Technology Bombay. In a conversation with Physics World’s Hamish Johnston, he explains how computational physics is being used to develop new materials and devices for quantum science and technology. He also shares his personal perspective on quantum physics in this International Year of Quantum Science and Technology.

Our second guest is Daniel Sarno of the UK’s National Physical Laboratory, who is an expert in the medical uses of ultrasound. In a conversation with Physics World’s Tami Freeman, Sarno explains why conventional mammography can struggle to detect cancer in patients with higher density breast tissue. This is a particular problem because women with such tissue are at higher risk of developing the disease. To address this problem, Sarno and colleagues have developed a ultrasound technique for measuring tissue density and are commercializing it via a company called sona.

• Bhaskaran Muralidharan is an editorial board member on Materials for Quantum Technology. The journal is produced by IOP Publishing, which also brings you Physics World

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A counterintuitive result from Einstein’s special theory of relativity has finally been verified more than 65 years after it was predicted. The prediction states that objects moving near the speed of light will appear rotated to an external observer, and physicists in Austria have now observed this experimentally using a laser and an ultrafast stop-motion camera.

A central postulate of special relativity is that the speed of light is the same in all reference frames. An observer who sees an object travelling close to the speed of light and makes simultaneous measurements of its front and back (in the direction of travel) will therefore find that, because photons coming from each end of the object both travel at the speed of light, the object is measurably shorter than it would be for an observer in the object’s reference frame. This is the long-established phenomenon of Lorentz contraction.

In 1959, however, two physicists, James Terrell and the future Nobel laureate Roger Penrose, independently noted something else. If the object has any significant optical depth relative to its length – in other words, if its extension parallel to the observer’s line of sight is comparable to its extension perpendicular to this line of sight, as is the case for a cube or a sphere – then photons from the far side of the object (from the observer’s perspective) will take longer to reach the observer than photons from its near side. Hence, if a camera takes an instantaneous snapshot of the moving object, it will collect photons from the far side that were emitted earlier at the same time as it collects photons from the near side that were emitted later.

This time difference stretches the image out, making the object appear longer even as Lorentz contraction makes its measurements shorter. Because the stretching and the contraction cancel out, the photographed object will not appear to change length at all.

But that isn’t the whole story. For the cancellation to work, the photons reaching the observer from the part of the object facing its direction of travel must have been emitted later than the photons that come from its trailing edge. This is because photons from the far and back sides come from parts of the object that would normally be obscured by the front and near sides. However, because the object moves in the time it takes photons to propagate, it creates a clear passage for trailing-edge photons to reach the camera.

The cumulative effect, Terrell and Penrose showed, is that instead of appearing to contract – as one would naïvely expect – a three-dimensional object photographed travelling at nearly the speed of light will appear rotated.

The Terrell effect in the lab

While multiple computer models have been constructed to illustrate this “Terrell effect” rotation, it has largely remained a thought experiment. In the new work, however, Peter Schattschneider of the Technical University of Vienna and colleagues realized it in an experimental setup. To do this, they shone pulsed laser light onto one of two moving objects: a sphere or a cube. The laser pulses were synchronized to a picosecond camera that collected light scattered off the object.

The researchers programmed the camera to produce a series of images at each position of the moving object. They then allowed the object to move to the next position and, when the laser pulsed again, recorded another series of ultrafast images with the camera. By linking together images recorded from the camera in response to different laser pulses, the researchers were able to, in effect, reduce the speed of light to less than 2 m/s.

When they did so, they observed that the object rotated rather than contracted, just as Terrell and Penrose predicted. While their results did deviate somewhat from theoretical predictions, this was unsurprising given that the predictions rest on certain assumptions. One of these is that incoming rays of light should be parallel to the observer, which is only true if the distance from object to observer is infinite. Another is that each image should be recorded instantaneously, whereas the shutter speed of real cameras is inevitably finite.

