The original description of Archaeocerus uenoi in 2019 was based on a single male specimen, the holotype, preserved in Cretaceous amber dating to roughly the Albian/Cenomanian boundary. Now, a second specimen has come to light, deposited in the private collection of Michel Perreau, and it is a female. This discovery allowed the researchers to describe the female of the species for the first time, along with the internal genital morphology of both sexes, using a technique that amounts to virtual dissection without ever touching the fragile fossil.

The imaging was performed at the European Synchrotron Radiation Facility in Grenoble, France, using two complementary methods. Propagation phase contrast micro-tomography on beamline BM05 delivered voxel resolutions of 0.73 micrometers for the female and an astonishing 0.34 micrometers for the male, acquiring 6000 projections over a full 360-degree rotation at an energy of 29 kiloelectronvolts. For the finest structures, the team turned to beamline ID16B, where X-ray holotomography pushed the resolution down to 60 nanometers, using four tomographic scans at slightly different propagation distances and a contrast transfer function algorithm for phase retrieval. The result is a dataset sharp enough to resolve individual setae and the delicate internal sclerotized structures of the male genitalia.

That resolution matters enormously for a beetle measuring just 1.2 millimeters long as a male and 1.5 millimeters as a female. The scans revealed a body that is elongate, flattened, and dark brown, with antennae, legs, and mouthparts in lighter brown. The antennae carry 11 antennomeres, with the eighth extremely flat and significantly narrower than its neighbors, a distinctive feature. The pronotum is transverse, about 1.4 times as wide as long, with a shiny surface bearing tiny punctures and fine microreticulation. The elytra are parallel in their basal two-thirds before rounding at the apex, with a single parasutural longitudinal stria and punctures aligned in oblique strigae associated with short setae.

Perhaps the most surprising external finding is that Archaeocerus uenoi possesses developed eyes and flight wings, probably functional ones, with nervation present near the base and ciliate margins. This sets it apart from every living member of the subfamily, all of which are anophthalmic and apterous, having abandoned both sight and flight as they adapted to life underground. Most extant Catopocerinae are endogean, living within the soil, while one species, Glacicavicola bathyscioides, is troglobitic, inhabiting lava caves in Idaho and Wyoming with a slender elongated body shape reminiscent of European cave beetles. The fossil, by contrast, retains eyes and wings while otherwise resembling its soil-dwelling relatives, and its size matches the smallest species of the North American genus Pinodytes.

The virtual dissection also exposed the beetle’s leg architecture in unprecedented detail. The tarsal formula is 5-4-4 in both sexes, another departure from the 5-5-5 formula of most extant genera. Male protarsi are imperceptibly dilated and equipped with tenent setae of two kinds on their ventral side: some very long and straight, others shorter, curved, and slightly dilated at the apex. Protibiae are thickened in their basal half and bear a dense bunch of setae on the inner margin of the apical half in both sexes. The outer side of the protibiae is spineless, while the meso- and metatibiae carry strong spines on their outer edges, features now documented in stereo-anaglyph images viewable with simple red/cyan glasses.

The crown jewel of the redescription is the aedeagus, the male genital structure, which the nano-tomography resolved with a voxel size of just 0.06 micrometers. In dorsal or ventral view it is parallel in its basal two-thirds before pointing triangularly at the apex, and flat in lateral view. The parameres are slightly shorter than the median lobe, each bearing two subapical distant setae. Most remarkably, the endophallus, the internal sac of the genitalia, carries a wide basal structure with two lateral expansions and a long, roughly cylindrical stylus that is not closed on the dorsal side, giving it a gutter-like shape. No living genus of Catopocerinae shows anything like this long tubular stylus, making it a truly unique internal signature of this Cretaceous beetle.

Comparing these genital structures with extant genera provides crucial phylogenetic evidence. The apical setae of the parameres are distant and dorso-lateral, a configuration shared with Muganryus, Perkovskius, and a few species of Pinodytes. The complex basal structure of the endophallus is in some ways similar to that of Perkovskius, but the long tubular stylus remains unmatched. The internal structures look somewhat like the Y-shaped basal piece found in the tribe Leptodirini of the subfamily Cholevinae, which also extends into a long stylus, though that stylus has never been observed to be tubular. An internal stylus also occurs in Ptomaphagini, but without the dorsal longitudinal opening seen in Archaeocerus, although some species of Adelopsis hint at an internal void near the apex.

The subfamily Catopocerinae is a small group, currently containing six genera and 53 described species, and it is one of only two subfamilies of Leiodidae recovered as monophyletic in a major molecular phylogeny of beetles. Archaeocerus shares all the defining characteristics of the subfamily: the invagination of abdominal segment VIII inside the abdomen, leading to five visible abdominal coxosternites instead of six; a prosternum longer than the coxal width; and the presence of a spiculum ventrale in both sexes. Both male and female ventrite VIII carry this spiculum ventrale, a genital feature now documented in the fossil for the first time. The female genital segment, however, lacks visible appendicular parts, though the researchers cannot determine whether this reflects an actual reduction or simply the poor state of preservation of the amber specimen.

The bionomics of these beetles remain poorly known, but the new anatomy offers tantalizing clues about how they lived. Except for the cave-dwelling Glacicavicola, which has been observed feeding on decayed arthropods, the other extant genera are at least partly mycophagous, feeding on fungal sporocarps, and fungal spores have been found directly in the guts of several species. The mixing of plesiomorphic character states, such as the retention of eyes and wings, with presumably apomorphic features like the tarsal formula and the complex basal structure of the endophallus suggests that Archaeocerus might be the sister group of all extant genera, though the researchers caution that this remains speculative in the absence of a comprehensive phylogenetic analysis. What is certain is that a beetle trapped in amber for 99 million years has now had its most intimate anatomy revealed, thanks to X-rays a billion times more penetrating than any scalpel.

Subject of Research: Redescription of the Cretaceous species Archaeocerus uenoi Perreau, 2019 based on synchrotron radiation micro-tomography and nano-tomography (Coleoptera, Leiodidae, Catopocerinae)

Article Title: Redescription of the Cretaceous species Archaeocerus uenoi Perreau, 2019 based on synchrotron radiation micro-tomography and nano-tomography ( Coleoptera , Leiodidae , Catopocerinae )

Article References: Perreau, M., Njunjić, I., de Groot, M. D., Van Caenegem, W., & Haelewaters, D. (2025). Redescription of the Cretaceous species Archaeocerus uenoi Perreau, 2019 based on synchrotron radiation micro-tomography and nano-tomography (Coleoptera, Leiodidae, Catopocerinae). Subterranean Biology, 52, 187-200. https://doi.org/10.3897/subtbiol.52.154293

Image Credits: AI Generated

DOI: 10.3897/subtbiol.52.154293

Keywords: Redescription, Cretaceous, species, Archaeocerus, uenoi, Perreau, based, synchrotron, radiation, micro-tomography, nano-tomography, Coleoptera

In a review published in Nature Water, scientists led by Matthew Landsman of Arizona State University and Lawrence Berkeley National Laboratory, together with colleagues from SLAC National Accelerator Laboratory, Oak Ridge National Laboratory, Brookhaven National Laboratory, Argonne National Laboratory and several universities, lay out a detailed case for expanding the use of synchrotron X-ray and neutron techniques in water treatment research. These facilities, which accelerate electrons to near light speed or generate intense beams of neutrons, have transformed fields from structural biology to battery development. Yet the water treatment community, the authors contend, remains a strikingly small fraction of their user bases, leaving transformative research opportunities untapped.

