Effect of molecular permanent dipole moment on guest aggregation and exciton quenching in phosphorescent organic light emitting diodes.

This study explores the effect of molecular permanent dipole moment (PDM) on aggregation of guest molecules in phosphorescent host-guest organic light-emitting diodes (OLEDs). Through a combination of photoluminescence measurements, high-angle annular dark-field scanning transmission electron microscopy analysis, and an Ising model based physical vapor-deposition simulation, we show that higher PDM of tris[2-phenylpyridinato-C2,N]iridium(III) guest can actually lead to a reduced aggregation relative to tris[bis[2-(2-pyridinyl-N)phenyl-C] (acetylacetonato)iridium(III) when doped into a non-polar host 1,3,5-tris(carbazol-9-yl)benzene. This study further explores the effect of host polarity by using a polar host 3',5'-di(carbazol-9-yl)-[1,1'-biphenyl]-3,5-dicarbonitrile, and it is shown that the polar host leads to reduced guest aggregation. This study provides a comprehensive understanding of the impact of molecular PDM on OLED material efficiency and stability, providing insights for optimizing phosphorescent OLED materials.

Hybrid bilayered vanadium oxide electrodes with large and tunable interlayer distances in lithium-ion batteries.

The interlayer distances in layered electrode materials, influenced by the chemical composition of the confined interlayer regions, have a significant impact on their electrochemical performance. Chemical preintercalation of inorganic metal ions affects the interlayer spacing, yet expansion is limited by the hydrated ion radii. Herein, we demonstrate that using varying concentrations of decyltrimethylammonium (DTA+) and cetyltrimethylammonium (CTA+) cations in chemical preintercalation synthesis followed by hydrothermal treatment, the interlayer distance of hybrid bilayered vanadium oxides (BVOs) can be tuned between 11.1 Å and 35.6 Å. Our analyses reveal that these variations in interlayer spacing are due to different amounts of structural water and alkylammonium cations confined within the interlayer regions. Increased concentrations of alkylammonium cations not only expand the interlayer spacing but also induce local bending and disordering of the V-O bilayers. Electrochemical cycling of hybrid BVO electrodes in non-aqueous lithium-ion cells show that specific capacities decrease as interlayer regions expand, suggesting that the densely packed alkylammonium cations obstruct intercalation sites and hinder Li+ ion transport. Furthermore, we found that greater layer separation facilitates the dissolution of active material into the electrolyte, resulting in rapid capacity decay during extended cycling. This study emphasizes that layered electrode materials require both spacious interlayer regions as well as high structural and chemical stabilities, providing guidelines for structural engineering of organic-inorganic hybrids.

Quantifying Atomically Dispersed Catalysts Using Deep Learning Assisted Microscopy.

The catalytic performance of atomically dispersed catalysts (ADCs) is greatly influenced by their atomic configurations, such as atom-atom distances, clustering of atoms into dimers and trimers, and their distributions. Scanning transmission electron microscopy (STEM) is a powerful technique for imaging ADCs at the atomic scale; however, most STEM analyses of ADCs thus far have relied on human labeling, making it difficult to analyze large data sets. Here, we introduce a convolutional neural network (CNN)-based algorithm capable of quantifying the spatial arrangement of different adatom configurations. The algorithm was tested on different ADCs with varying support crystallinity and homogeneity. Results show that our algorithm can accurately identify atom positions and effectively analyze large data sets. This work provides a robust method to overcome a major bottleneck in STEM analysis for ADC catalyst research. We highlight the potential of this method to serve as an on-the-fly analysis tool for catalysts in future in situ microscopy experiments.

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 milling with scanning electron microscopy and spectroscopy. Journal of Visualized Experiments. (185), e61955 (2022). Ohtsuka, M., Muto, S. Quantitative atomic-site analysis of functional dopants/point defects in crystalline materials by electron-channeling-enhanced microanalysis. Journal of Visualized Experiments. (171), e62015 (2021). Miao, L., Chmielewski, A., Mukherjee, D., Alem, N. Picometer-precision atomic position tracking through electron microscopy. Journal of Visualized Experiments. (173), e62164 (2021). Unocic, K. A. et al. Performing in situ closed-cell gas reactions in the transmission electron microscope. Journal of Visualized Experiments. (173), e62174 (2021). Zheng, F. et al. Magnetic field mapping using off-axis electron holography in the transmission electron microscope. Journal of Visualized Experiments. (166), e61907 (2020).

Chemical and Physical Drivers for Improvement in Permeance and Stability of Linker-Free Graphene Oxide Membranes.

Graphene oxide (GO) is a promising membrane material for chemical separations, including water treatment. However, GO has often required postsynthesis chemical modifications, such as linkers or intercalants, to improve either the permeability, performance, or mechanical integrity of GO membranes. In this work, we explore two different feedstocks of GO to investigate chemical and physical differences, where we observe up to a 100× discrepancy in the permeability-mass loading trade-off while maintaining nanofiltration capacity. GO membranes also show structural stability and chemical resilience to harsh pH conditions and bleach treatment. We probe GO and the resulting assembled membranes through a variety of characterization approaches, including a novel scanning-transmission-electron-microscopy-based visualization approach, to connect differences in sheet stacking and oxide functional groups to significant improvements in permeability and chemical stability.

