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At least 37 records · Page 2

Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding

Over the last decade, scanning transmission electron microscopy (STEM) has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision, opening the pathway toward exploring ferroelectric, ferroelastic, and chemical phenomena on the atomic scale. Analyses to date extracting a polarization signal from lattice coupled distortions in STEM imaging rely on discovery of atomic positions from intensity maxima/minima and subsequent calculation of polarization and other order parameter fields from the atomic displacements. Here, we explore the feasibility of polarization mapping directly from the analysis of STEM images using deep convolutional neural networks (DCNNs). In this approach, the DCNN is trained on the labeled part of the image (i.e., for human labelling), and the trained network is subsequently applied to other images. We explore the effects of the choice of the descriptors (centered on atomic columns and grid-based), the effects of observational bias, and whether the network trained on one composition can be applied to a different one. This analysis demonstrates the tremendous potential of the DCNN for the analysis of high-resolution STEM imaging and spectral data and highlights the associated limitations.

36 MATERIALS SCIENCE↗

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗

Detection of defects in atomic-resolution images of materials using cycle analysis

The automated detection of defects in high-angle annular dark-field Z-contrast (HAADF) scanning-transmission-electron microscopy (STEM) images has been a major challenge. Here, we report an approach for the automated detection and categorization of structural defects based on changes in the material’s local atomic geometry. The approach applies geometric graph theory to the already-found positions of atomic-column centers and is capable of detecting and categorizing any defect in thin diperiodic structures (i.e., “2D materials”) and a large subset of defects in thick diperiodic structures (i.e., 3D or bulk-like materials). Despite the somewhat limited applicability of the approach in detecting and categorizing defects in thicker bulk-like materials, it provides potentially informative insights into the presence of defects. The categorization of defects can be used to screen large quantities of data and to provide statistical data about the distribution of defects within a material. This methodology is applicable to atomic column locations extracted from any type of high-resolution image, but here we demonstrate it for HAADF STEM images.

36 MATERIALS SCIENCE↗

Strain-Induced asymmetry and on-site dynamics of silicon defects in graphene

In the last decade, the atomically-focused electron beams utilized in scanning transmission electron microscopes (STEMs) have been shown to induce a broad set of local structural transformations in materials, opening pathways for directing material synthesis and modification atom-by-atom. The mechanisms underlying these transformations remain largely unknown, due to the intractability of modeling the myriad of reaction pathways that can be accessed through high-energy electron scattering. The information on materials’ structure and dynamics that can be extracted from STEM images is similarly left underexplored. Here, we report the observation of anomalous on-site dynamics of individual silicon impurity atoms in graphene during STEM imaging. Density functional theory-based structural optimizations of anisotropically-strained molecular nanographenes reveal two distinct (but nearly degenerate) stable structures for four-fold coordinated silicon impurities, where interconversion between the two structures manifests slight changes of the silicon position within the lattice site. Implications for defect-based strain engineering in graphene are discussed.

36 MATERIALS SCIENCE↗

$\mathrm{SIM}$-$\mathrm{STEM}$ $\mathrm{Lab}$: Incorporating Compressed Sensing Theory for Fast STEM Simulation

We report recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future

47 OTHER INSTRUMENTATION↗

Secondary-electron imaging of bulk crystalline specimens in an aberration corrected $\text{STEM}$

Atomic-scale electron microscopy traditionally probes thin specimens, with thickness below 100 nm, and its feasibility for bulk samples has not been documented. Here in this study, we explore the practicality of scanning transmission electron microscope (STEM) imaging with secondary electrons (SE), using a silicon-wedge specimen having a maximum thickness of 18 μm. We find that the atomic structure is present in the entire thickness range of the SE images although the background intensity increases moderately with thickness. The consistent intensity of secondary electron (SE) images at atomic positions and the modest increase in intensity in between (background) observed in silicon suggest a limited contribution from SEs generated by backscattered electrons, a conclusion supported by our multislice calculations. We conclude that achieving atomic resolution in SE imaging for bulk specimens is indeed attainable using aberration-corrected STEM and that an aberration-corrected scanning electron microscope (SEM) may have the capacity for atomic-level resolution, holding great promise for future strides in materials research.

