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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

BEACON—automated aberration correction for scanning transmission electron microscopy using Bayesian optimization

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments. Here, we present an automated method of correcting first- and second-order aberrations called BEACON, which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings. We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano- and atomic-scale experiments. BEACON can correct all first- and second-order aberrations simultaneously to achieve an initial alignment and first- and second-order aberrations independently for fine alignment. Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.

techniques and instrumentation↗
DOE OSTI2024

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scanning Transmission Electron Microscopy–Atom Probe Tomography Correlative Analysis for the Characterization of Solute-defect Interactions

Atom probe tomography (APT) and (scanning) transmission electron microscopy ((S)TEM) are complementary techniques that provide spatially resolved chemical and structural information at the atomic scale. Here, in this study, we employ two different STEM/APT correlative analysis methods to investigate Cr segregation at dislocation loops in ultra-high purity Fe–Cr alloys. APT needles for the correlative analysis were extracted either from bulk material or from thinned TEM lamellae. STEM analysis was used to determine the Burgers vectors of ion-irradiation-induced dislocation loops, while APT reconstruction of the same region revealed the Cr segregation to these loops. We extended the g•b = 0 invisibility criterion of dislocation loops from TEM mode in a lamella to STEM mode in a needle-shaped specimen. STEM and APT analysis on the same needle provide straightforward correlative analysis, although it is limited by a small observation volume. In contrast, iterative STEM analysis of TEM lamellae, followed by the selective extraction of specific regions of interest for APT analysis, expands the observation area by up to 100 times but requires additional time-consuming steps for APT needle extraction from the lamellae.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2025

Effect of growth dynamics on the structural, photophysical and pseudocapacitance properties of famatinite copper antimony sulphide colloidal nanostructures (including nanosheets)

Facile phase selective synthesis of copper antimony sulphide (CAS) nanostructures is important because of their tunable photoconductive and electrochemical properties. In this study, off-stoichiometric famatinite phase CAS (fCAS) quasi-spherical and quasi-hexagonal colloidal nanostructures (including nanosheets) of sizes, 2.4–18.0 nm were grown under variable conditions of temperature (60–200 °C), time and oleylamine capping ligand concentration using copper(II) acetylacetonate and antimony(III) diethyldithiocarbamate precursors. Data from powder X-ray diffraction, Raman spectroscopy and high-resolution scanning/transmission electron microscopy confirm the tetragonal structure of the famatinite phase. X-ray photoelectron spectroscopy, transmission electron microscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy data suggest a correlation of particle size, morphology and composition of the off-stoichiometric fCAS nanostructures with growth temperature and time, and oleylamine concentration. The off-stoichiometric Cu 3-a Sb 1+b S 4±c (a, b, c – mole fractions) nanostructures being severely copper-deficient and antimony-rich, exhibit shallow-lying acceptor copper vacancy states, deep-lying donor states of antimony interstitials, sulphur vacancies and antimony-copper antisites and shallow-lying acceptor surface trapping states. Further, these electronic states are likely implicated in tunable UV-visible absorption and bandgaps between 2.3 and 2.8 eV, and broad visible-NIR photoluminescence with fast recombination of radiative lifetimes between 0.2 and 6.2 ns, confirmed from absorption, steady-state and time-resolved photoluminescence spectroscopies. Additionally, cyclic voltammetry and electrochemical impedance spectroscopy confirm that electrodes of the fCAS nanostructures display slightly variable pseudocapacitance of charge-storage primarily via possible sodium ion intercalation with a high specific capacitance of ~84 F g -1 obtained at a scan rate of 5 mV s -1 . Overall, these results show the influence of composition, in particular point defects, phase quality and morphology on the optical and pseudocapacitance properties of fCAS nanostructures, suitable as solar absorbers or electrodes for energy storage devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Quantitative Structure Determination from Experimental Four-Dimensional Scanning Transmission Electron Microscopy via the Scattering Matrix

Considerable inroads have recently been made on algorithms to determine the sample potential from four-dimensional scanning transmission electron microscopy data from thick samples where multiple scattering cannot be neglected. This paper further develops the scattering matrix approach to such structure determination. Through simulation, we demonstrate how this approach can be modified to better handle partial spatial coherence, unknown probe defocus, and information from the dark field region. By combining these developments we reconstruct the electrostatic potential of a monolithic SrTiO 3 crystal showing good quantitative agreement with the expected structure.

