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Cryogenic electron microscopy (cryoEM), advanced through NSF’ STROBE, a National Science Foundation Science and Technology Center, enables unparalleled resolution for complex membrane proteins like the dystrophin-glycoprotein complex (DGC). DGC is critical in Duchenne Muscular Dystrophy (DMD), affecting 1 in 3,500–5,000 male newborns. This enormous membrane protein complex, with dystrophin at its core, links the extracellular matrix to the cytoskeleton, protecting muscle membranes during contraction. Its multi-subunit complexity defies traditional methods like X-ray crystallography. STROBE’s cutting-edge cryoEM techniques allowed us to image DGC from rabbit skeletal muscle directly, collecting ~27,000 high-resolution images for near-atomic resolution 3D reconstruction, bypassing recombinant artifacts and revealing structural details unattainable by prior approaches (see figure).

Zhou lab’s cryoEM study unveiled DGC’s “keychain-like” architecture. Extracellularly, a β-helix trimer (β-, γ-, δ-sarcoglycans) anchors dystroglycan to the matrix; mutations disrupting its flexible bend cause Limb-Girdle Muscular Dystrophy. Sarcospan stabilizes the transmembrane region via a β-DG-mediated interface, a promising therapeutic target. Cytoplasmically, novel interactions between β-DG, α-/δ-SG, and dystrophin’s ZZ domain, plus a conformationally dynamic WW-α-dystrobrevin interface, drive signaling. Over 110 mutations were mapped, linking structural defects to DMD, Becker, and Limb-Girdle dystrophies, clarifying disease mechanisms.

This STROBE-supported, NSF-funded cryoEM study elucidates DGC’s mechanoprotective role, guiding therapies like gene replacement and small-molecule stabilizers for muscular dystrophies. It showcases cryoEM’s transformative potential for native membrane complexes, with implications for other diseases like cardiomyopathies, advancing precision medicine.

The most ubiquitous form of aberration correction for microscopy is deconvolution; however, deconvolution relies on the assumption that the system’s point spread function is the same across the entire field of view. This assumption is often inadequate, but space-variant deblurring techniques generally require impractical amounts of calibration and computation. We present an imaging pipeline that leverages symmetry to provide simple and fast spatially varying deblurring. Our ring deconvolution microscopy method utilizes the rotational symmetry of most microscopes and cameras, and naturally extends to sheet deconvolution in the case of lateral symmetry. We derive theory and algorithms for ring deconvolution microscopy and propose a neural network based on Seidel aberration coefficients as a fast alternative. We demonstrate improvements in speed and image quality as compared to standard deconvolution and existing spatially varying deblurring across a diverse range of microscope modalities, including miniature microscopy, multicolor fluorescence microscopy, multimode fiber micro-endoscopy and light-sheet fluorescence microscopy. Our approach enables near-isotropic, subcellular resolution in each of these applications.

Ferroelectricity underpins many proposed next-generation memory technologies that are widely expected to have profound impacts on modern computing. Hf_0.5Zr_0.5O₂ (HZO) is the leading material candidate for the ultimate commercial implementation of ferroelectric memory because it is CMOS compatible, it has a large spontaneous polarization, and it can retain its ferroelectric properties in films as thin as 1 nm. Unfortunately, the crystal phase of HZO responsible for its ferroelectricity (orthorhombic phase, space group number 29) competes with several other non-ferroelectric phases of similar free energies, making stabilization of the orthorhombic phase a challenge. Encapsulating electrodes seem to play an important role in stabilizing the ferroelectric phase, but the mechanism by which they do so remains poorly understood.

Here, we examine a ferroelectric HZO capacitor with titanium nitride (TiN) electrodes using scanning transmission electronmicroscopy (STEM) imaging in plan view. The capacitor is encircled by a lithographically-defined TiN heater that we energize in situ. Conventional STEM imaging identifies crystal grains in the TiN electrodes and in the HZO film. Simultaneously acquired STEM electron beam-induced current (EBIC) images provide electric field contrast that highlights the ferroelectric domains. At low annealing temperatures we find that the HZO’s ferroelectric domain structure is correlated with the TiN electrodes’ grain structure. Annealing at higher temperatures causes the domains to outgrow the TiN grains. Eventually the HZO domains expand to the size of the HZO grains they inhabit.

Triple cation perovskites (TCPs) are organic-inorganic hybrid materials that first rose to prominence as efficient photovoltaic materials, yet also hold promise for other applications like lasing, exciton condensation, single photon emitter, photodetectors, or photocatalysis. Their high performance continues to surprise considering the nano- and microscale heterogeneities and high defect densities of the typically polycrystalline thin films used. It is believed that the soft dynamically deformable lattice and mobile cations have the unique ability to stabilize charge carriers by polaron formation. However, the material science of perovskites has remained largely empirical with a lack of spectroscopic access to the elementary processes defined at the low-energy scale of the electron and lattice dynamics in the infrared. The relevant information with its inter- and intragrain heterogeneity in composition and structure is lost in conventional spatially averaged spectroscopy or static imaging. 