25 ENERGY STORAGE↗

SURFACE EXOSURE TIMESCALES OF APOLLO CORE SAMPLE 73002 SPACE WEATHERED GRAINS

Introduction: Space weathering causes the surface regolith on airless bodies like the Moon to be morphologically, microstructurally, and chemically altered due to micrometeoroid bombardment and solar wind irradiation[1]. These processes produce a multitude of microstructural and chemical changes in individual soil grains that accumulate as grains are exposed on the surface over time. One microstructural feature produced by exposure to the solar wind is the development of ion-damaged rims on regolith grains via H+ and He+ ion irradiation. Also present are solar energetic particle (SEP) tracks, which are nanoscale lineations of ionization damage within grain interiors formed by high energy solar flare ions(primarily Fe group nuclei) which penetrate millimeters below the surface [2]. Recent work has confirmed that the thickness of solar wind-damaged amorphous rims on anorthite grains, nanocrystalline rims on olivine grains, and their respective SEP track densities are correlated with their surface exposure ages [3].Core sample 73002, recently released under the Apollo Next Generation Sample Analysis (ANGSA) Program, has provided an opportunity to study material collected from the light mantle formation during Apollo 17. The light mantle is thought to have been deposited via a landslide originating from the neighboring South Massif [4]. Spectral profiles and ferromagnetic resonance measurements of bulk soils sampled at cm-intervals from 73002 indicate the existence of mature regolith extending ~8 cm below the surface, suggesting the presence of an in-situ reworking zone in the core[5,6].Here we present the distribution of SEP track densities, solar wind damaged rim widths, and the corresponding surface exposure ages of grains residing in the proposed in-situ reworking zone of core 73002. Methods: Bulk samples of regolith from the first eight intervals and every following fourth interval down the core (dissection Pass 2) were delivered to Purdue University as <45 μm size fractions. The first eight0.5 cm intervals, representing the top 4cmof regolith, were individually dry sieved to a<20 μm size fraction, and grains were prepared by ultramicrotomy for analysis in the scanning transmission electron microscope (STEM). Bright field (BF) and dark field (DF) STEM images of solar flare tracks and solar wind damaged rims were acquired on a JEOL 2500SE TEM, equipped with a 60 mm2ultra-thin window silicon drift energy dispersive X-ray (EDX) spectrometer at NASA John-son Space Center. Grain compositions were determined by EDX compositional spectrum imaging. SEP track densities and amorphous rim thicknesses were measured on BF and DF images. Results: The fraction of grains with discernable space weathering features decreased with depth, with 100% in the first interval exhibiting space weathering features as opposed to ~60% in Interval 8.BF and DF STEM images show splash-melt and vapor deposited rims on outermost grain margins with embedded Fe-bearing nanoparticles ranging in size up to ~10 nm in diameter. Images also show solar-wind damaged rims below the vapor deposits, and SEP tracks present in grain interiors. The rim thicknesses and SEP track densities were determined using the methods of [3] for 54grains spanning the top 4 cm. ~80% of the grains analyzed were anorthite and ~20% were olivine. The track production rate from[3] was used to estimate the surface exposure times of the grains in this study. The majority of exposure times are in the 1 -5 MY range for all intervals. The lowest value was 3.8x 10¬5years in Interval 8and the highest value was1.1x 107years in Interval 6. Grains with the highest solar wind damage rim thicknesses and SEP track densities are found in Interval 6.The highest rim thickness and track density observed for anorthiteis126.5 nm and4.7 x 1011tracks/cm2, while for olivine they are 98.6 nm and 1.83 x 1011tracks/cm2, respectively. Discussion: Intervals from the top 4 cm of 73002 show similar SEP track density and solar wind damaged rim thickness distributions. Spectral and ferromagnetic resonance measurements of 73002 indicate an in-situ reworking zone up to~8 cm below the surface[5,6].The depth analyzed in this work is within the core’s uppermost in-situ reworking zone and may serve as an explanation to the homogenous distribution of exposure ages. The decreasing abundance of space weathered features with depth is consistent with regolith mixing models showing an exponential decay in regolith maturity with depth over time[7].A maximum surface exposure age determined via SEP track density is approximately 10million years. This timescale is consistent with the lower estimate of surface exposure ages of the light mantle determined in previous studies, which can range from 10s to over 100 Ma [4].It also falls within the core regolith reworking development timescale of ~17 Ma [5,6]. Additional analysis will be performed for a further seven intervals in 73002.

