Holotomography, in its standard form, is a phase-contrast technique. Rather than relying on the absorption of X-rays, which becomes vanishingly small for light elements at the energies needed for nanoscale work, it measures the phase shifts that a wavefront accumulates as it passes through material of varying electron density. By illuminating the sample from many angles and recording holographic interference patterns, an algorithm can recover the refractive-index distribution throughout the object, producing quantitative three-dimensional maps in which contrast reflects electron density rather than mere attenuation. Because it avoids the resolving-power limits of physical X-ray optics, lensless holotomography uses computed diffractive imaging: a coherent, focused beam illuminates the specimen, and the fine structure of the outgoing wave is inferred entirely from measured diffraction and hologram data.

The fundamental obstacle to scaling this approach is computational as much as it is experimental. In the weak-object approximation that underlies most conventional reconstructions, the sample is treated as a thin, gently refracting phase screen: the wave is assumed to pass straight through, accumulating phase but never changing direction more than trivially. This approximation simplifies the mathematics dramatically, allowing fast Fourier-based solvers to run on the angle-by-angle projections independently. It works admirably for isolated cells and thin sections. But as reconstructed field of view and resolution grow together — the two axes along which gigavoxel datasets are defined — the assumption breaks down. Thick or densely structured specimens scatter light more than once, and those higher-order scattering events inject systematic errors that standard algorithms either ignore or mistake for genuine structure, producing artifacts that can be mistaken for biological features.

The new framework confronts this limitation head-on by embedding a multiple-scattering-aware forward model directly into the tomographic reconstruction. Instead of treating each projection as a simple line integral through the refractive-index distribution, the method models wave propagation through the sample using a multi-slice formulation. In this picture, the three-dimensional specimen is conceptually divided into a stack of thin slices along the beam direction. The wave is propagated through one slice, picks up the local phase, then is free-space propagated to the next slice, where it interacts again. Repeated through the full stack, this scheme naturally generates the beam-broadening, inter-slice coupling, and dynamical diffraction effects that single-pass approximations miss. Crucially, the inverse problem — recovering the slice-by-slice refractive index from the measured holograms — is solved iteratively, with the forward model refined at each step until the simulated exit wave agrees with the data.

What makes the achievement notable is not merely the physical fidelity of the model but the sheer scale at which it can be executed. Multi-slice wave propagation, when performed naively, is orders of magnitude more expensive than projection-based tomography, and iterative inversion multiplies that cost. The researchers coupled their scattering-aware solver to a computational architecture that distributes the work across many processing units, exploiting the fact that the propagation between slices is dominated by fast Fourier transforms — operations that parallelize efficiently and that modern graphics processors execute at extraordinary throughput. Combined with strategies for managing the gigantic datasets involved, in which each individual projection can occupy many gigabytes and the final reconstructed volume approaches a billion or more voxels, the pipeline brings what was previously a computationally prohibitive calculation within practical reach.

The payoff is quantitative imaging that remains accurate where conventional methods visibly falter. In single-scattering-based reconstructions of thick, strongly structured specimens, multiple scattering manifests as shadowing, ring-like artifacts, spatially varying resolution loss, and systematic underestimation of electron density in dense regions. These are not cosmetic defects. Quantitative electron density is precisely the measurable that makes holotomography scientifically valuable: it underpins the identification of organelles in cells, the characterization of material phases and porosity in functional materials, and the comparison of healthy and diseased tissue. By modeling the full wave-optical interaction, the new approach recovers electron densities that remain consistent across regions of very different thickness and composition, restoring confidence in the numbers rather than only the pictures.

The gigavoxel scale matters for a practical reason that is easy to overlook in discussions of resolution. Field of view and resolution trade against each other for a fixed detector and beam geometry: to image a large object at high resolution, one must either stitch together many partially overlapping exposures or record enormous detector frames, and in both cases the data volume grows with the cube of the linear resolution improvement. Doubling resolution in all three dimensions yields an eightfold increase in voxels. Datasets at the gigavoxel scale therefore represent the threshold at which whole, intact specimens — an entire cell in three dimensions at nanometre detail, or a sizable volume of battery electrode or bone — can be captured in a single self-consistent reconstruction rather than assembled from fragments, with all the seams and inconsistencies that assembly entails.

