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Results for “high-resolution electron microscopy”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

New Directions in Focused Ion Beam Induced Deposition for the Nanoprinting of Functional 3D Heterostructures

The focused ion beam (FIB) microscope is well established as a high-resolution machining instrument capable of site-selectively removing material down to the nanoscale. Beyond subtractive processing, however, the FIB can also add material via a technique known as focused ion beam induced deposition (FIBID). Using FIBID, the FIB can thus be employed for the direct-write of complex nanostructures. This work explores new directions in three-dimensional FIBID nanoprinting, harnessing unique features of helium and neon FIBs. In particular, the superior spatial resolution of these novel FIBs is leveraged to fabricate precise multimaterial architectures, an isotope effect is used to create satellite deposits, and dose-controlled implantation of the gaseous ions is used to engineer internal voids. In the context of voids, the fabrication of hollow nanopillars by helium-FIBID due to concurrent milling (as shown previously by others) is revisited. Insight into the chemical and structural composition of the nanostructures is obtained using advanced electron microscopy, accurately revealing buried interfaces, crystallite distributions, chemical compositions, and material transformations. Next-generation devices and technologies that could be enabled by the novel heterostructures demonstrated here are discussed, setting the stage for the potential evolution of FIBID into a versatile platform for functional nanomaterials design and fabrication.

FIBID↗
DOE OSTI2025

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High‐throughput combinatorial approach expedites the synthesis of a lead‐free relaxor ferroelectric system

Abstract Developing novel lead‐free ferroelectric materials is crucial for next‐generation microelectronic technologies that are energy efficient and environment friendly. However, materials discovery and property optimization are typically time‐consuming due to the limited throughput of traditional synthesis methods. In this work, we use a high‐throughput combinatorial synthesis approach to fabricate lead‐free ferroelectric superlattices and solid solutions of (Ba 0.7 Ca 0.3 )TiO 3 (BCT) and Ba(Zr 0.2 Ti 0.8 )O 3 (BZT) phases with continuous variation of composition and layer thickness. High‐resolution x‐ray diffraction (XRD) and analytical scanning transmission electron microscopy (STEM) demonstrate high film quality and well‐controlled compositional gradients. Ferroelectric and dielectric property measurements identify the “optimal property point” achieved at the composition of 48BZT–52BCT. Displacement vector maps reveal that ferroelectric domain sizes are tunable by varying {BCT–BZT} N superlattice geometry. This high‐throughput synthesis approach can be applied to many other material systems to expedite new materials discovery and properties optimization, allowing for the exploration of a large area of phase space within a single growth. image

36 MATERIALS SCIENCE↗
DOE OSTI2025

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↗
DOE OSTI2025

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗
DOE OSTI2025

Hybrid MBE Route to Adsorption-Controlled Growth of BaTiO 3 Membranes with Robust Polarization Switching

Freestanding ferroelectric membranes are promising for flexible electronics, nonvolatile memory, photonics, and spintronics, but their synthesis is challenged by the need for reproducibility with precise stoichiometric control. Here, we demonstrate the adsorption-controlled growth of single-crystalline, epitaxial BaTiO 3 films by hybrid molecular beam epitaxy (MBE) on a binary oxide sacrificial layer. Using a simple water-droplet lift-off method, we obtained submillimeter- to millimeter-sized membranes that retained crystallinity, as confirmed by high-resolution X-ray diffraction, and exhibited robust tetragonal symmetry, as verified by Raman spectroscopy. Impedance spectroscopy confirmed a high dielectric constant of ∼1340, reflecting the robust dielectric response of the membranes. Ferroelectric functionality was revealed by piezoresponse force microscopy (PFM) and further verified by polarization-electric field (P-E) loop measurements with Positive-Up-Negative-Down (PUND). The P-E loops exhibited a remnant polarization of ∼5 μC cm –2 and a coercive field of ∼63 kV cm –1 . Furthermore, these results were interpreted in relation to c- and a-domain configurations.

