Page 70 – Physics World

Home » Page 70

Quantum thermochemical engine could achieve high power with near-maximum efficiency

The engines in everyday devices such as cars, vacuum cleaners and fans rely on a classical understanding of heat, energy and work. In recent years, scientists have designed (and in some cases built) new types of engines that incorporate unique quantum features. In addition to boosting performance, these features allow quantum engines to perform tasks that classical machines cannot.

Vijit Nautiyal from the University of New England, Armidale, New South Wales, Australia has now proposed a new type of quantum engine that exchanges not only heat, but also particles, with thermal reservoirs. The advantage of Nautiyal’s proposed quantum thermochemical engine, as described in Physical Review E, is that it combines near-maximum efficiency with high power output. “It’s equivalent to driving a Ferrari at the running cost of a Toyota,” Nautiyal explains. “You enjoy the thrill of high power while saving on fuel efficiency.”

Classical and quantum engines

Car engines typically operate in a four-stroke (Otto) cycle. In the intake stroke, the piston moves downwards, drawing air and fuel into a cylinder. The compression stroke then causes the piston to move upwards, compressing the mixture and increasing its temperature and pressure adiabatically (that is, without losing or gaining heat). Next comes the expansion stroke, when heat is added in the form of an igniting spark, causing the gas to expand adiabatically and performing work on the piston. Finally, during the exhaust stroke, the piston moves up, expelling the spent exhaust gases out of the cylinder.

Nautiyal’s proposed quantum engine replaces the fuel in a car engine with a weakly interacting one-dimensional Bose-Einstein condensate, or Bose gas, in a harmonic trap. Here, the ignition and exhaust (thermalization) strokes are equivalent to coupling the Bose gas to a surrounding cloud of thermal atoms that serves as a hot or cold reservoir. Because the Bose gas (the working fluid) can exchange both heat and particles with this reservoir, the setup can be considered an open quantum system. During the two work strokes (compression and expansion), the gas is instead treated as an isolated quantum many-body system.

The piston in this quantum engine is the strength of inter-atomic interactions in the gas. To move the piston, Nautiyal’s scheme calls for abruptly increasing this interaction strength during the compression stroke and abruptly decreasing it during the expansion stroke.

Engine operations

When Nautiyal’s system exchanges only heat with the hot and cold reservoirs, it cannot operate as an engine because its beneficial output work is less than the input work. However, if it also exchanges particles with the reservoirs, it operates as a thermochemical engine with output work greater than the input, compensating for any quantum friction experienced during the process.

Like the classical Otto engine cycle, Nautiyal’s quantum engine experiences a trade-off between power and efficiency. In classical engines, operating the cycle at a faster speed increases engine power; however, it also typically decreases efficiency because dissipative effects such as heat and friction increase irreversible losses. Similarly, in quantum engines, driving the system faster during the work stroke produces losses in the form of non-adiabatic energy excitations.

These excitations can be suppressed if the work strokes are performed extremely slowly (a quasi-static quench), leading to maximum efficiency. However, this comes at the cost of null power output due to extremely long driving time. Optimizing this trade-off between power and efficiency is thus one of the main goals of this field of finite-time quantum thermodynamics.

Steampunk meets quantum physics at the GPS

The upper bound on the work and efficiency produced by Nautiyal’s thermochemical engine is set by an adiabatic quantum thermochemical engine operating at zero temperature. Remarkably, this engine can operate at near maximum efficiencies while maintaining high power output even in the sudden quench, out-of-equilibrium regime. This is because instead of increasing efficiency by extending cycle time, one can increase it by boosting the flow of particles from the hot reservoir, which raises the internal energy of the working fluid. The additional energy can then be converted into mechanical work during the expansion stroke.

Asked about possible applications of his quantum engine, Nautiyal referred to “quantum steampunk”. This term, which was coined by the physicist Nicole Yunger Halpern at the US National Institute of Standards and Technology and the University of Maryland, encapsulates the idea that as quantum technologies advance, the field of quantum thermodynamics must also advance in order to make such technologies more efficient. A similar principle, Nautiyal explains, applies to smartphones: “The processor can be made more powerful, but the benefits cannot be appreciated without an efficient battery to meet the increased power demands.” Conducting research on quantum engines and quantum thermodynamics is thus a way to optimize quantum technologies.