The technical argument rests on what these beams can actually reveal. Synchrotron X-rays are extraordinarily bright and tunable, spanning energies from tender X-rays that probe light elements like carbon and nitrogen to hard X-rays that penetrate thick samples and resolve atomic coordination around metals. Techniques such as X-ray absorption spectroscopy can determine the oxidation state and local bonding environment of contaminants like arsenic or chromium in real water matrices. Small-angle X-ray scattering can measure the size and arrangement of colloids and polymers in solution. X-ray computed tomography can map the three-dimensional internal structure of membranes and porous sorbents at resolutions reaching tens of nanometers. Neutrons, meanwhile, offer a complementary superpower: they are exceptionally sensitive to hydrogen, meaning they can directly visualize water itself as it moves through materials, something X-rays struggle to do because hydrogen scatters X-rays so weakly.

What makes the review particularly compelling is its emphasis on in situ and operando experiments, meaning studies conducted while a treatment process is actually running under realistic conditions. Traditional characterization typically requires drying, freezing or otherwise preparing samples, which can fundamentally alter the structures being studied. Modern user facilities increasingly offer sample environments that allow researchers to study flowing water, applied voltages, pressure and temperature while collecting data. The authors point to examples such as operando small-angle neutron scattering studies of silica fouling in reverse osmosis systems, in situ X-ray scattering measurements of concentration polarization layers during cross-flow ultrafiltration, and operando ambient-pressure X-ray photoelectron spectroscopy that directly probes the chemistry of polymer membranes as they absorb water and ions.

These dynamic measurements matter because water treatment performance is governed by nanoscale processes that unfold in real time. Fouling, the accumulation of unwanted material on membranes and sorbents, is a prime example. It is the dominant cost driver in membrane-based desalination and water reuse, yet its molecular origins remain poorly understood. X-ray and neutron techniques can reveal the composition, structure and evolution of fouling layers as they form, distinguishing between mineral scaling, organic adsorption and biofilm development. The authors cite work using X-ray absorption spectroscopy to identify the mechanisms of calcium and silicon fouling on reverse osmosis membranes in wastewater reclamation, and neutron reflectometry studies that expose the interfacial microenvironment driving electrochemical reactions.

The review also highlights opportunities in three specific technology areas where facility access could accelerate progress. Membranes for brine management, including zero and minimal liquid discharge systems, could benefit from molecular-level understanding of ion transport and membrane structure. Catalysts for contaminant degradation, such as single-atom catalysts embedded in membranes that activate hydrogen peroxide to destroy pollutants, could be characterized under operating conditions to identify their true active sites. Sorbents for resource recovery, including materials that selectively capture phosphate, ammonia nitrogen or critical minerals from wastewater, could be optimized by directly observing how their binding sites interact with target ions in complex water matrices.

Neutron techniques deserve particular attention in this context because of their unique sensitivity to light elements and their ability to distinguish isotopes. Hydrogen-deuterium contrast neutron radiography, for instance, can track water exchange and two-phase flow in porous materials by substituting heavy water for normal water. Quasielastic neutron scattering can measure the dynamics of confined water in polymer membranes on picosecond to nanosecond timescales, revealing how water molecules move through the aromatic polyamide layers of reverse osmosis membranes. These measurements directly connect molecular motion to macroscopic water permeability, offering a level of mechanistic insight that conventional laboratory techniques cannot match.

The authors also emphasize the growing role of advanced computational modelling coupled with facility experiments. Machine learning is increasingly used to process the enormous datasets generated by modern detectors, such as the 500-kilopixel X-ray photon correlation spectroscopy measurements that resolve dynamics on microsecond timescales. Multimodal experiments that combine X-ray and neutron tomography simultaneously, such as the NeXT system at the National Institute of Standards and Technology, allow researchers to register complementary information about structure and water distribution in the same sample. The integration of artificial intelligence with high-throughput scattering and imaging is proposed as part of a next-generation discovery pipeline that could dramatically accelerate materials development.

Access to these facilities is more attainable than many water researchers realize. User facilities at national laboratories typically provide beamtime free of charge to researchers whose proposals are accepted through competitive peer review, and many offer dedicated staff scientists who help design experiments and operate complex sample environments. The authors argue that expanding the user base at these facilities will require deliberate outreach, training programs and the development of standardized experimental workflows that lower the barrier to entry for water treatment researchers unfamiliar with synchrotron or neutron techniques.

The stakes extend well beyond academic curiosity. The authors frame their argument in terms of global water, resource and energy security, noting that molecular-level design insights bridge laboratory-scale discoveries to system-level improvements in real treatment infrastructure. As climate change intensifies water scarcity and as industries seek to recover valuable materials from waste streams, the ability to rationally design next-generation membranes, catalysts and sorbents becomes increasingly urgent. The review suggests that the water treatment community stands at a threshold, where the sophisticated characterization infrastructure built over decades at national laboratories could finally be brought to bear on one of humanity’s most fundamental challenges: ensuring clean water for all.

Subject of Research: Water treatment research opportunities at synchrotron and neutron user facilities

Article Title: Water treatment research opportunities at synchrotron and neutron user facilities

Article References: Landsman, M. R., Hesse, S. A., Aydogan-Gokturk, P., Yao, C., Bechtel, H. A., Dudchenko, A. V., Hexemer, A., Jiang, Z., Katz, L. E., Kumar, M., Urban, V. S., Waluyo, I., Mauter, M. S., Tassone, C. J., & Crumlin, E. J. (2026). Water treatment research opportunities at synchrotron and neutron user facilities. Nature Water, 4(10), 1244-1258. https://doi.org/10.1038/s44221-026-00723-9

Image Credits: AI Generated

DOI: 10.1038/s44221-026-00723-9

Keywords: synchrotron, neutron scattering, water treatment, membranes, desalination, fouling, X-ray absorption spectroscopy, operando characterization, user facilities, Nature Water, Water, treatment

The challenge stems from the sheer scale of modern tomographic reconstruction. Iterative reconstruction methods, which refine image estimates by comparing them against actual detector measurements over many iterations, are computationally intensive but produce high-quality results from limited or noisy data. To speed things up, researchers partition the reconstructed image and raw data into slices that can be processed independently in parallel across many compute nodes. This embarrassingly parallel structure allows performance to scale with the number of available nodes, but it also means the workflow runs on high-performance computing systems with thousands of components, including CPUs, GPUs, memory, communication links, and storage systems, all of which are susceptible to failures ranging from software crashes to complete system outages.

When a failure occurs, the progress of the affected task is typically lost unless appropriate recovery mechanisms are in place. Restarting failed tasks from scratch can recover the image but at a high cost, potentially doubling runtimes and leaving many nodes idle for extended periods. In extreme cases, the failure rate may surpass the system’s ability to make progress, trapping the workflow in an endless cycle of recomputation. The team’s performance model demonstrates that frequent failures can increase reconstruction time by up to four orders of magnitude without proper resilience mechanisms. For instance, if the mean time to failure of a single task is approximately one week, a reconstruction pipeline with 1,000 tasks would, on average, fail in about 10 minutes, often shorter than the runtime of many workflows of this size.

