TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy

Heterometallic Transition Metal Oxides Containing Lewis Acids as Molecular Catalysts for the Reduction of Carbon Dioxide to Carbon Monoxide with Bimodal Activity

Electrocatalytic CO2 reduction (e-CO2RR) to CO is replete with challenges including the need to carry out e-CO2RR at low overpotentials. Previously, a tricopper-substituted polyoxometalate was shown to reduce CO2 to CO with a very high faradaic efficiency albeit at -2.5 V versus Fc/Fc+. It is now demonstrated that introducing a nonredox metal Lewis acid, preferably GaIII, as a binding site for CO2 in the first coordination sphere of the polyoxometalate, forming heterometallic polyoxometalates, e.g., [SiCuIIFeIIIGaIII(H2O)3W9O37]8-, leads to bimodal activity optimal both at -2.5 and -1.5 V versus Fc/Fc+; reactivity at -1.5 V being at an overpotential of ∼150 mV. These results were observed by cyclic voltammetry and quantitative controlled potential electrolysis where high faradaic efficiency and chemoselectivity were obtained at -2.5 and -1.5 V. A reaction with 13CO2 revealed that CO2 disproportionation did not occur at -1.5 V. EPR spectroscopy showed reduction, first of CuII to CuI and FeIII to FeII and then reduction of a tungsten atom (WVI to WV) in the polyoxometalate framework. IR spectroscopy showed that CO2 binds to [SiCuIIFeIIIGaIII(H2O)3W9O37]8- before reduction. In situ electrochemical attenuated total reflection surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) with pulsed potential modulated excitation revealed different observable intermediate species at -2.5 and -1.5 V. DFT calculations explained the CV, the formation of possible activated CO2 species at both -2.5 and -1.5 V through series of electron transfer, proton-coupled electron transfer, protonation and CO2 binding steps, the active site for reduction, and the role of protons in facilitating the reactions.

Rational partitioning of spectral feature space for effective clustering of massive spectral image data

We have successfully proposed and demonstrated a clustering method that overcomes the "needle-in-a-haystack problem" (finding minuscule important regions from massive spectral image data sets). The needle-in-a-haystack problem is of central importance in the characterization of materials since in bulk materials, the properties of a very tiny region often dominate the entire function. To solve this problem, we propose that rational partitioning of the spectral feature space in which spectra are distributed, or defining of the decision boundaries for clustering, can be performed by focusing on the discrimination limit defined by the measurement noise and partitioning the space at intervals of this limit. We verified the proposed method, applied it to actual measurement data, and succeeded in detecting tiny (~ 0.5%) important regions that were difficult for human researchers and other machine learning methods to detect in discovering unknown phases. The ability to detect these crucial regions helps in understanding materials and designing more functional materials.

High absorptivity nanotextured powders for additive manufacturing

The widespread application of metal additive manufacturing (AM) is limited by the ability to control the complex interactions between the energy source and the feedstock material. Here, we develop a generalizable process to introduce nanoscale grooves to the surface of metal powders which increases the powder absorptivity by up to 70% during laser powder bed fusion. Absorptivity enhancements in copper, copper-silver, and tungsten enable energy-efficient manufacturing, with printing of pure copper at relative densities up to 92% using laser energy densities as low as 83 joules per cubic millimeter. Simulations show that the enhanced powder absorptivity results from plasmon-enabled light concentration in nanoscale grooves combined with multiple scattering events. The approach taken here demonstrates a general method to enhance the absorptivity and printability of reflective and refractory metal powders by changing the surface morphology of the feedstock without altering its composition.

Transmission X-ray microscopy-based three-dimensional XANES imaging

Full-field transmission X-ray microscopy (TXM) in conjunction with X-ray absorption near edge structure (XANES) spectroscopy provides two-dimensional (2D) or three-dimensional (3D) morphological and chemical-specific information within samples at the tens of nanometer scale. This technique has a broad range of applications in materials sciences and battery research. Despite its extensive applicability, 2D XANES imaging is subject to the disadvantage of information overlap when the sample thickness is uneven. 3D XANES imaging combines 3D TXM with XANES to obtain 3D distribution information on chemical states. A 3D XANES imaging method has been established at the Shanghai Synchrotron Radiation Facility (SSRF) and has been used to characterize the structure and chemical state of commercial LiNixCoyMnzO2 (NCM, x + y + z = 1) battery powder materials. The imaging results provide a visual representation of the 3D chemical state information of the particles with depth resolution, allowing for the direct observation of 3D nickel oxidation. This paper will describe in detail the data acquisition, data processing, quantification and visualization analysis of 3D XANES imaging.

TomoPyUI: a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data (i.e. organizing data/metadata, applying image filters etc.) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI, a user interface for the well known tomography data processing package TomoPy. This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI, along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI, and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments

Synchrotron tomography experiments are transitioning into multifunctional, cross-scale, and dynamic characterizations, enabled by new-generation synchrotron light sources and fast developments in beamline instrumentation. However, with the spatial and temporal resolving power entering a new era, this transition generates vast amounts of data, which imposes a significant burden on the data processing end. Today, as a highly accurate and efficient data processing method, deep learning shows great potential to address the big data challenge being encountered at future synchrotron beamlines. In this review, we discuss recent advances employing deep learning at different stages of the synchrotron tomography data processing pipeline. We also highlight how applications in other data-intensive fields, such as medical imaging and electron tomography, can be migrated to synchrotron tomography. Finally, we provide our thoughts on possible challenges and opportunities as well as the outlook, envisioning selected deep learning methods, curated big models, and customized learning strategies, all through an intelligent scheduling solution.