Honor Powrie: ‘So what has networking ever done for me?’

Dear Physics World readers, I’m going to let you in on a secret. I get anxious every time I see the word “networking” on a meeting or conference agenda. I’m nervous whether anyone will talk to me and – if they do – what I’ll say in reply. Will I end up stuck in a corner fiddling on my phone to make it seem like I want to join in but have something more important to do?

If you feel this way – or even if you don’t – please read on because I have some something important to say for anyone who attends or organizes scientific events.

Now, we all know there are many benefits to networking. It’s a good way to meet like-minded people, tell others about what you’re doing, and build a foundation for collaboration. Networking can also boost your professional and personal development – for example, by identifying new perspectives and challenges, finding a mentor, connecting with other organizations, or developing a tailor-made support system.

However, doing this effectively and efficiently is not necessarily easy. Networking can also soak up valuable time. It can create connections that lead nowhere. It can even be a hugely exploitative and one-sided affair where you find yourself under pressure to share personal and/or professional information that you didn’t intend to.

Top tips

Like most things in life, what you get from networking depends on what you put in. To make the most of such events, try to think about how others are feeling in the same situation. Chances are that they will be a bit nervous and apprehensive about opening the conversation. So there’s no harm in you going first.

A good opening gambit is to briefly introduce yourself, say who you are, where you work and what you do, and seek similar information from the other person. Preparing a short “elevator pitch” about yourself makes it easier to start a conversation and reduces the need to think on the spot. (Fun fact: elevator pitch gets its name from US inventor Elisha Otis, who needed a concise way of explaining his device to catch a plummeting elevator.)

Make an effort to remember other people’s names. I am not brilliant at this and have found that double checking and using people’s names in conversation is a good way to commit them to memory. Some advance preparation also helps. If possible, study the attendee list, so you know who else might be there and where they’re from. Be yourself and try to be an active listener – listen to what others are saying and ask thoughtful questions.

Don’t feel the need to stick with one person or group of people for the whole the time. Five minutes or so is polite and then you can move on and mingle further. Obviously, if you are making a good connection then it’s worth spending a bit more time. But if you are genuinely engaged, making plans to follow up post event should be straightforward.

Decide the best way to share your contact details. It could be an iPhone air drop, taking a photo of someone’s name badge, sending an e-mail, or swapping business cards (seems a bit unecological these days). If there are people you want to meet, don’t be afraid to seek them out. It’s always a nice compliment to approach someone and say: “Ah, I was hoping to speak to you today; I’ve heard a lot about you.”

On the flip side, avoid hanging out with your cronies, by which I mean colleagues from the same company or organization or people you already know well. Set yourself a challenge to meet people you’ve never met before. Remember few of us like being left out so try to involve others in a conversation. That’s especially true if someone’s listening but not getting the chance to speak; think of a question to bring that person into the discussion.

Of course, if someone you meet doesn’t seem to be relevant to you, don’t be afraid to admit it. I’m sure they won’t be offended if you don’t follow up after the meeting. And to those who are already comfortable with networking, remember not to hog all the limelight and to encourage others to participate.

A message to organizers

Let me end with a message to organizers, which – I’ll be honest – is the main reason I’m writing this article. I have recently attended conferences and events where the music is so loud that people, myself included, have gone with the smokers to the perishing cold outside simply so we can hear each other speak. Am I getting old or is this defeating the object of networking? Please, no more loud music!

I also urge event organizers to have places where people can connect, including tables and seating areas where you can put your plates and drinks down. There’s nothing worse than trying to talk while juggling cutlery to avoid a quiche collapsing down the front of your shirt. Buffets are always better than formal sit-down dinners as it provides more opportunity for people to mix. But remember that long queues for food can arise.

So what has networking ever done for me? Over the years the benefits have changed, but most recently I have met some great peer mentors, people whom I can share cross-industry experience and best practice with. And, if I hadn’t been at a certain Institute of Physics networking event last year and met Matin Durrani, the editor of Physics World, then I wouldn’t be writing this article for you today.

