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At least 127 records · Page 7

2D Polyhedral Template Matching for Atomic Resolution Microscopy

SAND2024-13879O The 2D Polyhedral Template Matching for Atomic Resolution Microscopy is a suite of functions for analyzing atomic resolution electron microscopy images using the 2D polyhedral template matching (2D-PTM) method. This software analyzes atomic resolution microscopy data from electron microscopic imaging or scanning probe microscopies. The primary application is for identifying different crystal phases, crystal orientations, and defect structures obtained in such atomic resolution images. Written in MATLAB and starting from an atomic resolution image, the code identifies the positions of atomic intensity peaks. It then matches predefined structural templates to the local atomic environments. Outputs include the local structural identification, the template scaling factor and rotation angle, root-mean-squared deviation (RMSD), and centrosymmetry parameter.

Medlin, Douglas↗

Raw electron microscopy images for "The Importance of Nano-edges in Atomic Stencilling and Chiroptically Active Assembly of Patchy Gold Tetrahedra"

This dataset contains the raw transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images used in the main figures of the paper “The Importance of Nano-edges in Atomic Stencilling and Chiroptically Active Assembly of Patchy Gold Tetrahedra (2026).” All the images were acquired at the Materials Research Laboratory, University of Illinois at Urbana-Champaign, by Qian Chen group. 1. We provide five subfolders, each named according to the corresponding figure numbers in the paper. 2. All files in the subfolders for Figures 1–3 and 5 are named as "Panel [letter]_*", where [letter] (e.g., a, b, c) represents the raw images used for the corresponding panels. 3. All files in the subfolder for Figure 4 correspond to panel f and show the configurations of patchy tetrahedra synthesized at varying concentrations of iodide and 2-naphthalenethiol. They are named "Experiment_[number]", where [number] represents the corresponding data points in the phase diagram. 4. In TEM images, the bright and dark regions indicate the polymer patches and nanoparticle cores, respectively. 5. In SEM images, the bright and dark regions indicate the nanoparticle cores and polymer patches, respectively. 6. Abbreviations in file names: HAADF-STEM (high-angle annular dark-field scanning transmission electron microscopy), PINEM (photon-induced near-field electron microscopy), and RCP/LCP (left-/right-handed circularly polarized).

chirality↗

Modal focal adaptive optics for Bessel-focus two-photon fluorescence microscopy

Adaptive optics (AO) improves the spatial resolution of microscopy by correcting optical aberrations. While its application has been well established in microscopy modalities utilizing a circular pupil, its adaptation to systems with non-circular pupils, such as Bessel-focus two-photon fluorescence microscopy (2PFM) with an annular pupil, remains relatively uncharted. Herein, we present a modal focal AO (MFAO) method for Bessel-focus 2PFM. Measuring and correcting aberration using a spatial light modulator placed in conjugation with the focal plane of the microscope objective, MFAO employs Zernike annular polynomials — a first in AO implementation — to achieve performance on par with a previous zonal AO method, but with a notably simplified optical configuration. We validated the performance of MFAO in correcting artificial and sample-induced aberrations, as well as in in vivo imaging of zebrafish larvae and mouse brains. By expanding the application of modal AO to annular pupils as well as aberration measurement and correction to a wavefront modulator at the objective focal plane, MFAO represents a notable advancement in the implementation of AO in microscopy.

47 OTHER INSTRUMENTATION↗

Real-time image denoising of mixed Poisson–Gaussian noise in fluorescence microscopy images using ImageJ

Fluorescence microscopy imaging speed is fundamentally limited by the measurement signal-to-noise ratio (SNR). To improve image SNR for a given image acquisition rate, computational denoising techniques can be used to suppress noise. However, common techniques to estimate a denoised image from a single frame either are computationally expensive or rely on simple noise statistical models. These models assume Poisson or Gaussian noise statistics, which are not appropriate for many fluorescence microscopy applications that contain quantum shot noise and electronic Johnson–Nyquist noise, therefore a mixture of Poisson and Gaussian noise. In this paper, we show convolutional neural networks (CNNs) trained on mixed Poisson and Gaussian noise images to overcome the limitations of existing image denoising methods. The trained CNN is presented as an open-source ImageJ plugin that performs real-time image denoising (within tens of milliseconds) with superior performance (SNR improvement) compared to conventional fluorescence microscopy denoising methods. The method is validated on external datasets with out-of-distribution noise, contrast, structure, and imaging modalities from the training data and consistently achieves high-performance ( > <#comment/> 8 d B ) denoising in less time than other fluorescence microscopy denoising methods.