Current fault tolerance mechanisms typically rely on checkpoint-restart techniques, which periodically save the state of each process so failed tasks can be restarted from the last checkpoint. While this reduces lost computation, it introduces I/O overhead due to frequent writes to parallel file systems, which can become a bottleneck in high-concurrency environments. Advanced systems such as VeloC and SCR alleviate this by asynchronously writing checkpoint data to local storage and deferring parallel file system writes. However, these systems are optimized for tightly coupled parallel tasks that require all tasks to restart simultaneously in the event of a failure. Tomographic reconstruction, in contrast, is embarrassingly parallel, and the failure of a single task does not require the restart of surviving tasks that have no dependencies on the failed ones.

The Argonne team’s solution incorporates two key innovations. First, they introduce an asynchronous, non-blocking checkpointing mechanism that operates independently for each task and supports variable-sized checkpoints reflecting the evolving critical state required for recovery. Tasks can continue without being blocked while critical state data is saved progressively, ensuring minimal disruption during execution. Each checkpoint is self-contained, embedding all necessary information to restore progress, such as completed iterations and sinogram indices, which eliminates computation and synchronization overhead during failure recovery. The team also dynamically adjusts the checkpoint period using a modified Young/Daly formula that accounts for changes in task availability and I/O performance, reconfiguring whenever a failure occurs.

Second, in the event of a failure, the team employs a lazy, balanced redistribution of failed tasks. Surviving tasks are allowed to continue their processing without interruption while the checkpointed slices of the failed tasks are redistributed among the survivors in the background. Rather than immediately recovering lost progress from checkpoints, surviving tasks treat the checkpointed progress as the most recent state of the failed task, and recovery is embedded into future reconstruction iterations. This avoids resource locking and enables tasks to utilize their resources more efficiently for ongoing computations. The redistribution strategy minimizes expensive read overheads associated with parallel file systems by relying on direct communication between surviving tasks, ensuring efficient resource utilization and balanced load distribution across available tasks.

To evaluate their effectiveness, the team implemented a 3D tomographic reconstruction pipeline based on the Trace reconstruction engine, supporting three iterative algorithms: Algebraic Reconstruction Technique, Simultaneous Iterative Reconstruction Technique, and Maximum Likelihood Expectation Maximization. They deployed it across Argonne’s Polaris supercomputer, where each compute node features a single AMD EPYC Milan processor with 64 physical cores and 512 GB of memory, interconnected by a 200 Gbps high-speed network. Checkpoints were managed by VeloC operating in asynchronous mode and stored in a Lustre file system. The team used two sample datasets from TomoBank, one comprising 1,500 X-ray projections of borosilicate glass spheres and another corresponding to a portion of an electronic circuit with 1,204 projections.

The results demonstrate that the proposed resilience techniques significantly reduce failure impact. Without resilient solutions, reconstruction time increases exponentially as the mean time to failure decreases, surging from 60 seconds in a failure-free environment to over 100,000 seconds at a mean time to failure of 10 seconds, a four-order-of-magnitude slowdown. Introducing checkpointing dramatically reduces this overhead by preserving progress and avoiding full recomputation of lost work, reducing reconstruction time to under 1,000 seconds at the same failure rate, a 100-fold improvement. Adding dynamic redistribution with balance-aware assignment and lazy recovery further enhances performance by an additional 4.3 times. Under the extreme condition of a mean time to failure of 10 seconds, the fully resilient pipeline completes the reconstruction in just 184 seconds, only 3 times slower than ideal execution and over 500 times faster than the naive resilient baseline.

These remarkable improvements come with minimal overhead. The combined checkpointing and communication overhead for dynamic redistribution remains consistently below 3 percent of the ideal reconstruction time across all failure scenarios. The team also evaluated robustness across diverse conditions, varying sinogram sizes, datasets, and reconstruction algorithms. Changes in sinogram size had minimal impact on efficiency, and as sinogram size increased from 640 by 640 to 1,280 by 1,280 pixels, the overhead ratio decreased by approximately 3.5 times because larger sinograms require longer computation, allowing the asynchronous, non-blocking mechanisms to overlap checkpointing with computation more effectively. The solutions also generalize across parallel-beam and cone-beam geometries, though cone-beam setups with cross-sinogram dependencies can only apply checkpointing without compromising algorithm correctness.

The team notes that their resilient solutions rely on two key properties common to many reconstruction pipelines: the iterative reconstruction pattern, in which the reconstructed object represents an intermediate state that can serve as a progress checkpoint, and partial updates with data-parallelism, where data can be partitioned and processed by independent tasks. Any tomographic reconstruction workflow exhibiting one or both of these properties can leverage these techniques. While the current implementation is CPU-based, the design is independent of any specific hardware architecture, and the approach can be adapted for GPU-based reconstruction pipelines with only minor modifications. Future work will address data transmission losses, file corruptions, storage failures, and the growing demand for real-time reconstruction with strict timing requirements.

Subject of Research: High Performance Computing

Article Title: Resilient execution of distributed X-ray image analysis workflows

Article References: Nguyen, H. D., Bicer, T., Nicolae, B., Kettimuthu, R., Huerta, E. A., & Foster, I. T. (2025). Resilient execution of distributed X-ray image analysis workflows. Frontiers in High Performance Computing, 3, Article 1550855. https://doi.org/10.3389/fhpcp.2025.1550855

Image Credits: AI Generated

DOI: 10.3389/fhpcp.2025.1550855

Keywords: X-ray tomography, checkpointing, fault tolerance, distributed computing, synchrotron, reconstruction workflows, Resilient, execution, distributed, X-ray, image, analysis

The advance centers on a concept that has been generating excitement in the particle therapy community: so-called mixed beams. Instead of accelerating a single ion species, the idea is to combine two different nuclei in one beam. Carbon nuclei do the destructive work, shattering the DNA of tumor cells at the target site. Helium nuclei, meanwhile, act as messengers, passing through the body and carrying information about what lies along the beam path. The helium ions effectively serve as continuous probes of the patient’s anatomy during irradiation, allowing clinicians to verify that the treatment is proceeding exactly as planned.

The physics behind this dual role is elegant. In the accelerator, every ion is stripped of its electrons, leaving bare nuclei. A carbon nucleus carries exactly three times the electric charge of a helium nucleus and almost exactly three times its mass. Because their charge-to-mass ratios are nearly identical, the two species follow almost exactly the same trajectory through the synchrotron, meaning they can be accelerated simultaneously to high energies and directed toward the patient together. Once inside the body, however, a crucial difference emerges: helium ions can travel roughly three times farther through tissue than carbon ions of the same energy per nucleon.

This difference is what makes the mixed beam so powerful. The beam can be tuned so that the carbon ions come to rest inside the tumor, depositing their destructive energy precisely at the target, while the lighter helium ions punch through the body and emerge on the far side. By measuring the residual energy of these exiting helium ions, physicists can reconstruct how much material the beam traversed and therefore how deeply the carbon ions actually penetrated. If the carbon range deviates from the plan, clinicians can know immediately rather than discovering a problem after the treatment is complete.