4D STEM↗
DOE OSTI2026

Effect of 316 stainless steel powder processing conditions on microstructure

One parameter that has both economic and performance effects in the manufacturing of steel parts is the powder feedstock used. 316 L steel powder can be produced through water atomization or gas atomization, where both the powder size and the atomization process determine the cost of powder feedstock. Gas atomized powder is spherical and has a lower oxygen content than water atomized powder, making it the preferred choice for performance, but comes at a higher financial cost. Here, in this study, various 316 L powder batches are characterized to understand physical properties and microstructural variations. Density and flowability were determined using gas pycnometry and Hall flow tests. Powder morphology and porosity were qualitatively analyzed via optical microscopy and scanning electron microscopy, Finally, transmission electron microscopy was used to determine changes in phases present. Spherical gas atomized powder of 30–100 μm contained Mn$-$Si rich oxides both on the surface and within the matrix. Meanwhile, irregular water atomized powder 30 μm in diameter contained silicon oxides without manganese. All powder particles contained a nickel rich cellular structure which was shown to support the formation of additional phases. While literature has observed general microstructural features across 316 L powder particles, transmission electron microscopy (TEM) in this study has identified variations in precipitation and cell structures. Information regarding morphology, flowability, density, and phase distributions can be applied to understand variations in part consolidation, which will in turn show which powder aspects are significant for production.

Chemical segregation↗
DOE OSTI2024

An Impedance Humidity Sensor Based on CVD Grown WSe 2 2D Films

2D materials-based planar devices have been sought after for gas and humidity sensor applications owing to their high sensitivity due to their ultrathin nature and increased surface area. Herein, 2D WSe 2 films-based planner devices were fabricated to evaluate their performance for potential application in humidity sensors. The structure and morphology of the WSe 2 sensing films were studied by Raman spectroscopy, photoluminescence, optical microscopy, and scanning electron microscopy (SEM) techniques. The relative humidity-dependent sensing performances of the 2D WSe 2 films were evaluated using current–voltage (I–V), relative impedance, and complex total impedance (electrochemical impedance spectroscopy, EIS) techniques. This sensor showed a very stable and repeatable performance investigated over the period of 18 months. The response and recovery times of the WSe 2 -based impedance sensors were found to be 40 and 30 s, respectively. The WSe 2 sensor exhibits a 2 ± 1% minimum hysteresis at a lower humidity level (50% RH) and around 8 ± 2% maximum hysteresis at relative humidity level (70% RH). This value of hysteresis is in the acceptable range during the initial investigation of any material to explore its potential for application in humidity sensors. The density functional theory (DFT) analysis was performed with the interaction from water molecules of the WSe 2 sample for a better understanding of the sensing mechanism of devices.

2D- WSe2↗
DOE OSTI2025

Chemical Vapor Deposition-Grown Hexagonal Boron Nitride and Graphene for Tandem Dielectric Capacitive Polymer Devices

To address the low energy density of polymeric capacitors, this work explores how tandem combinations of antagonistic properties can enhance energy storage. We introduce multilayer architecture integrating chemical vapor deposition (CVD)-grown ≈2 nm hexagonal boron nitride (hBN) and graphene with ferroelectric polyvinylidene fluoride (PVDF) and linear polyetherimide (PEI) layers to suppress leakage paths, reduce loss, and promote Maxwell–Wagner–Sillars polarization. Raman spectroscopy, X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), and plasma focused ion beam (PFIB) analyses confirm robust material integration. In conclusion, for the tandem device, E BD ≈600 V/μm, while individual layers show lower values (PVDF|Graphene (Gr)|PVDF ≈ 50 V/μm and PEI|hBN|PEI ≈ 275 V/μm), yielding an overall ≈6000% enhancement and demonstrating the effectiveness of the 2D multilayer design.