47 OTHER INSTRUMENTATION↗

High-Energy X-ray Diffraction Microscopy for Nuclear Forensics (FY23 Project Report)

Morphological information on nuclear material has been identified using visible light and scanning electron microscopy. These identify qualitative differences in particle morphology. Three-dimensional imaging of materials through alternating scanning electron microscopy imaging and focused ion beam milling has also been used. Unfortunately, these techniques are time- and labor-intensive, with significant sample preparation required and lengthy analysis times. Further, the resulting 3D images are qualitative, require manual identification, and do not capture statistically-representative populations. High energy X-ray 3D imaging using a direct-beam or diffracted-beam (High-Energy Diffraction Microscopy) have been developed at the Advanced Photon Source and can produce quantitative information on grains (phase, location, etc.) and pores (size distribution, sphericity) in a material. These techniques require only minutes to characterize a sample volume and are non-destructive, thus suitable for a wide range of existing samples and for confirmatory analyses to be carried out using conventional microscopy techniques.

36 MATERIALS SCIENCE↗

Imaging of Unstained DNA Origami Triangles with Electron Microscopy

Imaging of scaffolded DNA and DNA origami nanostructures has been dominated by atomic force microscopy of samples immobilized on bulk substrates. Less commonly used for DNA imaging are electron microscopy techniques, which are typically carried out either after negative staining of DNA or by direct imaging using a bright field cryo-TEM. Here, direct imaging of unstained DNA origami nanostructures on thin electron-transparent substrates utilizing high angular annular dark field scanning transmission electron microscopy )(HAADFSTEM) is reported. This approach establishes a simple method for depositing and imaging intact DNA triangles with mass-thickness contrast, sufficient to measure the scaffold-to-scaffold distances and the length of the triangle’s seam. The signal-to-noise ratio (SNR) of the DNA supported on amorphous carbon as a function of the carbon thickness is measured on three types of commercially available TEM grids to analyze the image resolution. This allows for an edge detection of ~1 nm height DNA triangles on carbon substrates as thick as ~25 nm. Additional observations on the effect on SNR with the imaging modes are discussed. The effect of cation concentration used for pre-treating the grid surface on the image resolution is also explored. Our work presents proof-of-concept results demonstrating that electron microscopy can be utilized to resolve key elements of the DNA origami triangle, without staining or employing exceedingly complicated preparation protocols.

Londono-Calderon, Alejandro↗

Inactivation of Fluorescent Lipid Bilayers by Irradiation With 300 keV Electrons Using Liquid Cell Transmission Electron Microscopy

Liquid cell transmission electron microscopy allows for imaging of samples in a fully hydrated state at high resolution and has the potential for visualizing static or dynamic biological structures. However, the ionizing nature of the electron beam makes it difficult to discern real physiological dynamics from radiation induced artifacts within liquid cell samples. Electron flux thresholds for achieving high resolution structures from biological samples frozen in ice have been described extensively by the cryo-electron microscopy field, while electron flux thresholds which do not result in a functional change for biological samples within the hydrated environment of a transmission electron microscope liquid cell is less clear. Establishing these functional thresholds for biologically relevant samples is important for accurate interpretation of results from liquid cell experiments. Here we demonstrate the electron damage threshold of fluorescently tagged lipid bilayers by quantifying the change in fluorescence before and after electron exposure. We observe the reduction of fluorescent signal in bilayers by 25% after only 0.0005 e − /Å 2 and a reduction of over 90% after 0.01 e − /Å 2 . These results indicate that the loss of function occurs at irradiation thresholds far below a typical single high resolution (scanning) transmission electron microscopy image and orders of magnitude below fluxes used for preserving structural features with cryo-electron microscopy.

Moser, Trevor↗

The Fluids Integrated Rack and Light Microscopy Module Integrated Capabilities

The Fluids Integrated Rack (FIR), a facility class payload, and the Light Microscopy Module (LMM), a subrack payload, are scheduled to be launched in 2005. The LMM integrated into the FIR will provide a unique platform for conducting fluids and biological experiments on ISS. The FIR is a modular, multi-user scientific research facility that will fly in the U.S. laboratory module, Destiny, of the International Space Station (ISS). The first payload in the FIR will be the Light Microscopy Module (LMM). The LMM is planned as a remotely controllable, automated, on-orbit microscope subrack facility, allowing flexible scheduling and control of fluids and biology experiments within the FIR. Key diagnostic capabilities for meeting science requirements include video microscopy to observe microscopic phenomena and dynamic interactions, interferometry to make thin film measurements with nanometer resolution, laser tweezers for particle manipulation, confocal microscopy to provide enhanced three-dimensional visualization of structures, and spectrophotometry to measure photonic properties of materials. The LMM also provides experiment sample containment for frangibles and fluids. This paper will provide a description of the current FIR and LMM designs, planned capabilities and key features. In addition a brief description of the initial five experiments planned for LMM/FIR will be provided.