Raman spectroscopy↗
DOE OSTI2025

Atom Efficiency of Pd Sites for Methane Combustion: Single Atom Catalysts Versus Nanocatalysts

Methane combustion is an important reaction for energy production and methane removal from the atmosphere. This reaction highly relies on the use of noble metal Pd-based catalysts, which therefore drives the pursuit of catalysts with high atomic dispersion and activity. In this work, Pd/ceria catalysts dominated with Pd single atoms or nanosized Pd clusters (∼1 nm) are prepared and characterized by combining high-resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS), and Raman and X-ray absorption spectroscopy (XAS) techniques. By comparing the turnover frequencies (TOF; per every Pd atom) of Pd/ceria single atom catalysts and nanocatalysts, it is found that the atom efficiency of Pd is increased by 10 ∼30 times from single atom catalysts to nanocatalysts. For Pd single atom catalysts, although their activity can be tuned by changing the local structures, the intrinsic activity and number of active sites need to be further improved by engineering the surfaces of supports. For nanosized Pd species, despite the high TOF, the Pd atoms in the bulk structure are not directly participating in the catalytic reaction. Furthermore, this work highlights the importance of increasing the intrinsic activity of individual noble atoms, as well as the homogeneity of their local structures. For Pd/ceria systems reported in this work, our results indicate that from the application point of view, at the current stage, it is not practical to replace Pd nanocatalysts with single atom catalysts for methane combustion.

Pd↗
DOE OSTI2024

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Atomic-Scale Scanning of Domain Network in the Ferroelectric HfO 2 Thin Film

Ferroelectric HfO 2 -based thin films have attracted much interest in the utilization of ferroelectricity at the nanoscale for next-generation electronic devices. However, the structural origin and stabilization mechanism of the ferroelectric phase are not understood because the film is typically nanocrystalline with active yet stochastic ferroelectric domains. Here, in this study, electron microscopy is used to map the in-plane domain network structures of epitaxially grown ferroelectric Y:HfO 2 films in atomic resolution. The ferroelectricity is confirmed in free-standing Y:HfO 2 films, allowing for investigating the structural origin for their ferroelectricity by 4D-STEM, high-resolution STEM, and iDPC-STEM. At the grain boundaries of <111>-oriented Pca2 1 orthorhombic grains, a high-symmetry mixed-(R3m, Pnm2 1 ) phase is induced, exhibiting enhanced polarization due to in-plane compressive strain. Nanoscale Pca2 1 orthorhombic grains and their grain boundaries with mixed-(R3m, Pnm2 1 ) phases of higher symmetry cooperatively determine the ferroelectricity of the Y:HfO 2 film. It is also found that such ferroelectric domain networks emerge when the film thickness is beyond a finite value. Furthermore, in-plane mapping of oxygen positions overlaid on ferroelectric domains discloses that polarization is suppressed at vertical domain walls, while it is active when domains are aligned horizontally with subangstrom domain walls. In addition, randomly distributed 180° charged domain walls are confined by spacer layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization

Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure–property relationships. In this study, we uncover intricate shape evolutions and growth mechanisms in Co 3 O 4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the sizedependent shape evolution in colloidal nanocrystals. Utilizing population-wide imaging data encompassing over 441,067 nanocrystals, we analyze their characteristics and elucidate previously unobserved size-resolved shape evolution. This high-throughput statistical analysis is essential for representing the entire population accurately and enables the study of the size dependency of growth regimes in shaping nanocrystals. Our findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, we introduce the concept of an “onset radius,” which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

High-resolution high-throughput spatiotemporal strain imaging reveals loss mechanisms in a surface acoustic wave device

Surface acoustic wave devices are key components for processing radio frequency signals in wireless communication because these devices offer simultaneously high performance, compact size and low cost. The optimization of the device structure requires a quantitative understanding of energy conversion and loss mechanisms. Here we use stroboscopic full-field diffraction x-ray microscopy to reveal an unanticipated acoustic loss in a prototypical one-port resonator device. A non-uniform acoustic excitation in the active area was responsible for the substantial end and side leakages observed at the design frequency. Quantitative analysis of the strain amplitude using a wave decomposition method allowed the determination of several key device parameters. This high-resolution high-throughput spatiotemporal strain imaging technique is more generally applicable to the study of dynamic strain modulation in nanoscale acoustic, electronic, optical and quantum devices. The high sensitivity allows precise measurement of the strain modulation with picometer-scale amplitude.