I’ll let you, though, be the judge of whether that was a success. [Editor’s note: it certainly was…]

Deep-learning model outperforms cardiologists in identifying hidden heart disease

Evaluating electrocardiogram (ECG) traces using a new deep-learning model known as EchoNext looks set to save lives by flagging patients at high risk of structural heart disease (SHD) who might otherwise be missed.

SHD encompasses a range of conditions affecting millions worldwide, including heart failure and valvular heart disease. It is, however, currently underdiagnosed because the diagnostic test for SHD, an echocardiogram, is relatively expensive and complex and thus not routinely performed. Late diagnosis results in unnecessary deaths, reductions in patient quality-of-life and an additional burden on healthcare services. EchoNext could reduce these problems as it provides a way of determining which patients should be sent for an echocardiogram – ultrasound imaging that shows the valves and chambers and how the heart is beating – by analysing the inexpensive and commonly collected ECG traces that record electrical activity in the heart.

The EchoNext model was developed by researchers at Columbia University and NewYork-Presbyterian Hospital in the US, led by Pierre Elias, assistant professor at Columbia University Vagelos College of Physicians and Surgeons and medical director for artificial intelligence at NewYork-Presbyterian. EchoNext is a convolutional neural network, which uses the mathematical operation of convolution to generate information and make predictions. In this case, EchoNext scans through the ECG data in bite-sized segments, generating information about each segment and subsequently assigning it a numerical “weight”. From these values, the AI model then determines if a patient is showing markers of SHD and so requires an echocardiogram. EchoNext learns from retrospective data by checking the accuracy of its predictions, with more than 1.2 million ECG traces from 230,000 patients used in its initial training.

In their study, reported in Nature, the researchers describe running EchoNext on ECG data from 85,000 patients. The AI model identified 9% of those patients as being in the high-risk category for undiagnosed SHD, 55% of whom subsequently had their first echocardiogram. This resulted in a positive diagnosis in almost three-quarters of cases; double the rate of positivity normally seen in first-time echocardiograms.

EchoNext also outperformed 13 cardiologists in making diagnoses based on 3200 ECGs by correctly flagging 77% of structural heart problems while its human colleagues were only 64% accurate – a result so good that it shocked the researchers.

“The really challenging thing here was that from medical school I was taught that you can’t detect things like heart failure or valvular disease from an electrocardiogram. So we initially asked: would the model actually pick out patients with disease that we were missing? I have read more than 10,000 ECGs in my career and I can’t look at an ECG and see what an AI model is seeing,” enthuses Elias. “It’s able to pick up on different sets of patterns that are not necessarily perceptible to us.”

Elias instigated the EchoNext project after an upsetting incident in which he was unable to save a patient transferred from another hospital with critical valvular heart disease because they had been diagnosed too late. “You can’t take care of the patient you don’t know about. So we said: is there a way that we can do a better job with diagnoses?”

EchoNext is now undergoing a clinical trial, based in eight hospital emergency departments, that ends in 2026. “My number one priority is to produce the right clinical evidence that is necessary to prove this technology is safe and efficacious, can be widely adopted and has value in helping patients,” says Elias.

He stresses that it is still early days for all AI technologies, but that even in these trial phases EchoNext – which was recently designated a breakthrough technology by the US Food and Drug Administration (FDA) – is already improving patient lives.

“It’s a really wonderful thing that every week we get to meet the patients that this helped. Our goal is for this to impact as many patients as possible over the next 12 months,” states Elias, adding that since EchoNext is successfully detecting 13 types of heart disease, a similar system should be useful in other healthcare domains too. “We think these kinds of AI-augmented biomarkers can become something that is routinely ordered and used as part of clinical practice,” he concludes.

Feynman diagrams provide insight into quasiparticles in solids

Artist's impression of a polaron — **Illustration of a polaron** The bright sphere is the electron, which is distorting the surrounding lattice. The wavy lines are high-order Feynman diagrams for the electron–phonon interaction. (Courtesy: Ella Maru Studio)

Electron–phonon interactions in a material have been modelled by combining billions of Feynman diagrams. Using a modified form of the Monte Carlo method, Marco Bernardi and colleagues at the California Institute of Technology predicted the behaviour of polarons in certain materials without racking up significant computational costs.