Beagle: a near-edge X-ray absorption fine-structure spectroscopy data processing solution for beamline experiments at Pohang Accelerator Laboratory

Near-edge X-ray absorption fine-structure (NEXAFS) spectroscopy is a powerful tool for identifying chemical bonding states at synchrotron radiation facilities. Advances in new materials require researchers in both academia and industry to measure tens to hundreds of samples during the available beam time on a synchrotron beamline, which is typically allocated to users. Automated measurement methods, along with analysis software, have been developed for beamlines. Automated measurements facilitate high-throughput experiments and accumulate vast amounts of measured spectral data. The analysis software supports various functions for analyzing the experimental data; however, these analysis methods are complicated, and learning them can be time-consuming. To process large amounts of spectral data, a new analysis software, dedicated to NEXAFS spectroscopy, that is easy to use and can provide results in a short time is desired. Herein, the development of Beagle is described, software calculating molecular orientation from NEXAFS spectroscopy data that can report results in a short time comparable with that required to measure one sample at the beamline. It was designed to progress in a single sequence from data loading to the printing of the results with a `click of a button'. The functions of the software include recognizing the dataset, correcting the background, normalizing the plot, calculating the electron yield and determining the molecular orientation. The analysis results can be saved as {\tt{.txt}} files (spectral data), {\tt{.pdf}} files (graphic images) and Origin files (spectral data and graphic images).

Correlated x-ray fluorescence and ptychographic nano-tomography on Rembrandt's The Night Watch reveals unknown lead "layer"

The Night Watch, one of the most famous masterpieces by Rembrandt, is the subject of a large research and conservation project. For the conservation treatment, it is of great importance to understand its current condition. Correlated nano-tomography using x-ray fluorescence and ptychography revealed a-so far unknown-lead-containing "layer", which likely acts as a protective impregnation layer applied on the canvas before the quartz-clay ground was applied. This layer might explain the presence of lead soap protrusions in areas where no other lead components are present. In addition to the three-dimensional elemental mapping, ptychography visualizes and quantifies components not detectable by hard x-ray fluorescence such as the organic fraction and quartz. The first-time use of this combination of synchrotron-based techniques on a historic paint micro-sample shows it to be an important tool to better interpret the results of noninvasive imaging techniques operating on the macroscale.

Designing of fluorine-substituted benzodithiophene-based small molecules with efficient photovoltaic parameters

In this study, four hole-transporting materials (JY-M1, JY-M2, JY-M3, and JY-M4) are designed by modifying benzothiadiazole-based core with diphenylamine-based carbazole via acceptors through thiophene linkers. The designed molecules exhibited deeper HOMO energy with smaller energy gaps than the reference JY molecule which enhance their hole mobility. The absorption spectra of the JY-M1, JY-M2, JY-M3, and JY-M4 molecules are located at 380 nm to 407 nm in the gaseous phase and 397 nm to 433 nm in the solvent phase, which is red-shifted and higher than the reference molecule, demonstrating that designed molecules possess improved light absorption properties and enhanced effective hole transfer. The dipole moments of the designed molecules (14.74 D to 26.12 D) indicate a greater ability for charge separation, solubility and will be beneficial to produce multilayer films. Moreover, the results of hole reorganization energy (0.38198 eV to 0.45304 eV) and charge transfer integral (0.14315 eV to 0.14665 eV) of designing molecules show improved hole mobility and lower recombination losses compared to the JY molecule. Overall, we suggested that the structural modifications in the designed molecules contributed to their enhanced efficiency in converting light energy into electrical energy and have the potential for utilization in solar devices, paving the way for future advancements in the field of photovoltaics.

A general image misalignment correction method for tomography experiments

Tomography experiments generate three-dimensional (3D) reconstructed slices from a series of two-dimensional (2D) projection images. However, the mechanical system generates joint offsets that result in unaligned 2D projections. This misalignment affects the reconstructed images and reduces their actual spatial resolution. In this study, we present a novel method called outer contour-based misalignment correction (OCMC) for correcting image misalignments in tomography. We use the sample's outer contour structure as auxiliary information to estimate the extent of misalignment in each image. This method is generic and can be used with various tomography imaging techniques. We validated our method with five datasets collected from different samples and across various tomography techniques. The OCMC method demonstrated significant advantages in terms alignment accuracy and time efficiency. As an end-to-end correction method, OCMC can be easily integrated into an online tomography data processing pipeline and facilitate feedback control in future synchrotron tomography experiments.

Critical Factors to Understanding the Electrochemical Performance of All-Solid-State Batteries: Solid Interfaces and Non-Zero Lattice Strain

All-solid-state lithium batteries have been developed to secure safety by substituting a flammable liquid electrolyte with a non-flammable solid electrolyte. However, owing to the nature of solids, interfacial issues between cathode materials and solid electrolytes, including chemical incompatibility, electrochemo-mechanical behavior, and physical contact, pose significant challenges for commercialization. Herein, critical factors for understanding the performance of all-solid-state batteries in terms of solid interfaces and non-zero lattice strains are identified through a strategic approach. The initial battery capacity can be increased via surface coating and electrode-fabrication methods; however, the increased lattice strain causes significant stress to the solid interface, which degrades the battery cycle life. However, this seesaw effect can be alleviated using a more compacted electrode microstructure between the solid electrolyte and oxide cathode materials. The compact solid interfaces contribute to low charge-transfer resistance and a homogeneous reaction between particles, thereby leading to improved electrochemical performance. These findings demonstrate, for the first time, a correlation between the uniformity of the electrode microstructure and electrochemical performance through the investigation of the reaction homogeneity among particles. Additionally, this study furthers the understanding of the relationship between electrochemical performance, non-zero lattice strain, and solid interfaces.