Lenslessness is central to reaching this scale. Refractive and diffractive X-ray lenses suffer from limited aperture, efficiency losses, and aberrations, and their use constrains both the achievable field of view and the fidelity of the recovered wavefront. Computed diffractive imaging replaces the lens’s fixed transfer function with an algorithmic reconstruction, letting the detector — which can be made large, efficient, and linear — define the numerical aperture. The cost is computational burden, which is exactly where the new work’s contribution lies: it shows that the computational overhead of a wave-optically accurate model can be absorbed at the very scales where lensless imaging offers its greatest advantages.

The implications extend across the communities that depend on synchrotron and X-ray free-electron laser facilities. For structural biologists, accurate gigavoxel-scale holotomography opens the prospect of imaging whole cryo-preserved cells and small organisms quantitatively, complementing electron tomography’s exquisite resolution with the penetration depth that only X-rays provide. For materials scientists, the technique promises non-destructive, quantitative three-dimensional characterization of energy-storage materials, catalysts, and structural alloys at length scales bridging the gap between electron microscopy and conventional computed tomography. And for the photon-source community, the demonstration establishes that the next generation of brighter, more coherent sources can be exploited fully only if reconstruction algorithms evolve in step — a message that resonates as diffraction-limited storage rings and free-electron lasers come online worldwide.

Challenges remain before such reconstructions become routine. Scattering-aware solvers demand accurate knowledge of experimental parameters — propagation distances, beam profiles, and detector geometry — because errors in these inputs propagate through the multi-slice model in ways that simple approximations tolerate more gracefully. Convergence of the iterative inversion must be monitored carefully for thick, strongly scattering samples, and the data and memory footprints will continue to strain storage and workflow infrastructure at user facilities. Yet the direction is unmistakable. As computational power grows and wave-optical forward models mature, the dividing line between what can be measured and what must be assumed continues to shift toward measurement. Gigavoxel-scale, multiple-scattering-aware lensless holotomography marks a concrete step across that line, bringing quantitative, non-destructive, nanometre-resolution three-dimensional imaging of whole intact specimens closer to everyday practice.

Subject of Research: Gigavoxel-scale multiple-scattering-aware lensless X-ray holotomography

Article Title: Gigavoxel-scale multiple-scattering-aware lensless holotomography

Article References: Rogalski, M., Winnik, J., Dudek, J., Arcab, P., Wdowiak, E., Matryba, P., Stefaniuk, M., Zdańkowski, P., & Trusiak, M. (2026). Gigavoxel-scale multiple-scattering-aware lensless holotomography. Light: Science & Applications, 15(1), Article 381. https://doi.org/10.1038/s41377-026-02416-0

Image Credits: AI Generated

DOI: 10.1038/s41377-026-02416-0

Keywords: holotomography, X-ray phase contrast, lensless imaging, multiple scattering, multi-slice method, computed tomography, synchrotron imaging, electron density, gigavoxel reconstruction, computational imaging, X-ray optics, nanoscale imaging

Hydrogen activation, the splitting of the tightly bound H–H bond, is famously difficult. Molecular hydrogen is stable and largely inert, which is precisely why catalysts such as platinum are so valuable. On a platinum surface, the molecule adsorbs, stretches and dissociates into individual hydrogen atoms that can then participate in downstream chemistry. For decades, scientists have measured how quickly this happens and how it depends on temperature, pressure and surface structure. What they could not do, until now, is map the reaction with nanoscale spatial resolution while simultaneously pumping the system with optical energy stored in plasmons, the collective oscillations of conduction electrons that can concentrate light into nanoscopic volumes.