Chemical vapor deposition (CVD)↗
DOE OSTI2025

Uptake of polystyrene nanospheres by wheat and Arabidopsis roots in agar, hydroponics, and soil

Plant uptake of micro- and nanoplastics can lead to contamination of food with plastic particles and subsequent human consumption of plastics. There is evidence that plant roots can take up micro and nanoplastics; however, most of this evidence stems from experiments conducted with plants grown in hydroponics or agar systems where uptake of nanoparticles by roots is more favorable than when plants were grown in soil. Here, we discern the root uptake and accumulation of polystyrene nanospheres in plants grown in different growth media: agar, hydroponics, and soil. In addition, we tested the impacts of nanospheres on plant biomass and plant stress. Wheat and Arabidopsis thaliana were grown in agar, hydroponics, and soil media and exposed to polystyrene nanospheres. Three different nanospheres were used (40 nm and 200 nm carboxylate-modified and 200 nm amino-modified polystyrene) and uniformly mixed into the growth media. Plants were grown for 7 to 10 days and the roots were then examined for the presence of nanospheres by confocal laser scanning microscopy and scanning electron microscopy. Plant stress was evaluated by measuring reactive oxygen species (ROS). We observed the 40 nm nanospheres inside the plant roots, but the 200 nm nanospheres only adhered to the root cap cells showing no uptake into the roots. Furthermore, confocal images indicated that root uptake of nanospheres was favored in hydroponic solutions as compared to agar and soil media. Plant biomass was generally not affected by the nanospheres, except for hydroponically grown Arabidopsis thaliana, where biomass was significantly reduced. Small sized (40 nm) and positively charged (200 nm amino-modified) nanospheres showed higher ROS accumulation in plants than negatively charged 200 nm carboxylate-modified nanospheres. In conclusion, this study provides evidence that polystyrene nanospheres can be taken up into the interior of plant roots and cause plant stress, but these impacts are less pronounced in media where the plastic particles are less mobile, like in agar and soil media as compared to hydroponic systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chemical imaging of individual stratospheric particles sampled over North America

The increasing size, severity, and frequency of wildfires have led to dramatic increases in particulate matter concentrations in the troposphere. Severe wildfires can generate intense convective systems capable of transporting large quantities of biomass burning organic aerosols (BBOA) to the upper troposphere and lower stratosphere (UTLS). Chemically complex organic matter and light-absorbing carbonaceous material is introduced into stratospheric regions that were historically isolated from direct surface emissions. In this study, stratospheric particles were sampled over North America during the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) campaign, an aircraft-based research project designed to characterize convective perturbation in the UTLS. Particle samples collected from six research flights during summer 2022 were analyzed using Computer-Controlled Scanning Electron Microscopy and Scanning Transmission X-ray Microscopy to investigate particle size distributions, morphology, chemical composition, and mixing state of stratospheric particles along transects across the continental United States and adjacent Pacific Ocean airspace. Analysis revealed that all sampled particles contained detectable levels of carbon, with most exhibiting organic volume fractions of 0.37 ± 0.20. Notably, about 5% of the particles also contained soot inclusions, which indicates the presence of refractory black carbon transported to stratospheric altitudes and provides direct evidence of wildfire-derived black carbon reaching the UTLS. Typical particle morphology exhibits organic shells over soot and inorganic cores and suggests secondary processing and aging of BBOA during transport to and within the UTLS. These findings provide compelling evidence that wildfire emissions play a critical role in affecting the long-term composition and radiative properties of stratospheric particles.