Softening of PEO-LiTFSI/LLZTO Composite Polymer Electrolytes for Solid-State Batteries under Cyclic Compression

Composite polymer electrolytes (CPEs) strike an effective balance between ionic conductivity and mechanical flexibility for lithium-ion solid-state batteries. Long-term performance, however, is limited by capacity fading after hundreds of charge and discharge cycles. The causes of performance degradation include multiple contributing factors such as dendrite formation, physicochemical changes in electrolytes, and structural remodeling of porous electrodes. Among the many factors that contribute to performance degradation, the effect of stress specifically on the composite electrolyte is not well understood. This study examines the mechanical changes in a poly(ethylene oxide) electrolyte with bis(trifluoromethane) sulfonimide. Two different sizes of Li6.4La3Zr1.4Ta0.6O12 particles (500 nm and 5 μm) are compared to evaluate the effect of the surface-to-volume ratio of the ion-conducting fillers within the composite. Cyclic compression was applied to mimic stress cycling in the electrolyte, which would be caused by asymmetric volume changes that occur during charging and discharging cycles. The electrolytes exhibited fatigue softening, whereby the compressive modulus gradually decreased with an increase in the number of cycles. When the electrolyte was tested for 500 cycles at 30% compressive strain, the compressive modulus of the electrolyte was reduced to approximately 80% of the modulus before cycling. While the extent of softening was similar regardless of particle size, CPEs with 500 nm particles exhibited a significant reduction in ionic conductivity after cyclic compression (1.4 × 10-7 ± 2.3 × 10-8 vs 1.1 × 10-7 ± 2.0 × 10-8 S/cm, mean ± standard deviation, n = 4), whereas there was no significant change in ionic conductivity for CPEs with 5 μm particles. These observations -performed deliberately in the absence of charge-discharge cycles -show that repetitive mechanical stresses can play a significant role in altering the performance of CPEs, thereby revealing another possible mechanism for performance degradation in all-solid-state batteries.

Temperature-Dependent Morphological Evolution during Corrosion of the Ni-20Cr Alloy in Molten Salt Revealed by Multiscale Imaging

Understanding the mechanisms leading to the degradation of alloys in molten salts at elevated temperatures is significant for developing several key energy generation and storage technologies, including concentrated solar and next-generation nuclear power plants. Specifically, the fundamental mechanisms of different types of corrosion leading to various morphological evolution characteristics for changing reaction conditions between the molten salt and alloy remain unclear. In this work, the three-dimensional (3D) morphological evolution of Ni-20Cr in KCl-MgCl₂ is studied at 600 °C by combining in situ synchrotron X-ray and electron microscopy techniques. By further comparing different morphology evolution characteristics in the temperature range of 500-800 °C, the relative rates between diffusion and reaction at the salt-metal interface lead to different morphological evolution pathways, including intergranular corrosion and percolation dealloying. In this work, the temperature-dependent mechanisms of the interactions between metals and molten salts are discussed, providing insights for predicting molten salt corrosion in real-world applications.

Solid-State Reaction Heterogeneity During Calcination of Lithium-Ion Battery Cathode

During solid-state calcination, with increasing temperature, materials undergo complex phase transitions with heterogeneous solid-state reactions and mass transport. Precise control of the calcination chemistry is therefore crucial for synthesizing state-of-the-art Ni-rich layered oxides (LiNi_1-x-y Co_x Mn_y O₂ , NRNCM) as cathode materials for lithium-ion batteries. Although the battery performance depends on the chemical heterogeneity during NRNCM calcination, it has not yet been elucidated. Herein, through synchrotron-based X-ray, mass spectrometry microscopy, and structural analyses, it is revealed that the temperature-dependent reaction kinetics, the diffusivity of solid-state lithium sources, and the ambient oxygen control the local chemical compositions of the reaction intermediates within a calcined particle. Additionally, it is found that the variations in the reducing power of the transition metals (i.e., Ni, Co, and Mn) determine the local structures at the nanoscale. The investigation of the reaction mechanism via imaging analysis provides valuable information for tuning the calcination chemistry and developing high-energy/power density lithium-ion batteries.

Structural Evolution of Mg-Doped Single-Crystal LiCoO2 Cathodes: Importance of Morphology and Mg-Doping Sites

Layered lithium cobalt oxide (LiCoO₂, LCO), which serves as a structural motif for the widely adopted layered cathodes in lithium-ion batteries, has a long history, and its unstable phase transition during high-voltage operation (∼4.5 V) remains an intractable problem. Many research strategies, such as surface coating and immobile ion doping, have been proposed to address this issue, but a clear understanding of the effects has not been demonstrated because of various potential parameters (e.g., particle size, shape, and dopant content). Herein, we report a molten salt synthesis method that produces sphere-like single-crystal magnesium (Mg)-doped LCO. In situ X-ray diffraction and X-ray absorption fine structure analyses confirmed that the lattice strain was effectively alleviated by the effects of both the particle shape and Mg doping compared to the plate-like and sphere-like single-crystal LCO samples. Furthermore, the preference for Mg doping in the Co site (3b) rather than in the Li site (3a) in the LCO framework is systematically revealed, and a clear understanding of Mg doping that suppresses the monoclinic phase transition is discussed in detail.

Surface coating by mechanofusion modulates bulk charging pathways and battery performance of Ni-rich layered cathodes

Ni-rich layered oxides as high-capacity battery cathodes suffer from degradation at high voltages. We utilize a dry surface modification method, mechanofusion (MF), to achieve enhanced battery stability. The simplicity, high yield, and flexibility make it cost-effective and highly attractive for processing at the industrial scale. The underlying mechanisms responsible for performance improvement are unveiled by a systematic study combining multiple probes, e.g., 3D nano-tomography, spectroscopic imaging, in situ synchrotron diffraction, and finite element analysis (FEA). MF affects the bulk crystallography by introducing partially disordered structure, microstrain, and local lattice variation. Furthermore, the crack initiation and propagation pattern during delithiation are regulated and the overall mechanical fracture is reduced after such surface coating. We validate that MF can alter the bulk charging pathways. Such a synergic effect between surface modification and bulk charge distribution is fundamentally important for designing next-generation battery cathode materials.

