Atomic-resolution imaging of battery materials is critical for identification of local defects and structural variations, which are tied to battery performance. However, since battery materials are, by design, optimized to allow ion motion in response to an applied electric field, they are also very sensitive to radiation damage by an electron beam. Image resolution is therefore severely constrained by the dose applied. Here, we show that multislice electron ptychography (MEP) can provide sub-ångström lateral resolution images of both light and heavy elements of a Li-ion battery cathode, along with nanometer-scale depth information and greater dose efficiency than conventional electron microscopy methods. Using the depth-sectioning capability of MEP, we have been able to obtain direct visualizations of Li vacancy clusters, atom column by atom column, in LixNi0.33Mn0.33Co0.33O2 (NMC111) cathodes. This capability to track Li distributions will be valuable in understanding, informing, and optimizing electrode material design for ion storage and transfer.

Abstract Aqueous acidic batteries utilizing corrosion-resistant Sn metal anodes have emerged as promising candidates for safe energy storage systems. However, uncontrolled dendritic growth under high-rate operation remains a major obstacle. Here we showed that artificial layers acting solely as a physical barrier are insufficient to regulate Sn deposition. We instead introduced an active-site-rich porous carbon (PC) layer with abundant N-defect sites that simultaneously governs the interfacial charge distribution and Sn nucleation. This architecture enabled highly uniform Sn deposition both within the PC layer and on the underlying substrate. Crucially, we identified the formation of an H3O+-enriched electric double layer in acidic electrolytes as the key factor driving Sn nanoparticle deposition within the carbon layer. Consequently, this artificial layer strategy significantly improved the reversibility and stability of Sn anodes, achieving a high average Coulombic efficiency of 99.72% for 16,000 cycles in asymmetric cells and maintaining 83.5% capacity retention after 20,000 cycles in pouch cells.

Oxygen dopants play a critical role in tuning the properties of cuprate superconductors, yet it is challenging to visualize them at the atomic scale. Here, we use multislice electron ptychography to directly image oxygen dopants in a Sr2CuO3+delta film. We observe oxygen dopants at interstitial sites between the Cu-O chains, with a strong preference for clustering in tensile-strained regions, which are often associated with dislocations and interfacial steps. These findings indicate that the oxygen dopant distribution in cuprates is not random but rather sensitive to strain field, suggesting strain as a doping tuning parameter.

The ability to tune electronic structure in twisted stacks of layered, two-dimensional (2D) materials has motivated the exploration of similar moiré physics with stacks of twisted oxide membranes. Due to the intrinsic three-dimensional nature of bonding in many oxides, achieving atomic-level coupling is significantly more challenging than in 2D materials. Although clean interfaces with atomic-level proximity have been demonstrated in bulk ceramic bicrystals using high-temperature and high-pressure processing to facilitate atomic diffusion that flattens rough interfaces, such conditions are not readily accessible when bonding oxide membranes. This study shows how topographic mismatch from surface roughness of the membranes restricts atomic-scale proximity at the interface to isolated patches even after contaminants and amorphous interlayers are eliminated. The reduced ability of 2D materials to conform to a membrane's step-terrace topography also limits atomic-scale contact. In all these material systems, the interface morphology is best characterized using cross-sectional imaging and is necessary to corroborate investigations of interlayer coupling. When imaging the stacked membranes in projection, conventional through-focal imaging is found to be insensitive to the buried interface, whereas electron ptychography reliably resolves structural variations on the order of a nanometer. These findings highlight interface roughness as a key challenge for oxide twistronics.

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub( https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1 ) and Zenodo ( https://zenodo.org/records/15579940 ).

A novel synthesis route torwards small (<5 nm), low-dispersity (<20%) high entropy and multi-metal rock-salt oxide nanoparticles is described. The synthesis was achieved using a combination of oleylamine and dodecanol as ligands and metal acetylacetonates as precursors with a simple heat-up procedure.

