The mystery began with a short report published in Nature describing a very intense magnetic disturbance on 18 October 1841. According to that account, the disturbance interfered with train signals and delayed the 10:05 p.m. departure from Exeter by sixteen minutes. If true, the event would predate the famous Carrington Event of 1859 by nearly two decades and would stand as the first documented case of solar activity disrupting critical infrastructure. Generations of space weather researchers have cited the episode as a historical curiosity, but no one had systematically checked whether the story could actually have happened when the anonymous author claimed it did.

That is precisely what a team led by Lancaster University set out to do, working with scientists from RMIT University, the British Geological Survey, Natural Resources Canada, Baylor University and the United Kingdom’s national space laboratory, RAL Space. Their investigation, published in the American Geophysical Union journal Space Weather, combined an unusually broad set of evidence: railway timetables, historical newspaper reports, records of solar observations, accounts of auroral displays and digitised geomagnetic measurements. The approach treated the question less like a routine literature review and more like a historical detective case, in which every document had to be cross-checked against the physical reality of the railway network in the 1840s.

The critical clue turned out to be startlingly simple. As RMIT University space weather expert Associate Professor Brett Carter explained, the railway line referenced in the Nature account did not even exist at the time of the alleged incident. The Exeter to Starcross line, which the report described, did not open until 1846, almost five years after the supposed 1841 event. In other words, the celebrated first space weather impact on technology rested on what was almost certainly a typographical error in a paper published in 1871. A single wrong digit in a date had propagated through the historical record for more than 150 years.

With the 1841 date debunked, the team turned to the archival record to establish when the Exeter delay actually occurred. By matching the available evidence from timetables, newspapers and geomagnetic data, they concluded that the incident most likely took place on 18 October 1848 rather than 1841. The corrected date changes the historical significance of the event. The Exeter delay remains one of the earliest well-documented examples of space weather disrupting technology, but it can no longer claim to be the first. That distinction currently belongs to an earlier episode: interference with telegraph systems on the Midland Railway in March 1847, which is now the earliest credible report known to researchers.

To understand why the 1840s matter so much, it helps to recall what was happening in the world of technology at the time. The first electric telegraph networks were being constructed during that decade, and telegraph operators quickly began to experience unexplained electrical effects caused by disturbances in the Earth’s magnetic field. Solar activity can induce currents in long conductors on the ground, and the expanding web of telegraph wires criss-crossing Britain and other countries provided exactly the kind of infrastructure that geomagnetic disturbances could disturb. The 1840s, Carter noted, marked a crossing point of no return in the relationship between electronic technology and space weather, a natural phenomenon that has always existed but had never before had human systems to affect. Since that line was crossed, he observed, humans have not looked back.

The most famous early demonstration of that vulnerability came just over a decade later. A massive solar flare and coronal mass ejection in 1859, now known as the Carrington Event, produced aurora borealis as far south as Hawaii and Central America. The displays were so bright that people could read newspapers by their light, and gold miners in the Americas mistook the glow for dawn and began cooking breakfast shortly after midnight. Telegraph systems around the world failed. Sparking lines gave electrical shocks to operators and even caught fire, and some systems continued operating without batteries, driven only by the geomagnetic currents induced in the wires themselves. The Carrington Event remains the benchmark against which extreme space weather is measured, but the newly corrected Exeter story shows that the encounter between solar storms and technology began well before 1859.

Study lead author Professor Jim Wild of Lancaster University said the research challenges the assumption that space weather is a purely modern concern. What the work highlights, he explained, is that space weather is not a new threat but a long-standing natural hazard, and that society has been experiencing its effects on technology for almost as long as electrical technologies have existed. The Exeter train delay, he noted, is fascinating precisely because it sits at the point where emerging technologies first began to encounter the realities of the space environment. By combining historical archives with scientific observations, the team was able to show that the event almost certainly happened in 1848 rather than 1841. Although that means it is not the earliest recorded space weather impact, it remains one of the first clear examples of solar activity disrupting critical infrastructure, and the study demonstrates the value of combining scientific records with contemporary newspaper reports and archival documents when reconstructing historic space weather events.

Dr Mike Hapgood, visiting scientist and space weather expert at RAL Space, described the investigation as feeling like a detective story. He emphasised that the work underscores the importance of preserving older records, which provide the evidence base researchers need to interpret past events and strengthen future predictions. The point is not merely historical. Nearly two centuries after the Exeter delay, railways and other critical infrastructure remain vulnerable to space weather, although through very different technologies, including power systems, signalling equipment, satellite navigation and communications networks. Hapgood cautioned that while today’s space weather capabilities are far more advanced than anything available in the 1800s, the modern technologies society depends on are also much more vulnerable to solar storms, making a deep understanding of past events essential for preparing for and mitigating future impacts, especially as a new solar cycle arrives in the 2030s.

The corrected story of the 10:05 p.m. train from Exeter is a reminder of how easily errors can become embedded in the scientific record, and of how archival work can set that record straight. A typo in an anonymous 1871 Nature report turned a real 1848 incident into a phantom 1841 event, obscuring the true chronology of humanity’s first encounters with space weather for generations. The real history is arguably more compelling than the myth: within a few years of the first telegraph lines being strung across the countryside, the Sun was already reaching out to disrupt them, delaying trains and confusing signals. The study, published in Space Weather under the title asking whether space weather delayed the 10:05 p.m. train departure from Exeter on 18 October 1841, answers its own question with a definitive no, and in doing so gives the technological age a more accurate account of its first stormy meeting with the Sun.

Subject of Research: Historical reconstruction of an 1840s geomagnetic disturbance that disrupted railway telegraph signals in Exeter, England

Article Title: 1840s space weather mystery finally solved

Article References: 1840s space weather mystery finally solved. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: space weather, geomagnetic disturbance, telegraph, railway history, Exeter, Carrington Event, solar storms, Nature 1871, archives, Midland Railway, aurora, Space Weather journal

The research, carried out by Wei Shen, Zhen-Yan Lu, Muhammad Waqas, Xun Chen, Zhi-Jun Ma and Guang-Xiong Peng, focuses on pure SU(3) gauge theory, the gluon-only sector of quantum chromodynamics with all quark flavors switched off. This simplified world is not a mere toy. It captures the essential nonperturbative dynamics of confinement and deconfinement, and it undergoes a first-order phase transition at a critical temperature T_c. Because quarks are absent, the theory is cleaner to simulate on the lattice and serves as a rigorous testing ground for the phenomenological frameworks that ultimately must describe the full quark-gluon plasma created in experiments at facilities such as the Relativistic Heavy Ion Collider and the Large Hadron Collider.

The team’s approach, which they call the temperature-dependent mass or TDM model, rests on a deceptively simple idea. All the complicated medium effects that make hot gluon matter deviate from an ideal gas are encoded in a single effective parameter: a temperature-dependent gluon mass m_g(T). Crucially, the authors stress that this mass is not a physical pole mass of a propagating particle and certainly not evidence of free massive gluons floating around below T_c. Below the transition, where color-singlet glueball-like excitations dominate, the effective mass is simply a convenient bookkeeping device that parametrizes the suppression of colored gluonic degrees of freedom inferred from lattice data. Above the transition, it plays a similar role for the deconfined but still strongly interacting medium.

What sets this work apart is the austerity of its input. The only lattice data used to constrain the entire framework is the normalized pressure P/T^4 of pure SU(3) gauge theory. At each temperature point, the researchers numerically solved for the value of m_g/T that makes the model pressure match the lattice pressure, yielding 48 pressure-extracted mass values. Below T_c these were fitted with a cubic polynomial in the reduced temperature, while above T_c the fit is expressed as a cubic polynomial in the running strong coupling, whose temperature dependence follows a renormalization-group-motivated form. No energy density, entropy density or trace anomaly data entered the fit. Everything else, including the entropy, energy density and trace anomaly, emerged from thermodynamically consistent relations that carefully treat both the explicit and implicit temperature dependence carried by the effective mass.