The stakes are considerable. Even with the high precision of ion beam therapy, uncertainties remain. Organ motion, for example, can shift the location where the beam deposits most of its energy, known as the beam’s range, by a few millimeters. To guarantee that the entire tumor receives a lethal dose despite these uncertainties, a small safety margin of healthy tissue around the tumor is irradiated as well. The smaller this margin can be made, the more precise the therapy becomes and the better nearby sensitive organs, such as the spinal cord or the brainstem, can be protected. Real-time range verification through helium monitoring could shrink those margins substantially, which is particularly valuable for tumors located very close to critical structures.

There was, however, a fundamental obstacle standing in the way. For the mixed beam concept to work, the ratio of carbon to helium in the beam must be known and controlled with great precision. Yet measuring a beam normally requires intercepting it, and intercepting it means it cannot simultaneously be used for treatment. Either the beam is measured, or it is used for irradiation. Doing both at the same time seemed, until now, to be a nearly impossible demand.

The TU Wien and MedAustron team found an ingenious way around this dilemma, and it hinges on a subtlety of nuclear mass that most textbooks gloss over. A carbon nucleus does not have exactly three times the mass of a helium nucleus; it is in fact about 0.065 percent lighter than that ratio would suggest. This tiny discrepancy means that carbon and helium nuclei are forced onto slightly different trajectories inside the particle accelerator. The difference is far too small to separate the beams for practical purposes, but it is large enough to leave a measurable fingerprint on the accelerator’s operation.

That fingerprint appears in the radio frequency system that keeps the beam on track. In the synchrotron, operators continuously monitor whether the center of the particle beam remains on its intended trajectory. If it deviates, the accelerator’s radio frequency is adjusted ever so slightly to pull it back. Because helium and carbon nuclei respond slightly differently to these corrections, owing to their tiny mass difference, the frequency correction required to stabilize the beam depends directly on the mixing ratio of the two species. By precisely tracking the frequency needed to hold the beam steady, the carbon-to-helium ratio can be determined continuously, without ever touching the beam itself.

The concept was calculated and developed at TU Wien and then tested in collaboration with MedAustron, with results showing excellent agreement between theory and experiment. The team demonstrated that the method allows the helium and carbon fractions in the beam to be determined without affecting or interrupting the beam. This means that during experiments, and possibly during actual treatments in the future, clinicians can verify that the helium fraction matches the desired value before the beam is cleared for irradiation. The work has been published in the journal Physical Review Accelerators and Beams and is already drawing international attention. On October 8 and 9, 2026, researchers from a range of particle accelerator facilities gathered at TU Wien for the first Workshop on Mixed Ion Beam Delivery to discuss the current state of the field and the challenges that remain.

Underlying all of this is a property of ion physics that makes these beams such effective cancer weapons in the first place. An atomic nucleus racing through biological tissue should not be pictured like a bullet passing through a wooden board, where kinetic energy is shed steadily along the path. How strongly an ion interacts with material depends on its energy. A fast ion can pass through tissue relatively undisturbed, losing only a small amount of energy. As it slows down, however, its interaction with the surrounding material grows stronger and stronger, until it finally deposits a large fraction of its energy over a very short distance, a phenomenon known as the Bragg peak. If the ion’s energy is chosen correctly, the beam passes through healthy tissue causing comparatively little damage, and only at the tumor does it enter the region of maximum energy deposition, selectively destroying cancer cells while sparing everything in front of and behind the target. By adding helium-based range verification to this already-precise delivery mechanism, the TU Wien and MedAustron collaboration has taken a significant step toward ion beam therapy that not only hits its target but continuously confirms, in real time, that it is doing so.

Subject of Research: Noninvasive quantification of mixed carbon-helium ion beams in synchrotrons for precision cancer radiotherapy

Article Title: Ion beams against cancer

Article References: Ion beams against cancer. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: ion beam therapy, carbon ions, helium ions, mixed beams, synchrotron, cancer treatment, radiotherapy, beam range verification, TU Wien, MedAustron, particle accelerator, Bragg peak

The technique addresses a fundamental bottleneck in X-ray fluorescence imaging, one of the most widely used tools for determining which chemical elements are present in a sample and where they are located. When an X-ray beam strikes a material, the atoms within it absorb energy and then re-emit fluorescent X-rays at characteristic energies, each one acting as a fingerprint for a specific element. By detecting these emissions, scientists can identify the presence of copper, zirconium, silver, or any other element without destroying the sample. The problem arises when researchers want a full three-dimensional picture. Traditional approaches require scanning the object point by point, measuring the fluorescence at each individual location, and repeating the process across many angles to build up a volumetric reconstruction. For large or intricate samples, that process can take considerable time and generate enormous volumes of data.

The Bar-Ilan-led team took a fundamentally different approach. Instead of measuring every point individually, they placed a randomly patterned tungsten mask in front of the X-ray beam. This mask imposes a structured pattern on the illumination, so that each measurement encodes information from multiple parts of the sample simultaneously. Rather than a series of isolated point readings, the detector captures compressed, overlapping signals that contain information about the whole volume in a form that is not immediately readable but is mathematically recoverable. The researchers then rotated a sample containing copper, zirconium, and silver while measuring the fluorescent X-rays emitted by the different elements, and a reconstruction algorithm pieced together the three-dimensional elemental structures directly from the compressed data.

The results were striking. The researchers were able to eliminate more than 97 percent of the measurements that would normally be required, yet still accurately reconstruct the locations of microscopic metal wires and particles within the sample. In practical terms, that means the same chemical map that once demanded a long, data-heavy scanning session can be recovered from a small fraction of the exposure. Adi Ben-Yehuda, a PhD student in Prof. Sharon Shwartz’s laboratory at Bar-Ilan University’s Department of Physics, described the surprise the team felt at how much information could be recovered from so little data. Instead of measuring every point separately, she explained, the method uses a structured X-ray pattern and lets the reconstruction algorithm assemble the information, a different way of thinking about how an X-ray image can be created.

The underlying idea belongs to a family of techniques known as ghost imaging, in which the image-bearing information is split between two correlated signals and recovered computationally rather than recorded directly. The new work builds on the team’s previous demonstration of two-dimensional X-ray fluorescence ghost imaging, extending the concept into a full three-dimensional imaging system. In the two-dimensional version, the structured illumination allowed the researchers to recover elemental maps without ever forming a conventional image on the detector. The leap to three dimensions required combining that compressed-sensing philosophy with tomographic reconstruction, the same mathematical framework that underlies computed tomography in medicine, but applied to fluorescence data rather than simple transmission. The result is a system in which the illumination pattern, the rotation of the sample, and the reconstruction algorithm work together as a single designed pipeline.

Why does speed matter so much in this field? The answer lies largely in the economics and physics of synchrotron facilities, the enormous particle-accelerator complexes where scientists use extremely bright X-ray beams to study materials at microscopic scales. Beamtime at these facilities is scarce and highly competitive, and every hour of measurement is precious. A technique that reduces the required measurements by more than 97 percent effectively multiplies the amount of science that can be extracted from a given allocation of beamtime. Faster imaging also opens experimental possibilities that are simply impractical today: scanning larger samples that would otherwise take days to map, following chemical processes as they unfold in real time, and studying delicate biological materials while reducing their cumulative exposure to damaging X-ray doses.

