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Physicists find unexpected connection between black hole mergers and thermodynamics

Usually, when physicists want to model the merger of two black holes, they use supercomputers. Now, however, physicists in the US have found a possible shortcut. In a study published in Physical Review Letters, they show that, of the final states permitted by energy and angular momentum, the remnant of a non-spinning black hole merger ends up in a state quite close to one that maximizes the system’s entropy – a surprising and puzzling result that reinforces the deep connection between thermodynamics and black holes.

“Our group has long believed that black hole thermodynamics could provide a new perspective on binary black hole mergers,” says team member Monica Rincon-Ramirez, a postdoctoral researcher at Pennsylvania State University. “While black hole thermodynamics is well established for equilibrium systems, much less is understood in the highly dynamical regime of mergers.”

Merging black holes

Black hole mergers occur when two black holes that orbit each other spiral inward with increasing speed, losing both energy and angular momentum by emitting gravitational waves until they eventually converge in a violent clash. After the moment of merger, the remnant oscillates vigorously, “ringing down” into a quiescent, rotating object known as a Kerr black hole that can be described in terms of just two quantities: mass and spin.

Meanwhile, the gravitational waves – ripples in the fabric of spacetime – from this energetic collision propagate through space virtually uninterrupted. These gravitational waves encode information about their source, and when we detect them on Earth (millions of light-years away from their origin), we can use them to predict the remnant’s size and spin. However, doing this requires solving complex equations from Einstein’s general theory of relativity using computationally expensive numerical simulations.

Connecting black holes and thermodynamics

Thermodynamics is the branch of physics concerned with the relationships between energy, heat, work and temperature. For ordinary matter, thermodynamics can describe how energy flows from one system to another in simple terms, even for complex systems with numerous particles and degrees of freedom. For example, rather than meticulously tracking each individual particle, concepts such as entropy – a measure of a system’s disorder – can be used to describe the final state of the entire system.

Physicists have long known that black holes obey laws that closely parallel the laws of thermodynamics, with the event horizon and surface gravity of black holes being analogous to entropy and temperature, respectively. Building on this established connection, Rincon-Ramirez and colleagues at the University of Mississippi, the University of California, Berkeley, and Northwestern University as well as Penn State investigated whether black hole thermodynamics could go beyond describing the properties of isolated, stationary black holes and provide, in addition, a principle for determining the final state of a merger.

The maximum-entropy conjecture

After accounting for the energy and angular momentum carried away by gravitational waves, the researchers tracked the evolving mass and angular momentum of a binary, mapped these values to those of hypothetical Kerr black holes, and calculated the corresponding entropy. They found that the Kerr entropy reaches a maximum at a mass and spin strikingly close to the final mass and spin predicted by numerical relativity simulations. Indeed, the two methods agreed with each other to within a few percent. “The Kerr entropy turned out to be remarkably meaningful for the binary system as a whole,” Rincon-Ramirez says.

Interpreting and presenting these results proved to be a challenge, however. “What we found was completely unexpected,” says Rincon-Ramirez. After deliberating among themselves as to why the final black hole’s parameters should lie so close to those of the maximum-entropy black hole, they ultimately chose to extend the conversation to the scientific community. By presenting their puzzling results and a broad conjecture, which they term the “maximum entropy conjecture for black hole mergers”, they hope to sharpen their findings through rigorous testing and eventually place them on a firm mathematical foundation within general relativity.

The unsung theory: why thermodynamics is as important as quantum mechanics and general relativity

In the meantime, the researchers plan to extend their conjecture to more general binary black hole systems. By studying systems such as highly spinning and eccentric binaries, they hope to gain further understanding of the role of thermodynamic quantities in general relativity. “Ultimately, we hope this work will contribute to a more complete thermodynamic framework for highly dynamical spacetimes,” Rincon-Ramirez says.

Nuclear fusion persists at ultralow energies inside metal foils

Deuterium nuclei fired into thin foils of palladium and titanium keep fusing when the nuclei’s incident energies are reduced to the level where the process should be all but extinguished. Instead, physicists in the US have found that as the incident energy is reduced, the fusion rate plateaus – even at the lowest energies probed. Indeed, the low-energy fusion rate exceeds predictions for isolated nuclei by more than 10¹⁸. While significant, the enhanced fusion rates remain far too small for energy generation.