Phonons are quantized collective vibrations of the atoms or molecules in a lattice. When an electron moves through certain solids, it can interact with phonons. This electromagnetic interaction creates a particle-like excitation that comprises a propagating electron surrounded by a cloud of phonons. This quasiparticle excitation is called a polaron.

By lowering the electron’s mobility, while increasing its effective mass, polarons can have a substantial impact on the electronic properties of a variety of materials – including semiconductors and high-temperature superconductors.

However, physicists have struggled to model polarons and it would be extremely helpful for them to represent polarons using Feynman diagrams. These are a mainstay of particle physics, which are used to calculate the probabilities of certain particle interactions taking place. This has been challenging because polarons emerge from a superposition of infinitely many higher-order interactions between electrons and phonons. With each successive order, the complexity of these interactions steadily increases – along with the computational power required to represent them with Feynman diagrams.

Higher-order trouble

Unlike some other interactions, each higher order becomes more and more important in representing the polaron as accurately as possible. As a result, calculations cannot be simplified using standard perturbation theory – where only the first few orders of interaction are required to closely approximate the overall process.

“If you can calculate the lowest order, it’s very likely that you cannot do the second order, and the third order will just be impossible,” Bernardi explains. “The computational cost typically scales prohibitively with interaction order. There are too many diagrams to compute, and the higher-order diagrams are too computationally expensive. It’s basically a nightmare in terms of scaling.”

Bernardi’s team – which also included Yao Luo and Jinsoo Park – approached the problem with the Monte Carlo method. This involves taking repeated random samples within a space of all possible events contributing to a process, then adding them together. It allows researchers to build up a close approximation of the process, without accounting for every possibility.

The team generated a series of Feynman diagrams spanning the full range of possible electron–phonon interactions. Then, they combined the diagrams to gain precise descriptions of the dynamic and ground-state properties of polarons in real materials.

Statistical noise

One issue with a fully-random Monte Carlo approach is the sign problem, which arises from statistical noise that can emerge as electrons scatter between different energy bands during electron–phonon interactions. Since different bands can contribute positively or negatively to the interaction probabilities represented by Feynman diagrams, these contributions can cancel each other out when added together.

To avoid this, Bernardi’s team adapted the Monte Carlo method to evaluate each band contribution in a structured, non-random way – preventing sign cancellations. In addition, the researchers applied a matrix compression approach. This vastly reduced the size and complexity of the electron–phonon interaction data, without sacrificing accuracy. Altogether, this enabled them to generate billions of diagrams without significant computational costs.

“The clever diagram sampling, sign problem removal, and electron–phonon matrix compression are the three key pieces of the puzzle that have enabled this paradigm shift in the polaron problem,” Bernardi explains.

The trio hopes that its technique will help us understand polaron behaviours. “The method we developed could also help study strong interactions between light and matter, or even provide the blueprint to efficiently add up Feynman diagrams in entirely different physical theories,” Bernardi says. In turn, it could help to provide deeper insights into a variety of effects where polarons contribute – including electrical transport, spectroscopy, and superconductivity.

The research is described in Nature Physics.

Too-close exoplanet triggers flares from host star

A young gas giant exoplanet appears to be causing its host star to emit energetic outbursts. This finding, which comes from astronomers at the Netherlands Institute for Radio Astronomy (ASTRON) and collaborators in Germany, Sweden and Switzerland, is the first evidence of planets actively influencing their stars, rather than merely orbiting them.

“Until now, we had only seen stars flare on their own, but theorists have long suspected that close-in planets might disturb their stars’ magnetic fields enough to trigger extra flares,” explains Maximilian Günther, a project scientist with the European Space Agency’s Cheops (Characterising ExOPlanet Satellite) mission. “This study now offers the first observational hint that this might indeed be happening.”

Stars with flare(s)

Most stars produce flares at least occasionally. This is because as they spin, they build up magnetic energy – a process that Günther compares to the dynamos on Dutch bicycles. “When their twisted magnetic field lines occasionally snap, they release bursts of radiation,” he explains. “Our own Sun regularly behaves like this, and we experience its bursts of energy as part of space weather on Earth.” The charged particles that follow such flares, he adds, are responsible for the aurorae at our planet’s poles.