J A McFadden↗

Scanning transmission election microscopy observations of twisted epitaxial gold nanodiscs in twisted molybdenum disulfide bilayers

Atomic scale, scanning transmission electron microscopy (STEM) analysis of the moiré structures in twisted epitaxial gold nanodiscs encapsulated in twisted bilayer molybdenum disulfide is presented. High angle annular dark field STEM imaging reveals that the period of the moiré patterns between gold and molybdenum disulfide varies with different twist angles of the bilayer molybdenum disulfide, ranging from 1.80 nm (epitaxial alignment of gold) to 1.53 nm (twisted epitaxial alignment of gold). Additionally, bright field STEM imaging reveals a faint, larger "moiré of moiré" structure in cases where the bilayer molybdenum disulfide twist angle is small (~6°), arising from the overlapping three-layers, which is not visible in conventional transmission electron microscopy images. In conclusion, our experiments indicate that scanning transmission electron microscopy as a suitable tool for moiré analysis of twisted multilayer planar heterostructures, complementary to information provided by conventional transmission electron microscopy and diffraction.

Au↗

Strain-driven oxygen vacancy ordering in LaNiO 3 thin films revealed by integrated differential phase contrast imaging in scanning transmission electron microscopy

Rare-earth nickelates, such as LaNiO 3 (LNO), exhibit complex electronic properties, with ordered oxygen vacancies (OOV) influencing conductivity and magnetic behavior. We investigate the structural stability of strain-induced OOV phases in LNO thin films grown on SrTiO 3 substrates and the impact of Ruddlesden–Popper (RP) faults. Using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and integrated differential phase contrast (iDPC) STEM imaging, we conducted atomic-scale structural and compositional analyses of OOV. Geometric phase analysis (GPA) was employed to measure the strain in fault-free and RP fault regions, while density functional theory (DFT) calculations explored different OOV arrangements in the LNO phase. Simulated iDPC-STEM imaging of energy-stabilized structures was performed to correlate with experimental results. Here, our findings reveal superstructure modulation in the chemical composition and atomic-scale lattice structure in LNO, primarily due to the formation of the OOV in Ni–O layers of the LaNiO 2.5 phase. The out-of-plane compressive strain of about 2% stabilizes this phase, reducing the strain, diminishing OOV, and transforming them into LNO.

36 MATERIALS SCIENCE↗

Hypervelocity Dust Impact in Olivine: Fib/Tem Characterization and Comparison of Experimental and Natural Microcraters

The flux of objects impacting the surfaces of solar system airless bodies is dominated by micrometeoroids less than 1 mm diameter whose impact effects play a major role in the space weathering of airless body surfaces. To obtain better understanding of how small scale impact effects vary as a function of impact speed in an important lunar and asteroidal mineral, we produced artificial microcraters in San Carlos olivine using Fe metal dust particles 0.10 to 5 µm in diameter electrostatically accelerated to speeds between 0.35 to 25 km s-1. The crater morphologies, size distrrubiton and microstruc-tures were characterized by field-emission SEM (FE-SEM) and also by FIB cross sectioning of selected craters for field-emission scanning transmission electron microscopy (FE-STEM). These same techniques were also applied to study a natural 20 µm-diameter microcrater in a olivine grain on the surface of lunar rock 12075. Measured microcrater diameters in the experimental sample range between 0.20 to 5 µm with larger craters having more irregular outlines dominated by spallation fractures. FE-SEM and FE-STEM imaging docu-ment the formation of shock melt in the size population of experimental craters below approximately 1 µm in diameter, corresponding to particle impact speeds in the 10-25 km s-1 range. The natural olivine crater exhibits similar shock melt features along the perimeter of its cavity, but the shock melt also contains nanophase Fe metal particles, something not observed in the experimental samples. FE-STEM imaging of the experimental craters reveals complex shock-generated dislocation and nanofracture microstructures in zones extend-ing 1-2 µm into the olivine from the crater cavity. The natural microcrater shows a lower density of shock-generated disloca-tions that extends a factor of 2 deeper into the the olivine than in the experimental samples.