The results suggest that a metal’s electrons and internal defects can influence how fusion occurs, according to the researchers at the University of California, Davis and Lawrence Berkeley National Laboratory

Nuclear fusion powers the stars, but here on Earth it has so far been impossible to create a practical fusion reactor that delivers usable energy to the electricity grid

“Fusion is hard in the laboratory because positive nuclei repel each other,” explains team member Thomas Schenkel at Berkeley. Quantum mechanics offers a loophole – nuclei can tunnel through the repulsive barrier without having enough kinetic energy to overcome it. However, the tunnelling probability is very small at low energies.

Not fade away

Physicists measure these nuclear collision energies in kiloelectronvolts (keV). Today’s fusion reactors tend to operate plasmas at temperatures that correspond to collision energies of about 10 keV. Below that, reactions fade away, and earlier experiments showed that fusion pretty well stopped near 5 keV.

Yet a solid is a very different environment to a plasma. “Metal lattices contain electrons, defects, and locally concentrated deuterium, all of which can combine to create reaction environments that do not exist in a conventional plasma,” says Jeremy Munday who along with Micah Karahadian is based at UC Davis . The metal’s electron cloud partly shields the repulsion between nuclei, letting them approach more closely. This “screening” effect has been studied since the 1990s and is still not fully understood. The field also carries the scars of the 1989 cold-fusion debacle, during which experiments reporting enhanced fusion rates in solids at room temperature could not be reproduced.

Schenkel and Munday came to this field in the 2010s as participants in a Google-funded effort that revisited the 1989 claims. The programme found no evidence for room-temperature fusion, but it seeded their current collaboration.

Membrane reactor

The team’s apparatus places a metal foil, a quarter of a millimetre thick, between two very different environments. “At the heart of our experimental setup is a type of membrane reactor that combines an electrochemical cell with a deuterium ion beam,” says Schenkel. On one side, an electrochemical process – “similar in principle to charging a battery,” says Munday – pushes deuterium into the metal from a liquid. On the other side, in vacuum, a beam of deuterium ions strikes the same foil, burying itself just a few millionths of a millimetre below the surface.

Each fusion event spits out a fast proton or neutron, caught by two independent detectors. “Detecting these products independently, along with extensive background and control measurements, gave us confidence that the signals came from fusion,” Munday says.

As the team reduced the incident energy, they were surprised. “We observed the well-known exponential rate drop, but then the rates did not drop anymore but rather plateaued as we further decreased the ion energy,” says Schenkel. The plateau appeared below about 2 keV in both metals, and loading extra deuterium electrochemically roughly doubled the yield.

“This is an enormous relative enhancement, although the absolute fusion rate remains far too small for energy production,” Munday stresses. “The immediate significance of our work is therefore the discovery of a new physical regime in which the material actively influences the nuclear reaction, rather than the demonstration of a practical energy source.”

Welcome corroboration

Konrad Czerski, professor of nuclear and medical physics at the University of Szczecin, Poland, sees the result as welcome corroboration. “The Berkeley study represents an independent confirmation of the effect found by our research group over two years ago within Europe’s CleanHME project,” he says. His team saw a similar plateau in zirconium, palladium and titanium with a different technique. The palladium results of the two groups agree well, he notes, but the titanium data differ.

Czerski is not persuaded by the American team’s explanation, which attributes the plateau to unusually strong screening in the foil’s damaged surface layer. His group’s measurements, he argues, “demonstrate unambiguously that the yield plateau arises from fusion of deuterium at ordinary thermal energies, and the screening energy doesn’t change.”

The disagreement underlines how much remains open in the field. “The most important next step is to identify the microscopic origin of the low-energy plateau,” says Munday. This would involve untangling the roles of screening, surface damage and the way deuterium moves and gets trapped in the metal. The US team also wants to test whether light or crystal vibrations can affect the reaction rate. Near-term applications, he suggests, might include compact neutron sources rather than reactors.