That thermodynamic consistency is not a technical nicety. Because the dispersion relation of each gluonic mode depends on temperature through m_g(T), naive differentiation misses an entire term, and response functions, which are derivatives of the thermodynamic potential, are exquisitely sensitive to exactly this kind of subtlety. The authors derive the entropy density and energy density with the implicit dependence included, and in the limit of a temperature-independent mass their expressions reduce to the standard ideal boson gas results. The payoff is that the model reproduces not only the lattice pressure but also the trace anomaly, defined as the energy density minus three times the pressure, which measures the violation of conformal, or scale-invariant, behavior. The pronounced peak of the trace anomaly near T_c, a hallmark of strong nonconformal dynamics, comes out naturally from the same pressure-constrained mass profile.

The heart of the new paper lies in its treatment of second-order response functions, quantities that involve second derivatives of the thermodynamic potential and are therefore far more delicate probes than bulk observables. The first of these is the specific heat at constant volume, which measures how the energy density responds to changes in temperature. In the normalized form C_V/T^3, the model predicts a striking nonmonotonic pattern: the quantity is strongly suppressed at low temperatures, rises rapidly as the deconfinement region is approached, reaches a sharp maximum near T_c, dips to a local minimum, and then climbs again toward a constant. This behavior directly reflects the rapid temperature variation of the energy density across the transition, amplified by the derivative structure of the specific heat formula.

Independent lattice estimates of the specific heat, which were not used as input, show a qualitatively similar enhancement near T_c, and the model reproduces their overall trend and magnitude above the transition, though noticeable differences appear right at the peak. The authors attribute this to the intrinsic sensitivity of derivative quantities to interpolation procedures and finite-volume effects near a first-order transition. They also verified that the sharp peak is not a numerical artifact: refining the temperature step near T_c only sharpens the structure further, leaving the behavior away from the critical region unchanged. At high temperatures, C_V/T^3 approaches the massless Stefan-Boltzmann reference value of 32 pi squared over 15, approximately 21.06, although the authors caution that because their fitted mass ratio tends to a small nonzero constant, this conformal value should be read as a reference point rather than an exact asymptote of the model.

The second response function, and arguably the more novel one, is the isentropic bulk modulus K_S, which quantifies the mechanical stiffness of the medium under compression at constant entropy. It is defined as minus the volume times the pressure derivative with respect to volume at fixed entropy, and it equals the enthalpy density times the square of the speed of sound. This makes the bulk modulus a bridge between thermodynamics and mechanics: it governs how efficiently the plasma converts energy density into pressure, and thereby how sound waves and density fluctuations propagate through it. The calculations show that K_S/T^4 is strongly suppressed in the confined phase, where both pressure and enthalpy are small and the medium offers little resistance to squeezing, but rises sharply across the deconfinement region, signaling a substantial stiffening of the equation of state. At high temperatures it settles toward the conformal reference value of 32 pi squared over 135, roughly 2.34, while the inverse quantity, the isentropic compressibility, correspondingly falls toward about 0.427 in the same normalized units.

Supporting this picture, the study also tracks the gluon number density and the energy per thermally active gluonic mode. Although gluon number is not conserved, the scaled density n_g/T^3 serves as a measure of how many gluonic degrees of freedom are thermally accessible. It is nearly zero below and near T_c, then rises rapidly as deconfinement liberates the effective degrees of freedom, before flattening onto a high-temperature plateau consistent with the ultrarelativistic scaling n_g proportional to T cubed. The energy per mode, E_g divided by n_g times T_c, shows a sharp peak just above the transition: near T_c, a small number of thermally excited modes each carry a comparatively large share of energy, a signature of the large effective mass suppressing the thermal population. As the temperature climbs, the population becomes denser and more evenly energetic, and the ratio eventually grows linearly with temperature, exactly as dimensional scaling demands.

Taken together, these results paint a coherent portrait of gluon matter evolving from a confined, nonconformal regime into an approximately scale-invariant plasma. The authors emphasize that the specific heat and the isentropic bulk modulus are complementary: the former probes thermal response through energy fluctuations, the latter mechanical response through sound propagation and stiffness. Because both involve additional temperature derivatives, they constrain the effective mass profile far more stringently than bulk quantities alone could, and their nontrivial structures cannot be inferred from the magnitudes of pressure or energy density. The TDM framework, minimal as it is, thus offers a predictive baseline for derivative-sensitive observables in pure gauge matter. The natural next steps, the authors suggest, are extensions toward transport properties and toward full QCD with dynamical quarks, bringing the framework closer to the conditions of the real quark-gluon plasma that heavy-ion experiments continue to probe with ever-greater precision.

Subject of Research: Thermodynamic response functions of pure SU(3) gluon matter near the deconfinement transition, derived from a lattice-data-constrained effective gluon mass model

Article Title: Lattice-data-driven specific heat and isentropic bulk modulus of SU(3) gluon matter at finite temperature

Article References: Shen, W., Lu, Z.-Y., Waqas, M., Chen, X., Ma, Z.-J., & Peng, G.-X. (2026). Lattice-data-driven specific heat and isentropic bulk modulus of SU(3) gluon matter at finite temperature. The European Physical Journal C, 86(9), Article 1079. https://doi.org/10.1140/epjc/s10052-026-16286-8

Image Credits: AI Generated

DOI: 10.1140/epjc/s10052-026-16286-8

Keywords: lattice QCD, SU(3) gauge theory, deconfinement, quark-gluon plasma, specific heat, bulk modulus, equation of state, trace anomaly, effective gluon mass, thermodynamics, speed of sound, conformal symmetry

Now a team at China University of Petroleum (Beijing), working with Shandong Kegu Jiequan Technology Co., Ltd., has built an artificial intelligence framework that learns to read fuel molecules the way a chemist would, capturing the structural subtleties that determine octane behaviour. Writing in the journal ENG. Chem. Eng., the researchers describe an interpretable multimodal molecular representation model that predicts RON for both pure compounds and complex blends with high accuracy, and then turns the prediction problem on its head to enable inverse fuel design, the task of finding blend compositions that hit a target octane number before a single drop is mixed in the laboratory.

The core innovation lies in how the model represents each molecule. Rather than relying on a single descriptor, the framework integrates three complementary views of molecular structure. The first is a graph neural network embedding, in which atoms become nodes and chemical bonds become edges, allowing the network to learn the topological relationships that define a molecule’s skeleton. The second is a set of MACCS fingerprints, binary strings that encode the presence or absence of predefined substructure fragments, giving the model a chemist’s vocabulary of functional groups and ring systems. The third consists of molecular descriptors, numerical summaries of physicochemical properties, selected through a residual-guided strategy that identifies which descriptors add explanatory power beyond what the learned representations already capture.

For pure-component RON prediction, the trimodal model achieved a coefficient of determination, R², of 0.9373 and a mean absolute error of 4.04 octane units on the test set. Ablation experiments, in which individual information channels were systematically removed, revealed that the graph topology contributed the strongest signal, while the MACCS fingerprints and descriptors supplied complementary information that sharpened the predictions. The result is a model that does not merely memorise correlations but assembles a genuinely multi-perspective picture of what makes a molecule knock-resistant.

What sets the framework apart from many black-box models is its interpretability. The graph neural network employs an atom-level attention mechanism that visualises which local structural environments the model emphasises when making a prediction. The patterns it highlights are strikingly consistent with decades of empirical knowledge about structure-octane relationships. In alkanes, the model concentrated on branching sites, the structural features long known to boost octane quality. In cycloalkanes, it attended to substitution sites; in olefins, to the reactive double-bond regions; and in aromatics, to the connection points between side chains and the aromatic ring. For fuel chemists, this alignment between machine attention and chemical intuition is a crucial trust signal, indicating that the model has internalised genuine structure-property physics rather than exploiting dataset artefacts.