Roy Gray Christoffersen↗

Atomic-scale Imaging of PGM-free Catalyst Active Sites by 30 keV 4D-STEM

Platinum group metal (PGM)-free catalysts have attracted a large amount of attention due to their potential for enabling low-cost, commercially viable hydrogen fuel cells and electrolyzers [1]. Degradation of cell performance remains a significant challenge, however, currently limiting implementation of devices that utilize PGM-free materials [2]. Controlling degradation in these materials requires a better understanding of the atomic structure of active sites, thought to be FeN4 structures within a graphitic carbon lattice, which would enable more accurate prediction of the associated degradation pathways. The exact structural arrangement of active sites in these materials is still debated since a range of structures have been computationally predicted and methods to directly validate these models are still needed [1,3-5].While scanning transmission electron microscopy (STEM) has provided initial glimpses into the nature of the proposed active sites, detailed evaluation of the structure of these sites is challenging since they involve defects, edges, and nitrogen dopants in the graphitic lattice, which are susceptible to beam damage [6,7]. Conventional STEM imaging and spectroscopy methods exacerbate this problem with dose-inefficiency or nonideal contrast characteristics for imaging light and heavy elements simultaneously. A method that minimizes damage while generating dose-efficient, easily-interpretable contrast for both light and heavy elements is therefore needed to facilitate imaging of sensitive active site atomic structure.Here, we demonstrate direct atomic-scale imaging of PGM-free catalyst active sites by low-voltage four-dimensional (4D)-STEM. To accomplish this, we pair a 30 keV aberration-corrected probe, which minimizes knock-on damage, with a fast pixelated detector that has optimal performance at low beam energies [8]. We show how this setup enables relatively simple center-of-mass (CoM) techniques [9,10] to produce images with an increased signal-to-noise ratio (SNR) and light-element contrast over conventional imaging modes, allowing the entire active site structure to be imaged at the atomic scale. Moreover, we show how electron ptychography [11,12] enables images with further improved characteristics to be obtained, for example by minimizing residual aberrations, which provides a more accurate structural representation. The increased understanding that these low-voltage 4D-STEM techniques will provide about the atomic structure of PGM-free active sites and their associated degradation pathways will facilitate rational design of next-generation materials, promoting development of low-cost hydrogen fuel cells, electrolyzers, and other energy conversion devices [13]. References:[1] U Martinez et al., Adv. Mater. 31 (2019), p. 1806545.[2] Y Shao et al., Adv. Mater. 31 (2019), p. 1807615.[3] J Kneebone et al., J. Phys. Chem. C 121, (2017), p.16283.[4] T Mineva et al., ACS Catal. 9 (2019), p. 9359.[5] J Li et al., Nat. Catal. 4 (2021), p. 10.[6] T Susi et al., ACS Nano 6 (2012), p. 8837.[7] P Zelenay and DJ Myers, US Department of Energy Hydrogen and Fuel Cells Program 2017 Annual Merit Review and Peer Evaluation Meeting, Washington, DC (2017).[8] H Ryll et al., J. Inst. 11 (2016), p. P04006.[9] K Müller et al., Nat. Commun. 5 (2014), p. 5653.[10] I Lazic et al., Ultramicroscopy 160 (2016), p. 265.[11] H Yang et al., Nat. Commun. 7 (2016), p. 12532.[12] Y Jiang et al., Nature 559 (2018), p. 343. [13] Research sponsored by the Hydrogen and Fuel Cell Technologies Office, Office of Energy Efficiency and Renewable Energy, US Department of Energy (DOE). Research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.