Because their research is awaiting publication by a journal with an embargo policy, Schattschneider and colleagues were unavailable for comment. However, the Harvard University astrophysicist Avi Loeb, who suggested in 2017 that the Terrell effect could have applications for measuring exoplanet masses, is impressed: “What [the researchers] did here is a very clever experiment where they used very short pulses of light from an object, then moved the object, and then looked again at the object and then put these snapshots together into a movie – and because it involves different parts of the body reflecting light at different times, they were able to get exactly the effect that Terrell and Penrose envisioned,” he says. Though Loeb notes that there’s “nothing fundamentally new” in the work, he nevertheless calls it “a nice experimental confirmation”.

The research is available on the arXiv pre-print server.

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Something extraordinary happened on Earth around 10 million years ago, and whatever it was, it left behind a “signature” of radioactive beryllium-10. This finding, which is based on studies of rocks located deep beneath the ocean, could be evidence for a previously-unknown cosmic event or major changes in ocean circulation. With further study, the newly-discovered beryllium anomaly could also become an independent time marker for the geological record.

Most of the beryllium-10 found on Earth originates in the upper atmosphere, where it forms when cosmic rays interact with oxygen and nitrogen molecules. Afterwards, it attaches to aerosols, falls to the ground and is transported into the oceans. Eventually, it reaches the seabed and accumulates, becoming part of what scientists call one of the most pristine geological archives on Earth.

Because beryllium-10 has a half-life of 1.4 million years, it is possible to use its abundance to pin down the dates of geological samples that are more than 10 million years old. This is far beyond the limits of radiocarbon dating, which relies on an isotope (carbon-14) with a half-life of just 5730 years, and can only date samples less than 50 000 years old.

Almost twice as much ¹⁰Be than expected

In the new work, which is detailed in Nature Communications, physicists in Germany and Australia measured the amount of beryllium-10 in geological samples taken from the Pacific Ocean. The samples are primarily made up of iron and manganese and formed slowly over millions of years. To date them, the team used a technique called accelerator mass spectrometry (AMS) at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). This method can distinguish beryllium-10 from its decay product, boron-10, which has the same mass, and from other beryllium isotopes.

The researchers found that samples dated to around 10 million years ago, a period known as the late Miocene, contained almost twice as much beryllium-10 as they expected to see. The source of this overabundance is a mystery, says team member Dominik Koll, but he offers three possible explanations. The first is that changes to the ocean circulation near the Antarctic, which scientists recently identified as occurring between 10 and 12 million years ago, could have distributed beryllium-10 unevenly across the Earth. “Beryllium-10 might thus have become particularly concentrated in the Pacific Ocean,” says Koll, a postdoctoral researcher at TU Dresden and an honorary lecturer at the Australian National University.

Another possibility is that a supernova exploded in our galactic neighbourhood 10 million years ago, producing a temporary increase in cosmic radiation. The third option is that the Sun’s magnetic shield, which deflects cosmic rays away from the Earth, became weaker through a collision with an interstellar cloud, making our planet more vulnerable to cosmic rays. Both scenarios would have increased the amount of beryllium-10 that fell to Earth without affecting its geographic distribution.

To distinguish between these competing hypotheses, the researchers now plan to analyse additional samples from different locations on Earth. “If the anomaly were found everywhere, then the astrophysics hypothesis would be supported,” Koll says. “But if it were detected only in specific regions, the explanation involving altered ocean currents would be more plausible.”

Whatever the reason for the anomaly, Koll suggests it could serve as a cosmogenic time marker for periods spanning millions of years, the likes of which do not yet exist. “We hope that other research groups will also investigate their deep-ocean samples in the relevant period to eventually come to a definitive answer on the origin of the anomaly,” he tells Physics World.

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While the biology of how an entire organism develops from a single cell has long been a source of fascination, recent research has increasingly highlighted the role of mechanical forces. “If we want to have rigorous predictive models of morphogenesis, of tissues and cells forming organs of an animal,” says Konstantin Doubrovinski at the University of Texas Southwestern Medical Center, “it is absolutely critical that we have a clear understanding of material properties of these tissues.”

