Nanoscale chemical imaging with structured X-ray illumination.

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

In situ visualization of multicomponents coevolution in a battery pouch cell.

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro-computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 µm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

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.

High-resolution multicontrast tomography with an X-ray microarray anode-structured target source.

Multicontrast X-ray imaging with high resolution and sensitivity using Talbot-Lau interferometry (TLI) offers unique imaging capabilities that are important to a wide range of applications, including the study of morphological features with different physical properties in biological specimens. The conventional X-ray TLI approach relies on an absorption grating to create an array of micrometer-sized X-ray sources, posing numerous limitations, including technical challenges associated with grating fabrication for high-energy operations. We overcome these limitations by developing a TLI system with a microarray anode-structured target (MAAST) source. The MAAST features an array of precisely controlled microstructured metal inserts embedded in a diamond substrate. Using this TLI system, tomography of a Drum fish tooth with high resolution and tri-contrast (absorption, phase, and scattering) reveals useful complementary structural information that is inaccessible otherwise. The results highlight the exceptional capability of high-resolution multicontrast X-ray tomography empowered by the MAAST-based TLI method in biomedical applications.

Fast Li Plating Behavior Probed by X-ray Computed Tomography.

Uneven lithium plating/stripping is an essential issue that inhibits stable cycling of a lithium metal anode and thus hinders its practical applications. The investigation of this process is challenging because it is difficult to observe lithium in an operating device. Here, we demonstrate that the microscopic lithium plating behavior can be observed in situ in a close-to-practical cell setup using X-ray computed tomography. The results reveal the formation of porous structure and its progressive evolution in space over the charging process with a large current. The elaborated analysis indicates that the microstructure of deposited lithium makes a significant impact on the subsequent lithium plating, and the impact of structural inhomogeneity, further exaggerated by the large-current charging, can lead to severely uneven lithium plating and eventually cell failure. Therefore, a codesign strategy involving delicate controls of microstructure and electrochemical conditions could be a necessity for the next-generation battery with lithium metal anode.

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 LixTa0.3Mn0.4O2 battery cathode particles to be revealed with significantly improved fidelity.

Deep-learning-based image registration for nano-resolution tomographic reconstruction.

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. The method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

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.

Surface-to-Bulk Redox Coupling through Thermally Driven Li Redistribution in Li- and Mn-Rich Layered Cathode Materials.

Li- and Mn-rich (LMR) layered cathode materials have demonstrated impressive capacity and specific energy density thanks to their intertwined redox centers including transition metal cations and oxygen anions. Although tremendous efforts have been devoted to the investigation of the electrochemically driven redox evolution in LMR cathode at ambient temperature, their behavior under a mildly elevated temperature (up to ∼100 °C), with or without electrochemical driving force, remains largely unexplored. Here we show a systematic study of the thermally driven surface-to-bulk redox coupling effect in charged Li1.2Ni0.15Co0.1Mn0.55O2. We for the first time observed a charge transfer between the bulk oxygen anions and the surface transition metal cations under ∼100 °C, which is attributed to the thermally driven redistribution of Li ions. This finding highlights the nonequilibrium state and dynamic nature of the LMR material at deeply delithiated state upon a mild temperature perturbation.

Mesoscale Battery Science: The Behavior of Electrode Particles Caught on a Multispectral X-ray Camera.

Functional materials and devices are usually morphologically complex and chemically heterogeneous. Their structures are often designed to be hierarchical because of the desired functionalities, which usually require many different components to work together in a coherent manner. The lithium ion battery, as an energy storage device, is a very typical example of this kind of structure. In a lithium ion battery, the cathode, anode, and separator are soaked in a liquid electrolyte, facilitating the back and forward shuttling of the lithium ions for energy storage and release. The desired performance of a lithium ion battery has many different aspects that need to be engineered and balanced depending on the targeted applications. In most cases, the cathode material has become the limiting factor for further improvements and, thus, has attracted intense attention from the research community. While the improvement in the overall performance of the lithium ion battery is the ultimate goal of the research in this field, understanding the relationship between the microscopic properties and the macroscopic behaviors of the materials/devices can inform the design of better battery chemistries for practical applications. As a result, it is of great fundamental and practical importance to investigate the electrode materials using experimental probes that can provide good chemical sensitivity and sufficient spatial resolution, ideally, under operating conditions. With this motivation, our group has been focusing on the development of the nanoscale full-field X-ray spectro-microscopy, which has now become a well-recognized tool for imaging battery electrode materials at the particle level. With nanoscale spatial resolution, this technique can effectively and efficiently tackle the intrinsically complicated mesoscale chemistry. It allows us to monitor the particles' morphological and chemical evolution upon battery operation, providing valuable insights that can be incorporated into the design of new battery chemistries. In this Account, we review a series of our recent studies of battery electrode materials using nanoscale full-field X-ray spectro-microscopy. The materials that are the subjects of our studies, including layer-structured and spinel-structured oxide cathodes, are technically very important as they not only play an important role in today's devices but also possess promising potential for future developments. We discuss how the subparticle level compositional and state-of-charge heterogeneity can be visualized and linked to the bulk performance through systematic quantification of the imaging data. Subsequently, we highlight recent ex situ and in situ observations of the cathode particles' response to different reaction conditions, including the spontaneously adjusted reaction pathways and the morphological changes for the mechanical strain release. The important role of surface chemistry in the system is also discussed. While the microscopic investigation at the particle level provides useful insights, the degree to which this represents the overall properties of the battery is always a question for further generalizing the conclusions. In order to address this concern, we finally discuss a high throughput experimental approach, in which a large number of cathode particles are scanned. We discuss a case study that demonstrates the identification and analysis of functionally important minority phases in an operating battery cell through big data mining methods. With an emphasis on the data/information mining aspect of the nanoscale X-ray spectro-microscopic study of battery cathode particles, we anticipate that this Account will attract more research to this field.

