Research Highlights

Dichroic X-ray tomography resolves a sample’s 3D crystal orientation (linear dichroism) or magnetization (circular dichroism) from projections taken at varying beam directions and polarizations. Like most tomographic methods, its reconstruction assumes that absorption along a ray is a simple line integral of a local, voxel-independent absorption coefficient. This work showed that for linear dichroism that assumption can fail: as the beam crosses an anisotropic material whose optic axis is misaligned with the polarization, the polarization itself rotates dynamically. Using a finite-element Maxwell solver, full-field tomography of a 2000 Å aragonite Voronoi polycrystal was simulated at the O K-edge. Reconstructions indicated that polarization rotation through propagation (PRP) introduces real artifacts, including spurious grain boundaries, false orientation gradients, and the apparent splitting of single grains. The authors found that the reconstruction error increased by three orders of magnitude as the dichroism was tuned from weak (0.1) to full strength (1.0). Qualitatively, the observed reconstruction artifacts mimic genuine microstructure, demonstrating a potential for false conclusions to be drawn about a material’s orientational statistics or grain-boundary structure.

These results identify a previously underappreciated, physics-based limitation of linear dichroic orientation tomography, a technique of growing importance for imaging anisotropic functional materials. This work also supplies practical diagnostics, including degraded sinogram fit residuals and a rotationally invariant biaxiality measure that flags voxels where the uniaxial reconstruction is likely to break down. The authors chart concrete mitigation paths: acquiring redundant data across additional tilt and polarization conditions so the reconstruction can down-weight the worst-affected angles, operating at energies where dichroism is weak, or folding a beam-propagation model directly into the reconstruction. Additionally, they outline a fixed-point iterative scheme and a more robust model-based iterative reconstruction (MBIR) framework for performing propagation-aware reconstructions that keep dichroic tomography quantitatively reliable.

Currently, host-guest interactions in metal–organic frameworks (MOFs) are mainly understood via theoretical simulations, bulk characterization techniques, and x-ray diffraction, all of which can average out information related to defects, interfaces, and spatial heterogeneity among adsorption sites. Since these structural features can directly impact the functionality of MOFs we applied local probes to investigate these effects.  Specifically, we applied both 3D electron diffraction and 4D scanning transmission electron microscopy to structurally characterize and spatially visualize the effect of gas-loading and diamine functionalization in MOF crystals. In addition, complementary infrared scattering scanning near-field optical microscopy measurements confirmed spatial variations of chemisorbed CO₂ inside an individual crystal.

The results of our multimodal approach was the ability to map heterogeneity arising from host-guest interactions and material functionalization.  Our 3D electron diffraction data has provided the only ab initio electrostatic potential map of any variant of Mg₂(dobpdc), which has been an elusive structure. Our 4D-STEM images are, to our knowledge, the only dual-space (i.e., real and reciprocal space) visualizations of a MOF. Most importantly, although we have applied this methodology to a specific material of interest in gas storage and separation, we hope to introduce these microscopy techniques to the community as effective tools, complementary to the established bulk techniques, by which to evaluate and optimize synthetic and post-synthetic modification procedures of MOFs.

Colloidal semiconductor nanocrystals (NCs) offer remarkable tunability of optoelectronic properties through synthetic control of their size, shape, and composition. An emerging strategy is the synthesis of III-V nanocrystals in molten salts, where high temperatures and unique redox chemistry enable the production of highly crystalline binary, ternary, and quaternary semiconductor NCs. A notable example of the compositional complexity that can be achieved by these methods is the cation exchange of InP_1-yAs_y in a gallium-containing molten salt to yield In_1-xGa_xP_1-yAs_y NCs. However, the process by which Ga atoms migrate through the NC lattice, and the resulting elemental distributions, was not fully understood.