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

Reviving degraded colors of yellow flowers in 17th century still life paintings with macro- and microscale chemical imaging

Over time, artist pigments are prone to degradation, which can decrease the readability of the artwork or notably change the artist's intention. In this article, the visual implication of secondary degradation products in a degraded yellow rose in a still life painting by A. Mignon is discussed as a case study. A multimodal combination of chemical and optical imaging techniques, including noninvasive macroscopic x-ray powder diffraction (MA-XRPD) and macroscopic x-ray fluorescence imaging, allowed us to gain a 3D understanding of the transformation of the original intended appearance of the rose into its current degraded state. MA-XRPD enabled us to precisely correlate in situ formed products with what is optically visible on the surface and demonstrated that the precipitated lead arsenates and arsenolite from the yellow pigment orpiment and the light-induced fading of an organic yellow lake irreversibly changed the artist's intentional light-shadow modeling.

Classification-based motion analysis of single-molecule trajectories using DiffusionLab

Single-particle tracking is a powerful approach to study the motion of individual molecules and particles. It can uncover heterogeneities that are invisible to ensemble techniques, which places it uniquely among techniques to study mass transport. Analysis of the trajectories obtained with single-particle tracking in inorganic porous hosts is often challenging, because trajectories are short and/or motion is heterogeneous. We present the DiffusionLab software package for motion analysis of such challenging data sets. Trajectories are first classified into populations with similar characteristics to which the motion analysis is tailored in a second step. DiffusionLab provides tools to classify trajectories based on the motion type either with machine learning or manually. It also offers quantitative mean squared displacement analysis of the trajectories. The software can compute the diffusion constant for an individual trajectory if it is sufficiently long, or the average diffusion constant for multiple shorter trajectories. We demonstrate the DiffusionLab approach via the analysis of a simulated data set with motion types frequently observed in inorganic porous hosts, such as zeolites. The software package with graphical user interface and its documentation are freely available.

Exploring spectroscopic X-ray nano-imaging with Zernike phase contrast enhancement

Spectroscopic full-field transmission X-ray microscopy (TXM-XANES), which offers electrochemical imaging with a spatial resolution of tens of nanometers, is an extensively used unique technique in battery research. However, absorption-based bright-field imaging has poor detection sensitivity for nanoscale applications. Here, to improve the sensitivity, we explored spectroscopic X-ray nano imaging with Zernike phase contrast (ZPC-XANES). A pinhole-type Zernike phase plate, which was optimized for high-contrast images with minimal artifacts, was used in this study. When the absorption is weak, the Zernike phase contrast improves the signal-to-noise ratio and the contrast of images at all energies, which induces the enhancement of the absorption edge step. We estimated that the absorption of the samples should be higher than 2.2% for reliable spectroscopic nano-imaging based on XANES spectroscopy analysis of a custom-made copper wedge sample. We also determined that there is a slight absorption peak shift and sharpening in a small absorption sample due to the inflection point of the refractive index at the absorption edge. Nevertheless, in the case of sub-micron sized cathode materials, we believe that better contrast and higher resolution spectroscopic images can be obtained using ZPC-XANES.

Thermal-healing of lattice defects for high-energy single-crystalline battery cathodes

Single-crystalline nickel-rich cathodes are a rising candidate with great potential for high-energy lithium-ion batteries due to their superior structural and chemical robustness in comparison with polycrystalline counterparts. Within the single-crystalline cathode materials, the lattice strain and defects have significant impacts on the intercalation chemistry and, therefore, play a key role in determining the macroscopic electrochemical performance. Guided by our predictive theoretical model, we have systematically evaluated the effectiveness of regaining lost capacity by modulating the lattice deformation via an energy-efficient thermal treatment at different chemical states. We demonstrate that the lattice structure recoverability is highly dependent on both the cathode composition and the state of charge, providing clues to relieving the fatigued cathode crystal for sustainable lithium-ion batteries.

The lattice strain and defects in layered oxides is critical to the intercalation chemistry and battery performance. Here, the authors demonstrate a thermal-healing of lattice defects in single-crystalline cathodes caused by the thermal-induced release of lattice strain and the structure ordering.

TXM-Sandbox: an open-source software for transmission X-ray microscopy data analysis

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook. Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

2D-to-3D image translation of complex nanoporous volumes using generative networks

Image-based characterization offers a powerful approach to studying geological porous media at the nanoscale and images are critical to understanding reactive transport mechanisms in reservoirs relevant to energy and sustainability technologies such as carbon sequestration, subsurface hydrogen storage, and natural gas recovery. Nanoimaging presents a trade off, however, between higher-contrast sample-destructive and lower-contrast sample-preserving imaging modalities. Furthermore, high-contrast imaging modalities often acquire only 2D images, while 3D volumes are needed to characterize fully a source rock sample. In this work, we present deep learning image translation models to predict high-contrast focused ion beam-scanning electron microscopy (FIB-SEM) image volumes from transmission X-ray microscopy (TXM) images when only 2D paired training data is available. We introduce a regularization method for improving 3D volume generation from 2D-to-2D deep learning image models and apply this approach to translate 3D TXM volumes to FIB-SEM fidelity. We then segment a predicted FIB-SEM volume into a flow simulation domain and calculate the sample apparent permeability using a lattice Boltzmann method (LBM) technique. Results show that our image translation approach produces simulation domains suitable for flow visualization and allows for accurate characterization of petrophysical properties from non-destructive imaging data.