Automatic projection image registration for nanoscale X-ray tomographic reconstruction.

Novel developments in X-ray sources, optics and detectors have significantly advanced the capability of X-ray microscopy at the nanoscale. Depending on the imaging modality and the photon energy, state-of-the-art X-ray microscopes are routinely operated at a spatial resolution of tens of nanometres for hard X-rays or ∼10 nm for soft X-rays. The improvement in spatial resolution, however, has led to challenges in the tomographic reconstruction due to the fact that the imperfections of the mechanical system become clearly detectable in the projection images. Without proper registration of the projection images, a severe point spread function will be introduced into the tomographic reconstructions, causing the reduction of the three-dimensional (3D) spatial resolution as well as the enhancement of image artifacts. Here the development of a method that iteratively performs registration of the experimentally measured projection images to those that are numerically calculated by reprojecting the 3D matrix in the corresponding viewing angles is shown. Multiple algorithms are implemented to conduct the registration, which corrects the translational and/or the rotational errors. A sequence that offers a superior performance is presented and discussed. Going beyond the visual assessment of the reconstruction results, the morphological quantification of a battery electrode particle that has gone through substantial cycling is investigated. The results show that the presented method has led to a better quality tomographic reconstruction, which, subsequently, promotes the fidelity in the quantification of the sample morphology.

Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery.

The in-depth understanding of the minority phases' roles in functional materials, e.g., batteries, is critical for optimizing the system performance and the operational efficiency. Although the visualization of battery electrode under operating conditions has been demonstrated, the development of advanced data-mining approaches is still needed in order to identify minority phases and to understand their functionalities. The present study uses nanoscale X-ray spectromicroscopy to study a functional LiCoO2/Li battery pouch cell. The data-mining approaches developed herein were used to search through over 10 million X-ray absorption spectra that cover more than 100 active cathode particles. Two particles with unanticipated chemical fingerprints were identified and further analyzed, providing direct evidence and valuable insight into the undesired side reactions involving the cation dissolution and precipitation as well as the local overlithiation-caused subparticle domain deactivation. The data-mining approach described in this work is widely applicable to many other structurally complex and chemically heterogeneous systems, in which the secondary/minority phases could critically affect the overall performance of the system, well beyond battery research.

Determination of copper nanoparticle size distributions with total reflection X-ray fluorescence spectroscopy.

Total reflection X-ray fluorescence (TXRF) analysis is extensively used by the semiconductor industry for measuring trace metal contamination on silicon surfaces. In addition to determining the quantity of impurities on a surface, TXRF can reveal information about the vertical distribution of contaminants by measuring the fluorescence signal as a function of the angle of incidence. In this study, two samples were intentionally contaminated with copper in non-deoxygenated and deoxygenated ultrapure water (UPW) resulting in impurity profiles that were either atomically dispersed in a thin film or particle-like, respectively. The concentration profile of the samples immersed into deoxygenated UPW was calculated using a theoretical concentration profile representative of particles, yielding a mean particle height of 16.1 nm. However, the resulting theoretical profile suggested that a distribution of particle heights exists on the surface. The fit of the angular distribution data was further refined by minimizing the residual error of a least-squares fit employing a model with a Gaussian distribution of particle heights about the mean height. The presence of a height distribution was also confirmed with atomic force microscopy measurements.

Engineering Ultra-Low Work Function of Graphene.

Low work function materials are critical for energy conversion and electron emission applications. Here, we demonstrate for the first time that an ultralow work function graphene is achieved by combining electrostatic gating with a Cs/O surface coating. A simple device is built from large-area monolayer graphene grown by chemical vapor deposition, transferred onto 20 nm HfO2 on Si, enabling high electric fields capacitive charge accumulation in the graphene. We first observed over 0.7 eV work function change due to electrostatic gating as measured by scanning Kelvin probe force microscopy and confirmed by conductivity measurements. The deposition of Cs/O further reduced the work function, as measured by photoemission in an ultrahigh vacuum environment, which reaches nearly 1 eV, the lowest reported to date for a conductive, nondiamond material.