STROBE scientists, together with collaborators at the University of Chicago, employed advanced scanning transmission electron microscopy (STEM) methods to reveal the atomic structure and elemental distribution of NCs taken throughout the cation exchange process. High angle annular dark field (HAADF-STEM) imaging revealed only subtle changes in NC morphology, with the tetrahedral shape and zinc blende crystal structure largely maintained throughout the exchange. Energy dispersive x-ray spectroscopy (STEM-EDS) was used to map the elemental distribution of the NCs. To overcome the beam sensitivity and low STEM-EDS signal resulting from the NCs, extensive experimental optimization and novel image processing methods were applied to produce elemental maps representative of individual In_1-xGa_xP_1-yAs_y NCs. The elemental maps revealed that Ga first exchanges as the surface of NCs, before diffusing inward. The In/Ga distribution becomes more, but never completely homogeneous, resulting in a compositional gradient that persists at long annealing times. Modeling in COMSOL suggests that the rate of diffusion becomes progressively slower as the cation exchange progresses.

These findings demonstrate that cation exchange occurs through a diffusion-limited process, resulting in a graded elemental distribution and incomplete exchange even at long annealing times. The intentional use of graded elemental distributions in II-VI NCs for superior optoelectronic performance suggests that diffusion-limited exchange may be desirable for producing high-performance III-V NCs. Furthermore, the image processing methods developed in this work may be generally useful for the analysis of NCs by methods like EDS or electron energy loss spectroscopy.

Lensless imagers can make cameras far thinner than conventional optics and can compress rich scene information into a single measurement. But the same optical multiplexing that enables those advantages can also scramble a scene so strongly that reconstruction loses the information it needs. We address this design problem by evaluating lensless encoders through mutual information estimated directly from noisy measurements. By combining a probabilistic model of measurement distributions with a detector-noise model, we compare encoders without tying performance to any one reconstruction algorithm and quantify how object sparsity, encoder multiplexing, and noise interact. Across simulations, we show that dense objects are best matched to low-multiplexing encoders, whereas progressively sparser objects benefit from higher multiplexing. We then optimize phase-mask encoders for specific object classes, and these information-optimal designs outperform heuristic masks in mutual information while also improving downstream reconstruction quality. Experiments with a conventional lens, a random multi-focal lenslet array, and a diffuser reinforce the same lesson for dense natural images: more multiplexing can reduce recoverable information. By making information capture itself the design target, our work offers decoder-independent engineering rules for lensless imaging and other multiplexed computational imaging systems. Because the best encoder depends on the assumed object distribution and mutual information does not guarantee every task-specific outcome, the next step is to test robustness under distribution shift, alternate noise models, and specialized downstream tasks.

Ferroelectric materials such as hafnium zirconium oxide (HZO) are likely to form the basis of a next-generation memory technology.  For instance, replacing the conventional gate dielectric in a field-effect transistor (FET) with HZO can form a ferroelectric FET, or FeFET.  Chris Regan’s group at UCLA has been working with Suman Datta’s group at Georgia Tech to speed development of this exciting technology.  Standard scanning transmission electron microscopy (STEM) (see top left figure), shows the basic layout of a device fabricated at Georgia Tech, but it reveals little about its function.  STEM electron-beam induced current (EBIC) imaging at UCLA, on the other hand, shows exactly how the FeFET works.  With two EBIC transimpedance amplifiers (Fig. X, top right), the STROBE team can form two linear combinations.  The STEM EBIC sum image (see lower left figure), gives secondary-electron EBIC (SEEBIC) contrast. It maps the conductors, correctly showing that the electrode in the upper left corner is not connected to the gate, source, or drain. The STEM EBIC difference image (see lower right figure) gives electron-hole-pair separation contrast, and it is even more informative. It reveals the electric fields that control the FeFET’s function: the depolarization fields in the ferroelectric HZO where the gate electrode overlaps the semiconducting indium tungsten oxide (IWO).  Moreover, it reveals these fields just as well whether it has to image through 40 nm of palladium or not. Higher magnification images of the FeFET in both polarization states (not shown) show exactly how much of the ferroelectric switches, providing a structural explanation of the FeFET threshold voltages and memory window. This functional imaging technique – STEM EBIC imaging – is a unique and uniquely powerful development enabled by STROBE.