Czerski has a bolder vision for the future. “The experimental setups and the results obtained can launch a new research field focused on materials and enhancing the electron screening effect in nuclear reactions,” he says – one that “can finally lead to commercial applications, and even possibly to construction of a new energy source.”

The research is described in Nature Communications.

Portable breast ultrasound enables imaging between cancer screening exams

<em>In vivo</em> ultrasound images — *In vivo* ultrasound images From left to right: a cyst, breast implant, dense fibrous tissue and solid mass. The top row shows conventional 2D ultrasound images while the bottom row shows the corresponding images using the 3D PURE system. (Courtesy: the researchers)

Women at high risk of breast cancer are more susceptible to developing cancers in the gap between routine screening exams. These so-called “interval cancers” tend to be fast-growing and account for 20% to 30% of all breast cancer cases.

To identify aggressive cancers that develop between scheduled screenings, researchers at Massachusetts Institute of Technology (MIT) have developed a point-of-care ultrasound system that generates high-resolution 3D images of breast tissue. The 3D portable ultrasound system for real-time examination (3D PURE) supplements mammography with its ability to detect anomalies reliably in dense breast tissue (in which mammography is less sensitive).

Guided by an easy-to-use visual interface, 3D PURE enables a nurse, a physician such as a primary care provider or gynaecologist, or even the patient herself to frequently perform longitudinal breast imaging.

Second-generation design

Principal investigator Canan Dagdeviren explains that this second-generation prototype overcomes limitations of a prior system designed by the MIT team, through advances in transducer design, acoustic materials and adaptive beamforming. These developments have enabled real-time wide-angle 3D imaging in a portable form factor, with improved image resolution to accurately identify cysts, solid masses, fibroadenomas and microcalcifications.

The ultrasound system comprises a newly designed 128-element box-shaped 2D transducer array incorporating a corner-gap offset geometry, which suppresses peak crosstalk by 3.73 dB at the corner-most element. This design prevents amplifier saturation, and supports operational transmit voltages of up to 24 V. The array is integrated into a compact multilayer electronics stack comprising preamplifiers, transmit electronics and a custom chirp data acquisition system.

There’s also a conductive backing layer (a toluene-diluted polyurethane matrix with a high percentage of tungsten and zirconia filler) that forms a continuous shielding layer around the elements, improving acoustic attenuation and providing electromagnetic shielding. The compliant mechanical nature of the material enhances acoustic damping, reducing ultrasound reverberations more effectively and improving signal fidelity.

“The addition of a backing layer to the ultrasound transducer is a key advantage to the system,” explains co-lead author Md Osman Goni Nayeem. “It provides both better directionality of ultrasound waves and better bandwidth, which improves the resolution and quality of the resulting images.”

The researchers also incorporated layered aberration-correction reconstruction (LACR), an adaptive 3D beamformer, into the 3D PURE design. LACR compensates for the heterogeneous speed-of-sound in the breast, which comprises glandular and fibrous tissues plus a superficial layer of fat. They believe that this represents the first wide-angle 3D ultrasound imaging system to implement aberration-correction beamforming.

“What we are trying to do is predict the speed-of-sound properties of the tissue being imaged, and then use that to reconstruct the image more accurately. We see up to a 10% improvement for the resolution just by applying this [beamforming] technique,” says co-lead author Shrihari Viswanath in a press statement.

A 3D ultrasound probe positioned on a tissue phantom — **Experimental validation** The 3D ultrasound probe is positioned on a tissue-mimicking breast phantom for visualization of embedded microtargets. (Courtesy: the researchers)

The system is designed for ease of use. A visual user interface called “Mirror my First UltraSound” (MyFUS) guides users to reliably reposition the ultrasound probe at the same anatomical location during repeated imaging and long-term monitoring. Meanwhile, a wide field-of-view minimizes the number of scans needed to cover the entire breast.