Zhou, Tao [ESRF - The European Synchrotron, Grenob↗
DOE OSTI2025

Molecular-resolution imaging of ice crystallized from liquid water by cryogenic liquid-cell TEM

Despite the ubiquity of ice, a molecular-resolution image of nanoscopic defects or microstructures in ice crystallized from liquid water has never been obtained. This is mainly due to the difficulties in preparing and preserving crystalline ice samples that can survive under high-resolution imaging conditions. Here, we report the stabilization and Å-resolution electron imaging of ice Ih crystallized from liquid water by developing cryogenic liquid-cell transmission electron microscopy (CRYOLIC-TEM). We combine lattice mapping with molecular dynamics simulations to reveal that ice formation is highly tolerant to nanoscale defects such as misoriented subdomains and trapped gas bubbles, which are stabilized by molecular-scale structural motifs. Importantly, bubble surfaces adopt low-energy nanofacets and create negligible strain fields in the surrounding crystal. These bubbles can dynamically nucleate, grow, migrate, dissolve, and coalesce under electron irradiation and be monitored in situ near a steady state. This work improves our understanding of water crystallization behaviors at a molecular spatial resolution.

Materials science↗
DOE OSTI2024

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-pressure phase transition in 3-D printed nanolamellar high-entropy alloy by imaging and simulation insights

Abstract We report on the high-resolution imaging and molecular dynamics simulations of a 3D-printed eutectic high-entropy alloy (EHEA) Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2 consisting of nanolamellar BCC and FCC phases. The direct lattice imaging of 3D-printed samples shows the Kurdjumov–Sachs (K–S) orientation relation {111} FCC parallel to {110} BCC planes in the dual-phase lamellae. Unlike traditional iron and steels, this alloy shows an irreversible BCC-to-FCC phase transformation under high pressures. The nanolamellar morphology is maintained after pressure cycling to 30 GPa, and nano-diffraction studies show both layers to be in the FCC phase. The chemical compositions of the dual-phase lamellae after pressure recovery remain unchanged, suggesting a diffusion-less BCC–FCC transformation in this EHEA. The lattice imaging of the pressure-recovered sample does not show any specific orientation relation between the two resulting FCC phases, indicating that many grain orientations are produced during the BCC–FCC phase transformation. Molecular dynamics simulations on phase transformation in a nanolamellar BCC/FCC in K–S orientation show that phase transformation from BCC to FCC is completed under high pressures, and the FCC phase is retained on decompression aided by the stable interfaces. Our work elucidates the irreversible phase transformation under static compression, providing an understanding of the orientation relationships in 3-D printed EHEA under high pressures.

3-D Printing↗
DOE OSTI2025

Ptychography at all wavelengths

Ptychography is a computational imaging technique that operates across multiple wavelength regimes, from electron (picometres) to X-ray (~0.1 nm), extreme ultraviolet (~10 nm) and visible light (micrometres). By reconstructing both amplitude and phase from diffraction patterns, ptychography enables high-resolution, quantitative imaging without conventional limitations imposed by lens-based optics. Ptychography has enabled advances across a range of scales: achieving deep-sub-angstrom resolution with electron microscopy, becoming an indispensable tool at X-ray synchrotron facilities worldwide and overcoming the trade-offs between resolution and field-of-view in optical imaging. This Primer provides a unified treatment of ptychography across these wavelength regimes. First, we discuss theoretical foundations, reconstruction algorithms, experimental considerations and wavelength-specific challenges. We then give examples of raw and processed data from various configurations and wavelengths. Next, we highlight key applications of ptychography in life sciences, materials science and industry. We also discuss data standards, open-source software implementations and best practices for ensuring reproducibility across different wavelength regimes. Finally, we consider limitations and future opportunities for ptychography. Together with accompanying datasets and code implementations, this Primer aims to serve newcomers and experienced practitioners in the field, facilitating broader adoption of ptychography across different disciplines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-resolution chemical patterns from negative tone resists for the integration of extreme ultraviolet patterns of metal-oxide resists with directed self-assembly of block copolymers