The real challenge, however, lies in mixtures. A fuel blend is not simply a collection of independent molecules; components interact in ways that shift the effective octane rating away from any weighted average. The researchers tackled this by transferring the trained pure-component encoder to the mixture problem. For a mixture containing multiple components, the embedding vector of each component was weighted according to its mole fraction and combined in the latent space, the abstract high-dimensional space where the neural network represents molecular structure. This composition-weighted latent representation was then fed into an XGBoost regressor, a gradient-boosted tree model, to produce the final RON prediction.

The performance gain over conventional methods was substantial. The first-order latent-space mixing model achieved an R² of 0.9736 and a mean absolute error of 1.46 on the mixture test set, dramatically outperforming the linear blending baseline, which managed only an R² of 0.7501 with a mean absolute error of 4.83. The comparison makes the failure of linear blending rules vivid: the AI approach cut prediction error by roughly seventy percent. Interestingly, when the team added second-order interaction terms designed to capture pairwise component interactions, the improvement was not significant. This suggests that the first-order model already captured the primary composition-dependent variation within the learned latent space, implying that the neural embeddings themselves encode much of the interaction chemistry that linear rules miss.

Prediction is only half the story. The researchers then demonstrated that the model could support fuel formulation design, the inverse problem of specifying a blend that meets a target octane constraint. Using a stochastic sampling search method, they identified feasible ternary blending compositions satisfying target RON requirements across four case studies. In every case, known formulations reported in the literature fell within the predicted feasible solution space, confirming that the computational search does not exclude chemically realistic answers and can genuinely guide formulation work. For refiners and fuel developers, this means candidate blends can be screened computationally, reserving laboratory time and materials for the most promising candidates rather than an exhaustive trial-and-error campaign.

The broader significance of the work is methodological. It demonstrates that molecular representations learned from pure components can be effectively transferred to mixture property prediction, a strategy that could spare researchers from assembling large, costly mixture datasets. It also establishes latent-space composition weighting as a promising general approach for mixture property modelling, one that respects the nonlinear reality of blending behaviour without requiring explicit knowledge of every possible interaction. Because the underlying encoder is trained on pure compounds, data that are far more abundant and cheaper to obtain, the framework lowers the barrier to accurate mixture modelling across the fuel industry.

The authors view the current model as a foundation rather than a finished product. The natural next step is multi-objective optimisation, in which octane number is balanced against additional fuel properties such as vapour pressure, density and viscosity, all of which constrain what a practical fuel formulation can look like. As transportation fuels evolve toward novel blends, oxygenated components and synthetic hydrocarbons, tools that can predict and design fuel properties computationally are likely to become indispensable. This study, published with the DOI 10.1007/s11705-026-2702-7, offers a concrete demonstration that interpretable machine learning can move fuel science from measurement toward design, turning the octane number from a laboratory bottleneck into a variable that engineers can dial in.

Subject of Research: Multimodal machine learning for research octane number prediction and inverse fuel blend design

Article Title: Multimodal AI model predicts octane number of fuel blends with high accuracy, enables inverse fuel design

Article References: Multimodal AI model predicts octane number of fuel blends with high accuracy, enables inverse fuel design. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: research octane number, multimodal AI, graph neural networks, fuel blending, inverse design, XGBoost, molecular descriptors, MACCS fingerprints, latent space mixing, fuel formulation, machine learning, chemical engineering

GPDs are the mathematical objects that go beyond the familiar parton distribution functions measured in inclusive deep inelastic scattering. While ordinary PDFs tell you the probability of finding a quark carrying a given fraction of the proton’s momentum, GPDs also encode what happens when the proton recoils, absorbing a momentum transfer that shifts it sideways. That extra information, accessed through processes like deeply virtual Compton scattering, where an electron knocks a virtual photon out of the proton and a real photon emerges, is what allows physicists to reconstruct genuinely three-dimensional portraits of nucleon structure, including the elusive orbital angular momentum carried by quarks and gluons.

The central difficulty is that experiments do not measure GPDs directly. What they measure are Compton form factors, convolutions of the GPDs with perturbatively calculable kernels that are sharply singular at particular points. Recovering the underlying GPDs from these convolutions is an inverse problem that is, in principle, intractable without additional input. The Virginia team’s strategy is to narrow the space of possible solutions by building the parametrization directly on the symmetries of quantum chromodynamics: crossing symmetry under the exchange of quark and antiquark momenta, polynomiality of the Mellin moments, and the area rules dictated by baryon number and momentum conservation.

The mathematical backbone of UVA2 is the reggeized spectator model, in which the proton is pictured as a struck parton bound to a remnant whose invariant mass is allowed to fluctuate. This yields compact analytic expressions for the two leading vector GPDs, H and E, for each quark flavor, including the valence u and d quarks, the antiquark sea, and the gluons. In a first for this framework, the authors provide fully analytic closed forms in all kinematic variables, eliminating the need for numerically expensive transverse momentum integrations and making the parametrization immediately usable in regression analyses, neural network training, and Monte Carlo event generators.

Constraining such a multidimensional function requires an enormous amount of input. In the forward limit, where the GPD H reduces to ordinary PDFs, the team fitted their parameters to reproduce the NNPDF21 parton distributions, checking the quality of the match with Kolmogorov-Smirnov tests. The t-dependence, describing how the distributions fall off with transverse momentum transfer, was then pinned down by fitting the flavor-separated Dirac and Pauli form factors extracted from lepton-nucleon scattering, together with the second Mellin moments recently computed in lattice QCD. The gluon sector was anchored to lattice determinations of the gluon form factors evaluated at a pion mass closer to the physical value than in previous versions.

All of these ingredients are defined at a common initial evolution scale of 0.58 square gigaelectronvolts, an improvement over earlier versions in which quarks and gluons started from inconsistent scales. From there, the distributions are evolved to higher energy scales using the leading-order off-forward DGLAP and ERBL evolution equations, which the authors solved with the Adams predictor-corrector method rather than the conventional Runge-Kutta approach. Because the right-hand side of the evolution equations involves convolution integrals that are notoriously expensive to evaluate, this choice of integrator delivers a substantial gain in computational speed, particularly in the low-momentum-fraction region that will dominate at future colliders.

The practical payoff comes in the form of predictions for the Compton form factors across a vast kinematic range, from the fixed-target regime of Jefferson Lab, where valence quarks dominate, all the way to the low Bjorken-x frontier of the upcoming Electron-Ion Collider, where sea quarks and gluons take over. The team’s calculations show that at EIC kinematics the Compton form factors are expected to be several orders of magnitude larger than at fixed-target facilities, and that the valence contribution is strongly suppressed in the collider setting. Crucially, because the flavor-singlet quark combination couples to gluons in the evolution equations, the gluon GPDs can in principle be extracted directly from DVCS data at the EIC, turning a machine designed to map gluon structure into a precision instrument for proton tomography.

The authors are careful about uncertainties. The error budget on their GPDs originates entirely from the fits to the t-dependence of the electromagnetic form factors, the lattice gluon form factors, and the second moments of the quark distributions, while the forward-limit parameters, obtained by matching to PDF parametrizations rather than raw data, carry no statistical errors and are instead validated through distribution-to-distribution comparisons. They flag this Hessian-based treatment as a first step, with maximum-likelihood and Markov-chain Monte Carlo analyses, along with neural network approaches, planned to properly capture correlations among the seven to eight parameters that define each flavor sector.

Everything is openly available. The UVA2 parametrization, including analytic forms at the initial scale and precomputed grids spanning momentum fractions from ten thousandths up to nearly one, momentum transfers up to four square gigaelectronvolts, and evolution scales up to a thousand square gigaelectronvolts, can be downloaded from a public GitHub repository in easily readable CSV formats. This openness matters, because GPD parametrizations are becoming shared infrastructure: they feed event generators, guide experimental analyses of exclusive processes, and provide the benchmark curves against which lattice QCD results and future DVCS measurements will be judged.