Zachman, Michael↗

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.↗

Palladium/Zeolite Low Temperature Passive NOx Adsorbers (PNA): Structure-Adsorption Property Relationships for Hydrothermally Aged PNA Materials

Zeolites with different framework structures (SSZ-13, ZSM-5, BEA) but similar Si/Al ratios and Pd loading (~1 wr%) were synthesized and evaluated as low temperature passive NOx adsorbers (PNA). These materials exhibit high NOx adsorption efficiency with atomically dispersed Pd the active adsorption site. Hydrothermal aging at 750 ºC for 16 hours in the presence of 10% water vapor in air resulted in the formation of PdO nanoparticles in all three samples as evidenced by high energy XRD. Hydrothermal aging of the small-pore Pd/SSZ-13 (Si/Al = 6), which contain ~100-90% atomically dispersed palladium ions, decreases its PNA performance only by ~10-20%. High-field solid state 27Al NMR studies on the fresh and aged samples substantiate dealumination and significant changes in the distribution of Al (and thus, Bronsted acid) sites after hydrothermal aging. FTIR measurements with NO probe molecule and titration of Bronsted acid sites with nitrosyl (NO+) ions further corroborate the 27Al NMR data. Because framework aluminum atoms are the anchoring sites for atomically dispersed Pd ions, their elution from the framework causes the loss of active atomically dispersed Pd species. Furthermore, with the aid of HAADF-STEM imaging and synchrotron XRD studies, we further confirm and visualize the fate of these Pd species – they agglomerate into PdO nanoparticles on the external surface of zeolite. Consequently, these changes lead to the decrease in PNA performance of these materials after hydrothermal aging. The thus formed agglomerates cannot be re-dispersed back to their ionic state due to the loss of framework Al T-sites and/or inherent stability of such large PdO particles. Our study clearly demonstrates that, unlike in previous studies that found increased PNA performance upon HTA , high temperatures hydrothermal aging of PNA materials that contain atomically dispersed Pd initially, results in a decrease in NOx storage efficiency due mostly to the formation of PdO agglomerates. However, we also highlight the high hydrothermal stability of predominantly atomically dispersed 1-3 wt% Pd/SSZ-13 (Si/Al = 6), whose performance decreases only marginally after prolonged hydrothermal aging at 750 ºC. Overall, this study shows that hydrothermally stable passive NOx materials can be prepared using small-pore SSZ-13 zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Atomic-Scale Understanding of UO 2 Surface Evolution during Anoxic Dissolution

Our present understanding of surface dissolution of nuclear fuels such as uranium dioxide (UO 2 ) is limited by the use of non-local characterization techniques. In this paper, we discuss the use of state-of-the-art scanning transmission electron microscopy (STEM) to reveal atomic–scale changes occurring to UO 2 thin films subjected to anoxic dissolution in deionised water. No amorphisation of the UO 2 film surface during dissolution is observed, and dissolution occurs preferentially at surface reactive sites that present as surface pits which increase in size as the dissolution proceeds. Using a combination of STEM imaging modes, energy-dispersive X-ray spectroscopy (STEM-EDS), and electron energy loss spectroscopy (STEM-EELS), we investigate structural defects and oxygen passivation of the surface that originates from the filling of the octahedral interstitial site in the centre of the unit cells and its associated lattice contraction. Taken together, our results reveal complex pathways for both the dissolution and infiltration of solutions into UO 2 surfaces.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Unveiling Structural Heterogeneity and Imbalance of Gold Decahedral Nanoparticles using Four-dimensional Scanning Transmission Electron Microscopy