Strain engineering of electrocatalysts has been an extensively studied field in recent years, but there has been limited investigation of strain and ligand effects in the catalysts of heterostructured oxides. Such studies could have significant impacts as the localized changes in the electronic structure of metal oxide shells may induce enhanced catalytic activity, complementing those from the well-studied metallic systems. Here, we developed a colloidal synthesis route to monodisperse core-shell spinel oxide nanocrystals with tunable shell thickness for the oxygen reduction reaction (ORR) in alkaline media. We compare the activity of these heterostructured particles, finding a higher activity for smaller shell thicknesses. The smallest shell thickness aligns with the highest shell strain. The best-performing core-shell sample achieved a half-wave potential of 0.893 V versus RHE in 1.0 M KOH, making it one of the best-reported values for a spinel oxide electrocatalyst for alkaline ORR with a PGM-free catalyst. In addition, this value is within 11 mV of that of the Pt/C reference material. Though a Pt/C reference sample has an overall higher mass activity at 0.9 V vs RHE, when cost is considered, the strained spinel outperforms the Pt/C by over 600-fold at this potential. Our results provide an impetus for exploring the deliberate and controlled use of strain engineering in metal oxides as high-performance, low-cost electrocatalysts.

Electron ptychography has recently achieved unprecedented resolution, offering valuable insights across diverse material systems, including in three dimensions. However, high-quality ptychographic reconstruction is computationally expensive and time consuming, requiring a significant amount of manually tuning even for experts. Additionally, essential tools for ptychographic analysis are often scattered across multiple software packages, with some advanced features available only in costly commercial software like MATLAB. To address these challenges, we introduce PtyRAD (Ptychographic Reconstruction with Automatic Differentiation), an open-source software framework offers a comprehensive, flexible, and computationally efficient solution for electron ptychography. PtyRAD provides seamless optimization of multiple parameters-such as sample thickness, local tilts, probe positions, and mixed probe and object modes-using gradient-based methods with automatic differentiation. By utilizing PyTorch's highly optimized tensor operations, PtyRAD achieves up to a 24× speedup in reconstruction time compared to existing packages without compromising image quality. In addition, we propose a real-space depth regularization, which avoids wrap-around artifacts and can be useful for twisted two-dimensional material datasets and vertical heterostructures. Moreover, PtyRAD integrates a Bayesian optimization workflow that streamlines hyperparameter selection. We hope the open-source nature of PtyRAD will foster reproducibility and community-driven development for future advances in ptychographic imaging.

With the decreasing sizes of integrated-circuit components, the semiconductor industry is in growing need of high-throughput strain mapping techniques that offer high precision and spatial resolution, with desired industry goals of 0.01-0.1

Modern electromechanical actuators and sensors rely on the piezoelectric effect that linearly couples strain and electric polarization. However, this effect is restricted to materials that lack inversion symmetry. In contrast, the flexoelectric effect couples strain gradients to electric polarization, and is a universal property in insulating materials of arbitrary symmetry. Flexoelectricity becomes prominent at the nanoscale from the inverse scaling of strain gradients with material dimensions. Here, we measure the strain-gradient-induced structural distortions in strontium titanate using multislice electron ptychography. This technique enables reliable picometer-scale measurements of the dominant oxygen-titanium distortions, correcting for artifacts that limited conventional imaging methods. This enables us to directly measure the sign of the net ionic contribution to the flexoelectric polarization. Guided by the experimental measurements, first-principles calculations show how the sign and magnitude of the bulk contribution to the flexoelectric coefficient in strontium titanate can be switched by tuning the strain state. Hybridization between the optical soft phonon and acoustic phonon modes drives this transition, yielding a large response and a polarity switch across the resonance. This strain-dependence might explain the sign discrepancy and orders of magnitude variation in the values of previously reported flexoelectric coefficients for strontium titanate. As the strain state of curved membranes can be tuned, our approach also suggests an approach to engineer nanoscale flexoelectric polarization using strain as a control parameter.

Spinel oxides such as ternary cobalt manganese spinel oxides (CMOs) are promising electrocatalysts for oxygen reduction reaction (ORR) in anion exchange membrane fuel cells. Current efforts to enhance fuel cell cathode performance predominantly focus on tuning the ORR activity through the chemical and crystallographic engineering of the active material. However, the impact of ink formulation and film homogeneity on fuel cell performance remains poorly understood and under-investigated. Here we show that the deliberate retention of organic ligands can enhance the performance of a CMO/C composite by improving its film homogeneity. Surprisingly, retaining the organic ligands can optimize the catalyst-ionomer affinity and subsequent film homogeneity of this system, thus enhancing its fuel cell peak power density from 0.8 W/cm(2) to 1.2 W/cm(2). We demonstrate this effect by pre- and postsynthetic characterizations of single-batch and monodisperse CMO/C composites and films, in the presence (retained) and absence (removed) of organic ligands. Our results demonstrate that ink dispersion and film homogeneity are critical parameters in fuel cell electrocatalysis and how organic ligands can help enhance electrocatalytic film performance in systems that suffer from unfavorable electrocatalyst-ionomer interactions.