Sharpe, Steven [Purdue Univ., West Lafayette, IN (↗
DOE OSTI2025

3013 Baseline Inner Container Report: Description, Imaging, and Analysis

This report presents consolidated findings from three microscopy studies of baseline Bagless Transfer Containers (BTCs), which are the inner containers used in DOE Standard 3013-compliant plutonium storage packages. The studies were conducted by Los Alamos National Laboratory (LANL), Savannah River National Laboratory (SRNL), and DNV, a subcontractor specializing in corrosion science. The baseline BTCs examined had not been exposed to corrosive environments, serving as control samples for comparison with destructively examined (DE) containers. Additionally, the Background section provides an overview of the BTC design, including manufacturing methods, material properties, and container configurations that may influence corrosion behavior. The primary objective of the LANL and SRNL studies was to establish reference characteristics of BTCs to distinguish manufacturing artifacts from corrosion-induced features observed in DE containers. Both laboratories used advanced microscopy techniques, including Wide Area Microscopy (WAMS), Laser Confocal Microscopy (LCM), Scanning Electron Microscopy (SEM), and Focused Ion Beam (FIB), to reveal that most surface anomalies were shallow and attributable to flow-forming processes, not corrosion. Subsurface impurities, identified as non-metallic inclusions, were also observed. DNV’s investigation focused on characterizing the mechanical and chemical properties of the BTC material to support crack growth modeling. Their findings indicate higher hardness and strength but reduced ductility—consistent with flow-formed 304L stainless steel and a higher-than-expected martensite content, in contrast to manufacturer claims. Ongoing and future studies, including Electron Backscatter Diffraction (EBSD), aim to further understand the microstructural factors influencing crack initiation and propagation. The combined studies provide a crucial baseline for distinguishing corrosion effects in DE containers, contributing to the safe and reliable long-term storage of plutonium-bearing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Photocatalytic Generation of Singlet Oxygen by Graphitic Carbon Nitride for Antibacterial Applications

Carbon-based functional nanocomposites have emerged as potent antimicrobial agents and can be exploited as a viable option to overcome antibiotic resistance of bacterial strains. In the present study, graphitic carbon nitride nanosheets are prepared by controlled calcination of urea. Spectroscopic measurements show that the nanosheets consist of abundant carbonyl groups and exhibit apparent photocatalytic activity under UV photoirradiation towards the selective production of singlet oxygen. Therefore, the nanosheets can effectively damage the bacterial cell membranes and inhibit the growth of bacterial cells, such as Gram-negative Escherichia coli, as confirmed in photodynamic, fluorescence microscopy, and scanning electron microscopy measurements. The results from this research highlight the unique potential of carbon nitride derivatives as potent antimicrobial agents.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Corrosion Testing Of Additively Manufactured Stainless Steel 316H In Molten Salt Environments

The development of a new ASTM standard for evaluating the corrosion resistance of additive manufactured (AM) stainless steel (SS) 316H in chloride molten salts is critical for the use of these materials in extreme environments such as molten salt reactors (MSRs). This report pertains to a work package of the Advaned Materials and Manufacturing Technologies (AMMT) developing a systematic methodology to link changes in AM fabrication parameters, namely surface finishing, porosity, microstructure, and chemical heterogeneity, to corrosion performance in NaCl-MgCl2 salt, a proposed secondary coolant for MSRs. During Fiscal Year 2024, Idaho National Laboratory investigators in the AMMT program, utilized SS316H bars, fabricated with laser bed powder fusion at Los Alamos National Laboratory, to establish and optimize the workflow for evaluating these process-to-performance relationships. Standard practices for specimen preparation were established using these specimens, with particular focus on descaling and sectioning methods that align with ASTM guidelines. A comprehensive experimental design for static corrosion testing was developed, with pre- and post-exposure analysis utilizing optical microscopy and scanning electron microscopy. So far standard descaling techniques were optimized, one static corrosion test was conducted on the LANL AM SS316H specimens, and pre- and post-corrosion practices were established. In addition, the work package yielded a review paper on corrosion testing gaps for AM materials in nuclear applications and submitted a proposal for a rapid-turnaround experiment to the Nuclear Science User Facilities Program to investigate the combined effects of proton irradiation and corrosion on AM SS316H. This work package establishes a foundation for evaluating processing-to-performance relationships for AM SS316H in harsh conditions, contributing to the safe and efficient design of components for next-generation nuclear reactors. The creation of a standardized methodology and the generation of relevant publications and future research pathways represent significant strides towards integrating AM materials into critical applications where corrosion resistance is paramount.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗
DOE OSTI2026

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗
DOE OSTI2024

High‐speed 4‐dimensional scanning transmission electron microscopy using compressive sensing techniques

Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Robinson, Alex W.↗
DOE OSTI2024

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr 2 Ge 2 Te 6 , CuIr 2 S 4 , and CrCl 3 . In conclusion, our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

36 MATERIALS SCIENCE↗