Multi-twinned structures have been observed in technologically important crystal systems, for example diamond cubic and face-centered cubic (FCC) lattices, that include materials such as diamond, silicon, a wide range of noble metals, and their nanoscale counterparts. Beyond atomic building blocks, the special arrangements also occur in the self-assembly of nanoparticles (NP) and μm-sized colloidal particles and occupy parts of their phase diagrams. Spanning a wide range of length scales, the universality of the structures arises when the systems attempt to achieve multitwinned structures by overcoming geometric misfits during minimizing surface energies with entirely {111} or close-packing facets. While it is fundamental to understand how strain is sustained upon twinned structures and symmetry breaking, the knowledge will be paramount in practical aspects such as guiding and controlling the thin film growth, anisotropic NP growth, and self-assembly of NPs. Au decahedral (Dh) NP, as the most prevalent multi-twinned model system, fits five tetrahedral motifs into a circle by sharing an axis resulting in a geometric misfit angle of 7.35°, or a disclination with power of -7.35°. Postulating how Au FCC lattice adopts the misfit, theoretical models have been developed to address the underlying lattice symmetry and inhomogeneous strain distribution separately. Yet, experimental reports regarding the former have been limited due to the relatively large X-ray beam sizes that do not fit the sizes of NPs. On the other hand, though the latter has been widely adapted in the thermodynamics of small (<10 nm) multi-twinned nanoparticles, previous literature has shown that, at edge length of 17 nm, the theory’s is invalidated by shear strain that is observed in a defect-free Au Dh NP by high-resolution transmission electron microscopy (HR-TEM) imaging. Though the advancement of aberrationcorrected scanning transmission electron microscopy (AC-STEM) imaging and ab initio calculation techniques brings new opportunities, along with challenges in complicated image analysis and limitation in particle size (usually below 10 nm), the gap between nanoscale and mesoscale has never been extended to gain insight from atomic system with straightforward interaction potentials.

4D-STEM↗

Role of Cations in the Cation-Driven Assembly Process and their Effect on the Charge Storage Properties of Bilayered Vanadium Oxide and Reduced Graphene Oxide Heterostructures in Alkali Ion Systems

Exfoliated δ-Li x V 2 O 5 ·nH 2 O (ex-LVO) and reduced graphene oxide (rGO) heterostructures were constructed using different assembling cations (i.e., Li⁺, Na⁺, and K⁺ ions). The ex-LVO and rGO nanoflakes were stacked together using a concentrated chloride solution of each assembling cation and vacuum annealed at 200 °C to form three distinct two-dimensional (2D) layered architectures. X-ray diffraction and thermogravimetric analysis confirmed that the assembling ions can control the interlayer spacing of the bilayered vanadium oxide (BVO) phase as well as impact the crystallographic water content, which in turn affects the electrochemical performance. Scanning electron microscopy, scanning transmission electron microscopy (STEM), electron energy-loss spectroscopy (EELS), and X-ray photoelectron spectroscopy confirmed that a 2D heterointerface formed between LVO and rGO and that the cations used to assemble the heterostructure are trapped in the interlayer BVO region. High-resolution STEM imaging also showed the rGO dispersion throughout the LVO layers. Moreover, STEM-EELS identified a V 2 O 3 phase that forms along the rGO interface and can stabilize the materials during cycling. A charge storage mechanism analysis, combined with the galvanostatic intermittent titration technique, found that increased interlayer spacings of the BVO phase and using the assembling cations to define intercalation sites for identical charge-carrying ions lead to improved ion diffusion and increased capacities during cycling. Therefore, the Li⁺ and Na⁺ ion assembled heterostructures showed improved charge-carrying ion diffusion and charge storage capacities in each of their respective charge storage systems (i.e., Li-ion and Na-ion half-cells). In total, the cation used for heterostructure assembly can modify the final material structure and tailor the ion diffusion and charge storage capacity to tune its properties for the desired electrochemical system using a variety of 2D materials.

25 ENERGY STORAGE↗

Data for: Climatic Imprint on Interfacially-Controlled Platinum-Palladium Resources