Registration of the rotation axis in X-ray tomography.

There is high demand for efficient, robust and automated routines for tomographic data reduction, particularly for synchrotron data. Registration of the rotation axis in data processing is a critical step affecting the quality of the reconstruction and is not easily implemented with automation. Existing methods for calculating the center of rotation have been reviewed and an improved algorithm to register the rotation axis in tomographic data is presented. The performance of the proposed method is evaluated using synchrotron-based microtomography data on geological samples with and without artificial reduction of the signal-to-noise ratio. The proposed method improves the reconstruction quality by correcting both the tilting error and the translational offset of the rotation axis. The limitation of this promising method is also discussed.

Nanoscale morphological and chemical changes of high voltage lithium-manganese rich NMC composite cathodes with cycling.

Understanding the evolution of chemical composition and morphology of battery materials during electrochemical cycling is fundamental to extending battery cycle life and ensuring safety. This is particularly true for the much debated high energy density (high voltage) lithium-manganese rich cathode material of composition Li(1 + x)M(1 - x)O2 (M = Mn, Co, Ni). In this study we combine full-field transmission X-ray microscopy (TXM) with X-ray absorption near edge structure (XANES) to spatially resolve changes in chemical phase, oxidation state, and morphology within a high voltage cathode having nominal composition Li1.2Mn0.525Ni0.175Co0.1O2. Nanoscale microscopy with chemical/elemental sensitivity provides direct quantitative visualization of the cathode, and insights into failure. Single-pixel (∼ 30 nm) TXM XANES revealed changes in Mn chemistry with cycling, possibly to a spinel conformation and likely including some Mn(II), starting at the particle surface and proceeding inward. Morphological analysis of the particles revealed, with high resolution and statistical sampling, that the majority of particles adopted nonspherical shapes after 200 cycles. Multiple-energy tomography showed a more homogeneous association of transition metals in the pristine particle, which segregate significantly with cycling. Depletion of transition metals at the cathode surface occurs after just one cycle, likely driven by electrochemical reactions at the surface.

Asynchronous domain dynamics and equilibration in layered oxide battery cathode.

To improve lithium-ion battery technology, it is essential to probe and comprehend the microscopic dynamic processes that occur in a real-world composite electrode under operating conditions. The primary and secondary particles are the structural building blocks of battery cathode electrodes. Their dynamic inconsistency has profound but not well-understood impacts. In this research, we combine operando coherent multi-crystal diffraction and optical microscopy to examine the chemical dynamics in local domains of layered oxide cathode. Our results not only pinpoint the asynchronicity of the lithium (de)intercalation at the sub-particle level, but also reveal sophisticated diffusion kinetics and reaction patterns, involving various localized processes, e.g., chemical onset, reaction front propagation, domains equilibration, particle deformation and motion. These observations shed new lights onto the activation and degradation mechanisms of state-of-the-art battery cathode materials.

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

Transmission X-ray microscopy (TXM) has been well recognized as a powerful tool for non-destructive investigation of the three-dimensional inner structure of a sample with spatial resolution down to a few tens of nanometers, especially when combined with synchrotron radiation sources. Recent developments of this technique have presented a need for new tools for both system control and data analysis. Here a software package developed in MATLAB for script command generation and analysis of TXM data is presented. The first toolkit, the script generator, allows automating complex experimental tasks which involve up to several thousand motor movements. The second package was designed to accomplish computationally intense tasks such as data processing of mosaic and mosaic tomography datasets; dual-energy contrast imaging, where data are recorded above and below a specific X-ray absorption edge; and TXM X-ray absorption near-edge structure imaging datasets. Furthermore, analytical and iterative tomography reconstruction algorithms were implemented. The compiled software package is freely available.

Extended depth of focus for transmission x-ray microscope.

A fast discrete curvelet transform based focus-stacking algorithm for extending the depth of focus of a transmission x-ray microscope (TXM) is presented. By analyzing an image stack of a sample taken in a Z-scan, a fully in-focus image can be generated by the proposed scheme. With the extended depth of focus, it is possible to obtain 3D structural information over a large volume at nanometer resolution. The focus-stacking method has been demonstrated using a dataset taken with a laboratory x-ray source based TXM system. The possibility and limitations of generalizing this method to a synchrotron based TXM are also discussed. We expect the proposed method to be of important impact in 3D x-ray microscopy.

3D elemental sensitive imaging using transmission X-ray microscopy.

Determination of the heterogeneous distribution of metals in alloy/battery/catalyst and biological materials is critical to fully characterize and/or evaluate the functionality of the materials. Using synchrotron-based transmission x-ray microscopy (TXM), it is now feasible to perform nanoscale-resolution imaging over a wide X-ray energy range covering the absorption edges of many elements; combining elemental sensitive imaging with determination of sample morphology. We present an efficient and reliable methodology to perform 3D elemental sensitive imaging with excellent sample penetration (tens of microns) using hard X-ray TXM. A sample of an Al-Si piston alloy is used to demonstrate the capability of the proposed method.