The flares the ASTRON team spotted came from a star called HIP 67522. Although classified as a G dwarf star like our own Sun, HIP 67522 is much younger, being 17 million years old rather than 4.5 billion. It is also slightly larger and cooler, and astronomers had previously used data from NASA’s Transiting Exoplanet Survey Satellite (TESS) to identify two planets orbiting it. Denoted HIP 67522 b and HIP 67522 c, both are located near their host, but HIP 67522 b is especially close, completing an orbit in just seven Earth days.

In the latest work, which is detailed in Nature, ASTRON’s Ekaterina Ilin and colleagues used Cheops’ precision targeting to make more detailed observations of the HIP 67522 system. These observations revealed a total of 15 flares, and Ilin notes that almost all of them appeared to be coming towards us as HIP 67522 b transited in front of its host as seen from Earth. This is significant, she says, because it suggests that the flares are being triggered by the planet, rather than by some other process.

“This is the first time we have seen a planet influencing its host star, overturning our previous assumptions that stars behave independently,” she says.

Six times more flaring

The ASTRON team estimate that HIP 67522 b is exposed to around six times as many flares as it would be if it wasn’t triggering some of them itself. This is an unusually high level of radiation, and it may help explain recent observations from the James Webb Space Telescope (JWST) that show HIP 67522 b losing its atmosphere faster than expected.

“The new study estimates that the planet is cutting its own atmosphere’s life short by half,” Günther says. “It might lose its atmosphere in the next 400‒700 million years, compared to the 1 billion years it would otherwise.”

If such a phenomenon turns out to be common, he adds, “it could help explain why some young planets have inflated atmospheres or evolve into smaller, denser worlds. And it could inform how we see the demography of ‘adult planets’.”

Astrobiology implications

One big unanswered question, Günther says, is whether the slightly more distant planet HIP 67522 c shows similar interactions with its host. “Comparing the two would be incredible, not only doubling the sampling size, but revealing how distance from the star affects magnetic interactions.”

The ASTRON researchers say they also want to understand the magnetic field of HIP 67522 b itself. More broadly, they plan to look for other such systems, hoping to find out how common they really are.

For Günther, who was not directly involved in the present study, even a single example is already important. “I have worked on exoplanets and stellar flares myself for many years, mostly inspired by the astrobiology implications, but this discovery opens a whole new window into how stars and planets can influence each other,” he says. “It is a wake-up call to me that planets are not just passive passengers; they actively shape their environments,” he tells Physics World. “That has big implications for how we think about planetary atmospheres, habitability and the evolution of worlds across the galaxy.”

Third age careers for physicists: writing and the arts beckon

Many of us will have careers with three distinct eras: education, work and retirement. While the first two tend to be regimented, the third age offers the possibility of pursuing a wide range of interests.

Our guest in this episode of the Physics World Weekly podcast is the retired particle physicist Michael Albrow, who is scientist emeritus at Fermilab in the US. He has just published his book Space Times Matter: One Hundred Short Stories About The Universe, which is a collection of brief essays and poems related to science.

Much of the book comes from a newspaper column that Albrow wrote earlier in his retirement and he has also been involved in collaborations with visual and musical artists. In this podcast he talks about this third age of his career as a physicist and gives some tips for your retirement.

Global ocean simulations examine tritium release from Fukushima

Ever since the Fukushima Daiichi nuclear power plant accident that caused the discharge of radionuclides from the power plant into the ocean, operators at the Tokyo Electric Power Company (TEPCO) have been implementing measures to reduce groundwater inflow into the damaged reactor buildings. TEPCO has also been pumping water into the reactors since the accident to cool them.

The cooled water is then treated using the Advanced Liquid Processing System (ALPS), which removes all radioactive materials from the water except for tritium – which is very difficult to remove and has a half-life of 12.32 ±0.02 years. This treated water ended up being accumulated and stored at the site, with limited space to store it.

To combat this storage issue, the Japanese government implemented a new policy in 2021 focused on discharging the ALPS-treated water into the ocean using a 1 km long tunnel. The release of the treated water (containing tritium) began on 24th August 2023, and the plan is to continue releasing it until 2050. The government set a threshold for tritium suspension levels of 700 Bq/L in the discharge outlet vicinity and 30 Bq/L in the ocean. If the concentrations exceed these thresholds, then the discharging must stop immediately.