As the Electron-Ion Collider moves from blueprint to beamline, tools like UVA2 will determine how much physics can be squeezed out of the first data. By fusing elastic scattering, inclusive deep inelastic data, and lattice QCD into a single symmetry-respecting framework, the Virginia collaboration has delivered what amounts to a flexible, evolving atlas of the proton’s interior, one that promises to turn the coming decade of scattering experiments into a genuine three-dimensional census of the most abundant visible matter in the universe.

Subject of Research: Global parametrization of generalized parton distributions describing the three-dimensional quark and gluon structure of the proton

Article Title: Updated flexible global parametrization of generalized parton distributions from elastic and deep inelastic inclusive scattering data

Article References: Panjsheeri, Z., Adams, D. Q., Khawaja, A., Pandey, S., Tezgin, K., & Liuti, S. (2026). Updated flexible global parametrization of generalized parton distributions from elastic and deep inelastic inclusive scattering data. The European Physical Journal C, 86(9), Article 1078. https://doi.org/10.1140/epjc/s10052-026-15872-0

Image Credits: AI Generated

DOI: 10.1140/epjc/s10052-026-15872-0

Keywords: generalized parton distributions, proton structure, quantum chromodynamics, deeply virtual Compton scattering, lattice QCD, parton distribution functions, Electron-Ion Collider, QCD evolution, elastic form factors, Compton form factors, nucleon tomography, reggeized spectator model

The research, published in the Monthly Notices of the Royal Astronomical Society, was led by Anmol Aggarwal, a PhD student at UCL’s Mullard Space Science Laboratory, together with Dr Ralph Schoenrich, also based at the same laboratory. Their central insight is deceptively simple: when a star explodes, its material is not flung evenly into space. Different elements are ejected in different directions, with oxygen potentially streaming one way and sulphur another. New stars that condense from this debris may therefore inherit a lopsided sample of the supernova’s ingredients rather than its overall chemical blend.

Previous models, the researchers argue, assumed that the gas ejected by a supernova was thoroughly mixed before it formed new stars. Under that assumption, the peculiar chemical signatures observed in certain stars could not be produced by an ordinary supernova, and something far more energetic was required. Aggarwal and Schoenrich built mathematical models that instead accounted for the uneven, asymmetric way material is expelled, fitting how much material from each layer or region of an exploding star would be needed to match the composition of the observed stars.

Across the two studies, the team examined four stars that had previously been judged to have formed from material expelled by a hypernova. In the first study, they found that for three of these stars, formation from an ordinary supernova was statistically favoured over a hypernova. The unusual abundance patterns that had seemed to demand an ultra-powerful explosion could instead arise naturally if the stars formed from incomplete, patchy samples of supernova debris. As Aggarwal put it, stars with a very unusual mix of ingredients were most likely formed from ordinary supernovae, and all the evidence for hypernovae suddenly disappears.

To understand why this matters, it helps to consider how a supernova actually works. When a massive star exhausts its nuclear fuel, its core collapses under gravity, triggering an immense explosion that blasts the star’s outer layers into space. Just before this happens, the star is structured like an onion, with the heaviest elements concentrated at the centre and progressively lighter elements in the outer layers. A hypernova is theorised to occur when the same collapse happens in an even more massive, rapidly spinning star, producing an explosion of vastly greater energy.

These explosions seed nearby star-forming clouds with heavy elements, and the process gives astronomers a powerful investigative tool. By analysing the composition of a star, researchers can infer its family history, effectively reading the chemical record of the stellar explosions that contributed to the gas from which it formed. But this forensic method depends on assumptions about how well ejected material mixes with the surrounding interstellar gas before new stars are born. Schoenrich emphasised that, despite decades of work in this area, scientists still do not know how thoroughly supernova material gets mixed before forming new stars. The new research suggests that some mixing occurs, but that it is incomplete, a conclusion with consequences far beyond the handful of stars studied.

The second study focused on a single red giant in the Milky Way’s halo, the vast cloud of stars surrounding the galaxy’s disc. This star has an exceptionally peculiar chemical make-up, including an abundance of certain heavy elements such as silver and uranium. Elements this heavy can only be produced by neutron star mergers, the collisions of ultra-dense stellar remnants, or, in theory, by the hypernova of a highly magnetised massive star capable of forging both these heavy elements and the standard supernova elements no heavier than iron and nickel.

Earlier work had ruled out a neutron star merger as the origin of this star’s material, on the grounds that the star is extremely metal-poor, meaning it contains a very low proportion of heavier elements created in stellar explosions. Such metal-poor stars are understood to have formed from gas barely enriched by earlier generations of stars. The previous analysis relied on a model of the Milky Way in which the galaxy’s gas was enriched with heavy elements very quickly, implying that by the time the star was born, insufficient time had passed for neutron stars to form, spiral together, and collide. That reasoning left the hypernova as the only remaining explanation, and the star became one of the flagship cases for these ultra-powerful explosions.

Aggarwal and Schoenrich presented a different picture. They noted the star’s exceptional speed and the fact that it orbits the Milky Way in the opposite direction to most other stars, characteristics typical of stars captured from smaller galaxies. They argued that the star most likely originated in a small dwarf galaxy, where metal-poor stars can form much later, many millions of years after the Big Bang, before being pulled into the Milky Way. In tiny galaxies, star formation proceeds more slowly, and when stars do explode, most of the ejected material is blasted out into intergalactic space, keeping the galaxy’s gas metal-poor for far longer than in a large galaxy like our own. Using their mathematical model of asymmetric explosions, the researchers concluded that this star most likely formed from a neutron star merger combined with a single ordinary supernova, removing the need to invoke a hypernova at all.

The implications of the two studies extend well into the future of galactic chemistry modelling. If supernova ejecta are not well mixed, then models of how chemicals evolve in galaxies, and of how the interstellar medium behaves, need to incorporate this incompleteness explicitly. Chemical evolution models that treat each supernova as delivering a uniform, averaged blend of elements may misinterpret unusual abundance patterns as signs of exotic events, when they are in fact the natural consequence of patchy, directional ejecta. The UCL team’s work suggests that astronomers should be cautious before attributing strange stellar chemistries to the most extreme explosions imaginable, and that the humble supernova, viewed through a more realistic lens, may be capable of far more chemical variety than previously assumed. Whether genuine hypernovae exist at all remains an open question, but according to this new analysis, the evidence once marshalled in their favour has suddenly gone.

Subject of Research: The chemical signatures of hypernovae and supernovae in metal-poor stars

Article Title: Ultra-powerful star explosions might not have occurred after all

Article References: Ultra-powerful star explosions might not have occurred after all. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: hypernova, supernova, stellar nucleosynthesis, metal-poor stars, neutron star merger, Milky Way halo, dwarf galaxy, chemical evolution, interstellar medium, UCL, Monthly Notices of the Royal Astronomical Society, stellar explosions

The mechanism hinges on a subtle piece of quantum field theory. The researchers considered a model in which a Dirac fermion, the class of matter particles that includes electrons and quarks, couples directly to the oscillating inflaton through a pseudoscalar Yukawa interaction. In plain terms, the coupling involves the gamma-five matrix, an object in the Dirac equation that distinguishes between the two possible spin orientations of a particle relative to its direction of motion. Because the inflaton field swings back and forth like a cosmic pendulum, the effective mass that the fermion experiences, which the authors call the pseudo-mass, repeatedly changes sign. Every time it crosses zero, the quantum vacuum becomes unstable and pairs of fermions are wrenched into existence, and crucially, the two helicity states are not created in equal numbers.