Synthesis of high-entropy oxide (HEO) nanocrystals has focused on increasing the temperature in the entropy term (T(ΔS)) to overcome the enthalpy term. However, these high temperatures lead to large, polydisperse nanocrystals. In this work, we leverage the low solubility product (Ksp) of metal oxides and optimize the Lewis-acid-catalyzed esterification reaction for equal rate production of the cation monomers to synthesize HEO nanocrystals at low temperatures, producing the smallest (<4 nm) and most monodisperse (<15% size dispersity) HEOs to date. We apply these HEO nanocrystals as electrocatalysts, exhibiting promising activity toward the oxygen evolution reaction in alkaline media, with an overpotential of 345 mV at 10 mA/cm2.

We present a facile colloidal synthesis method to produceuniform-sized(9 nm) CoMn2O4 spinel nano-octahedra tailoredwith {101} facets. These nano-octahedra demonstrate enhanced electrocatalyticactivity for the oxygen reduction reaction (ORR) in alkaline mediacompared to their spherical counterparts and previously reported spinelelectrocatalysts. At 0.85 V, they achieve a high mass activity (MA)of 60.0 A/g, surpassing their spherical counterparts (38.6 A/g). Moreover,the CoMn2O4 nano-octahedra exhibit favorablestability, maintaining an MA of 47.2 A/g after 10 000 durabilitycycles. This work highlights a promising approach for synthesizingadvanced spinel nanooxides with controlled crystal facets, which holdthe potential to serve as nonprecious metal ORR electrocatalysts.The enhanced ORR performance is attributed to the exposed active catalystsurfaces in the well-defined structures of the nano-octahedra, emphasizingthe significance of catalyst shape control.

Surface structural transformations are important in electrocatalysis as reactions take place at surfaces [1,2].Many electrocatalysts such as metal alloy, metal oxide, and metal nitride nanoparticles undergo surface transformations and generate a different phase on the surface, forming a core-shell structure [3][4][5] altering the expected surface chemistry [6].Measuring the structure, coverage and continuity of the shell, and how it coupled to the core requires a method that can provide atomic-resolution information with a depth-sensitivity beyond that of conventional imaging modes, and at a lower dose than tilt-series tomography.Multi-slice electron ptychography can in principle meet this challenge by providing a dose-efficient, high-spatial-resolution reconstruction of the scattering potential with depth information [7].Here we studied MnN nanoparticles that are of interest as cathode electrode catalysts for anion-exchange membrane fuel cells (AEMFCs) [8].As with many other metal nitrides, MnN nanoparticles generate a layer of manganese oxide (e.g., Mn 3 O 4 ) on their surface in the presence of air or during alkaline oxygen reduction reaction (ORR) electrochemical testing.Here, the combination of high angle annular dark field (HAADF) images along the [110] zone axis of MnN nanoparticles and electron energy-loss spectroscopy (EELS) demonstrated island-like growth of Mn 3 O 4 layers with different thicknesses after 10k ORR cycles (Figure 1 a-b).With less electron dose, the reconstructed ptychography stack provides the position of Mn, O, and N atoms, with an improved resolution compared to HAADF (Figure 1c).Moreover, without dose-intensive tomography, HAADF images lack the depth sensitivity to resolve the complex surface structures with overlapping nanoparticles along the Z axis and tilting often occurring in nano-domains.By changing the defocus value in HAADF, we get some sense that the some overlapped trapezoidal Mn 3 O 4 nano-islands nucleated heterogeneously on the MnN nanoparticle surface (Figure 2 a).Nonetheless, the overlap greatly complicates prospects for obtaining physically meaningful strain maps from the HAADF images.Here we apply multi-slice electron ptychography [7] to characterize the electrocatalyst surface in 3D, imaging with both heavy and light elements at sub-Angstrom lateral resolution.A single ptychographic reconstruction shows details of different MnN/ Mn 3 O 4 interfaces at different depths of view (Figure 2b).Within a single ptychography stack, we separate the structural information from two different Mn 3 O 4 nano-islands at different depths of view even when overlapped with sufficient details to allow us to study lattice displacements and strain separately from each grain.The heterogenous nucleation of the Mn 3 O 4 nano-islands is visible in the orthogonal XZ slices.The misregistration between the two Mn 3 O 4 grains can be seen in slices 2-5, and is a consequence of the degeneracy of possible registrations between the Mn-O unit and O-Mn-O unit in Mn 3 O 4 unit cells.These quantitative insights into three-dimensional atomic structures of electrocatalyst surface layers, especially continuity, uniformity and strain help us better understand reaction mechanisms and durability of the catalyst nanoparticles.[9]