Researchers at the University of Tokyo have now collaborated with Fukushima University to investigate the effects of discharging tritium into the local ocean environment, and whether the discharging of this treated water is actually having an adverse impact. The study used an ocean general circulation model known as COCO4.9 to look at the influence of climate conditions – such as long-term global warming – on the discharge scenarios of tritium from the power plant. The researchers examined multiple discharge scenarios (based on the amount of tritium released) up until 2099.

Previously, no modelling had been performed looking at long-term impacts relating to the changing environmental conditions of the planet. In a press release from the University of Tokyo, lead author Alexandre Cauqouin states that: “In our global ocean simulations, we could investigate how ocean circulation changes due to the global warming and representation of fine-scale ocean eddies influence the temporal and spatial distribution of tritium originating from these treated-water releases”.

It is important to find out how fast and far the tritium discharge spreads because both climate change and eddies in water currents can speed up the movement of tritium through the ocean.

The study revealed that in all but one of the modelled scenarios (and at the release location, which has a much higher concentration because the treated water hasn’t dissipated yet), the tritium concentration in the ocean remained almost the same, and at a very low concentration. This was true for both long- and short-term scenarios – showing that the discharge from the Fukushima Daiichi nuclear power plant has an almost negligible impact on the ocean.

Other than the worst-case scenario, the model discovered that the increase in tritium from the treated water is 0.1% or less of the tritium background concentration of 0.03–0.2 Bq/L within 25 km of the discharge site in the Pacific Ocean. This is well below detection limits – such a small amount that the presence of the added tritium from the treated water cannot be measured directly in the seawater. The results are also far below the safety standards of 10,000 Bq/L set by the World Health Organization and consistent with physical seawater monitoring being performed today.

Even in the worst-case scenario, the levels of tritium still fell well below the detection limits, but the model did find that in such a high-CO₂ emission scenario, there would be an increased concentration of tritium in the south of Japan due to the Kuroshio current – which could theoretically reach the western coast of the US, but in insufficient concentrations to have any adverse effects throughout the Pacific Ocean.

Overall, the study showed that the long-term safety threshold won’t be exceeded under the current treated water release plans. The study could also help with building future models to better understand how tritium moves through both water vapour and ocean water – as tritium could be used in the future as a chemical tracer to track atmospheric and oceanic circulation, precipitation patterns, river catchments, moisture sources and groundwater flow.

The research is published in Marine Pollution Bulletin.

Optical imaging probe designed to increase safety and efficacy of glioblastoma surgery

Glioblastoma is the most aggressive brain cancer and the hardest to treat, as it spreads and invades healthy brain tissue in a diffuse, microscopic way. Surgical treatment calls for a fine balance between excising all cancerous tissues and removing as little healthy brain tissue as possible. To help neurosurgeons more accurately remove glioblastoma, an international research collaboration has developed an optical imaging probe that identifies microscopic cancer cells in the margins of tumour-resected cavities in the brain.

The imaging probe works by exploiting the significantly increased fatty acid (FA) metabolism exhibited by glioblastoma cells. FA metabolism plays a key role in tumour progression and proliferation and is central to cancer immunity. To enable real-time, non-invasive imaging of FA absorption, the researchers – from Erasmus University Medical Center (Erasmus MC) in The Netherlands and the University of Missouri in the US – covalently linked a long-chain saturated FA with the clinically approved near-infrared (NIR) dye indocyanine green (ICG).

ICG has intrinsic low autofluorescence, enables deep tissue imaging and exhibits a high signal-to-noise ratio compared with visible fluorophores. The team hypothesized that a probe combining ICG with a FA might specifically accumulate in tumours and enable efficient intraoperative visualization of tumour margins. Importantly, the spectral characteristics of ICG make it compatible with many existing intraoperative cameras and surgical microscopes.

The researchers initially investigated the uptake of the FA-ICG probe in living cells, confirming that the dye’s physiological uptake resembles that of natural FAs. They then used fluorescence imaging to assess FA-ICG uptake in mice with implanted glioblastoma, observing high accumulation in the brain tumours.

Comparing the fluorescence signal from mice administered with equivalent doses of FA-ICG and ICG revealed that the average radiance from FA-ICG was approximately 2.2 times higher than that from IGC. At 12 and 24 h post-injection, retention of the probe in the brain was approximately two to three times higher in the tumour-bearing than the non-tumour-bearing hemisphere.