Transmission x-ray microscopy and its applications in battery material research-a short review

Transmission x-ray microscopy (TXM), which can provide morphological and chemical structural information inside of battery component materials at tens of nanometer scale, has become a powerful tool in battery research. This article presents a short review of the TXM, including its instrumentation, battery research applications, and the practical sample preparation and data analysis in the TXM applications. A brief discussion on the challenges and opportunities in the TXM applications is presented at the end.

Spatio-Chemical Heterogeneity of Defect-Engineered Metal-Organic Framework Crystals Revealed by Full-Field Tomographic X-ray Absorption Spectroscopy

The introduction of structural defects in metal-organic frameworks (MOFs), often achieved through the fractional use of defective linkers, is emerging as a means to refine the properties of existing MOFs. These linkers, missing coordination fragments, create unsaturated framework nodes that may alter the properties of the MOF. A property-targeted utilization of this approach demands an understanding of the structure of the defect-engineered MOF. We demonstrate that full-field X-ray absorption near-edge structure computed tomography can help to improve our understanding. This was demonstrated by visualizing the chemical heterogeneity found in defect-engineered HKUST-1 MOF crystals. A non-uniform incorporation and zonation of the defective linker was discovered, leading to the presence of clusters of a second coordination polymer within HKUST-1. The former is suggested to be responsible, in part, for altered MOF properties; thereby, advocating for a spatio-chemically resolved characterization of MOFs.

Influence of Metal-Alkyls on Early-Stage Ethylene Polymerization over a Cr/SiO2 Phillips Catalyst: A Bulk Characterization and X-ray Chemical Imaging Study

The Cr/SiO2 Phillips catalyst has taken a central role in ethylene polymerization since its invention in 1953. The uniqueness of this catalyst is related to its ability to produce broad molecular weight distribution (MWD) PE materials as well as that no co-catalysts are required to attain activity. Nonetheless, co-catalysts in the form of metal-alkyls can be added for scavenging poisons, enhancing catalyst activity, reducing the induction period, and tailoring polymer characteristics. The activation mechanism and related polymerization mechanism remain elusive, despite extensive industrial and academic research. Here, we show that by varying the type and amount of metal-alkyl co-catalyst, we can tailor polymer properties around a single Cr/SiO2 Phillips catalyst formulation. Furthermore, we show that these different polymer properties exist in the early stages of polymerization. We have used conventional polymer characterization techniques, such as size exclusion chromatography (SEC) and 13 C NMR, for studying the metal-alkyl co-catalyst effect on short-chain branching (SCB), long-chain branching (LCB) and molecular weight distribution (MWD) at the bulk scale. In addition, scanning transmission X-ray microscopy (STXM) was used as a synchrotron technique to study the PE formation in the early stages: allowing us to investigate the produced type of early-stage PE within one particle cross-section with high energy resolution and nanometer scale spatial resolution.

Automatic 3D image registration for nano-resolution chemical mapping using synchrotron spectro-tomography

Nano-resolution synchrotron X-ray spectro-tomography has been demonstrated as a powerful tool for probing the three-dimensional (3D) structural and chemical heterogeneity of a sample. By reconstructing a number of tomographic data sets recorded at different X-ray energy levels, the energy-dependent intensity variation in every given voxel fingerprints the corresponding local chemistry. The resolution and accuracy of this method, however, could be jeopardized by non-ideal experimental conditions, e.g. instability in the hardware system and/or in the sample itself. Herein is presented one such case, in which unanticipated sample deformation severely degrades the data quality. To address this issue, an automatic 3D image registration method is implemented to evaluate and correct this effect. The method allows the redox heterogeneity in partially delithiated Li_xTa_0.3Mn_0.4O₂ battery cathode particles to be revealed with significantly improved fidelity.

Direct Measure of Electrode Spatial Heterogeneity: Influence of Processing Conditions on Anode Architecture and Performance

In this work, the spatial (in)homogeneity of aqueous processed silicon electrodes using standard poly(acrylic acid)-based binders and slurry preparation conditions is demonstrated. X-ray nanotomography shows segregation of materials into submicron-thick layers depending on the mixing method and starting binder molecular weights. Using a dispersant, or in situ production of dispersant from the cleavage of the binder into smaller molecular weight species, increases the resulting lateral homogeneity while drastically decreasing the vertical homogeneity as a result of sedimentation and separation due to gravitational forces. This data explains some of the variability in the literature with respect to silicon electrode performance and demonstrates two potential ways to improve slurry-based electrode fabrications.

Depth-dependent valence stratification driven by oxygen redox in lithium-rich layered oxide

Lithium-rich nickel-manganese-cobalt (LirNMC) layered material is a promising cathode for lithium-ion batteries thanks to its large energy density enabled by coexisting cation and anion redox activities. It however suffers from a voltage decay upon cycling, urging for an in-depth understanding of the particle-level structure and chemical complexity. In this work, we investigate the Li1.2Ni0.13Mn0.54Co0.13O2 particles morphologically, compositionally, and chemically in three-dimensions. While the composition is generally uniform throughout the particle, the charging induces a strong depth dependency in transition metal valence. Such a valence stratification phenomenon is attributed to the nature of oxygen redox which is very likely mostly associated with Mn. The depth-dependent chemistry could be modulated by the particles' core-multi-shell morphology, suggesting a structural-chemical interplay. These findings highlight the possibility of introducing a chemical gradient to address the oxygen-loss-induced voltage fade in LirNMC layered materials.