Amorphous materials — solids lacking long-range periodic order — are vital to technologies spanning thin-film electronics, solar cells, phase-change memory, magnetic components, biomedical devices, and quantum hardware. Yet their structural disorder has long prevented full three-dimensional (3D) atomic mapping. Despite major advances in probing short- and medium-range order, experimentally determining complete 3D atomic arrangements in amorphous solids remains challenging. Atomic electron tomography (AET) now offers a route to direct 3D atomic imaging without requiring crystallinity or averaging. In a forthcoming Nature paper, Miao and collaborators present a quantitative analysis of AET, showing how coordinated preprocessing, denoising, projection alignment, normalization, tomographic reconstruction, atom tracing, elemental classification, and atomic position refinement enable reliable 3D atomic coordinate and chemical-identity determination in amorphous materials. Using multislice-simulated datasets, they demonstrate accurate 3D reconstruction of amorphous Si, SiGeSn, and CoPdPt nanoparticles with picometer-scale precision across a range of noise levels. In the CoPdPt system, for example, 95.1 percent of Co, 99.0 percent of Pd, and 100 percent of Pt atoms are correctly identified with 3D positional precisions of 29, 12, and 6 pm. These results establish practical guidelines and quantitative benchmarks for accurate AET of non-crystalline materials, and the underlying workflow provides a general framework for high-fidelity 3D reconstruction in other tomographic imaging modalities.

Researchers from UCLA have used ultrafast electron diffraction to reveal a hidden electronic phase that cannot be reached by ordinary heating. The study focuses on 1T-TaS₂, a layered material in which electrons naturally organize into a periodic charge pattern known as a charge density wave. Theory has long suggested that such ordered electronic patterns could “melt” into a liquid-like state, but in this material a competing structural transformation occurs near 600 K and normally prevents that regime from being observed. By using femtosecond laser pulses, the experiment bypassed this limitation: the material was driven into a transient, superheated state while compressed electron pulses captured how the electronic order evolved in real time.

The diffraction measurements show that, after laser excitation, the charge order first disappears and then partially reforms through a sequence of intermediate states controlled by defects. At lower starting temperature, the diffraction pattern indicates a partially melted state: the regular spacing of the charge pattern is lost, but a preferred angular alignment remains. At higher temperature, the diffraction peaks spread into a nearly uniform ring, showing that both positional and angular order have disappeared. This is the experimental signature of a liquid charge density wave. More broadly, the work demonstrates how ultrafast electron diffraction can uncover short-lived phases of matter that are hidden from conventional equilibrium experiments.

A new approach for high-resolution, three-dimensional elemental imaging has been demonstrated using soft X-ray ptychographic tomography. This technique leverages both optical density and phase contrast reconstructions to identify elements from a single-energy tilt series, reducing acquisition time by more than half compared to traditional multi-energy tomography. The method was validated on nickel-alumina catalyst particles, where nickel nanoparticles were distinguished from the porous alumina matrix with nanometer-scale resolution. By combining high optical density and low phase contrast signals near an absorption edge, nickel precipitates were identified robustly within the reconstructed volumes, providing critical insights into how metallic particles exsolve and redistribute under catalytic conditions.

This advance opens the door for efficient, element-specific 3D characterization of complex materials, with particular relevance for catalytic systems where nanoscale compositional changes drive performance. The approach not only streamlines experiments at synchrotron facilities, where acquisition time is highly limited, but also establishes a scalable framework for future studies involving multiple transition metals. Such capabilities are essential for unraveling the nanoscale dynamics of catalytic processes, and ultimately for guiding the design of more efficient and durable catalysts for environmentally important applications such as methane reforming.