Here a STROBE team from CU Boulder in collaboration with researchers from imo-imomec (Belgium) combined three nano-imaging modalities developed through STROBE previously, and in the application to an important hybrid perovskite photovoltaic material, provide for the first time a real space view of composition, lattice structure, and carrier dynamics simultaneously. Mid-infrared nano-spectroscopy of the ground state vibrational response probing composition and the static lattice parameter was correlated with excited state spectroscopy resolving both ps- to ns- polaron relaxation and associated coupled lattice dynamics. The researchers could watch for the first time the transient lattice deformation and cation-lattice coupling as the polaron forms, grows, and evolves into the long-lived carriers giving rise to the photovoltaic response. Our work shows how correlated ground and excited state structural and dynamics nano-imaging could guide optimization of composition and thin film preparation to transform the field from the conventional trial and error approach to a targeted material design.

Preterm birth is defined as delivery before 37 weeks of gestation and is a major factor in infant mortality worldwide. Premature birth can cause lifelong developmental disabilities for the child. Unfortunately, there is a significant lack of tools to assess preterm birth risk, which hinders patient care and the development of new treatments.

The aim of this effort was to develop a speculum-free, portable preterm imaging system (PPRIM) for cervical imaging; to test the polarization properties of birefringent samples using the PPRIM system; and to test the PPRIM under an IRB on healthy, non-pregnant volunteers for visualization and polarization analysis of cervical images.

The PPRIM can perform 4 × 3 Mueller-matrix imaging to characterize the remodeling of the uterine cervix during pregnancy. The PPRIM is built with a polarized imaging probe and a flexible insertable sheath made with a compatible flexible rubber-like material to maximize comfort and ease of use.

STROBE scientists demonstrated that the combination of Mueller-matrix imagery into a portable imaging system holds strong potential to aid in the early diagnosis and assistance for those at risk of preterm birth.

This device eliminates the need for a speculum used in standard clinical cervical examination. It can allow the system to be self-inserted, and future studies will focus on point-of-care testing.

The polarimetric results shown in this paper match well with earlier data on similar samples. This system can help reduce patient dropout during prenatal care. This tool’s ease of use and flexibility make it very suitable for in vivo polarization-sensitive imaging beyond the cervix. It could be added to various diagnostic tools focused on women’s health. With current healthcare trends emphasizing telemedicine and remote care, the PPRIM can provide better access and communication between healthcare providers and women through new information channels that weren’t available before.

Researchers from SLAC and UCLA have developed a compact radially magnetized permanent-magnet solenoid (PMS) that brings high-performance focusing of relativistic electron beams into a form factor ideal for next-generation imaging tools. The dual-ring PMS generates axial magnetic fields up to 1 T and achieves focal lengths below 10 cm for relativistic electrons, offering a cost-effective power-free, cryogen-free alternative to conventional solenoids. Detailed field characterization and modeling confirmed its ability to deliver precise, axisymmetric focusing while minimizing aberrations, meeting the stringent requirements of modern electron imaging experiments.

Tests at UCLA’s Pegasus beamline showed that the PMS can reduce the transverse size of 7 MeV electron bunches by an order of magnitude, down to tens of microns, in excellent agreement with simulations. This capability unlocks new opportunities for high-resolution and high-speed imaging: in ultrafast electron diffraction, the PMS acts as a post sample lens to magnify reciprocal-space patterns beyond detector limits, while in inverse Compton sources or microprobes it enables sub-10 μm beam waists, boosting brightness and spatial resolution.

Electron microscopy has been used throughout the years to visualize structural changes in materials undergoing phase transformations. However, there are always details about what happens right before a transformation and the repeatability of a transformation that are difficult to track. In this paper we demonstrated that electron microscopy coupled with high-speed direct electron detectors can be used to characterize the forward and reverse martensitic transformations exhibited in NiTi, with nanoscale precision, and at large fields of view. Our method enables direct observation and characterization of 3 unique B19′ martensite variants that are differentiated by the planes on which they appear. Moreover, we track their formation while cooling past the martensitic transformation temperature. The B19′ variant phases and associated strains are mapped at different temperature steps and are directly compared via intermittent 4D-STEM scans to study the transformation. The B2 austenite pre-transitional microstructure is compared to the martensite phase transformation after multiple temperature cycles in order to improve our understanding of cyclic evolution of the martensite lath structure. Our results demonstrated how 4D-STEM can improve our understanding of complex transformation mechanisms that are of particular importance for engineering materials such as shape memory alloys.