Understanding Stabilization in Nanoporous Intermetallic Alloy Anodes for Li-Ion Batteries Using Operando Transmission X-ray Microscopy

Tin-based alloying anodes are exciting due to their high energy density. Unfortunately, these materials pulverize after repetitive cycling due to the large volume expansion during lithiation and delithiation; both nanostructuring and intermetallic formation can help alleviate this structural damage. Here, these ideas are combined in nanoporous antimony-tin (NP-SbSn) powders, synthesized by a simple and scalable selective-etching method. The NP-SbSn exhibits bimodal porosity that facilitates electrolyte diffusion; those void spaces, combined with the presence of two metals that alloy with lithium at different potentials, further provide a buffer against volume change. This stabilizes the structure to give NP-SbSn good cycle life (595 mAh/g after 100 cycles with 93% capacity retention). Operando transmission X-ray microscopy (TXM) showed that during cycling NP-SbSn expands by only 60% in area and then contracts back nearly to its original size with no physical disintegration. The pores shrink during lithiation as the pore walls expand into the pore space and then relax back to their initial size during delithiation with almost no degradation. Importantly, the pores remained open even in the fully lithiated state, and structures are in good physical condition after the 36th cycle. The results of this work should thus be useful for designing nanoscale structures in alloying anodes.

Mutual modulation between surface chemistry and bulk microstructure within secondary particles of nickel-rich layered oxides

Surface lattice reconstruction is commonly observed in nickel-rich layered oxide battery cathode materials, causing unsatisfactory high-voltage cycling performance. However, the interplay of the surface chemistry and the bulk microstructure remains largely unexplored due to the intrinsic structural complexity and the lack of integrated diagnostic tools for a thorough investigation at complementary length scales. Herein, by combining nano-resolution X-ray probes in both soft and hard X-ray regimes, we demonstrate correlative surface chemical mapping and bulk microstructure imaging over a single charged LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811) secondary particle. We reveal that the sub-particle regions with more micro cracks are associated with more severe surface degradation. A mechanism of mutual modulation between the surface chemistry and the bulk microstructure is formulated based on our experimental observations and finite element modeling. Such a surface-to-bulk reaction coupling effect is fundamentally important for the design of the next generation battery cathode materials.

The interplay of surface chemistry and bulk microstructure in layered oxides is critical to battery performance. Here, the authors demonstrate a comprehensive understanding of such a reaction mechanism within an individual cathode particle using integrated synchrotron imaging methods.

Synchrotron radiation Ca K-edge 2D-XANES spectroscopy for studying the stratigraphic distribution of calcium-based consolidants applied in limestones

In Heritage Science, the evaluation of stone consolidation treatments by investigating the nature of in situ newly formed products and their penetration depth within the consolidated matrix is a grand challenge. A number of analytical methods have been proposed, but, currently, most of them are not able to supply a full overview of the spatial, structural and compositional information of the newly formed crystalline and amorphous phases with a submicrometric lateral resolution. Here, we examined, the capabilities of synchrotron radiation (SR)-based two-dimensional X-ray absorption near-edge structure (2D-XANES) spectroscopy at Ca K-edge for determining the structural and compositional properties of the compounds formed after the application of a calcium acetoacetate-based consolidant on a porous carbonatic stone (limestone) and for investigating their stratigraphic distribution at the submicrometric scale length. We evaluated advantages and drawbacks of three Ca K-edge 2D-XANES-based approaches: (i) transmission mode full-field-XANES (FF-XANES) imaging; (ii) micro-X-ray fluorescence (μ-XRF) mapping above the Ca K-edge combined with the acquisition of XRF mode μ-XANES spectra at a limited number of spots; (iii) full-spectral µ-XANES (FS µ-XANES) mapping in XRF mode and its variant called selectively induced X-ray emission spectroscopy (SIXES) mapping. Overall, Ca K-edge 2D-XANES spectroscopy provided accurate qualitative and semi-quantitative information on the newly formed calcium carbonates (i.e., amorphous calcium carbonate, vaterite and calcite) and their stratigraphic distribution at the submicrometric scale, thus opening a new scenario to study the carbonatation process of calcium-based consolidants in limestones.

Robust framework and software implementation for fast speciation mapping

One of the greatest benefits of synchrotron radiation is the ability to perform chemical speciation analysis through X-ray absorption spectroscopies (XAS). XAS imaging of large sample areas can be performed with either full-field or raster-scanning modalities. A common practice to reduce acquisition time while decreasing dose and/or increasing spatial resolution is to compare X-ray fluorescence images collected at a few diagnostic energies. Several authors have used different multivariate data processing strategies to establish speciation maps. In this manuscript, the theoretical aspects and assumptions that are often made in the analysis of these datasets are focused on. A robust framework is developed to perform speciation mapping in large bulk samples at high spatial resolution by comparison with known references. Two fully operational software implementations are provided: a user-friendly implementation within the MicroAnalysis Toolkit software, and a dedicated script developed under the R environment. The procedure is exemplified through the study of a cross section of a typical fossil specimen. The algorithm provides accurate speciation and concentration mapping while decreasing the data collection time by typically two or three orders of magnitude compared with the collection of whole spectra at each pixel. Whereas acquisition of spectral datacubes on large areas leads to very high irradiation times and doses, which can considerably lengthen experiments and generate significant alteration of radiation-sensitive materials, this sparse excitation energy procedure brings the total irradiation dose greatly below radiation damage thresholds identified in previous studies. This approach is particularly adapted to the chemical study of heterogeneous radiation-sensitive samples encountered in environmental, material, and life sciences.

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical consequences of battery particles’ evolving (de)attachment with the conductive matrix. Herein, we tackle this issue with a unique combination of multiscale experimental approaches, machine-learning-assisted statistical analysis, and experiment-informed mathematical modeling. Our results suggest that the degree of particle detachment is positively correlated with the charging rate and that smaller particles exhibit a higher degree of uncertainty in their detachment from the carbon/binder matrix. We further explore the feasibility and limitation of utilizing the reconstructed electron density as a proxy for the state-of-charge. Our findings highlight the importance of precisely quantifying the evolving nature of the battery electrode’s microstructure with statistical confidence, which is a key to maximize the utility of active particles towards higher battery capacity.