The team undertook an in vitro study comparing the performance of the 3D PURE system with that of a conventional 2D handheld ultrasound system (HHUS). Ten study participants imaged a breast-shaped tissue phantom embedded with sub-millimetre targets. Nine of the 10 participants showed improved microtarget detection efficiency with 3D PURE relative to the conventional system – identifying more of the targets using 3D PURE (79.7%, compared with 60.7% for the 2D HHUS), with a higher detection efficiency (14.02% of available targets per minute, compared with 9.58%).

The researchers also worked with radiologists to assess a variety of breast anomalies in vivo. The radiologists verified that the 3D PURE system could accurately visualize calcifications, cysts, implants, fibrous tissues and solid masses within a large volumetric field-of-view. The researchers independently validated the system’s accuracy when imaging dense fibrous breast tissue and rib structures.

Seven volunteers with no prior experience of using an ultrasound system tested the MyFUS visual interface. After initial instruction by an ultrasound technician, they were able to repetitively position the probe at a specific location on their breasts, achieving a 94.10% mean overlap value on frontal projections, and 87.42% on side projections. This test reconfirmed that novice users could achieve reproducible longitudinal monitoring results with the aid of the visual interface.

The researchers now hope to create an interface for use with mobile phones or tablets. This type of system could make breast ultrasound more accessible to patients in economically constrained countries lacking adequate breast cancer scanning and regions with shortages of trained ultrasound technicians.

“The high operator dependence of conventional ultrasound is a barrier to its use in decentralized or home-monitoring settings,” the researchers write. “The MyFUS vision interface transforms longitudinal monitoring from an expert-driven procedure to a self-guided, reproducible process that can be used by novice users. This reproducibility is vital for longitudinal monitoring in limited clinical settings, to regularly track the growth of an anomaly or the response of a tumour to therapies without visiting clinics.”

The 3D PURE system is described in Nature Communications.

Quiz of the week: what type of radiation travels on a photonic highway?

From pit stop to plant food: how Grand Prix crowd’s urine becomes fertilizer

Peeing at the Grand Prix just got a lot more meaningful. In the latest episode of Physics World Stories, Lucy Bell-Reeves and Olivia Wilson, who work for the start-up NPK Recovery, based at the University of the West of England, explain how their mobile system upcycles urine into fertilizer, right where it’s produced.

The pair unpack the physics and chemistry behind their approach, contrasting it with the energy-intensive Haber-Bosch process, which converts natural gas into ammonia under extreme heat and pressure at centralized plants. With the UK importing 100% of its nitrogen, and recent global conflicts exposing the fragility of fertilizer supply chains, the case for local, circular alternatives is growing stronger.

Host Andrew Glester hears about the pair’s experience at the British Grand Prix in Silverstone, the UK’s leg of the Formula 1 World Championship. Bell-Reeves and Wilson reflect on what it’s like to experience the “Grand Pee”, and how attendees react when they discover where their urine ends up.

While not pitched as a replacement for industrial-scale ammonia production, the system offers a smart fix for off-grid sites facing sudden spikes in human waste.

AI sniffs out tuberculosis in breath’s chemical signature

Every breath we exhale carries a complex chemical narrative written in thousands of volatile organic compounds (VOCs). These tiny molecules, produced by human metabolic processes and invading pathogens, hold immense diagnostic potential. Yet, translating this molecular cloud into a definitive medical diagnosis has long faced an analytical bottleneck. Now, an international team of physicists from Botswana and South Africa has harnessed machine learning to decode these complex signatures, offering a rapid, non-invasive pathway to detect tuberculosis (TB) directly from human breath.

Breaking the analytical bottleneck

Traditional gas chromatography-mass spectrometry (GC-MS) excels at separating complex molecular mixtures based on volatility and mass-to-charge ratios. However, a single breath sample generates thousands of overlapping spectral peaks. Manually sifting through this dense landscape is a painstaking, time-consuming process.

To find a faster, more systematic approach to molecule identification, researchers in the Nano –Breath taking group led by George Chimowa from Botswana International University of Science and Technology (BIUST) collected breath samples from three distinct cohorts: patients with active TB, individuals with multidrug-resistant TB (MDR-TB), and healthy control volunteers.