Cation-Driven Assembly of Bilayered Vanadium Oxide and Graphene Oxide Nanoflakes to Form Two-Dimensional Heterostructure Electrodes for Li-Ion Batteries.

Lithium preintercalated bilayered vanadium oxide (LVO or δ-LixV2O5·nH2O) and graphene oxide (GO) nanoflakes were assembled using a concentrated lithium chloride solution and annealed under vacuum at 200 °C to form two-dimensional (2D) δ-LixV2O5·nH2O and reduced GO (rGO) heterostructures. We found that the Li+ ions from LiCl enhanced the oxide/carbon heterointerface formation and served as stabilizing ions to improve structural and electrochemical stability. The graphitic content of the heterostructure could be easily controlled by changing the initial GO concentration prior to assembly. We found that increasing the GO content in our heterostructure composition helped inhibit the electrochemical degradation of LVO during cycling and improved the rate capability of the heterostructure. A combination of scanning electron microscopy and X-ray diffraction was used to help confirm that a 2D heterointerface formed between LVO and GO, and the final phase composition was determined using energy-dispersive X-ray spectroscopy and thermogravimetric analysis. Scanning transmission electron microscopy and electron energy-loss spectroscopy were additionally used to examine the heterostructures at high resolution, mapping the orientations of rGO and LVO layers and locally imaging their interlayer spacings. Further, electrochemical cycling of the cation-assembled LVO/rGO heterostructures in Li-ion cells with a non-aqueous electrolyte revealed that increasing the rGO content led to improved cycling stability and rate performance, despite slightly decreased charge storage capacity. The heterostructures with 0, 10, 20, and 35 wt % rGO exhibited capacities of 237, 216, 174, and 150 mAh g-1, respectively. Moreover, the LVO/rGO-35 wt % and LVO/rGO-20 wt % heterostructures retained 75% (110 mAh g-1) and 67% (120 mAh g-1) of their initial capacities after increasing the specific current from 20 to 200 mA g-1, while the LVO/rGO-10 wt % sample retained only 48% (107 mAh g-1) of its initial capacity under the same cycling conditions. In addition, the cation-assembled LVO/rGO electrodes exhibited enhanced electrochemical stability compared to electrodes prepared through physical mixing of LVO and GO nanoflakes in the same ratios as the heterostructure electrodes, further revealing the stabilizing effect of a 2D heterointerface. The cation-driven assembly approach, explored in this work using Li+ cations, was found to induce and stabilize the formation of stacked 2D layers of rGO and exfoliated LVO. The reported assembly methodology can be applied for a variety of systems utilizing 2D materials with complementary properties for applications as electrodes in energy storage devices.

Dual-site catalysts featuring platinum-group-metal atoms on copper shapes boost hydrocarbon formations in electrocatalytic CO2 reduction.

Copper-based catalyst is uniquely positioned to catalyze the hydrocarbon formations through electrochemical CO2 reduction. The catalyst design freedom is limited for alloying copper with H-affinitive elements represented by platinum group metals because the latter would easily drive the hydrogen evolution reaction to override CO2 reduction. We report an adept design of anchoring atomically dispersed platinum group metal species on both polycrystalline and shape-controlled Cu catalysts, which now promote targeted CO2 reduction reaction while frustrating the undesired hydrogen evolution reaction. Notably, alloys with similar metal formulations but comprising small platinum or palladium clusters would fail this objective. With an appreciable amount of CO-Pd1 moieties on copper surfaces, facile CO* hydrogenation to CHO* or CO-CHO* coupling is now viable as one of the main pathways on Cu(111) or Cu(100) to selectively produce CH4 or C2H4 through Pd-Cu dual-site pathways. The work broadens copper alloying choices for CO2 reduction in aqueous phases.

High Velocity, Low-Voltage Collective In-Plane Switching in (100) BaTiO3 Thin Films.

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) BaTiO3 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 1 ¯ $\bar{1}$ ] 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-1 at 5 V (7 kV cm-1 ), orders-of-magnitude faster than expected. These combinations of properties are promising for high-speed tunable dielectrics and low-voltage ferroelectric memories and logic.

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

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.

Measuring and directing charge transfer in heterogenous catalysts.

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/SrTiO3-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.

Atomically Dispersed Dual-Metal Site Catalysts for Enhanced CO2 Reduction: Mechanistic Insight into Active Site Structures.

Carbon-supported nitrogen-coordinated single-metal site catalysts (i.e., M-N-C, M: Fe, Co, or Ni) are active for the electrochemical CO2 reduction reaction (CO2 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)N6 , in which FeN4 and NiN4 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 (FeN4 or NiN4 ) with improved intrinsic catalytic activity and selectivity.

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

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 VRHE), 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 VRHE 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 ex situ aqueous experiments and MEA tests. While different catalysts may require a unique modification to the AST protocol, strategies provided in this work enable future in situ and identical-location experiments that will play an important role in the development of robust catalysts for heavy-duty vehicle applications.

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

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.

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

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.

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

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 Nd1/2Sr1/2MnO3. 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.

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

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.