Plasmons have become one of the hottest topics in physical chemistry because they promise to do something remarkable: take abundant visible light and squeeze its energy into regions of space far smaller than the wavelength of the light itself. When light strikes a metallic nanostructure, the electrons slosh back and forth coherently, creating intense local electromagnetic fields at edges, tips and gaps. These hot spots can dramatically accelerate chemical reactions, in some cases enabling chemistry that simply will not proceed under ordinary thermal conditions. Yet a long-standing frustration has shadowed the field. Spectroscopic measurements of plasmon-driven catalysis typically average over millions or billions of sites on a surface, leaving researchers to debate whether the enhancement is truly electromagnetic, thermal, or driven by energetic charge carriers called hot electrons.

The new study cuts through that ambiguity by combining plasmonic excitation with a technique capable of nanoscale chemical imaging. The researchers devised an approach in which the catalytic activity of a platinum surface could be visualized with a spatial resolution approaching tens of nanometers, revealing precisely which regions of the surface light up with hydrogen activation when plasmons are excited. Rather than reporting a single rate constant for the whole sample, the measurement delivers a spatial map, an activity landscape in which the influence of local geometry, field strength and plasmonic hot spots is laid bare.

The choice of Pt(111) is significant. This crystallographic plane is the smoothest, most densely packed face of platinum and serves as the reference surface against which virtually all models of platinum catalysis are calibrated. Decades of ultrahigh-vacuum surface science have established how hydrogen adsorbs and dissociates on it under well-controlled conditions. By anchoring their plasmon-enhanced measurements to this benchmark surface, the team could interpret their nanoscale maps against a deep existing body of knowledge, isolating the contribution that plasmonic excitation makes over and above ordinary thermal catalysis.

The central finding is striking: hydrogen activation on the platinum surface is not uniform when plasmons are engaged. Instead, the reaction is strongly localized, concentrated in regions where the optical fields are amplified. The nanoscale visualization demonstrates that plasmon excitation does not merely heat the whole surface or produce a uniform boost in reactivity. Rather, the enhancement is spatially patterned, tracking the distribution of the electromagnetic near-fields generated by the collective electron oscillations. This spatial correlation between optical hot spots and chemical activity is precisely the kind of evidence the plasmon-catalysis community has been seeking, because it distinguishes true field-driven enhancement from diffuse thermal effects that would raise activity everywhere at once.

From a mechanistic standpoint, the result lends strong support to the picture in which plasmon decay generates energetic charge carriers, hot electrons and hot holes, that can transfer into the antibonding orbitals of adsorbed hydrogen molecules, weakening the H–H bond and lowering the barrier to dissociation. Alternatively, the intense local fields can directly polarize the molecule, stretching the bond before it even contacts the surface. The nanoscale maps do not by themselves settle every mechanistic detail, and the authors are careful about what their data do and do not prove. But by showing that activity concentrates where the fields concentrate, the work establishes a causal spatial link that bulk-averaged spectroscopy could never deliver, and it provides quantitative constraints that any proposed mechanism must now satisfy.

The technical achievement behind these observations should not be underestimated. Imaging a chemical reaction at nanometer resolution requires balancing several demanding constraints simultaneously. The measurement must be sensitive enough to detect hydrogen, the lightest and most elusive of adsorbates. It must maintain the integrity of the atomically defined platinum surface throughout the experiment. And it must permit controlled optical excitation of the plasmonic modes without overwhelming the signal with background heating. The experimental architecture described in the paper threads this needle, pairing a pump pathway for plasmon excitation with a probe pathway that reads out the local chemical state of the surface. The result is essentially a microscope for catalytic function rather than merely for structure.

The implications extend well beyond a single surface and a single molecule. Hydrogen activation on platinum underpins proton-exchange membrane fuel cells, electrolysers and a vast range of industrial hydrogenation processes. If plasmonic excitation can steer and amplify that activation step with spatial precision, catalyst designers gain a new dimension of control: not just what a catalyst is made of, but where on its surface the chemistry happens and how strongly light is coupled into it. This opens a concrete design pathway toward photocatalysts in which sunlight directly supplements or replaces thermal energy, potentially reducing the energy footprint of hydrogen-based technologies. It also suggests a strategy for catalysts that can be switched on and off with light, a level of temporal control that conventional thermal catalysis cannot offer.