Data package for manuscript "Climatic Imprint on Interfacially-Controlled Platinum-Palladium Resources" by Emily G. Wright, Ivey Wang, Yihang Fang, Elaine D. Flynn, and Jeffrey G. Catalano. This dataset contains adsorption results from experiments designed to investigate the effect of chloride on Pd(II) adsorption to goethite and Pt(II) adsorption to hematite and goethite, including lab experiments, X-ray absorption fine structure spectroscopy, and models of retention within a laterite. See the associated manuscript for full methods information. The file "Wright2025_PtAds_data.csv" contains the target starting Pt concentration (uM), final aqueous Pt and associated error (in uM), calculated adsorbed Pt and associated error (in umol/m2), target and measured aqueous chloride (mM), target aqueous nitrate (mM), final pH, and mineral concentration/loading (g/L). Associated mineral-free controls (mineral loading = 0 g/L) are included; the aqueous Pd error was not calculated and chloride was not measured in every sample. These data appear in Figures 1, S3, S4, S5, S20, and S22 in the associated manuscript. The file "Wright2025_PdAds_data.csv" contains the target starting Pd concentration (uM), final aqueous Pd and associated error (in uM), calculated adsorbed Pd and associated error (in umol/m2), target and measured aqueous chloride (mM), and mineral concentration/loading (g/L). Associated mineral-free controls (mineral loading = 0 g/L) are included; the aqueous Pd error was not calculated and chloride was not measured in every sample. These data appear in Figures 1, S3, S4, S5, and S20 in the associated manuscript. The file "Wright2025_MineralBatches_data.csv" contains the mineral identity and BET specific surface area (m2/g) for every mineral batch synthesized and used in experiments. The annealing time used is listed for hydrothermally annealed goethite. These data appear in Table S2 in the associated manuscript. The file "Wright2025_XRD_data.csv" contains the XRD patterns for every mineral batch synthesized as the counts as a function of two theta (in degrees). See "Wright2025_MineralBatches_data.csv" for more details on specific mineral batches. These data appear in Figure S2 in the associated manuscript. The file "Wright 2025_ZetaPotential_data.csv" contains the measured zeta potentials for samples of goethite (batch G2) at pH 4 the presence of varying amounts of sodium chloride. These data appear in Table S3 in the associated manuscript. The file "Wright2025_XAFSSamples_data.csv" contains the specific mineral batch, measured final aqueous Pd or Pt (uM), measured final aqueous chloride (mM), and estimated adsorbed Pd or Pt (umol/m2) of all XAFS samples. These data appear in Tables S4, S7, S8, and S10 in the associated manuscript. The files "Wright2025_PdXAFS_data.csv" and "Wright2025_PtXAFS_data.csv" contain the normalized spectra of Pd and Pt, respectively, adsorbed to minerals at varying chloride concentrations. See "Wright2025_XAFSSamples_data.csv" for a guide to sample names. Note that "05" in a sample name is equivalent to "0.5". These data appear in Figures 2, S6, S7, S8, S12, S13, and S14 in the associated manuscript. The file "Wright2025_LateriteProfileProfileModelParameters_data.csv" include the ratio of hematite to hematite and goethite in two synthetic, modeled profiles, as well as the modeled surface areas of goethite and hematite as a function of relative depth within the modeled weathering zone. These data were used, in conjunction with equations presented in the paper, to calculate the theoretical concentrations of Pd and Pt (and the resulting Pt/Pd ratio) within the profiles. These data appear in Figure 3 in the associated manuscript. The file "Wright2025_Imagery_data.zip" is a zipped folder containing the TEM and STEM images appear in Figures S18 and S19. Individual files are labeled as either STEM (Fig. S18) or TEM (Fig. S19) with a letter representing the part of the multipart figure.

58 GEOSCIENCES↗

Unsupervised machine learning discovery of structural units and transformation pathways from imaging data

We show that unsupervised machine learning can be used to learn chemical transformation pathways from observational Scanning Transmission Electron Microscopy (STEM) data. To enable this analysis, we assumed the existence of atoms, a discreteness of atomic classes, and the presence of an explicit relationship between the observed STEM contrast and the presence of atomic units. With only these postulates, we developed a machine learning method leveraging a rotationally invariant variational autoencoder (VAE) that can identify the existing molecular fragments observed within a material. The approach encodes the information contained in STEM image sequences using a small number of latent variables, allowing the exploration of chemical transformation pathways by tracing the evolution of atoms in the latent space of the system. The results suggest that atomically resolved STEM data can be used to derive fundamental physical and chemical mechanisms involved, by providing encodings of the observed structures that act as bottom-up equivalents of structural order parameters. The approach also demonstrates the potential of variational (i.e., Bayesian) methods in the physical sciences and will stimulate the development of more sophisticated ways to encode physical constraints in the encoder–decoder architectures and generative physical laws and causal relationships in the latent space of VAEs.

97 MATHEMATICS AND COMPUTING↗