Microscopy and crystallography have long served as two foundational pillars of experimental science. Microscopy relies on lenses to visualize local structures, whereas crystallography determines the global atomic arrangement of crystals through diffraction. Over the past two decades, these traditionally distinct methodologies have been unified through the rise of computational microscopy, particularly coherent diffractive imaging (CDI) and ptychography. These approaches replace physical lenses with coherent scattering and algorithmic phase retrieval, overcoming long-standing resolution limits in conventional imaging. In a recent comprehensive review, Miao summarized how CDI and ptychography now deliver exceptional imaging performance across nine orders of magnitude in length scale, from sub-angstrom visualization of atomic structures to quantitative phase imaging of centimeter-scale tissues, all based on the same underlying physical principles and closely related iterative algorithms.

Beyond 2D reconstruction, CDI and ptychography can be integrated with advanced tomographic methods to achieve 3D imaging with unprecedented detail. These combined techniques have enabled the 3D atomic structure determination of crystal defects and amorphous materials, the mapping of magnetic and electronic textures in quantum and energy materials, and high-resolution, non-destructive 3D characterization of nanomaterials and integrated circuits. They have also facilitated quantitative phase imaging of biological tissues, cells, viruses, and protein complexes, extending computational microscopy into the life sciences.

The rapid progress in this field is driven by the convergence of multiple technological advances, including fourth-generation synchrotron radiation sources, X-ray free-electron lasers, tabletop high-harmonic generation, state-of-the-art electron and optical microscopes, high-dynamic-range detectors, and deep-learning–accelerated phase retrieval. As these capabilities continue to evolve, CDI and ptychography are poised to make even broader and deeper contributions across physics, chemistry, materials science, engineering, biology, and medicine in the coming years.

The convolutional network is the preferred option for handling large input sizes and is commonly used in neural networks for most applications. In this experiment we demonstrate the performance of a modified convolutional neural networks (CNN) using an exponent based weight. The Exponential Convolutional Neural Network (ECNN) was tested on bacteria classification, with different model deployed on edge devices such as a Raspberry Pi and Esp32. Additionally, we created a model with 3-output that can detect a specific bacteria like E. coli, aiding environmental engineers in improving efficiency. As a result, our 4-layer standard CNN model was able to achieve an accuracy of 85% for 30 bacteria strains and this 4-layer model was successfully deployed to an edge device (the Raspberry Pi 5), with model quantization using TensorFlow Lite. ECNN is having an accuracy of 68% on test set and 89% accuracy training set. This study shows the potential of deploying a CNN for bacterial detection on edge devices. Future work will be focused on improving model generalization, reducing overfitting, and improving real-time inference performance to create a more reliable and efficient system for the environment and water quality monitoring.

This study demonstrates that CNNs can be deployed on edge devices for bacterial detection, highlighting the potential applications for environmental engineers. It offers a method for developing real-time, low-cost water quality monitoring systems. Future work will focus on refining the model architecture, addressing overfitting, and improving the overall reliability of bacterial detection on edge devices.

High fidelity soft X-ray imaging using both tabletop and facility-scale light sources is very powerful, enabling static and dynamic imaging with ~10 nm spatial resolution. However, it can suffer from several challenges. First, phase-matched soft x-ray high harmonic generation (SXR HHG) produces a bright supercontinuum that is spatially and temporally coherent. However, reconstructing objects from broadband illumination poses a severe challenge to widely used phase retrieval techniques. The performance is further degraded by photon shot noise, detector noise, and parasitic scattering from optics. For example, stray scattered light can be a challenge for tomographic imaging – since at high tilt angles, this stray light can appear close to the scattered light from the sample (see image).

To address this challenge, STROBE developed the first ptychography algorithms that simultaneously model broadband illumination, shot/detector noise, and parasitic scattering. The first algorithm, PaCMAN, corrects bandwidth using numerical monochromatization, enabling ~4x faster data acquisition relative to ePIE when both are speed-optimized, and 1.5-2x lower dose when dose-optimized. Thus, PaCMAN can advance low-dose imaging of delicate materials (cells, polymers, catalysts). A variant, Ms. PaCMAN, replaces monochromatization with multiple wavelength-dependent modes, providing superior reconstructions to multi-wavelength ePIE, and should provide state-of-the-art reconstructions from broadband illumination across elemental absorption edges. Figure shows experimental data on soft x-ray ptychography of skyrmion samples from the COSMIC beamline at the ALS that was used to test the base ADMM algorithm in the monochromatic limit, demonstrating a substantial improvement relative to ePIE in the presence of shot noise and parasitic scattering.

This advance required the combination of x-ray imaging (Thrust II), new models and algorithms to optimize the image extraction (Thrust IV), and data from a COSMIC beam time.