Developing understanding of degradation phenomena in nickel rich cathodes is under intense investigation. Here the authors use learning-assisted statistical analysis and experiment-informed mathematical modelling to resolve the microstructure of a Ni-rich NMC composite cathode.

Probing the chemistry of CdS paints in The Scream by in situ noninvasive spectroscopies and synchrotron radiation x-ray techniques

The degradation of cadmium sulfide (CdS)-based oil paints is a phenomenon potentially threatening the iconic painting The Scream (ca. 1910) by Edvard Munch (Munch Museum, Oslo) that is still poorly understood. Here, we provide evidence for the presence of cadmium sulfate and sulfites as alteration products of the original CdS-based paint and explore the external circumstances and internal factors causing this transformation. Macroscale in situ noninvasive spectroscopy studies of the painting in combination with synchrotron-radiation x-ray microspectroscopy investigations of a microsample and artificially aged mock-ups show that moisture and mobile chlorine compounds are key factors for promoting the oxidation of CdS, while light (photodegradation) plays a less important role. Furthermore, under exposure to humidity, parallel/secondary reactions involving dissolution, migration through the paint, and recrystallization of water-soluble phases of the paint are associated with the formation of cadmium sulfates.

Quantifying redox heterogeneity in single-crystalline LiCoO2 cathode particles

Active cathode particles are fundamental architectural units for the composite electrode of Li-ion batteries. The microstructure of the particles has a profound impact on their behavior and, consequently, on the cell-level electrochemical performance. LiCoO2 (LCO, a dominant cathode material) is often in the form of well-shaped particles, a few micrometres in size, with good crystallinity. In contrast to secondary particles (an agglomeration of many fine primary grains), which are the other common form of battery particles populated with structural and chemical defects, it is often anticipated that good particle crystallinity leads to superior mechanical robustness and suppressed charge heterogeneity. Yet, sub-particle level charge inhomogeneity in LCO particles has been widely reported in the literature, posing a frontier challenge in this field. Herein, this topic is revisited and it is demonstrated that X-ray absorption spectra on single-crystalline particles with highly anisotropic lattice structures are sensitive to the polarization configuration of the incident X-rays, causing some degree of ambiguity in analyzing the local spectroscopic fingerprint. To tackle this issue, a methodology is developed that extracts the white-line peak energy in the X-ray absorption near-edge structure spectra as a key data attribute for representing the local state of charge in the LCO crystal. This method demonstrates significantly improved accuracy and reveals the mesoscale chemical complexity in LCO particles with better fidelity. In addition to the implications on the importance of particle engineering for LCO cathodes, the method developed herein also has significant impact on spectro-microscopic studies of single-crystalline materials at synchrotron facilities, which is broadly applicable to a wide range of scientific disciplines well beyond battery research.

Multi-Spectroscopic Interrogation of the Spatial Linker Distribution in Defect-Engineered Metal-Organic Framework Crystals: The [Cu3 (btc)2-x (cydc)x ] Showcase

In the past few years, defect-engineered metal-organic frameworks (DEMOFs) have been studied due to the plethora of textural, catalytic, or magnetic properties that can be enhanced by carefully introducing defect sites into the crystal lattices of MOFs. In this work, the spatial distribution of two different non-defective and defective linkers, namely 1,3,5-benzenetricarboxylate (BTC) and 5-cyano-1,3-benzenedicarboxylate (CYDC), respectively, has been studied in different DEMOF crystals of the HKUST-1 topology. Raman micro-spectroscopy revealed a nonhomogeneous distribution of defect sites within the [Cu3 (btc)2-x (cydc)x ] crystals, with the CYDC linker incorporated into defect-rich or defect-free areas of selected crystals. Additionally, advanced bulk techniques have shed light on the nature of the copper species, which is highly dynamic and directly affects the reactivity of the copper sites, as shown by probe molecule FTIR spectroscopy. Furthermore, electron microscopy revealed the effect of co-crystallizing CYDC and BTC on the crystal size and the formation of mesopores, further corroborated by X-ray scattering analysis. In this way we have demonstrated the necessity of utilizing micro-spectroscopy along with a whole array of bulk spectroscopic techniques to fully describe multicomponent metal-organic frameworks.

Development of XANES nanoscopy on BL7C at PLS-II

X-ray absorption near-edge structure (XANES) imaging is a powerful tool to visualize the chemical state distribution of transition-metal-based materials at synchrotron radiation facilities. In recent years, the electrochemical working rechargeable battery has been the most studied material in XANES imaging owing to the large increase of portable electronics and electric vehicles. This work acknowledges the importance of battery analysis and has developed the XANES imaging system on BL7C at Pohang Light Source-II (PLS-II). BL7C employs an undulator taper configuration to obtain an energy band >130 eV near the K-absorption edge of the target element with a minimum energy interval >0.2 eV. While measuring energy-dependent images, the zone plate translation maintains the best focus, and then various data processes such as background correction, image registration and clustering allow single XANES spectrum extraction and chemical distribution mapping. Here, the XANES imaging process is described, the XANES spectrum quality is identified and the chemical states of the partially charged cathode material used in lithium-ion batteries as an application example are examined.

PyXAS - an open-source package for 2D X-ray near-edge spectroscopy analysis

In the synchrotron X-ray community, X-ray absorption near-edge spectroscopy (XANES) is a widely used technique to probe the local coordination environment and the oxidation states of specific elements within a sample. Although this technique is usually applied to bulk samples, the advent of new synchrotron sources has enabled spatially resolved versions of this technique (2D XANES). This development has been extremely powerful for the study of heterogeneous systems, which is the case for nearly all real applications. However, associated with the development of 2D XANES comes the challenge of analyzing very large volumes of data. As an example, a single 2D XANES measurement at a synchrotron can easily produce ∼10⁶ spatially resolved XANES spectra. Conventional manual analysis of an individual XANES spectrum is no longer feasible. Here, a software package is described that has been developed for high-throughput 2D XANES analysis. A detailed description of the software as well as example applications are provided.