The potential applications span an unusually broad range of disciplines. In materials science, three-dimensional elemental maps reveal how alloys, catalysts, and electronic components are structured at the microscopic level, information that guides the design of stronger and more efficient materials. In green energy research, understanding the chemical distribution inside batteries and fuel cells as they charge and discharge is central to improving performance and longevity. In biology, researchers could map the distribution of trace elements within cells and tissues, where metals such as zinc, iron, and copper play essential roles in enzymes and signaling. In geology, elemental tomography can expose the growth history of minerals and the microstructure of rocks that record the planet’s past. For all of these fields, a 43-fold acceleration in acquisition time changes not just efficiency but the very scope of what can be attempted.

Prof. Sharon Shwartz of Bar-Ilan University framed the advance as a change in a long-standing trade-off. X-ray imaging has traditionally forced researchers to balance the amount of information they want against the time and data required to obtain it, he noted, but the new approach shows that this trade-off can be altered. By designing the X-ray illumination together with the computational reconstruction, the team can recover detailed three-dimensional chemical information from a remarkably small number of measurements. That co-design principle, in which hardware and software are developed as an integrated system rather than as separate stages, reflects a broader trend in modern imaging science, where clever mathematics increasingly substitutes for brute-force data collection.

The study was conducted with Dr. Alexander Rack of the European Synchrotron Radiation Facility and Dr. Nicola Viganò of CEA and Université Grenoble Alpes, and was supported by the Israel Science Foundation and the European Synchrotron Radiation Facility. The combination of an academic physics laboratory with two major European photon facilities underscores the kind of collaboration this technique will need as it matures, since structured-illumination experiments depend on precisely engineered masks and stable, brilliant X-ray sources of the kind found only at synchrotrons.

The researchers are already looking ahead. Their next steps include applying the technique to more complex biological and geological samples, whose heterogeneous structures and weaker elemental signals will test the robustness of the reconstruction algorithm, and incorporating artificial intelligence and deep learning to further improve imaging speed and resolution. If those efforts succeed, the compressed-measurement philosophy demonstrated here could become a standard tool at light sources around the world, turning what was once a slow, data-hungry mapping process into something fast enough to watch chemistry happen in three dimensions, live.

Subject of Research: Compressive three-dimensional X-ray fluorescence ghost tomography for rapid chemical imaging

Article Title: New X-ray imaging method maps 3D chemical structures 43 times faster

Article References: New X-ray imaging method maps 3D chemical structures 43 times faster. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: X-ray fluorescence, ghost imaging, tomography, Bar-Ilan University, synchrotron, compressed sensing, chemical imaging, Optica, tungsten mask, 3D reconstruction, materials science, beamtime efficiency

Enceladus is a small moon, only about 500 kilometres across, yet it behaves like a geologically active world. Its south polar region is scarred by warm fractures, informally known as tiger stripes, from which enormous plumes of water vapour and icy grains erupt continuously into space. NASA’s Cassini spacecraft flew through these plumes and analysed their composition, revealing a salty ocean rich in sodium, chloride and carbonate species beneath the ice shell. That measured composition is the starting point for the new study. The researchers prepared a laboratory analogue of the Enceladus ocean, a sodium-chloride-carbonate solution whose proportions match the constraints derived from Cassini’s plume measurements, and then set out to answer a deceptively simple question: what actually happens to such a solution when it freezes at the frigid temperatures characteristic of the moon’s surface and near-surface environment?

The answer is far from trivial. The phase behaviour of concentrated brines at cryogenic temperatures is notoriously difficult to predict, and the authors emphasise that the phase behaviour of Enceladus-type solutions has been poorly constrained until now. When an aqueous solution freezes, it does not simply turn into ice. As pure water ice crystallises first, the remaining liquid becomes increasingly concentrated in dissolved salts, a process called brine rejection. Eventually the residual brine becomes so concentrated that salts begin to precipitate out as their own solid minerals. For a sodium carbonate-rich solution like the one modelled on Enceladus, the key precipitating mineral is natron, the hydrated sodium carbonate Na2CO3·10H2O, a compound familiar on Earth from the evaporite deposits of soda lakes and famously used by the ancient Egyptians in mummification.

To watch this freezing process unfold at the microscopic scale, the team turned to a powerful combination of synchrotron X-ray techniques at Diamond Light Source. Using the DIAD beamline, they performed X-ray computed microtomography, which builds three-dimensional images of the internal structure of a frozen sample, alongside X-ray diffraction, which identifies the crystal structures of the solid phases present. This dual approach allowed the researchers to see both where liquid pockets survived within the growing ice and salt matrix and exactly which minerals formed as the temperature dropped. The experiments were carried out under cryogenic conditions that replicate the extreme cold of Enceladus, where surface temperatures plunge below 75 kelvin and even the near-subsurface remains far colder than any terrestrial environment.

What the tomography revealed was striking. As the Enceladus-type solution froze and natron precipitated, the growing crystals trapped and preserved discrete pockets of the parent fluid, forming classic fluid inclusions within the cryogenic natron. These inclusions are familiar features to terrestrial geologists, who routinely use fluid inclusions trapped in ancient minerals to reconstruct the chemistry and temperature of fluids that flowed through rocks millions or billions of years ago. The new results demonstrate that the same preservation mechanism operates in the sodium carbonate brines of an icy moon. In other words, wherever natron forms on or within Enceladus, it should be locking away microscopic samples of the ocean from which it crystallised, providing a window into the geochemistry of the moon’s interior that would otherwise be inaccessible beneath kilometres of ice.

The implications for the search for life are immediate and profound. If natron traps parent fluid as it precipitates, then any organic molecules, biosignatures or other chemical traces of biological activity present in the ocean could become sequestered within these inclusions and shielded from the harsh radiation environment at the moon’s surface. On Enceladus, the ice crust is geologically active, and material from the ocean is continually cycled to the surface through the plumes and their fallout deposits. Fresh plume deposits, the snow-like layers of material that settle near the tiger stripes after being ejected from the ocean, are predicted to be rich in natron precisely because they represent recently frozen ocean water. According to the authors, direct sampling by future missions should therefore prioritise these fresh deposits, where natron is abundant and its trapped inclusions offer the best chance of capturing preserved signatures of life.

The timing of this work is significant for mission planning. Enceladus is a priority target for both a NASA Flagship-class mission and the European Space Agency’s L4 large-class mission, and both agencies are currently weighing instrument suites and sampling strategies for a journey to the Saturnian system. The authors argue that future missions must have the capability to identify natron at the surface, because recognising this mineral remotely or in situ would immediately flag locations where ocean-derived material and its trapped fluid inclusions are concentrated. An orbiter or lander equipped to detect natron’s distinctive spectral signature could map the freshest, most astrobiologically promising deposits before any sample acquisition takes place, dramatically improving the scientific return of an enormously expensive and technically demanding mission.