Motil, Susan M.↗

Fast Scanning Probe Microscopy via Machine Learning: Non-Rectangular Scans with Compressed Sensing and Gaussian Process Optimization

Fast scanning probe microscopy enabled via machine learning allows for a broad range of nanoscale, temporally resolved physics to be uncovered. However, such examples for functional imaging are few in number. Here, using piezoresponse force microscopy (PFM) as a model application, a factor of 5.8 reduction in data collection using a combination of sparse spiral scanning with compressive sensing and Gaussian process regression reconstruction is demonstrated. It is found that even extremely sparse spiral scans offer strong reconstructions with less than 6% error for Gaussian process regression reconstructions. Further, the error associated with each reconstructive technique per reconstruction iteration is analyzed, finding the error is similar past ≈15 iterations, while at initial iterations Gaussian process regression outperforms compressive sensing. Finally, this study highlights the capabilities of reconstruction techniques when applied to sparse data, particularly sparse spiral PFM scans, with broad applications in scanning probe and electron microscopies.

36 MATERIALS SCIENCE↗

Electron microscopy techniques employed to explore mitochondrial defects in the developing rat brain following ketamine treatment

Ketamine, an FDA-approved N-methyl-D-aspartate (NMDA) receptor antagonist, is commonly used for general pediatric anesthesia. Accumulating evidence has indicated that prolonged exposure to ketamine induces widespread apoptotic cell death in the developing brains of experimental animals. Although mitochondria are known to play a pivotal role in cell death, little is known about the alterations in mitochondrial ultrastructure that occur during ketamine-induced neurotoxicity. The objective of this pilot study was to utilize classic and contemporary methods in electron microscopy to study the impact of ketamine on the structure of mitochondria in the developing rat brain. While transmission electron microscopy (TEM) was employed to comprehensively study mitochondrial inner membrane topology, serial block-face scanning electron microscopy (SBF-SEM) was used as a complementary technique to compare the overall mitochondrial morphology from a representative treated and untreated neuron. In this study, postnatal day 7 (PND-7) Sprague-Dawley rats were treated with ketamine or saline (6 subcutaneous injections × 20 mg/kg or 10 ml/kg, respectively, at 2-h intervals with a 6-h withdrawal period after the last injection, n=6 each group). Samples from the frontal cortex were harvested and analyzed using TEM or SBF-SEM. While classic TEM revealed that repeated ketamine exposure induces significant mitochondrial swelling in neurons, the newer technique of SBF-SEM confirmed the mitochondrial swelling in three dimensions (3D) and showed that ketamine exposure may also induce mitochondrial fission, which was not observable in the two dimensions (2D) of TEM. Furthermore, 3D statistical analysis of these reconstructed mitochondria appeared to show that ketamine-treated mitochondria had significantly larger volumes per unit surface area than mitochondria from the untreated neuron. The ultrastructural mitochondrial alterations demonstrated here by TEM and SBF-SEM support ketamine’s proposed mechanism of neurotoxicity in the developing rat brain.

60 APPLIED LIFE SCIENCES↗

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy

What does materials science look like in the “Age of Artificial Intelligence?” Each material’s domain—synthesis, characterization, and modeling—has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

2D materials↗

Atomic force microscopy imaging of fragments from the Martian meteorite ALH84001

A combination of scanning electron microscopy (SEM) and environmental scanning electron microscopy (ESEM) techniques, as well as atomic force microscopy (AFM) methods has been used to study fragments of the Martian meteorite ALH84001. Images of the same areas on the meteorite were obtained prior to and following gold/palladium coating by mapping the surface of the fragment using ESEM coupled with energy-dispersive X-ray analysis. Viewing of the fragments demonstrated the presence of structures, previously described as nanofossils by McKay et al. (Search for past life on Mars--possible relic biogenic activity in martian meteorite ALH84001. Science, 1996, pp. 924-930) of NASA who used SEM imaging of gold-coated meteorite samples. Careful imaging of the fragments revealed that the observed structures were not an artefact introduced by the coating procedure.