To make this statement precise, the team turned to the WKB approximation, a semiclassical technique borrowed from quantum mechanics in which wave functions are written as exponentials with slowly varying amplitude and phase. By matching the solutions on either side of each zero crossing of the pseudo-mass, they derived analytical expressions for the Bogoliubov coefficients, the mathematical objects that encode how many particles are produced in each quantum mode. The calculation, which involves parabolic cylinder functions, remains valid for an arbitrary number of successive production events, a significant advance over earlier treatments that could only handle a single pass of the oscillating field.

The key result is that the pseudoscalar coupling injects an imaginary contribution into the first-order adiabatic phase, denoted by the authors as the complex phase of the fermion mode. This imaginary piece depends on the helicity state of the particle, and it is solely responsible for breaking the symmetry between left- and right-handed fermions. When the coupling is switched off, the phase vanishes and the familiar helicity-symmetric result of standard fermionic preheating is recovered, with occupation numbers falling off as a clean Gaussian in momentum space. With the coupling present, that Gaussian is warped, and the two helicities peel apart in a way that can be computed exactly.

The researchers also identified a sharp boundary condition on where the asymmetry can live. Helical asymmetry is generated only for comoving momenta much smaller than a characteristic wavelength set by the fermion mass and the expansion rate of the Universe. Once a mode’s wavelength enters the corresponding horizon scale, the asymmetry is dramatically suppressed. This means the imbalance is fundamentally a large-scale phenomenon, imprinted on the longest wavelengths available in the early cosmos, precisely the scales that could matter for subsequent cosmological evolution.

Perhaps the most striking finding concerns coherence. In an expanding Universe, the authors show that the combined effects of parametric resonance and Pauli blocking, the quantum-mechanical exclusion principle that caps fermion occupation at one particle per mode, produce coherent enhancement in certain frequency bands and coherent suppression in others. Unlike bosons, whose occupation numbers grow exponentially through Bose enhancement, fermions can only be nudged up or down within strict limits. The real part of the complex WKB phase governs this coherent superposition, and the numerical simulations reveal that it significantly boosts the number density of each helicity state after roughly eight oscillations of the inflaton, a periodicity traced back to a numerical factor in the imaginary part of the phase.

The team validated their analytics with numerical simulations in both a static universe and an expanding one. In the static case, the helical asymmetry appears as isolated narrow resonance bands in momentum space, reminiscent of the instability bands familiar from bosonic preheating. When cosmic expansion is included, these bands wash out, but the deviation from Gaussian helicity distributions persists and grows with each successive production event. The authors also found that heavier fermions concentrate their production on smaller physical scales, and that massless fermions, consistent with earlier results on gravitational particle production, escape the mechanism entirely.

What elevates this work beyond a technical exercise is its potential connection to one of the deepest mysteries in cosmology: why the Universe contains vastly more matter than antimatter. Helicity-asymmetric fermion production is a natural ingredient in leptogenesis scenarios, in which an early asymmetry in neutrino-like particles is eventually converted into the baryon asymmetry we observe today. Because the mechanism identified by the authors does not depend on the precise value of the inflaton mass, it applies equally to low-scale inflationary models such as small-field and hybrid inflation, widening the range of theories in which such an asymmetry could have been seeded.

The framework is also extendable in directions that touch other observational frontiers. The authors note that the same WKB machinery can accommodate momentum-dependent pseudoscalar couplings, quantum chromodynamics effects, and electroweak interactions, and that helical fermion production may be linked to the generation of primordial magnetic fields, chiral gravitational waves, and even dark matter production in the early Universe. Each of these connections offers a potential observational handle on a process that unfolded when the cosmos was a fraction of a second old.

For now, the result remains theoretical, resting on analytical mathematics and numerical simulation rather than direct measurement. But it sharpens a growing realization among cosmologists that the transition from inflation to the hot Big Bang was not a passive fade but an active, symmetry-breaking crucible. If the inflaton really did couple to fermions through a pseudoscalar channel, the newborn Universe may have emerged from preheating with a slight but decisive twist, a handedness written into its matter content that echoes, in principle, all the way to the galaxies we see today.

Subject of Research: Helical asymmetry in fermionic preheating induced by a pseudoscalar Yukawa coupling between the inflaton and Dirac fermions after inflation

Article Title: Pseudoscalar Yukawa coupling induced helical asymmetry in fermionic preheating

Article References: Fu, K., Liu, L.-S., Wang, Y.-F., Gu, X.-Y., & Li, X.-B. (2026). Pseudoscalar Yukawa coupling induced helical asymmetry in fermionic preheating. The European Physical Journal C, 86(9), Article 1083. https://doi.org/10.1140/epjc/s10052-026-16298-4

Image Credits: AI Generated

DOI: 10.1140/epjc/s10052-026-16298-4

Keywords: preheating, cosmic inflation, fermion production, helicity asymmetry, pseudoscalar Yukawa coupling, inflaton, WKB approximation, Bogoliubov coefficients, leptogenesis, baryogenesis, early universe, quantum field theory

An international team led by researchers at Shandong University examined Juno’s magnetic field and energetic particle measurements from multiple events in the Jovian magnetodisk. Their study, published in Science China Earth Sciences with Ruilong Guo of Shandong University as first and corresponding author, reveals a current sheet that behaves in a way planetary scientists had not previously documented. Under quiet conditions, Juno, orbiting close to the equatorial plane of the magnetodisk, should cross the current sheet twice during each rotation of the planet. During the reconnection events analyzed by the team, however, the spacecraft crossed the sheet again and again — in one striking case four times within only ten minutes — and nearly every crossing carried the unmistakable magnetic signature of reconnection, accompanied by bursts of energized electrons and ions.

Magnetic reconnection is one of the most fundamental processes in plasma physics. Wherever magnetic field lines of opposite orientation are pressed together, they can break and rejoin in new configurations, converting stored magnetic energy into heat, bulk plasma flow, and the acceleration of charged particles. On Earth, reconnection in the magnetotail is famously linked to geomagnetic substorms and the dazzling auroras that follow. At Jupiter, the magnetodisk stores rotational energy drawn from the planet’s spin and plasma mass supplied by Io’s volcanoes, and reconnection is thought to be a principal mechanism by which that stored energy is released. The new results show that this release does not happen as a single, orderly event but through numerous small reconnection sites distributed widely across the disk.

The crucial insight came from a careful analysis of the orientation of the current sheet itself. If the sheet were merely flapping up and down like a flag in the wind, or if a single kink wave were traveling outward from one reconnection site, the crossings recorded by Juno would follow a predictable pattern with a fixed period. Instead, the team found that the sheet undulates in a kink-like, surface-wave manner, with individual ripples persisting from several minutes to more than an hour, and with no fixed periodicity tying the motion together. The researchers concluded that numerous small reconnection sites, discretely distributed across roughly one hundred degrees of longitude, continually break the disk’s magnetic field lines and push the current sheet away from its equilibrium position, producing a rotating, crumpled structure rather than a coherent traveling wave.

The contrast with Earth’s magnetotail is instructive and helps explain why the finding matters. In Earth’s magnetosphere, flapping waves are generated locally: a reconnection site launches a kink wave that propagates away from it, and the motion of the current sheet can be traced back to a specific disturbance. At Jupiter, reconnection signatures appeared at almost every crossing Juno made during the active intervals, and the motion showed no fixed period. Both observations rule out a simple traveling wave. Instead, the entire rippled current sheet is carried around with the planet’s rapid rotation, like a crumpled tablecloth spinning on a turntable, so that any spacecraft sampling the equatorial region encounters a succession of ripples as the deformed sheet sweeps past.

The scale of the Jovian system makes this dynamics extraordinary. Jupiter’s magnetodisk extends outward for millions of kilometers, dwarfing the entire Earth-Moon system many times over, and it is populated by plasma originating from Io, the most volcanically active body in the solar system. Io injects roughly a ton of material per second into Jupiter’s magnetosphere, where it is ionized and flung into corotation with the planet by the powerful magnetic field. This centrifugally driven plasma stretches the field lines into the disk-like configuration that gives the magnetodisk its name. Understanding how that disk deforms, tears, and reconnects is therefore central to understanding how mass, energy, and momentum circulate through the largest magnetosphere in the solar system.