The study also fills a more fundamental gap in cryogeochemistry, the discipline that the authors identify as the essential lens through which future missions must understand Enceladus’s habitability. Because the moon’s ice crust is geologically active, ocean material is not static; it freezes, deforms, fractures and is re-erupted, and every stage of that cycle is governed by the phase behaviour of its brines. Laboratory experiments like this one, which combine real-time imaging with crystallographic identification at synchrotron resolution, provide the ground truth that modellers and mission designers need. Knowing that natron precipitation traps fluid inclusions means that models of the ice shell can now account for pockets of concentrated brine preserved within salt layers, which could influence mechanical properties, thermal evolution and even the delivery of organics to the surface.

There is a satisfying symmetry in the fact that natron, a mineral entwined with humanity’s earliest attempts to preserve biological material, may now hold the key to detecting biology on another world. The Egyptian embalmers of three thousand years ago prized natron for its ability to desiccate and preserve; the astrobiologists of today value it for its ability to encapsulate and protect. On Enceladus, where the ocean is completely hidden from direct view, the plumes offer the only free samples, and the deposits they leave behind are the only accessible archive of ocean chemistry. The demonstration that this archive actively traps and preserves its parent fluid transforms the way scientists should think about where to look and what to collect.

As mission concepts mature over the coming years, the message from Diamond Light Source is clear: the humble sodium carbonate hydrate that crusts the shores of soda lakes on Earth deserves a central place in the strategy for exploring Enceladus. Mapping natron, sampling fresh plume fallout and reading the microscopic fluid inclusions within it could allow scientists to taste the moon’s ocean without drilling through its ice shell, and perhaps, if biology has ever taken hold in that dark, distant sea, to find its fingerprints sealed inside a mineral that has been quietly keeping the secret all along.

Subject of Research: Fluid inclusions in cryogenic natron formed from Enceladus-type brines and their astrobiological significance

Article Title: Fluid inclusions establish natron as a key astrobiological target on Enceladus

Article References: Perera, L. J., Le Houx, J., Leonardi, A., Day, S. J., & Thompson, S. P. (2026). Fluid inclusions establish natron as a key astrobiological target on Enceladus. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04080-z

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04080-z

Keywords: Enceladus, natron, fluid inclusions, astrobiology, cryogeochemistry, synchrotron, X-ray microtomography, Saturn moons, ocean world, plume deposits, Diamond Light Source, habitability

The team’s chosen arena is Taylor–Couette flow, the fluid trapped between two concentric cylinders with the inner one rotating and the outer one held still. This configuration has served as a benchmark for instability studies since G. I. Taylor’s seminal 1923 experiments, and its lineage stretches back even further, to James Clerk Maxwell’s unsuccessful nineteenth-century attempts to observe flow-induced birefringence. As the Reynolds number, the ratio of inertial to viscous forces, is increased, the fluid passes through a well-charted cascade of states. In laminar Couette flow, a fluid element traces a simple circular path. Above a critical Reynolds number, the flow reorganizes through a pitchfork bifurcation into Taylor vortex flow, a pattern of counter-rotating toroidal vortices separated by radial inflow and outflow regions. Further increases in speed trigger a Hopf bifurcation into wavy vortex flow, in which the vortices carry a travelling wave, followed by modulated wavy vortices, chaotic merging and splitting, and eventually turbulent Taylor vortices.

What has remained unknown is whether actual suspended particles, rather than idealized continuum fluid elements, follow the same spatiotemporal choreography as the macroscopic flow field. Anisotropic nanoparticles complicate the picture considerably. Their interactions with velocity gradients and vorticity produce distinct rotational and alignment dynamics, and the secondary vortex flows of transitional flow are expected to impose intricate, position-dependent alignment. The theoretical framework for this question rests on the rotational Péclet number, the ratio of the apparent shear rate to the rotational diffusion coefficient. At large values, flow-driven rotation dominates and particles should align with the flow; at small values, Brownian motion wins and orientations should be nearly isotropic. At moderate values near unity, the interplay between advection and diffusion could produce far more convoluted behaviour, but testing this hypothesis demanded a measurement technique capable of resolving both the macroscopic vortex patterns and the nanoscale orientation of the particles simultaneously.

Existing tools fell short. Flow visualization and particle image velocimetry routinely map macroscopic flow fields, but they operate at length scales far above those of the suspended nanoparticles and cannot access their orientational dynamics directly. Spatially resolved small-angle X-ray scattering, or SAXS microscopy, can map the size, shape, packing and preferential alignment of nanoscale constituents, and pioneering experiments had already identified time-averaged alignment of plate-like clay particles in Taylor–Couette flow. Yet the technique’s temporal resolution, roughly a minute in state-of-the-art implementations, confined it to slow processes such as the assembly of nanoparticle superlattices or the sodiation of battery electrodes. The new work shatters that limitation by exploiting the extreme X-ray flux of diffraction-limited synchrotron sources, achieving millisecond temporal resolution through frequency-domain analysis.

The experimental set-up is a custom Taylor–Couette cell manufactured by Anton Paar and mounted on an MCR702 rheometer, with inner and outer cylinder radii of 20.5 and 22.5 millimetres. Polarized light imaging is performed in the radial configuration, visualizing the flow in the plane defined by the velocity and vorticity directions, while SAXS data are collected in the tangential configuration, probing the plane defined by the velocity gradient and vorticity. Crucially, the use of the suspensions’ intrinsic flow-induced birefringence to determine macroscopic flow patterns eliminates the need for tracer particles, which would otherwise perturb the nanoscale flow being studied. The X-ray measurements were carried out at the ForMAX beamline of the MAX IV Laboratory, using an incident beam of roughly five times ten to the fourteen photons per second at 16.3 kiloelectronvolts, with scattering patterns recorded at 100 hertz by an EIGER2 X 4M photon-counting detector.

To make the macroscopic and nanoscopic observations directly comparable, the researchers developed a common spatiotemporal analysis framework. Lines of single pixels extracted from the polarized light video recordings are assembled into space-time diagrams, whose two-dimensional Fourier transforms yield the characteristic wavenumber and frequencies of each instability mode. On the X-ray side, two-dimensional scattering patterns are azimuthally integrated to construct azimuthal angle–time diagrams, from which a spatiotemporally resolved variant of the Hermans orientation parameter provides an instantaneous, ensemble-averaged and local measure of the nanoparticles’ preferential alignment. Based on Jeffery’s classical result for rigid anisotropic particles in simple shear, a temporal resolution of about one millisecond suffices to resolve single-particle rotation at shear rates up to roughly one thousand per second for the aspect ratios involved.

Two suspensions served as the test subjects: platelet-like graphene oxide nanoparticles, roughly two micrometres across and one nanometre thick, dispersed at 0.7 percent by weight, and rod-like cellulose nanocrystals, about 230 nanometres long and 6 nanometres in diameter, at 3 percent by weight. The validation experiments on the onset of the first instability already revealed striking differences. Graphene oxide destabilizes the flow, with the critical Reynolds number falling below the Newtonian reference value of approximately 184, and the transition initially appears as an elasticity-modified pattern in which Taylor vortices are triggered first in the middle of the flow domain. Cellulose nanocrystals, by contrast, stabilize the flow, pushing the critical Reynolds number above the Newtonian value, while shear-thinning effects yield smaller characteristic vortex wavenumbers. For both suspensions, all supercritical flow patterns remain Newtonian-like in character, although their onsets and ranges differ considerably.