Standard analytical pipelines often rely on aggressive data pre-processing to smooth and simplify the GC-MS spectra. However, this filtering risks erasing subtle, low-concentration molecular features that might hold critical diagnostic clues. Bypassing this limitation, the BIUST group fed a high-dimensional dataset of 1867 spectral features (from 87 breath samples) directly into four competing supervised machine-learning algorithms: decision trees, random forest, k-nearest neighbours, and support vector machines (SVM). The researchers published their findings in Discover Artificial Intelligence.

Geometric optimization avoids the pitfalls of high-dimensional data

The team found that the linear SVM classifier led the algorithmic comparison, distinguishing among the three patient cohorts with 93% accuracy.

This performance stems from how the algorithm handles high-dimensional data spaces. While distance metric models often suffer from overfitting errors, where experimental noise is misidentified as a meaningful diagnostic signal, SVM relies on geometric boundary optimization to separate classes.

Much like clearing a wide highway down the centre of two opposing crowds, it identifies a hyperplane that maximizes the margin between groups. Instead of tracking every individual in the crowd, the algorithm relies solely on a sparse subset of border points known as support vectors. By focusing strictly on these boundary “guards” and ignoring the background movement, this approach completely isolates the classifier from the noise inherent to the surrounding high-dimensional feature space.

Beyond raw classification accuracy, the model yielded a crucial insight for future clinical applications. It pinpointed a specific window within the gas chromatogram, a retention time between 10 and 30 min, where the most diagnostic, high-variance VOCs elute. This 20-min window corresponds to medium- and large-molecule VOCs, including specific chemical biomarkers associated with TB, such as tridecane, decane and O-cymene.

By demonstrating that these vital diagnostic features are concentrated within this single slice of data, the physicists have shown that future diagnostic hardware can be specialized, eliminating the need to analyse the entire spectrum. Narrowing the focus to this specific elution window can drastically shrink data-processing times and maximize instrument throughput in clinical settings.

AI and the future of medical diagnostics

TB remains one of the world’s deadliest infectious diseases. Traditional diagnostics rely heavily on slow sputum cultures and backlogged laboratory queues, delaying critical treatment. A rapid, non-invasive breath test powered by an optimized physical classifier offers an ideal alternative for resource-limited settings where laboratory infrastructure may be scarce.

While the researchers emphasize that larger validation trials are required, the work signals a profound shift in medical diagnostics. It mirrors advanced data-modelling techniques used in engineering, such as those predicting structural degradation in self-healing aerospace composites.

By fusing analytical physics with artificial intelligence, this research points to a future where immediate, automated bedside disease detection could be rapid, accessible and driven entirely by the mathematical profiling of a patient’s breath.

Heat-transfer fins give phase change materials a boost

If you’ve ever kept a drink cool on a hot summer day by placing it inside a frozen, gel-filled sleeve, you’ll understand the appeal of phase change materials (PCMs). The reason these sleeves work so well (and so much better than simply putting your drink in a cold bath or cool room) is that the solid inside them has a high latent heat, meaning it can absorb relatively large quantities of energy before melting and beginning to warm up.

But what if surrounding your drink with a frozen PCM isn’t enough? What if you want to cool your drink more quickly and evenly? One option would be to create a PCM sleeve with fin-shaped extensions that protrude into your drinking vessel. These fins would cool your drink – or, equivalently, allow your drink to melt the PCM – much more efficiently than a simple sleeve. But what should the fins look like? How far apart should they be? And how many of them do you need?

These are the questions that Paolo Proia, Mauro Sbragaglia and Giacomo Falcucci considered in a study published in EPL – though not with the aim of keeping their drinks cold. As researchers at the University Tor Vergata of Rome, Italy, Proia, Sbragaglia and Falcucci are interested in PCMs that store and release heat like a battery. Such materials are useful in fields such as electronics and refrigeration where heat is a common byproduct. Other applications include maintaining the efficiency of solar panels by preventing them from getting too hot and keeping buildings cool in the daytime via insulation.

Physics World spoke with them about their work.