Charge distribution guided by grain crystallographic orientations in polycrystalline battery materials

Architecting grain crystallographic orientation can modulate charge distribution and chemomechanical properties for enhancing the performance of polycrystalline battery materials. However, probing the interplay between charge distribution, grain crystallographic orientation, and performance remains a daunting challenge. Herein, we elucidate the spatially resolved charge distribution in lithium layered oxides with different grain crystallographic arrangements and establish a model to quantify their charge distributions. While the holistic “surface-to-bulk” charge distribution prevails in polycrystalline particles, the crystallographic orientation-guided redox reaction governs the charge distribution in the local charged nanodomains. Compared to the randomly oriented grains, the radially aligned grains exhibit a lower cell polarization and higher capacity retention upon battery cycling. The radially aligned grains create less tortuous lithium ion pathways, thus improving the charge homogeneity as statistically quantified from over 20 million nanodomains in polycrystalline particles. This study provides an improved understanding of the charge distribution and chemomechanical properties of polycrystalline battery materials.

The authors here report on the influence of grain orientation on the charge distribution in polycrystalline materials for batteries. The quantitative characterization provides mechanistic insight into the way the grain orientation can be engineered to mitigate the charge heterogeneity.

Chemical Fingerprint of Zn-Hydroxyapatite in the Early Stages of Osteogenic Differentiation

The core knowledge about biomineralization is provided by studies on the advanced phases of the process mainly occurring in the extracellular matrix. Here, we investigate the early stages of biomineralization by evaluating the chemical fingerprint of the initial mineral nuclei deposition in the intracellular milieu and their evolution toward hexagonal hydroxyapatite. The study is conducted on human bone mesenchymal stem cells exposed to an osteogenic cocktail for 4 and 10 days, exploiting laboratory X-ray diffraction techniques and cutting-edge developments of synchrotron-based 2D and 3D cryo-X-ray microscopy. We demonstrate that biomineralization starts with Zn-hydroxyapatite nucleation within the cell, rapidly evolving toward hexagonal hydroxyapatite crystals, very similar in composition and structure to the one present in human bone. These results provide experimental evidence of the germinal role of Zn in hydroxyapatite nucleation and foster further studies on the intracellular molecular mechanisms governing the initial phases of bone tissue formation.

3D Raman Spectroscopy of Large Zeolite ZSM-5 Crystals

Hydrothermal treatment is a common method used to modify the physicochemical properties of zeolite‐based catalyst materials. It alters the number and type of acid sites through dealumination and increases molecular diffusion by mesopore formation. Steaming also reduces the structural integrity of zeolite frameworks. In this study, Raman microscopy has been used to map large zeolite ZSM‐5 crystals before and after steaming. 3D elemental maps of T−O (T: Al or Si) sites of the zeolite were obtained. The Raman active vibrational bands were determined, which are indicative of (non‐) framework Al, as well as of structural integrity. Zeolite steaming caused the introduction of additional heterogeneities within the zeolite framework. Al migration and the formation of extra‐framework Al species were observed. The described experiments demonstrate the capability of 3D Raman spectroscopy as a valuable tool to obtain information on the spatial distributions of framework elements as well as defects within a zeolite‐based material.

Finding Degradation Trigger Sites of Structural Materials for Airplanes Using X-Ray Microscopy

Macroscopic properties of carbon fiber-reinforced plastic (CFRP) and environmental barrier coating (EBC), widely used for airplanes, can be deteriorated by local cracks or degradation ("trigger sites"). We have tried to find these trigger sites using x-ray microscopy (XM), which can provide the 2D or 3D images of the chemical states and microstructures. Crack initiation in CFRP was observed in a non-destructive manner in multi-scales (nm-mm). 3D chemical-state mapping of Yb in EBC was achieved with high resolution (<50 nm). In addition to XM, in-situ observations at high temperatures were conducted for obtaining complementary information. X-ray absorption spectroscopy (XAS) and x-ray diffraction (XRD) analysis were performed simultaneously up to 1773 K. Dynamic XAS with short time-resolution (<10 ns) was conducted to investigate changes in the local structure of metal. These approaches can help us identify degradation trigger sites in the materials.

Probing the Location and Speciation of Elements in Zeolites with Correlated Atom Probe Tomography and Scanning Transmission X-Ray Microscopy

Characterizing materials at nanoscale resolution to provide new insights into structure property performance relationships continues to be a challenging research target due to the inherently low signal from small sample volumes, and is even more difficult for nonconductive materials, such as zeolites. Herein, we present the characterization of a single Cu-exchanged zeolite crystal, namely Cu-SSZ-13, used for NOX reduction in automotive emissions, that was subject to a simulated 135,000-mile aging. By correlating Atom Probe Tomography (APT), a single atom microscopy method, and Scanning Transmission X-ray Microscopy (STXM), which produces high spatial resolution X-ray Absorption Near Edge Spectroscopy (XANES) maps, we show that a spatially non-uniform proportion of the Al was removed from the zeolite framework. The techniques reveal that this degradation is heterogeneous at length scales from micrometers to tens of nanometers, providing complementary insight into the long-term deactivation of this catalyst system.

Micro-spectroscopy of HKUST-1 metal–organic framework crystals loaded with tetracyanoquinodimethane: effects of water on host–guest chemistry and electrical conductivity

Guest@MOF materials have potential in next-generation materials for electroconductive devices. Micro-spectroscopy studies of TCNQ@HKUST-1 electroconductive composites revealed the effects of spatial distribution and water vapor on this material.