The rippling current sheet identified by the team has consequences that reach far beyond the geometry of the disk itself. The researchers point out that the rippling may affect how volcanic particles from Io are transported and accelerated, filling the magnetodisk with energetic particles that can be injected toward the inner magnetosphere or channeled along field lines into Jupiter’s polar auroras. Jupiter’s auroras are the most powerful in the solar system, radiating hundreds of gigawatts of energy, and their intense emissions depend on the transfer of particles and currents between the magnetodisk and the planet’s upper atmosphere. A current sheet that is crumpled by reconnection complicates the magnetic linkage between the ionosphere and the magnetodisk, meaning that models of auroral power and particle transport may need to account for a far more structured and dynamic environment than previously assumed.

Methodologically, the study demonstrates the power of combining magnetic field measurements with energetic particle observations from a single well-placed spacecraft. Juno, which entered orbit around Jupiter in 2016 on a polar trajectory, repeatedly samples the equatorial regions of the magnetodisk during its extended mission. By tracking the orientation of the current sheet at each crossing and correlating it with the reconnection signatures and particle bursts recorded simultaneously, the team could reconstruct the three-dimensional shape of the sheet over time. The repeated crossings within minutes — four in ten minutes in one case — provided the temporal resolution needed to distinguish a rippling, rotating sheet from a smoothly rocking one, a distinction that would have been impossible to make from sparser data.

The finding also reframes how scientists think about reconnection in rapidly rotating magnetospheres generally. Giant, rotation-dominated magnetospheres are not unique to Jupiter; Saturn possesses a similar magnetodisk, and the physics explored here may apply across a family of planetary systems in which centrifugal forces, rather than the solar wind, dominate the internal dynamics. If small-scale reconnection sites are discretely distributed across a hundred degrees of longitude at Jupiter, the same process could crumple current sheets elsewhere in the solar system and beyond, including in astrophysical disks where reconnection governs how magnetic energy is dissipated. The Jovian magnetodisk thus becomes a natural laboratory for plasma processes that cannot be reproduced in terrestrial facilities.

For now, the image that emerges is a dramatic revision of an old picture. The magnetodisk of Jupiter is not a quiet, smoothly rotating sheet but a highly structured, dynamic environment, continually wrinkled by reconnection and spinning with the planet like a rippled fabric in the dark. The work, supported by the National Natural Science Foundation of China and the Shandong Provincial Natural Science Foundation, was published in Science China Earth Sciences as volume 69, issue 10, pages 3619 to 3625, with the article by Guo, Zhao, Xiao, Grodent, Yao, Bonfond, and Shi titled Rippling current sheet generated by magnetodisk reconnection on Jupiter. As Juno continues its mission and future missions to the giant planets are planned, the rippling current sheet stands as a reminder that even the most familiar structures in planetary magnetospheres can hide unexpected, wave-shaped complexity when examined closely enough.

Subject of Research: Magnetic reconnection–driven rippling of Jupiter's magnetodisk current sheet observed by the Juno spacecraft

Article Title: Juno spacecraft reveals a rippling current sheet in Jupiter's magnetodisk generated by magnetic reconnection

Article References: Juno spacecraft reveals a rippling current sheet in Jupiter's magnetodisk generated by magnetic reconnection. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Juno, Jupiter, magnetodisk, current sheet, magnetic reconnection, magnetosphere, Io, plasma physics, auroras, space physics, energetic particles, Science China Earth Sciences

Pa 30 is no ordinary stellar corpse. The nebula is the likely remnant of a supernova that blazed in the night sky in the year 1181, an event independently documented by astronomers in Japan, China, and the Arabic-speaking world. That historical record places it among just five supernovae recorded before the invention of the telescope whose remnants had long remained unidentified, and it makes Pa 30 one of the very few explosive objects in the sky that humans watched being born and can now study in forensic detail. Adding to its singular character is a surviving star at the nebula’s core, often described as a ‘zombie star,’ which endured an explosion that should have destroyed it. This kind of incomplete stellar detonation defines a rare class of events known as Type Iax supernovae, and Pa 30 is the only place in the Milky Way where astronomers can resolve both the expanding debris and the surviving stellar remnant at its heart.

The road to this discovery began in 2013, when a citizen scientist first identified the nebula that would later be named Pa 30. Subsequent work connected the object to the historical accounts of the 1181 event, transforming an anonymous smudge of glowing gas into a confirmed relic of a documented stellar catastrophe. Researchers have proposed that the explosion occurred when two white dwarfs—extremely dense, Earth-sized cores of dead stars that have exhausted their nuclear fuel and shed their outer layers—collided with one another. In most such mergers, the outcome is a total destruction of both stars. In the scenario that produced Pa 30, however, the explosion was incomplete, leaving behind the zombie star that still glows at the center of the nebula today, surrounded by the dandelion-shaped spray of its own shredded companion material.

The new observations were obtained with the Gemini Multi-Object Spectrograph (GMOS) mounted on NOIRLab’s Gemini North telescope, one half of the International Gemini Observatory, whose twin instrument, Gemini South, sits in Chile. Gemini North occupies Mauna Kea on the island of Hawai’i at an elevation of more than 4,200 meters, one of the premier astronomical observation sites on the planet, where the thin, dry, stable air above the summit allows telescopes to capture extraordinarily sharp images. It is partly funded by the U.S. National Science Foundation and run by NSF NOIRLab. The combination of the telescope’s optical capabilities and its exceptional location enabled the team to achieve the best-resolution images and analysis of Pa 30 to date, resolving structures that had blurred together in every previous observation.

The technical key to the new view lies in the way the team selected the light they studied. The astronomers analyzed emission lines from ionized sulfur (S II) in the red part of the visible spectrum, along with emission from doubly ionized oxygen (O III), which appears in blue-green tones. These spectral fingerprints trace gas at specific temperatures and ionization states within the ejecta, allowing the observers to isolate the fine filamentary structure of the remnant. The sulfur observations proved especially revealing: they disclosed roughly ten times as many filamentary features as earlier images had been able to resolve. Where previous data showed broad, smooth streaks radiating from the center like the spokes of a cosmic firework, the new data reveal that each streak is in fact composed of tight chains of individual gas knots.

The scale and regularity of those knots surprised the team. Each one is wide enough to fit the planetary region of our solar system about ten times, with room to spare—meaning a single knot comfortably exceeds the orbit of Neptune, the most distant planet, by an enormous margin. Yet despite their colossal size, the knots appear strikingly uniform in their dimensions, a regularity that demands explanation. “The planetary region of our solar system could fit in each knot about ten times with room to spare,” Caiazzo says. “The knots are quite strikingly uniform. We are excited to try to model them.” Understanding how such evenly sized clumps form within an expanding shell of stellar debris could shed light on the fluid instabilities and physical processes that shape supernova ejecta in their earliest phases of expansion.

Equally telling is what the observations revealed about the zombie star itself. In many supernova explosions, the blast is asymmetric, and any surviving star receives a gravitational ‘kick’ that sends it flying away from the center of the debris cloud it left behind. Momentum, however, must be conserved: a perfectly symmetric explosion produces perfectly symmetric ejecta and imparts no substantial kick to the remnant. When the team measured the position of the surviving star within Pa 30, they found it sitting almost perfectly at the nebula’s center. “Explosions conserve momentum. If the explosion itself was perfectly symmetric, the ejecta should also be symmetric, and the surviving star should not receive a substantial kick,” Caiazzo explains. “We were able to measure a precise upper limit of the remnant star’s transverse kick speed, showing that it was surprisingly small. We practically don’t see the star moving away at all.” That near-perfect central placement is a powerful clue that the 1181 explosion was remarkably symmetric, constraining the geometry of the white dwarf merger that produced it.