What was your motivation for doing this research?

Our interest in PCMs stems, in part, from our interest in their many applications, especially in the ecological transition to less carbon-intensive fuels. PCMs are particularly good at managing heat in hydrogen storage with metal hydrides, for example, because storing hydrogen in these materials produces heat, while releasing the hydrogen requires it. Using a PCM to store the heat of the adsorption process and give it back during the release means that the produced heat doesn’t go to waste. Instead, it improves the efficiency of the process.

We’re also fascinated by the complexity of the equations involved. The coupling of fluid and temperature dynamics already causes interesting phenomena such as convection. By adding a phase transition to the mix, you introduce a moving boundary that complicates the system even more, both phenomenologically and analytically, since the describing equations must account for it.

We started this paper as a way of extending our previous work on the insertion of fins inside a PCM to three dimensions. PCMs are exceptionally good in latent heat but severely lacking in sensible heat; in other words, they store heat well, but they absorb and release it poorly. Fins are useful in relieving this flaw since they enhance the heat transfer surface and provide a horizontal heat source, which is instrumental for the development of convection, the main driver of heat transfer in this kind of system. By switching to a 3D system, we had more freedom to explore complex layouts of multiple fins and the importance of their relative position.

Individual head shot photos of Paolo Proia, Mauro Sbragaglia and Giacomo Falcucci — Phase change modellers: (left-right) Paolo Proia, Mauro Sbragaglia and Giacomo Falcucci. (Courtesy: Paolo Proia)

What is the most important advance in the paper?

The most important result is that naively inserting fins too close to each other can cause interference. If there are overlaps in the fins’ “influence zone”, the system will waste energy by, in effect, trying to melt something that was already molten from heating by a nearby fin. Moreover, by comparing a single fin and multiple fins with the same total surface, we found that the latter configuration benefits from the gaps between the fins. This is because the substance in these gaps melts early and starts acting as an extra heating surface, contributing to the development of bigger convective structures.

Why is it so challenging to model melting in phase change materials in 3D?

Beyond the analytical requirements we already mentioned, the success of this type of modelling depends on having a resolution that is high enough to capture correctly all the phenomena in the system. This means the number of computational sites N must be sufficiently large. In 2D, we “only” have N² sites to model, but in 3D, this scales to N³. That creates a challenge because making N too large would severely slow down the simulation. Moreover, we must be sure to respect the restraints on the physical parameters for which the lattice Boltzmann method is a correct approximation of the equations involved. So, we underwent a thorough validation process to pinpoint the best parameters for the algorithm.

What do you plan to do next?

First, we’d like to further optimize the code. The main bottleneck is the speed of a single iteration. Ideally, we’d like to study a wider range of layouts and physical conditions, but with the code we have now, that would impact heavily on performance. For example, a slower-melting substance requires more iterations to completely melt, which translates into more real-life time to model, sometimes outside the limits of feasibility. This problem would obviously be solved if we can make a single iteration faster.

Another issue we have is that some ranges of physical parameters can make the simulation unstable. Fortunately, there exist some remedies to this, and we plan to eventually adopt them.

Finally, we would be happy to see other researchers use these findings in their own optimization studies on fin shapes and spatial layouts. It would also be very interesting to see someone study this problem from an analytical angle or to see some experimental validation. In the medium term, we are planning to conduct our own experiments to use as a benchmark for our computational results.

Pressurizing EV battery electrodes could make them last longer, if it’s done right

Pressure-dependent battery degradation mechanisms — **Pressure-dependent degradation mechanisms** Low stack pressure accelerates cathode cracking, while high pressure promotes lithium plating. At the optimal pressure, balanced interparticle contact and porosity minimize mechanical degradation. (Courtesy: CC BY 4.0/*Nat Energy* 10.1038/s41560-026-02087-6)

Engineers are constantly striving to improve the safety and performance of electric vehicle (EV) batteries. Much effort has been put into developing new electrode materials over the years, but future improvements may not follow the same path and may just be as simple as utilizing physical pressure.