The central result emerges when the two suspensions are compared under modulated wavy vortex flow at similar Reynolds numbers. The graphene oxide platelets, whose rotational Péclet number is large at around one hundred, follow the macroscopic dynamics of the secondary flows exactly as expected: the nanoscale characteristic frequency measured by SAXS matches the main wavy-mode frequency of about 7 hertz identified by polarized light imaging, and the spatial periodicity of the particle alignment mirrors that of the macroscopic flow field. The cellulose nanocrystal rods, operating at a moderate rotational Péclet number near unity, behave entirely differently. Although their director exhibits the same spatial periodicity as the macroscopic flow, it shows no signature of the large-scale wavy dynamics. Instead, the nanoscale dynamics is dominated by a frequency of about 29 hertz, far exceeding the wavy-mode frequencies of roughly 10 and 2.5 hertz and the rotational frequency of the inner cylinder, and correlating instead with the turnover frequency of the vortex instabilities, the rate at which a fluid element circulates within a single Taylor vortex.

The researchers interpret this divergence through a rotational supercritical flow Péclet number, defined as the ratio of the wavy-mode frequency to the rotational diffusion coefficient. For graphene oxide this quantity is of order ten, meaning flow dominates; for cellulose nanocrystals it is of order one-tenth, meaning Brownian de-orientation prevails. In plain terms, a cellulose nanocrystal loses its orientational memory many times within a single vortex wave cycle, its rotational decorrelation time of about 11 milliseconds being far shorter than the roughly 100-millisecond wave period, whereas a graphene oxide platelet, with a decorrelation time of about 6 seconds, tracks the wave faithfully. Yet the Péclet framework alone cannot explain the distinct high-frequency spectral peaks observed for the rods, which are nearly an order of magnitude faster than the extensively studied shear-induced Jeffery orbits. A simple kinematic model shows that rotational diffusion should suppress any coherent spectral peak even in the presence of vortex advection, so the observed peaks suggest a collective orientational mechanism in which interparticle interactions, plausibly stronger in the denser cellulose nanocrystal suspension, sustain coherence against rotational diffusion.

Beyond its immediate findings, the work raises questions that reach to the heart of pattern formation in nonequilibrium systems. The critical transition from laminar flow to Taylor vortices proves to be length-scale and particle-type independent, while the orientational response to the subsequent Hopf bifurcation is particle dependent, revealing a particle-shape-mediated transition in the orientational phase space of the suspension. Which small-scale degrees of freedom genuinely participate in macroscopic pattern formation, and which can be coarse-grained away, remains unresolved, as does the detailed impact of the observed multiscale dynamics on flow stability through elastic and shear-thinning effects. With millisecond-resolved X-ray scatter microscopy now demonstrated, combined with first-principles dynamical simulations, researchers have a powerful new instrument for dissecting the flow–microstructure coupling that underlies one of physics’ oldest and most beautiful instabilities.

Subject of Research: Multiscale orientational dynamics of anisotropic nanoparticles in transitional Taylor–Couette flow

Article Title: Multiscale transitional flow in anisotropic nanoparticle suspensions revealed by time-resolved X-ray scatter microscopy

Article References: Sekar, K., Ghai, V., Ghanbari, R., Bek, M., Liebi, M., Matic, A., Terry, A. E., Nygård, K., & Kádár, R. (2026). Multiscale transitional flow in anisotropic nanoparticle suspensions revealed by time-resolved X-ray scatter microscopy. Nature Physics. https://doi.org/10.1038/s41567-026-03467-1

Image Credits: AI Generated

DOI: 10.1038/s41567-026-03467-1

Keywords: fluid dynamics, Taylor–Couette flow, nanoparticles, X-ray scattering, SAXS microscopy, polarized light imaging, flow instabilities, turbulence transition, graphene oxide, cellulose nanocrystals, rotational Péclet number, synchrotron

Nitrogen fixation is the conversion of atmospheric nitrogen gas, which makes up roughly 78 percent of the air we breathe, into ammonia that living cells can incorporate into amino acids, nucleotides and other essential molecules. The obstacle is the nitrogen-nitrogen triple bond, one of the strongest chemical bonds known in nature, which locks the two atoms together with an energy that neither plants nor animals can unlock. Only certain microorganisms, equipped with the enzyme nitrogenase, can break it under the mild conditions of ambient pressure and temperature that life tolerates. Industrial chemistry, by contrast, needs the Haber-Bosch process, with its high temperatures, high pressures and substantial energy consumption, to accomplish the same transformation at scale.

The nitrogenase enzyme carries at its heart the most complicated metallocofactor known in biology, a cluster of metal and sulfur atoms that orchestrates the reduction of N2 to ammonia. Nitrogenases come in three main varieties, distinguished by the metal at the centre of the cofactor: molybdenum, vanadium or iron alone. The molybdenum form is the best studied and generally the most efficient, yet how the different metal centres enable the breaking of the triple bond, and how the three enzyme families relate to one another evolutionarily, remain open questions in biochemistry.

Methanocaldococcus infernus offered an unusual opportunity to probe those questions. The archaeon thrives in marine volcanic areas, and the team led by Tristan Wagner managed to cultivate it in the laboratory under conditions that forced it to fix nitrogen at temperatures above 90 degrees Celsius. How, Wagner wondered, could an enzyme tasked with splitting the N2 triple bond remain functional in heat that denatures most proteins within seconds? The answer, it turns out, lies in a molecular architecture of remarkable robustness.

When the researchers isolated the nitrogenase directly from the microbe, they found that the protein does not begin to fall apart until around 90 degrees Celsius, and a fraction of it even survives at 98 degrees, just shy of water’s boiling point. Nevena Maslać, the study’s first author, compared the fate of ordinary proteins in such conditions to egg white cooked in hot water, noting that this enzyme is instead built for exactly those extremes. Intriguingly, the enzyme is not active at room temperature; it produces ammonia only when hot. That thermal rigidity proved to be a scientific gift, because it stabilised reaction states that normally collapse before they can be studied.

Obtaining a detailed picture of the enzyme demanded a tour de force spanning microbial physiology, native enzyme purification, biochemistry and structural biology, all conducted under strictly oxygen-free conditions. Nitrogenase metallocofactors are exquisitely sensitive to oxygen, which irreversibly damages them, so every step of the work had to exclude air. The team crystallised the enzyme and examined the crystals at the Institut de Biologie Structurale in Grenoble, using the on-site synchrotron, a circular particle accelerator that generates intense X-rays capable of resolving atomic-scale structure.

The resulting images delivered a near-atomic-resolution view of the simplest nitrogenase known to date, and one with a strikingly hybrid character. The archaeal enzyme combines structural features of all three nitrogenase families, the molybdenum, vanadium and iron-only forms. This mosaic architecture supports the idea that ancestral nitrogenases, the ancient systems from which the modern families evolved, may have resembled this archaeal enzyme more closely than their bacterial counterparts. In other words, studying M. infernus’s nitrogenase may be the closest researchers can get to examining a molecular fossil of the original nitrogen-fixing machinery.