Now Doubrovinski and his colleagues report a rheological study explaining why the developing fruit fly (Drosophila melanogaster) epithelial tissue stretches as it does over time to allow the embryo to change shape.

Previous studies had shown that under a constant force, tissue extension was proportional to the time the force had been applied to the power of one half. This had puzzled the researchers, since it did not fit a simple model in which epithelial tissues behave like linear springs. In such a model, the extension obeys Hooke’s law and is proportional to the force applied alone, such that the exponent of time in the relation would be zero.

They and other groups had tried to explain this observation of an exponent equal to 0.5 as due to the viscosity of the medium surrounding the cells, which would lead to deformation near the point of pulling that then gradually spreads. However, their subsequent experiments ruled out viscosity as a cause of the non-zero exponent.

For their measurements, the researchers had exploited a convenient feature of Drosophila epithelial cells – a small hole, through which they could manipulate a droplet of ferrofluid to enter using a permanent magnet. Once inside the cell, a magnet acting on this droplet could exert forces on the cell to stretch the surrounding tissue.

For the current study, the researchers first tested the observed scaling law over longer periods of time. A power law gives a straight line on a log–log plot but as Doubrovinski points out, curves also look like straight lines over short sections. However, even when they increased the time scales probed in their experiments to cover three orders of magnitude – from fractions of a second to several minutes – the observed power law still held.

Understanding the results

One of the post docs on the team – Mohamad Ibrahim Cheikh – stumbled upon the actual relation giving the power law with an exponent of 0.5 while working on a largely unrelated problem. He had been modelling ellipsoids in a hexagonal meshwork on a surface, in what Doubrovinski describes as a “large” and “relatively complex” simulation. He decided to examine what would happen if he allowed the mesh to relax in its stretched position, which would model the process of actin turnover in cells.

Cheikh’s simulation gave the power law observed in the epithelial cells. “We totally didn’t expect it,” says Doubrovinski. “We pursued it and thought, why are we getting it? What’s going on here?”

Although this simulation yielded the power law with an exponent of 0.5, because the simulation was so complex, it was hard to get a handle on why. “There are all these different physical effects that we took into account that we thought were relevant,” he tells Physics World.

To get a more intuitive understanding of the system, the researchers attempted to simplify the model into a lattice of springs in one dimension, keeping only some of the physical effects from the simulations, until they identified the effects required to give the exponent value of 0.5. They could then scale this simplified one-dimensional model back up to three dimensions and test how it behaved.

According to their model, if they changed the magnitude of various parameters, they should be able to rescale the curves so that they essentially collapse onto a single curve. “This makes our prediction falsifiable,” says Doubrovinski, and in fact the experimental curves could be rescaled in this way.

When the researchers used measured values for the relaxation constant based on the actin turnover rate, along with other known parameters such as the size of the force and the size of the extension, they were able to calculate the force constant of the epithelial cell. This value also agreed with their previous estimates.

Doubrovinski explains how the ferrofluid droplet engages with individual “springs” of the lattice as it moves through the mesh. “The further it moves, the more springs it catches on,” he says. “So the rapid increase of one turns into a slow increase with an exponent of 0.5.” Against this model, all the pieces fit into place.

“I find it inspiring that the authors, first motivated by in vivo mechanical measurements, could develop a simple theory capturing a new phenomenological law of tissue rheology,” says Pierre Françoise Lenne, group leader at the Institut de Biologie du Development de Marseille at L’Universite d’Aix-Marseille. Lenne specializes in the morphogenesis of multicellular systems but was not involved in the current research.

Next, Doubrovinski and his team are keen to see where else their results might apply, such as other developmental stages and other types of organisms, such as mammals, for example.

The research is reported in Physical Review Letters and bioRxiv.

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