state-of-the-art-electron-microscopy-for-physical-sciences-research

State-of-the-Art Electron Microscopy For Physical Sciences Research

ARTICLES DISCUSSED:
Moon, T., Colletta, M., Kourkoutis, L. F. Nanoscale characterization of liquid-solid interfaces by couple cryo-focused ion beam ...

Oak Ridge National Laboratory

Interfaces play a fundamental role in many areas of chemistry. However, their localized nature requires characterization techniques with high spatial resolution in order to fully understand their structure and properties. State-of-the-art atomic resolution or in situ scanning transmission electron microscopy and electron energy-loss spectroscopy are indispensable tools for characterizing the local structure and chemistry of materials with single-atom resolution, but they are not able to measure many properties that dictate function, such as vibrational modes or charge transfer, and are limited to room-temperature samples containing no liquids. Here, we outline emerging electron microscopy techniques that are allowing these limitations to be overcome and highlight several recent studies that were enabled by these techniques. We then provide a vision for how these techniques can be paired with each other and with in situ methods to deliver new insights into the static and dynamic behavior of functional interfaces.

Emerging Electron Microscopy Techniques for Probing Functional Interfaces in Energy Materials.

Electrochemical cells that utilize lithium and sodium anodes are under active study for their potential to enable high-energy batteries. Liquid and solid polymer electrolytes based on ether chemistry are among the most promising choices for rechargeable lithium and sodium batteries. However, uncontrolled anionic polymerization of these electrolytes at low anode potentials and oxidative degradation at working potentials of the most interesting cathode chemistries have led to a quite concession in the field that solid-state or flexible batteries based on polymer electrolytes can only be achieved in cells based on low- or moderate-voltage cathodes. Here, we show that cationic chain transfer agents can prevent degradation of ether electrolytes by arresting uncontrolled polymer growth at the anode. We also report that cathode electrolyte interphases composed of preformed anionic polymers and supramolecules provide a fundamental strategy for extending the high voltage stability of ether-based electrolytes to potentials well above conventionally accepted limits.

Stabilizing polymer electrolytes in high-voltage lithium batteries.

Dental enamel is a principal component of teeth, and has evolved to bear large chewing forces, resist mechanical fatigue and withstand wear over decades. Functional impairment and loss of dental enamel, caused by developmental defects or tooth decay (caries), affect health and quality of life, with associated costs to society. Although the past decade has seen progress in our understanding of enamel formation (amelogenesis) and the functional properties of mature enamel, attempts to repair lesions in this material or to synthesize it in vitro have had limited success. This is partly due to the highly hierarchical structure of enamel and additional complexities arising from chemical gradients. Here we show, using atomic-scale quantitative imaging and correlative spectroscopies, that the nanoscale crystallites of hydroxylapatite (Ca(PO)(OH)), which are the fundamental building blocks of enamel, comprise two nanometric layers enriched in magnesium flanking a core rich in sodium, fluoride and carbonate ions; this sandwich core is surrounded by a shell with lower concentration of substitutional defects. A mechanical model based on density functional theory calculations and X-ray diffraction data predicts that residual stresses arise because of the chemical gradients, in agreement with preferential dissolution of the crystallite core in acidic media. Furthermore, stresses may affect the mechanical resilience of enamel. The two additional layers of hierarchy suggest a possible new model for biological control over crystal growth during amelogenesis, and hint at implications for the preservation of biomarkers during tooth development.

Chemical gradients in human enamel crystallites.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Chemical gradients in human enamel crystallites.

The capacity of soil as a carbon (C) sink is mediated by interactions between organic matter and mineral phases. However, previously proposed layered accumulation of organic matter within aggregate organo-mineral microstructures has not yet been confirmed by direct visualization at the necessary nanometer-scale spatial resolution. Here, we identify disordered micrometer-size organic phases rather than previously reported ordered gradients in C functional groups. Using cryo-electron microscopy with electron energy loss spectroscopy (EELS), we show organo-organic interfaces in contrast to exclusively organo-mineral interfaces. Single-digit nanometer-size layers of C forms were detected at the organo-organic interface, showing alkyl C and nitrogen (N) enrichment (by 4 and 7%, respectively). At the organo-mineral interface, 88% (72-92%) and 33% (16-53%) enrichment of N and oxidized C, respectively, indicate different stabilization processes than at organo-organic interfaces. However, N enrichment at both interface types points towards the importance of N-rich residues for greater C sequestration.

Organo-organic and organo-mineral interfaces in soil at the nanometer scale.