Next, lead authors Meedie Ali and Pavlo Khodakivskyi and their colleagues investigated the application of FA-ICG as a preclinical imaging agent in a patient-derived model of glioblastoma. They showed that the probe could successfully image tumour growth at different time points in several mice.

“This finding is of importance for preclinical research since patient-derived xenograph models of glioblastoma are characterized by an unpredictable growth pattern and low tumour implantation rates,” explains principal investigator Elena Goun from the University of Missouri. “Thus, monitoring of tumour status by sensitive, non-invasive in vivo fluorescence imaging would be of high value as the introduction of optical imaging of reporter genes [an alternative monitoring approach] is known to result in tumour phenotypic alterations.”

Fluorescence-guided surgery

The researchers also demonstrated the feasibility of FA-ICG as a contrast agent for NIR image-guided cancer surgery, performing surgery on tumour-bearing mice using a standard NIR camera approved for use in surgical suites. Not only did the FA-ICG probe successfully image glioblastoma in the animals’ brains, but the brains also exhibited a considerably higher fluorescence signal than seen from similar mice injected with an ICG-only dye.

Subsequently, the team employed the probe during surgical resection of veterinarian-diagnosed symptomatic canine mastocytoma (a skin cancer) in a pet dog. Ten hours after injection with FA-ICG, the dog underwent surgery, with image-guided surgery performed successfully using an open-air NIR surgical camera.

If the probe transitions to routine clinical use, it could prove be of great benefit to neurosurgeons. If they can identify cancer cells, which are microscopic and resemble healthy brain tissue, outside the surgical margins, follow-up chemotherapy and radiation treatments should be more effective and cancer recurrence may be delayed. The probe also offers the practical features of a workable surgical procedure, an appropriate half-life and fluorescence that can be seen under normal operating room lights.

“Our results demonstrate that FA metabolism represents an excellent target for tumour imaging, leading to significantly enhanced uptake of the FA-ICG probe in tumours,” the researchers write. “[The probe] represents a promising candidate for a wide range of applications in the fields of metabolic imaging, drug development and most notably for translation in image-guided surgery.”

The researchers are now planning a Phase I clinical trial to examine the safety and efficacy of the probe. Specifically, they aim to determine how well patients tolerate the probe, what side effects may occur at an effective dose, and how the probe’s performance compares to existing optical imaging surgical tools.

“The upside of fluorescence-guided surgery is that you can make little remnants much more visible using the light emitting properties of these tumour cells when you give them a dye,” says Rutger Balvers, a neurosurgeon at Erasmus MC who is expected to lead the human clinical trials, in a press statement. “And we think that the upside of FA-ICG compared to what we have now is that it’s more select in targeting tumour cells. The visual properties of the probe are better than what we’ve used before.”

The study is described in npj Imaging.

Illuminating light: a colourful physics book for children

As a mother of two, I’ve read a lot of children’s books. While there are some so good that even parents don’t mind reading them again and again, it’s also very easy for them to miss the mark and end up “accidentally” hidden behind other books. They’ve not only got to have an exciting story, but also easy wording, a rhythmic pace, flowing language and captivating pictures.

Great non-fiction kids’ books are especially hard to find as they need to add in yet another ingredient: facts. As a result, they can often struggle to portray educational topics in an accessible and engaging way without being boring. So when I saw the ever impressive Jess Wade had published her second children’s book about physics, Light: the Extraordinary Energy That Illuminates Our World, I was intrigued.

Wade is a woman of many talents. She’s an accomplished physicist at Imperial College London, a trailblazing advocate for equality in science, and an enthusiastic science communicator. Her first book, Nano: the Spectacular Science of the Very (Very) Small, won the 2022 UK Literary Association (UKLA) Book Award for information books (3–14+ years).

And now, with the help of beautiful illustrations by Argentinian artist Ana Sanfelippo, Wade has created a clear, concise explanation of light, how it behaves and how we use it. The book starts by describing where light comes from and why we need it, and goes on to more complex topics like reflection, scattering and dispersion, the electromagnetic spectrum, and technologies that use light.