Pa 30’s proximity to Earth is what makes this level of scrutiny possible at all. At about 7,500 light-years away, it is relatively close by astronomical standards—far nearer than the center of the Milky Way, which lies some 26,000 light-years distant. While astronomers have identified a handful of similar objects in other galaxies, Pa 30 remains the only one in which telescopes can resolve the surviving remnant star at the core. “We can see this much detail because of Pa 30’s proximity to Earth,” Caiazzo says. “This proximity makes Pa 30 uniquely valuable for study.” The object thus serves as a natural laboratory for a class of explosions that, in more distant galaxies, can only be detected as single points of light without any spatial structure.

Rarity, the team emphasizes, does not mean uniqueness. Type Iax supernovae are uncommon, but Cunningham argues that the Milky Way could harbor other remnants of the same class that simply have not been found. Reliable historical records of stellar explosions extend back only about a thousand years, a brief window compared with the galaxy’s age, and many ancient remnants may be too faint or too diffuse to have caught attention. “Reliable historical records of stellar explosions extend back only about a thousand years. For all we know, there might well be similar remnants still lurking in the dark in our own galaxy,” Cunningham says. “Today, we are lucky to study an intriguing object we know was observed by astronomers who made three independent historical records of the event centuries before the invention of the telescope.” Now an assistant professor at the University of Warwick in the UK, he adds that more similar objects will likely be identified as new telescopes continue to inspect the depths of the night sky.

The new Pa 30 observations arrive at a moment when astronomy is drowning in data, and the team sees its work as a template for future searches. “Astronomy has entered the big data era,” Cunningham says. “Our findings will help us screen through the enormous datasets.” The distinctive signature of Pa 30—its knot-like filaments, its symmetric ejecta, its central zombie star—gives astronomers a checklist of features to look for in survey data covering the Milky Way and nearby galaxies. “In general, the farther into space we look, the more difficult it is to detect faint signals and interpret them,” Caiazzo says. “While we can see Type Iax supernovae in distant galaxies as point sources of light, resolving the remnants of such explosions is only possible in our own galaxy and in very few nearby ones. Eventually, we plan to use Pa 30’s distinctive properties to search the Milky Way and nearby galaxies for similar objects.” Nearly nine centuries after observers on three continents recorded a sudden ‘guest star’ in the sky, its remnant is finally telling its story in full—and it may not be the only one waiting to be found.

Subject of Research: High-resolution imaging of the Type Iax supernova remnant Pa 30, the relic of the historical supernova of 1181

Article Title: International team of astronomers detect striking new details in unique supernova remnant

Article References: International team of astronomers detect striking new details in unique supernova remnant. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Pa 30, supernova remnant, Type Iax supernova, zombie star, white dwarf merger, Gemini North telescope, supernova of 1181, ionized sulfur emission, Milky Way, stellar ejecta, NSF NOIRLab, astronomy

The team centered their investigation on the Daya Bay Reactor Neutrino Experiment, whose gadolinium-doped liquid scintillator detectors sit under 250 meters-water-equivalent of rock in Experimental Hall 1. Daya Bay had previously performed a precision measurement of muon-induced neutron production with relative systematic uncertainties below 10 percent, making it an ideal yardstick. Earlier comparisons had exposed a troubling gap: default simulations overpredicted the measured neutron yield by roughly 20 percent, while at KamLAND the discrepancy reached 30 percent or more. For future experiments like the Jiangmen Underground Neutrino Observatory, JUNO, which will need exquisitely accurate background models, closing that gap is not a luxury but a necessity.

To dissect the problem, the researchers built a full GEANT4-based simulation of the Daya Bay detector geometry, complete with the surrounding water Cherenkov veto, and tested three representative hadronic physics lists: FTFP_BERT_HP, QGSP_BERT_HP, and QGSP_BIC_HP. These lists differ in two crucial ways. At high energies, hadronic interactions are described by string models, either the Fritiof model or the quark-gluon string model, while at low and intermediate energies the intranuclear cascade is handled by either the Bertini or the binary cascade model. All three lists share the high-precision neutron package, which uses evaluated data-driven cross sections below 20 MeV to describe neutron moderation and capture with high fidelity.

The muon flux itself was modeled with care. Starting from a modified version of Gaisser’s sea-level formula adapted for the Daya Bay site, the team propagated muons through a digitized mountain profile using the MUSIC code, reproducing a simulated muon rate of 1.27 per second per square meter and an average muon energy of 63.9 GeV underground. Both values agree well with the measured flux of 1.21 plus or minus 0.12 per second per square meter and with the angular distributions validated by Daya Bay’s resistive plate chamber telescope system. Roughly 61 percent of muons depositing at least 20 MeV in the scintillator were found to traverse the gadolinium-loaded target, with an average path length of 206.3 centimeters, closely matching the 204.1 centimeters from Daya Bay’s own simulations.

The heart of the study lies in its innovative hybrid correction scheme. The TALYS nuclear reaction code, version 1.8, was used to compute more accurate inelastic cross sections for neutrons, protons, and gamma rays striking carbon-12 below 200 MeV, the energy range where most secondary cascade particles reside. Because a single muon-induced cascade contains many individual neutron-producing vertices, the authors implemented a vertex-level reweighting: each neutron-producing interaction was rescaled by the ratio of the TALYS to the GEANT4 exclusive cross section for that channel and projectile energy. Crucially, the method preserves GEANT4’s final-state kinematics rather than substituting TALYS event-by-event, avoiding violations of momentum balance with the nuclear remnant.

The cross-section comparison itself was revealing. Inclusive inelastic cross sections from the three GEANT4 lists were nearly identical for each projectile type, but TALYS predicted values about 20 percent higher for neutrons and 30 percent higher for protons, while its gamma-ray cross-section peak sat at lower energies with a magnitude roughly 50 percent below GEANT4’s. In exclusive neutron-multiplying channels, the choice of intranuclear cascade proved far more influential than the high-energy string model. The BIC-based list shifted production weight away from neutron-induced reactions, about 32.8 percent versus 37.9 percent for the BERT lists, toward charged pion and proton channels, and favored final states with higher neutron multiplicity.

When the corrected simulations were benchmarked against the Daya Bay measurement of the neutron yield, the improvement was striking. The original GEANT4 lists overestimated the measured value of 10.26 times ten to the minus five per muon per gram per square centimeter by roughly 13 to 20 percent. After TALYS-based reweighting, the deviation for the BERT-based model shrank from about 20 percent to approximately 6 percent, while for the BIC-based model it collapsed from roughly 13 percent to the sub-percent level, about 0.3 percent. The correction systematically reduced yields by 12 to 14 percent, demonstrating that the total neutron yield is acutely sensitive to inelastic cross sections in the 50 to 200 MeV window, where TALYS values run systematically lower than GEANT4’s.

Yet the story is not one of unqualified triumph. The team also compared the tagged neutron multiplicity, the number of neutrons captured on gadolinium following each muon, against Daya Bay data. Here a clear tension persists across every model tested: simulations systematically underproduce single-neutron events while overproducing multi-neutron events. The deficit at multiplicity one, the dominant category, had already been flagged in Daya Bay’s earlier comparison using GEANT4 version 9.2, and the TALYS correction actually worsens it, since the fraction of gamma-carbon reactions contributing to single-neutron events drops in the corrected simulation. Quantitative chi-squared tests confirm that the BIC-based model agrees better with data than the BERT-based one across all multiplicities, but the single-neutron deficit remains the largest residual discrepancy.