Van der Waals materials composed of stacks of individual atomic layers have attracted considerable attention due to their exotic electronic properties that can be altered by, e.g., manipulating the twist angle of bilayer materials or the stacking sequence of trilayer materials. To fully understand and control the unique properties of these few-layer materials, a technique that can provide information about their local in-plane structural deformations, twist direction, and out-of-plane structure is needed. In principle, interference in overlap regions of Bragg disks originating from separate layers of a material encodes 3D information about the relative positions of atoms in the corresponding layers. Here, an interferometric 4D scanning transmission electron microscopy technique is described that utilizes this phenomenon to extract precise structural information from few-layer materials with nm-scale resolution. It is demonstrated how this technique enables measurement of local pm-scale in-plane lattice distortions as well as twist direction and average interlayer spacings in bilayer and trilayer graphene, and therefore provides a means to better understand the interplay between electronic properties and precise structural arrangements of few-layer 2D materials.

Interferometric 4D-STEM for Lattice Distortion and Interlayer Spacing Measurements of Bilayer and Trilayer 2D Materials.

The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system NdSrMnO. In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale.

Charge order textures induced by non-linear couplings in a half-doped manganite.

Forming an ultra-thin, permeable encapsulation oxide-support layer on a metal catalyst surface is considered an effective strategy for achieving a balance between high stability and high activity in heterogenous catalysts. The success of such a design relies not only on the thickness, ideally one to two atomic layers thick, but also on the morphology and chemistry of the encapsulation layer. Reliably identifying the presence and chemical nature of such a trace layer has been challenging. Electron energy-loss spectroscopy (EELS) performed in a scanning transmission electron microscope (STEM), the primary technique utilized for such studies, is limited by a weak signal on overlayers when using conventional analysis methods, often leading to misinterpreted or missed information. Here, a robust, unsupervised machine learning data analysis method is developed to reveal trace encapsulation layers that are otherwise overlooked in STEM-EELS datasets. This method provides a reliable tool for analyzing encapsulation of catalysts and is generally applicable to any spectroscopic analysis of materials and devices where revealing a trace signal and its spatial distribution is challenging.

Machine Learning Method Reveals Hidden Strong Metal-Support Interaction in Microscopy Datasets.

The performance of energy storage materials is often governed by their structure at the atomic scale. Conventional electron microscopy can provide detailed information about materials at these length scales, but direct imaging of light elements such as lithium presents a challenge. While several recent techniques allow lithium columns to be distinguished, these typically either involve complex contrast mechanisms that make image interpretation difficult or require significant expertise to perform. Here, we demonstrate how center-of-mass scanning transmission electron microscopy (CoM-STEM) provides an enhanced ability for simultaneous imaging of lithium and heavier element columns in lithium ion conductors. Through a combination of experiments and multislice electron scattering calculations, we show that CoM-STEM is straightforward to perform and produces directly interpretable contrast for thin samples, while being more robust to variations in experimental parameters than previously demonstrated techniques. As a result, CoM-STEM is positioned to become a reliable and facile method for directly probing all elements within energy storage materials at the atomic scale.

Robust Atomic-Resolution Imaging of Lithium in Battery Materials by Center-of-Mass Scanning Transmission Electron Microscopy.

The recent surge in interest of proton exchange membrane fuel cells (PEMFCs) for heavy-duty vehicles increases the demand on the durability of oxygen reduction reaction electrocatalysts used in the fuel cell cathode. This prioritizes efforts aimed at understanding and subsequently controlling catalyst degradation. Identical-location scanning transmission electron microscopy (IL-STEM) is a powerful method that enables precise characterization of degradation processes in individual catalyst nanoparticles across various stages of cycling. Recreating the degradation processes that occur in PEMFC membrane electrode assemblies (MEAs) within the aqueous cell used for IL-STEM experiments is vital for generating an accurate understanding of these processes. In this work, we investigate the type and degree of catalyst degradation achieved by cycling in an aqueous cell compared to a PEMFC MEA. While significant degradation is observed in IL-STEM experiments performed on a traditional Pt catalyst using the standard accelerated stress test potential window (0.6-0.95 V), degradation of a PtCo catalyst designed for heavy-duty vehicle use is very limited compared to that observed in MEAs. We therefore explore various experimental parameters such as temperature, acid type, acid concentration, ionomer content, and potential window to identify conditions that reproduce the degradation observed in MEAs. We find that by extending the cycling potential window to 0.4-1.0 V in an electrolyte containing Pt ions, the degraded particle size distribution and alloy composition better match that observed in MEAs. In particular, these conditions increase the relative contribution of Ostwald ripening, which appears to play a more significant role in the degradation of larger alloy particles supported on high-surface-area carbons than coalescence. Results from this work highlight the potential for discrepancies between  aqueous experiments and MEA tests. While different catalysts may require a unique modification to the AST protocol, strategies provided in this work enable future  and identical-location experiments that will play an important role in the development of robust catalysts for heavy-duty vehicle applications.