A recent study, led by researchers at the University of Cambridge, suggests that EV batteries could be made to last up to twice as long, by applying the right amount of pressure to the electrodes. It is, however, a fine balancing act, as too high or too low a pressure can cause the battery to fail. To employ this approach in real world systems, engineers will need to make sure that the process is easily repeatable without significant pressure error, but it’s an interesting avenue of battery engineering that has come to fruition.

“We carried this work out to improve the sustainability of batteries,” says Michael de Volder, one of the lead researchers on the study. “Given that we are not very good at recycling batteries, extending the lifetime of batteries reduces the need for mining critical minerals for making new batteries and therefore improves their sustainability.”

For their study, reported in Nature Energy, the researchers developed a dilatometer with pneumatic bellows to apply pressure to the electrodes. The bellows act like a clamp to maintain a uniform and constant pressure on the electrode, while a sensor detects small volume changes that occur as the battery charges and discharges.

The researchers tested their electrode pressurization approach on commercial nickel manganese cobalt (NMC) lithium-ion pouch batteries (which have a flexible packaging), without changing their electrolyte or electrode composition. By using commercial batteries with a standard setup, they could test them fairly under different pressures.

“In this work we optimized how hard battery anodes and cathodes should be pushed together to maximize the lifetime of batteries,” de Volder tells Physics World. “Importantly, we also unravel which degradation mechanisms kick in if you press too hard, or not hard enough.”

Doubling battery lifetime

The researchers found that increasing the stack pressure fourfold over typical initial values used in conventional coin cells – to an optimal pressure of 12.5 bar – doubled the lifetime of the NMC811 cells. They compared the results with NMC cells tested at an extra-low pressure of 1.5 bar, a low pressure of 3 bar, a medium pressure of 6.5 bar and a high pressure of 37.5 bar.

Different degradation mechanisms emerged at high and low pressures outside of the optimal pressure zone. Low stack pressure accelerated cathode cracking, causing an increase in transition metal dissolution and excessive formation of the solid electrolyte interphase (SEI) layer. The cracking is likely due to a small number of particles bearing most of the mechanical load, leading to localized high-stress concentrations that initiate crack propagation.

Higher stack pressures, meanwhile, caused increased lithium plating on the anode. The team observed that the electrode thickness reduced during initial cycling but then underwent rapid thickness growth. When the electrodes are at their thinnest, they have a lower porosity that limits lithium transport, leading to higher overpotentials and higher lithium plating. This increases the amount of “dead” lithium and reduces the usable lithium inventory in the battery, causing it to degrade faster.

“We found that when the pressure applied to battery cells is sub-optimal, certain dangerous degradation processes can be accelerated. So, in a way, pressure optimization might improve the safety of batteries. However, more research is needed before we can draw reliable conclusions on this front,” says de Volder.

The pressurization results in this study are still in the early stages, but if shown to be viable at scale in commercial systems, could help EV batteries to last longer. In theory, this could give second-hand EVs a higher market value as the vehicle will have a longer battery life when sold. Additionally, if EV batteries can last longer, it will reduce the pressure on lithium mining operations and reduce the amount of raw material required for battery manufacturing (assuming the same demand) – something that is becoming an issue due to the skyrocketing price of lithium.

Cambridge Enterprise, the university’s innovation arm, has filed a patent, so the research team and university obviously see commercial viability in the process. When asked about the team’s future plans, de Volder tells Physics World that “we studied pressure optimization for one specific battery chemistry, but we anticipate that gains can be made in the lifetime of other battery chemistries too”.

How scholarly publishers are safeguarding trust in science

This episode of the Physics World Weekly podcast features Antonia Seymour, who is chief executive of IOP Publishing.

Seymour has more than 30 years’ experience in a publishing industry that has evolved significantly from the days of paper journals to today’s sophisticated digital technologies.

In this interview we explore how scholarly publishers are responding to the rapid growth in research output, the rise of artificial intelligence and the increase in threats to research integrity.

A wholly owned subsidiary of the Institute of Physics, IOP Publishing produces more than 100 scholarly journals as well as Physics World.

Identifying maximum viscosity: a slide puzzle

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