The work also delivers a methodological gift to the field. Nanoscale visualization of plasmon-enhanced reactivity provides a template that other groups can adapt to different catalytic systems, from other transition-metal surfaces to bimetallic nanoparticles and semiconductor-supported metal clusters. Any long-standing mechanistic controversy in plasmon catalysis, whether about hot carriers, thermal gradients or near-field effects, can now be interrogated with the same spatially resolved toolkit. In science, the ability to see a phenomenon directly has repeatedly proven more decisive than any indirect argument, and this study hands the plasmon-catalysis community exactly that capability for one of the most important reactions in chemistry.

There remain, of course, substantial steps between a benchmark ultrahigh-vacuum demonstration and a working industrial device. Real catalysts operate at high pressure, on complex nanoparticle morphologies, under conditions far removed from the carefully controlled environment of a surface-science experiment. The plasmonic enhancements reported here must be scaled, made durable and integrated into reactor engineering before they can influence the hydrogen economy at scale. Yet the conceptual barrier has fallen. Plasmon-enhanced hydrogen activation on platinum is no longer a hypothesis supported by averaged spectra; it is a mapped, visualized phenomenon whose spatial structure can be measured, modeled and ultimately engineered. For a field that has spent years arguing about what plasmons really do in catalysis, seeing is, quite literally, believing.

The distinction between spatially patterned and uniform enhancement carries practical weight for how plasmonic catalysts should be engineered. If activity tracked only temperature, the sensible design goal would be maximizing heat delivery across the entire active surface. Because the observed reactivity instead follows the near-field distribution, designers can in principle concentrate catalytic function at specific sites, such as nanoparticle corners, edges or narrow gaps between adjacent structures, where field amplification is strongest. This decouples the location of light absorption from the location of chemical turnover, a degree of freedom unavailable in purely thermal catalysis.

Hydrogen is a particularly demanding test case for such imaging. Its single electron offers a very small scattering cross-section, and its adsorbed states on platinum are mobile and weakly bound, making them easy to overlook or displace during measurement. That the technique resolves hydrogen activation at all, let alone with spatial contrast, suggests the approach could be extended to other light adsorbates and reaction intermediates that have resisted direct nanoscale observation.

The benchmark character of Pt(111) also matters for theory. Computational models of hydrogen dissociation on this surface, built from density functional theory and refined over decades, now have a plasmon-enhanced counterpart against which to be tested. Any mechanism proposing hot-carrier transfer, near-field polarization or transient thermal excitation must reproduce not only an overall rate enhancement but also its spatial fingerprint. This converts a class of mechanistic debates from qualitative argument into quantitative comparison.

Finally, the study illustrates a broader trend in which optical excitation and local probe microscopy are merged into a single experimental platform. As such platforms mature, spatially resolved maps of light-driven reactivity may become as routine as conventional kinetic measurements, reshaping how photocatalytic materials are screened and optimized.

Subject of Research: Nanoscale imaging of plasmon-enhanced hydrogen molecule activation on a platinum (111) surface

Article Title: Nanoscale visualization of plasmon-enhanced hydrogen activation on a Pt(111) surface

Article References: Cai, Z.-F., Manae, M. A., Tang, Z.-X., Zhang, J.-X., Zhang, Y., Richardson, J. O., & Kumar, N. (2026). Nanoscale visualization of plasmon-enhanced hydrogen activation on a Pt(111) surface. Nature Chemistry. https://doi.org/10.1038/s41557-026-02245-z

Image Credits: AI Generated

DOI: 10.1038/s41557-026-02245-z

Keywords: plasmonics, hydrogen activation, platinum catalyst, Pt(111), nanoscale imaging, hot electrons, surface science, photocatalysis, catalysis mechanisms, hydrogen economy, near-field enhancement, chemical imaging