Recreating Fuel Cell Catalyst Degradation in Aqueous Environments for Identical-Location Scanning Transmission Electron Microscopy Studies.

Carbon-supported nitrogen-coordinated single-metal site catalysts (i.e., M-N-C, M: Fe, Co, or Ni) are active for the electrochemical CO reduction reaction (CO RR) to CO. Further improving their intrinsic activity and selectivity by tuning their N-M bond structures and coordination is limited. Herein, we expand the coordination environments of M-N-C catalysts by designing dual-metal active sites. The Ni-Fe catalyst exhibited the most efficient CO2RR activity and promising stability compared to other combinations. Advanced structural characterization and theoretical prediction suggest that the most active N-coordinated dual-metal site configurations are 2N-bridged (Fe-Ni)N , in which FeN and NiN moieties are shared with two N atoms. Two metals (i.e., Fe and Ni) in the dual-metal site likely generate a synergy to enable more optimal *COOH adsorption and *CO desorption than single-metal sites (FeN or NiN ) with improved intrinsic catalytic activity and selectivity.

Atomically Dispersed Dual-Metal Site Catalysts for Enhanced CO Reduction: Mechanistic Insight into Active Site Structures.

Precise control of charge transfer between catalyst nanoparticles and supports presents a unique opportunity to enhance the stability, activity, and selectivity of heterogeneous catalysts. While charge transfer is tunable using the atomic structure and chemistry of the catalyst-support interface, direct experimental evidence is missing for three-dimensional catalyst nanoparticles, primarily due to the lack of a high-resolution method that can probe and correlate both the charge distribution and atomic structure of catalyst/support interfaces in these structures. We demonstrate a robust scanning transmission electron microscopy (STEM) method that simultaneously visualizes the atomic-scale structure and sub-nanometer-scale charge distribution in heterogeneous catalysts using a model Au-catalyst/SrTiO-support system. Using this method, we further reveal the atomic-scale mechanisms responsible for the highly active perimeter sites and demonstrate that the charge transfer behavior can be readily controlled using post-synthesis treatments. This methodology provides a blueprint for better understanding the role of charge transfer in catalyst stability and performance and facilitates the future development of highly active advanced catalysts.

Measuring and directing charge transfer in heterogenous catalysts.

Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resolution, which allows direct visualization of composition and morphology with atomic precision. This typically comes at the cost of sample size, potentially limiting the accuracy and relevance of STEM results, as well as the ability to meaningfully track changes in properties that vary spatially. In this work, automated STEM data acquisition and analysis techniques are employed that enable physical and compositional properties of nanoparticles to be obtained at high resolution over length scales on the order of microns. This is demonstrated by studying the localized effects of potential cycling on electrocatalyst degradation across proton exchange membrane fuel cell cathodes. In contrast to conventional, manual STEM measurements, which produce particle size distributions representing hundreds of particles, these high-throughput automated methods capture tens of thousands of particles and enable nanoparticle size, number density, and composition to be measured as a function of position within the cathode. Comparing the properties of pristine and degraded fuel cells provides statistically robust evidence for the inhomogeneous nature of catalyst degradation across electrodes. These results demonstrate how high-throughput automated STEM techniques can be utilized to investigate local phenomena occurring in nanoparticle systems employed in practical devices.

Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy.

Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly-correlated electrical and elastic coupling that elicit fast and efficient collective switching. Designing domain structures with advantageous properties is difficult because the mechanisms involved in collective switching are poorly understood and difficult to investigate. Collective switching is a hierarchical process where the nano- and mesoscale responses control the macroscopic properties. Using chemical solution synthesis, epitaxially nearly-relaxed (100) BaTiO films are synthesized. Thermal strain induces a strongly-correlated domain structure with alternating domains of polarization along the [010] and [001] in-plane axes and 90° domain walls along the [011] or [01  ] directions. Simultaneous capacitance-voltage measurements and band-excitation piezoresponse force microscopy revealed strong collective switching behavior. Using a deep convolutional autoencoder, hierarchical switching is automatically tracked and the switching pathway is identified. The collective switching velocities are calculated to be ≈500 cm s at 5 V (7 kV cm ), orders-of-magnitude faster than expected. These combinations of properties are promising for high-speed tunable dielectrics and low-voltage ferroelectric memories and logic.

Michael J. Zachman

Center for Nanophase Materials Sciences

Oak Ridge National Laboratory

State-of-the-Art Electron Microscopy For Physical Sciences Research

Michael J. Zachman

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Oak Ridge National Laboratory

State-of-the-Art Electron Microscopy For Physical Sciences Research

Center for Nanophase Materials Sciences