Confirming that the enzyme truly carried a molybdenum cofactor pushed the synchrotron instrumentation to its absolute limits, according to Wagner. The measurement succeeded, detecting the characteristic molybdenum signal, but it also delivered an unexpected bonus. The team observed a so-called turnover state of the enzyme, a configuration believed to represent an intermediate step in the nitrogen reduction reaction, that had previously been captured only in vanadium and iron-only nitrogenases. Seeing this state in a molybdenum-containing enzyme for the first time stunned the researchers, and it carries a significant implication: nitrogenases of all three metal types may universally follow the same mechanistic pattern when they dismantle the N2 triple bond.

The significance of understanding nitrogen fixation extends well beyond deep-sea microbiology. Nitrogen-fixing microorganisms such as M. infernus do more than make ammonia; they are also major players in Earth’s carbon cycle, generating roughly half of the methane present in the atmosphere. Wagner and colleagues point to a future in which such heat-loving organisms, or the enzymes they carry, could serve as biological platforms for converting gases into useful products, including methane and ammonia, powered by green hydrogen as an energy source. Enzymes that operate at near-boiling temperatures could offer advantages of reaction speed and stability that their mesophilic cousins cannot match.

Agriculture stands to gain as well. Wagner speculates about a future in which crops might one day obtain nitrogen directly from atmospheric N2, freeing farming from its heavy dependence on industrial fertilisers. Today’s fertiliser production through the Haber-Bosch process consumes substantial energy and is associated with greenhouse gas emissions, while the overuse of fertilisers drives eutrophication of waterways and other environmental damage. For now, however, the study delivers something more fundamental: an updated molecular view of one of biology’s most remarkable chemical reactions, seen through an enzyme that keeps working at temperatures where almost everything else in the cell falls apart.

Subject of Research: Structure and mechanism of a hyperthermophilic archaeal nitrogenase involved in biological nitrogen fixation

Article Title: Molecular insight into biological nitrogen fixation close to the boiling point

Article References: Molecular insight into biological nitrogen fixation close to the boiling point. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: nitrogenase, nitrogen fixation, Methanocaldococcus infernus, deep-sea hydrothermal vents, metallocofactor, molybdenum, hyperthermophile, structural biology, synchrotron, ammonia, Haber-Bosch, Nature Communications

The research, led by Lena Merten and Felix Roosen-Runge of Lund University together with Gudrun Lotze of Malmö University and Marianne Ahmad, also of Malmö University, focused on yellow pea seeds, a crop of growing importance for sustainable food manufacturing. Peas are prized as a plant-based protein source, but the way their internal structure varies between species, cultivars, developmental stages and processing treatments remains poorly understood. Because seeds are multi-component biological materials, their characterization must stretch across length scales, from the arrangement of macromolecules to the architecture of cells. The team set out to build a workflow capable of spanning that entire hierarchy in a single, coherent analysis.

At the heart of the method is scanning Small- and Wide-Angle X-ray Scattering, or SWAXS, performed at the European Synchrotron Radiation Facility in Grenoble on beamline ID13. In a scanning experiment, a finely focused X-ray beam is stepped across the sample point by point. At each position, the scattered intensity records how molecules and nanostructures are organized locally: wide-angle patterns speak to packing at near-atomic distances, while small-angle patterns reveal features on the scale of tens to hundreds of nanometers. Rastered across an entire seed section, these measurements assemble into a map in which every pixel carries a full scattering fingerprint of its neighborhood, effectively turning the seed into a mosaic of nanoscale structural signatures.

Scattering alone, however, says nothing about which chemical elements reside where. To add that dimension, the researchers paired the scattering scan with X-ray fluorescence, or XRF, a technique in which the excited sample emits element-specific radiation. By recording fluorescence signals alongside the diffraction patterns, the team could overlay maps of elemental composition onto maps of molecular organization. This multi-modal integration is what elevates the approach: regions of the seed with similar scattering behavior can be compared against their elemental makeup, exposing relationships between structure and composition that neither measurement could reveal on its own.

The real bottleneck in such experiments is not data collection but data interpretation. A scanning SWAXS run on a seed produces thousands of scattering patterns, each a complex curve of intensity versus angle, and traditional analysis would require fitting each one with a predefined structural model. That approach is slow, subjective and biased toward structures the analyst already expects. The Swedish team instead implemented a fitting-free, data-driven segmentation workflow built on machine learning. Rather than asking what each pattern should look like, the algorithms group patterns by similarity, letting distinct structural domains emerge from the data itself.

This unsupervised strategy allowed the researchers to identify and characterize heterogeneous regions within the pea seeds and to classify structurally distinct domains without relying on predefined models. The payoff is quantitative comparability: because the classification is generated by the same data-driven procedure for every sample, domains can be compared systematically across different seeds, cultivars, developmental stages or processing conditions. A seed that has been stored for months, germinated, or exposed to industrial treatment can be mapped with the same yardstick, turning what was once a descriptive picture into a measurable, reproducible analysis.

The implications reach well beyond one legume. Seed structure underpins germination, aging, storage stability and the response of seeds to treatment during food processing, and structural variation is written into the genetic setup of each species and cultivar. A method that captures molecular organization, cellular architecture and elemental composition in one pass gives plant scientists a new lens on early growth stages and gives food scientists a way to connect processing steps to structural consequences. The authors emphasize that the approach is broadly applicable to other hierarchically organized biological materials, positioning it as a versatile tool for both plant science and plant-based food science.

Technically, the study demonstrates how synchrotron facilities and modern data science have become inseparable partners. Beamline ID13 provided the brilliant, focused X-rays needed to interrogate the seed at high spatial resolution, and the resulting datasets, recorded under a documented experimental DOI, were rich enough to sustain a fully data-driven analysis. The workflow sidesteps the model-fitting stage entirely, which not only accelerates analysis but also guards against circular reasoning, since the segmentation is derived from the measurements rather than from assumptions about what the seed contains. Combined with the complementary XRF channel, the pipeline delivers a layered portrait of the seed: where the elements are, how the molecules are arranged, and which structural territories dominate the tissue.

For the growing plant-based food industry, the timing is significant. As manufacturers reformulate products around pea protein and other legume ingredients, understanding how seed microstructure governs texture, nutrition and processing behavior becomes a competitive necessity. The multi-scale, multi-modal framework described by Merten and colleagues opens the possibility of screening varieties for desirable structural traits, monitoring how storage and treatment alter internal architecture, and ultimately breeding or engineering seeds whose structure is optimized from molecule to tissue. What was once invisible, the quiet hierarchy inside a humble pea, is now legible, pixel by pixel, pattern by pattern.

Subject of Research: Multi-scale structural and compositional analysis of yellow pea seeds using scanning SWAXS, X-ray fluorescence and machine learning segmentation

Article Title: Integrating scanning X-ray scattering and fluorescence for multi-scale analysis of seed structure supported by machine learning tools

Article References: Merten, L., Lotze, G., Ahmad, M., & Roosen-Runge, F. (2026). Integrating scanning X-ray scattering and fluorescence for multi-scale analysis of seed structure supported by machine learning tools. Plant Methods, 22(1), Article 78. https://doi.org/10.1186/s13007-026-01585-8

Image Credits: AI Generated

DOI: 10.1186/s13007-026-01585-8

Keywords: X-ray scattering, SWAXS, X-ray fluorescence, machine learning, pea seeds, plant science, food science, synchrotron, data-driven analysis, seed structure, hierarchical organization, Plant Methods