The authors trace this deficit to the final-state modeling of highly excited carbon-12 nuclei, pointing to GEANT4’s Fermi break-up and evaporation models as the components most in need of refinement. Their analysis shows that single-tagged-neutron events are predominantly induced by gamma-carbon and neutron-carbon reactions, whereas multi-neutron events arise mainly from secondary neutron interactions. This diagnosis suggests a concrete two-step strategy for future work: first, apply TALYS-based cross-section adjustments to nail down the overall normalization of the cosmogenic neutron yield for background subtraction; second, use the residual multiplicity discrepancies, especially the single-neutron deficit, as quantitative constraints for tuning intranuclear cascade parameters and channel-specific reweighting.

The implications reach well beyond liquid scintillator. The authors emphasize that the same framework applies to water Cherenkov detectors like Hyper-Kamiokande and liquid-argon time-projection chambers like DUNE, where cosmogenic neutrons pose equally serious background threats. The methodology may even transfer to atmospheric neutrino neutral-current interactions, whose final-state particle energies overlap the range probed here. By establishing a reproducible, data-driven benchmark and a clear refinement roadmap, the study transforms cosmogenic neutron modeling from a source of nagging uncertainty into a tractable engineering problem, one that the next generation of rare-event searches will be better equipped to solve.

Subject of Research: Cosmogenic neutron production and hadronic simulation modeling in large underground liquid scintillator detectors

Article Title: Comprehensive study of cosmogenic neutron production in large liquid scintillator detectors

Article References: Jiang, Y., Cheng, J., Lu, H., & Wang, Y. (2026). Comprehensive study of cosmogenic neutron production in large liquid scintillator detectors. The European Physical Journal C, 86(9), Article 1082. https://doi.org/10.1140/epjc/s10052-026-16173-2

Image Credits: AI Generated

DOI: 10.1140/epjc/s10052-026-16173-2

Keywords: cosmogenic neutrons, liquid scintillator, Daya Bay, GEANT4, TALYS, hadronic physics lists, neutron yield, neutron multiplicity, cosmic-ray muons, underground experiments, JUNO, background modeling

The research, conducted by Farshad Malekpour, MASc 2026, and Mehdi Hojjati, a professor in Concordia’s Department of Mechanical, Industrial and Aerospace Engineering, was published in the journal Composites Part B: Engineering. The team set out to answer a question that sits at the heart of lunar in-situ resource utilization, or ISRU: can a space-grade polymer be recycled and blended with simulated moon soil to produce printed parts that actually perform under load? Their answer, demonstrated through a series of carefully controlled experiments, was yes, with important caveats about the trade-offs involved.

The material at the center of the study is poly(ether ketone ketone), commonly abbreviated PEKK, a high-performance thermoplastic prized in aerospace applications for its strength, thermal stability and resistance to harsh environments. Crucially, the PEKK used in the demonstrations was not virgin material. It had been recycled from a previously printed sacrificial structure, proving that this demanding engineering polymer can be processed and reused while retaining its thermal and mechanical properties. The researchers recycled the material three times and observed no significant degradation or loss of structural and mechanical performance, a result with major implications for missions where every gram of feedstock must be conserved and nothing can be wasted.

The recycling process itself was methodical. Collected PEKK scrap was shredded, milled into a powder, heat dried and then mixed with a commercially available lunar regolith simulant, a terrestrial stand-in designed to mimic the mineralogy and particle characteristics of actual moon soil. The resulting composite was extruded into filament and fed into a 3D printer, where it was formed into standard test shapes and into a sacrificial structure: a strong, lightweight, sponge-like configuration engineered to deform and absorb energy under load and then recover its original shape without damage. Sacrificial structures of this kind are not meant to be permanent load-bearing elements. Instead, they are designed to take the hit, so to speak, absorbing stresses the way the landing mechanism of a lunar module would have to cushion the shock of touchdown on the moon’s surface.

With the printed parts in hand, the researchers subjected them to a battery of mechanical and thermal tests. Samples were stretched, bent and compressed to measure how the composite responded to the kinds of stresses a real lunar component would encounter. Some specimens were also heat-treated to see how this additional processing step affected performance, an important consideration because any manufacturing process on the moon will have limited access to post-processing equipment. The team even printed a functional wrench from the same composite material, a small but symbolic demonstration that the blend can produce recognizable, practical tools rather than only test coupons.

The results revealed several genuine advantages of adding regolith to the polymer. The recycled composite showed strong thermal stability, and microscopic examination found the regolith particles evenly distributed throughout the plastic matrix, indicating a well-mixed, homogeneous material. Perhaps most significantly, the addition of regolith simulant lowered the temperature at which PEKK crystallized during heating, making the heat treatment process more efficient. On the moon, where energy is scarce and every watt counts, a material that crystallizes at a lower temperature translates directly into reduced power demands and faster processing cycles. The regolith also helped reduce shrinkage and warping during heat treatment, an advantage the researchers describe as especially important for manufacturing in an environment with little to no access to equipment for further processing. A warped part on Earth is a nuisance; a warped part on the moon may be an unusable one.

The composite was not without its weaknesses. The printed material exhibited more internal porosity than unmixed PEKK, and that porosity made the composite more brittle. Brittleness is a meaningful concern for components expected to absorb impact energy, since a material that cracks rather than deforms fails in a less forgiving way. The researchers note, however, that the recycled plastic itself was not degraded, meaning the brittleness stems from the regolith particles and the voids they introduce rather than from any breakdown of the polymer through repeated recycling. This distinction matters for mission design: it suggests engineers can plan around the composite’s limitations by reserving it for applications where energy absorption and dimensional stability matter more than maximum toughness, while keeping pure recycled polymer for parts that demand it.

What makes the study notable in the broader landscape of space manufacturing research is its circularity. Many proposed ISRU techniques envision using lunar soil as a bulk construction material, for example in sintered bricks or concrete-like structures, but few have demonstrated a closed loop in which a high-performance, space-grade polymer is recycled multiple times and combined with regolith in a single workflow. Hojjati says the study is among the first to demonstrate such a closed-loop approach, combining the recycling of PEKK with lunar regolith in this way. In a circular system, a sacrificial structure printed for one mission phase could be shredded, reprocessed and printed again for the next, with regolith extending the feedstock each cycle. The economics are compelling: every kilogram of locally sourced or recycled material is a kilogram that does not need to be launched from Earth at a cost that can reach seven figures.

The implications extend beyond the moon. Thermoplastic recycling of this kind could apply to any long-duration space mission where manufacturing scrap accumulates, from orbital fabrication facilities to Mars habitats, and the principle of reinforcing recycled polymers with locally gathered mineral fillers is adaptable to planetary surfaces beyond the lunar environment. The researchers are careful to frame the technology as still very new, and the study published on 25 July 2026 represents an early experimental demonstration rather than a flight-ready process. Real lunar regolith differs from simulants in ways that could affect printing behavior, and the porosity and brittleness observed in the composite will need to be addressed before such parts could be trusted in critical applications.

Even so, the work offers a promising pathway toward efficient use of scarce materials in space exploration, the researchers note. As space agencies and commercial partners move from brief sortie missions toward sustained lunar presence, the ability to print, use, recycle and reprint components from a blend of moon dust and recovered engineering polymer could transform the logistics of living off-world. The Concordia study provides a concrete, tested demonstration that the loop can close: a printed sacrificial structure becomes powder, the powder becomes filament, the filament becomes a wrench, and the moon itself supplies the filler. For a species hoping to stay on the lunar surface rather than merely visit, that kind of resourcefulness may prove to be the difference between an outpost that endures and one that never gets built.

Subject of Research: Recycled PEKK thermoplastic and lunar regolith composites for 3D-printed lunar infrastructure

Article Title: Simulated moon soil and recyclable thermoplastics could help build future space infrastructure, study shows

Article References: Simulated moon soil and recyclable thermoplastics could help build future space infrastructure, study shows. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: lunar regolith, 3D printing, PEKK, thermoplastics, in-situ resource utilization, recycling, space manufacturing, Concordia University, additive manufacturing, sacrificial structures, lunar habitat, composites