Carbonates/analysis↗

Time-Resolved Electrical Scanning Probe Microscopy of Layered Perovskites Reveals Spatial Variations in Photoinduced Ionic and Electronic Carrier Motion

We study light-induced dynamics in thin films comprising Ruddlesden–Popper phases of the layered 2D perovskite (C 4 H 9 NH 3 ) 2 PbI 4 . We probe ionic and electronic carrier dynamics using two complementary scanning probe methods, time-resolved G-mode Kelvin probe force microscopy and fast free time-resolved electrostatic force microscopy, as a function of position, time, and illumination. Here, we show that the average surface photovoltage sign is dominated by the band bending at the buried perovskite–substrate interface. However, the film exhibits substantial variations in the spatial and temporal response of the photovoltage. Under illumination, the photovoltage equilibrates over hundreds of microseconds, a time scale associated with ionic motion and trapped electronic carriers. Surprisingly, we observe that the surface photovoltage of the 2D grain centers evolves more rapidly in time than at the grain boundaries. We propose that the slower evolution at grain boundaries is due to a combination of ion migration occurring between PbI 4 planes, as well as electronic carriers traversing grain boundary traps, thereby changing the time-dependent band unbending at grain boundaries. These results provide a model for the photoinduced dynamics in 2D perovskites and are a useful basis for interpreting photovoltage dynamics on hybrid 2D/3D structures.

14 SOLAR ENERGY↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

Imaging Carrier Dynamics and Transport in Hybrid Perovskites with Transient Absorption Microscopy

In this review, the recent progress in using transient absorption microscopy to image charge transport and dynamics in semiconducting hybrid organic–inorganic perovskites is discussed. The basic principles, instrumentation, and resolution of transient absorption microscopy are outlined. With temporal resolution as high as 10 fs, sub-diffraction-limit spatial resolution, and excited-state structural resolution, these experiments have provided crucial details on charge transport mechanisms that have been previously obscured in conventional ultrafast spectroscopy measurements. Morphology-dependent mapping unveils spatial heterogeneity in carrier recombination and cooling dynamics. By spatially separating the pump and probe beams, carrier transport across grain boundaries has been directly visualized. Further, femtosecond temporal resolution allows for the examination of nonequilibrium transport directly, revealing extraordinarily long-range hot carrier migration. The application of transient absorption microscopy is not limited to hybrid perovskites but can also be useful for other polycrystalline materials in which morphology plays an important role in carrier transport.

36 MATERIALS SCIENCE↗

Electron Microscopy Approaches to Unraveling the Structure of Amorphous Materials

Determining atomic structures in crystalline materials—where atoms are arranged in rigid, periodic lattices—has been highly successful using probes such as electrons, X-rays, and neutrons. In contrast, amorphous materials, despite their ubiquity and technological importance, remain far more challenging to characterize with comparable accuracy and precision. This review highlights existing, emerging, and potential (scanning) transmission electron microscopy ((S)TEM) techniques for probing short- and medium-range order in amorphous materials. Approaches ranging from high-resolution (S)TEM imaging and selected electron diffraction pattern to four-dimensional STEM (4D-STEM) based pair distribution function, fluctuation electron microscopy, tomography, ptychography, and spectroscopic methods are discussed, emphasizing their ability to provide complementary insights across multiple length scales—from sub-angstrom local environments to nanometer-scale correlations. Here, we further explore the promise of multimodal and correlative strategies, as well as the growing role of machine learning and physics-informed AI in enabling real-time, quantitative interpretation of complex structural signatures. Together, these advances point toward a future where electron microscopy not only reveals the hidden order in amorphous systems but also establishes robust structure–property relationships, paving the way for materials innovation in disordered matter.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Visualizing quantum phenomena at complex oxide interfaces: An atomic view from scanning transmission electron microscopy

Complex oxide interfaces have been one of the central focuses in condensed matter physics and material science. Over the past decade, aberration corrected scanning transmission electron microscopy and spectroscopy has proven to be invaluable to visualize and understand the emerging quantum phenomena at an interface. In this paper, we briefly review some recent progress in the utilization of electron microscopy to probe interfaces. Furthermore, we discuss several important challenges for electron microscopy to advance our understanding on interface phenomena, from the perspective of variable temperature, magnetism, electron energy loss spectroscopy analysis, electronic symmetry, and defects probing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