The language is clear, the sentences are simple, and there is a flow to the narrative that makes up for the lack of a story. Wade makes the science relatable for children by bringing in real-world examples – such as how your shadow changes length during the day, and how apples reflect red light so look red. And throughout, Sanfelippo’s gorgeous illustrations fill the pages with colourful images of a girl and her dog exploring the concepts discussed, keeping the content bright and cheerful.

Cats and secrets

Now obviously I am not the target audience for Light. So, as my own children are too young (the age range listed is 7–12 years), I asked my eight-year-old niece, Katie, to take a look.

Colourful illustration of a cat sat under a desk lamp casting a shadow — **Everyday science** Jess Wade’s new book also examines familiar concepts such as shadows. (Courtesy: Walker Books 2025. Text © 2025 Jess Wade. Illustrations © 2025 Ana Sanfelippo. All rights reserved.)

Instantly, Katie loved the illustrations, which helped keep her engaged with the content as she read – her favourite was one of a cat using a desk lamp to create a shadow. She was intrigued by how fast light is – “you’d have to run seven and a half times around Planet Earth in a single second” – and liked being “let in on a secret” when Wade explains that white light actually contains a rainbow.

But as the book went on, she found some bits confusing, like the section on the electromagnetic spectrum. “It’s definitely a book someone Katie’s age should read with a grown up, and maybe in two sittings, because it’s very information heavy (in a good way),” said her mum, Nicci. Indeed, there are a couple of page spreads that stand out as being particularly busy and wordy, and these dense parts somewhat interrupt the book’s flow. “But overall, she found the topic very interesting, and it provoked a lot of questions,” Nicci continued. “I enjoyed sharing it with her!”

I think it’s safe to say that Wade can add another success to her list of many accomplishments. Light is beautiful and educational, and personally, I wouldn’t hesitate to give it as a gift or keep it at the front of the bookshelf.

2025 Walker Books 32pp £12.99hb

Vortex self-organization in confined chiral liquid crystals

Superconductors are materials that, below a certain critical temperature, exhibit zero electrical resistance and completely expel magnetic fields, a phenomenon known as the Meissner effect. They can be categorized into two types.

Type-I superconductors are what we typically think of as conventional superconductors. They entirely repel magnetic fields and abruptly lose their superconducting properties when the magnetic field exceeds a certain threshold, known as the critical field, which depends on both magnetic field strength and temperature.

In contrast, Type-II superconductors have two critical field values. As the magnetic field increases, the material transitions through different states. At low magnetic fields below the first critical field, magnetic flux is completely excluded. Between the first and second critical fields, some magnetic flux enters the material. Above the second critical field, superconductivity is destroyed.

In Type-II superconductors, when magnetic flux enters the material, it does so at discrete points, forming quantized vortices. These vortices repel each other and self-organize into a regular pattern known as the Abrikosov lattice. This effect has also been observed in Bose-Einstein condensates (bosons at extremely low temperatures) and chiral magnets (magnetic materials with spirally aligned magnetic moments). Interestingly, similar vortex self-organization is seen in liquid crystals, offering deeper insights into the underlying physics.

In this study, the researchers investigate vortex behaviour within a liquid crystal droplet, revealing a novel phenomenon termed Abrikosov clusters, which parallels the structures seen in Type-II superconductors. They examine the transition from an isotropic liquid phase to a chiral liquid phase upon cooling. Through a combination of experimental observations and theoretical modelling, the study demonstrates how chiral domains, in other words topological defects, cluster due to the interplay between vortex repulsion and the spatial confinement imposed by the droplet.

To model this behaviour, the researchers use a mathematical framework originally developed for superconductivity called the Ginzburg-Landau equation, which helps identify how certain vortex patterns emerge by minimizing the system’s energy. An interesting observation is that light passing through the chiral domains of the droplet can resultingly obtain chirality. This suggests that the research may offer innovative ways to steer and shape light, making it valuable for both data communication and astronomical imaging.

Read the full article

Abrikosov clusters in chiral liquid crystal droplets

V Fernandez-Gonzalez et al 2024 Rep. Prog. Phys. 87 120502

Do you want to learn more about this topic?

Vortex dynamics and mutual friction in superconductors and Fermi superfluids by N B Kopnin (2002)