Extreme ultraviolet (EUV) lithography faces significant challenges in designing suitable resist materials that can provide adequate precision, while maintaining economically viable throughput. These challenges in resist materials have led to printing failures and high roughness in EUV patterns, compromising the performance of semiconductor devices. Integrating directed self-assembly (DSA) of block copolymers (BCPs) with EUV lithography offers a promising solution because, while the BCPs register to the EUV-defined chemical guiding pattern, the thermodynamically determined structures of the BCPs automatically rectify defects and roughness in the EUV pattern. Despite the superior resolution of metal-oxide EUV resists (MORs), their application to DSA is limited by the difficulty in converting them into chemical patterns that allow effective transfer of the rectified patterns of DSA films into inorganic materials. To address this challenge, this study introduces a novel strategy for fabricating chemical patterns using hydrogen silsesquioxane (HSQ), a high-resolution negative tone inorganic resist, as a model system for MORs. Initially, a sacrificial Cr pattern is generated from HSQ patterns via reactive ion etching. The sacrificial Cr pattern is converted into a chemical pattern by first grafting a water-soluble polyethylene oxide brush onto the substrate, then wet etching the Cr, and finally grafting nonpolar polystyrene brushes. Assembling polystyrene-block-poly(methyl methacrylate) on these patterns results in structures oriented and registered with the underlying pattern, achieving 24 nm full-pitch resolutions. In conclusion, this approach has the potential to integrate MOR patterns into the DSA process, thereby enabling the generation of high-quality sub-10 nm patterns with high-χ BCPs.

Atomic force microscopy↗
DOE OSTI2025

Nanotomography for Quantitative 3D Particle Reconstruction

Particulates are ubiquitous across fuel cycle operations and carry critical information about particle formation, processing, and potential proliferation-related activities. Traditional analytical techniques, including micro-Raman spectroscopy and standard electron microscopy, are often limited in spatial resolution or dimensionality, particularly when used to examine metallic or submicron-scale features. Understanding particle morphology, phase distribution, and internal porosity is essential for constraining formation conditions, thermodynamic environments, and material transport behavior. In this report, we demonstrate the application of plasma focused ion beam nanotomography to reconstruct micron-scale particulates at nanoscale resolution. Using high-resolution backscattered electron imaging and Avizo software, we obtained 3D reconstructions that enabled quantitative analysis of particle morphology, phase composition, and internal voids. Representative examples include a Ta particle with a large central void and a composite particle with embedded tetrahedral crystalline structures. These reconstructions reveal structural and compositional details that are inaccessible through conventional 2D imaging. The results demonstrate that nanotomography provides both qualitative and quantitative insights into particle formation and behavior. Using nanotomography, porosity and phase distributions can be quantified to inform models of particle density, transport, and solidification conditions. Beyond technical insights, the workflow developed here establishes a transferable capability for analyzing heterogeneous particles and has potential applications in bulk materials studies via x-ray computed tomography or other volumetric imaging modalities. Ongoing efforts are focused on optimizing the workflow to process multiple particles simultaneously, increasing throughput and statistical robustness. Overall, this work illustrates the power of nanotomography as a tool for connecting particulate morphology to formation mechanisms, composition, and transport, thereby strengthening analytical capabilities for nuclear forensics, fuel cycle analysis, and related scientific investigations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques

Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.

36 MATERIALS SCIENCE↗