The structural characteristics of supports, such as surface area and type of porosity, affect the deposition of electrocatalysts and greatly influence their electrochemical performance in fuel cells. In this work, we use a series of high surface area hierarchical porous carbons (HPCs) with defined mesoporosity as model supports to study the deposition mechanism of Pt nanoparticles. The resulting electrocatalysts are characterized by several analytical techniques, and their electrochemical performance is compared to a state-of-the-art, commercial Pt/C system. Despite the similar chemical composition and surface area of the supports, as well as similar amounts of Pt precursor used, the size of the deposited Pt nanoparticles varies, and it is inversely proportional to the mesopore size of the system. In addition, we show that an increase in the size of the catalyst particles can increase the specific activity of the oxygen reduction reaction. We also report on our efforts to improve the overall performance of the above electrocatalyst systems and show that increasing the electronic conductivity of the carbon support by the addition of highly conductive graphene sheets improves the overall performance of an alkaline fuel cell.

While certain ternary spinel oxides have been well-explored with colloidal nanochemistry, notably the ferrite spinel family, ternary manganese (Mn)-based spinel oxides have not been tamed. A key composition is cobalt (Co)-Mn oxide (CMO) spinel, CoxMn3-xO4, that, despite exemplary performance in multiple electrochemical applications, has few reports in the colloidal literature. Of these reports, most show aggregated and polydisperse products. Here, we describe a synthetic method for small, colloidally stable CMO spinel nanocrystals with tunable composition and low dispersity. By reacting 2+ metal-acetylacetonate (M(acac)2) precursors in an amine solvent under an oxidizing environment, we developed a pathway that avoids the highly reducing conditions of typical colloidal synthesis reactions; these reducing conditions typically push the system toward a monoxide impurity phase. Through surface chemistry studies, we identify organic byproducts and their formation mechanism, enabling us to engineer the surface and obtain colloidally stable nanocrystals with low organic loading. We report a CMO/carbon composite with low organic contents that performs the oxygen reduction reaction (ORR) with a half-wave potential (E1/2) of 0.87 V vs RHE in 1.0 M potassium hydroxide at 1600 rpm, rivaling previous reports for the highest activity of this material in ORR electrocatalysis. We extend the general applicability of this procedure to other Mn-based spinel nanocrystals such as Zn-Mn-O, Fe-Mn-O, Ni-Mn-O, and Cu-Mn-O. Finally, we show the scalability of this method by producing inorganic nanocrystals at the gram scale.

Journal Article Imaging Li Vacancies in a Li-Ion Battery Cathode Material by Depth Sectioning Multi-slice Electron Ptychographic Reconstructions Get access Dasol Yoon, Dasol Yoon School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United StatesDepartment of Materials Science and Engineering, Cornell University, Ithaca, NY, United States Search for other works by this author on: Oxford Academic Google Scholar Yu-Tsun Shao, Yu-Tsun Shao School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United StatesMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Yao Yang, Yao Yang Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States Search for other works by this author on: Oxford Academic Google Scholar Dong Ren, Dong Ren Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States Search for other works by this author on: Oxford Academic Google Scholar Hector D Abruña, Hector D Abruña Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States Search for other works by this author on: Oxford Academic Google Scholar David A Muller David A Muller School of Applied and Engineering Physics, Cornell University, Ithaca, NY, United StatesKavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY, United States Corresponding author: david.a.muller@cornell.edu Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 29, Issue Supplement_1, 1 August 2023, Pages 1263–1264, https://doi.org/10.1093/micmic/ozad067.647 Published: 22 July 2023