Spatial control of perilacunar canalicular remodeling during lactation.

Osteocytes locally remodel their surrounding tissue through perilacunar canalicular remodeling (PLR). During lactation, osteocytes remove minerals to satisfy the metabolic demand, resulting in increased lacunar volume, quantifiable with synchrotron X-ray radiation micro-tomography (SRµCT). Although the effects of lactation on PLR are well-studied, it remains unclear whether PLR occurs uniformly throughout the bone and what mechanisms prevent PLR from undermining bone quality. We used SRµCT imaging to conduct an in-depth spatial analysis of the impact of lactation and osteocyte-intrinsic MMP13 deletion on PLR in murine bone. We found larger lacunae undergoing PLR are located near canals in the mid-cortex or endosteum. We show lactation-induced hypomineralization occurs 14 µm away from lacunar edges, past a hypermineralized barrier. Our findings reveal that osteocyte-intrinsic MMP13 is crucial for lactation-induced PLR near lacunae in the mid-cortex but not for whole-bone resorption. This research highlights the spatial control of PLR on mineral distribution during lactation.

Visualization of Porous Composite Battery Electrode Fabrication Dynamics for Different Formulations and Conditions Using Hard X-ray Microradiography.

Porous composite battery electrode performance is influenced by a large number of manufacturing decisions. While it is common to evaluate only finished electrodes when making process adjustments, one must then make inferences about the fabrication process dynamics from static results, which makes process optimization very costly and time-consuming. To get information about the dynamics of the manufacturing processes of these composites, we have built a miniature coating and drying apparatus capable of fabricating lab-scale electrode laminates while operating within an X-ray beamline hutch. Using this tool, we have collected the first radiography image sequences of lab-scale battery electrode coatings in profile, taken throughout drying processes conducted under industrially relevant conditions. To assist with interpretation of these image sequences, we developed an automated image analysis program. Here, we discuss our observations of battery electrode slurry samples, including stratification and long-term fluid flow, and their relevance to composite electrode manufacturing.

tomoCAM: fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms.

X-ray-based computed tomography is a well established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in situ and in operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projection often results in poor quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time. Here, tomoCAM, is introduced, a new GPU-accelerated implementation of model-based iterative reconstruction that leverages non-uniform fast Fourier transforms to efficiently compute Radon and back-projection operators and asynchronous memory transfers to maximize the throughput to the GPU memory. The resulting code is significantly faster than traditional MBIR codes and delivers the reconstructive improvement offered by MBIR with affordable computing time and resources. tomoCAM has a Python front-end, allowing access from Jupyter-based frameworks, providing straightforward integration into existing workflows at synchrotron facilities.

Deploying Machine Learning Based Segmentation for Scientific Imaging Analysis at Synchrotron Facilities.

Scientific user facilities present a unique set of challenges for image processing due to the large volume of data generated from experiments and simulations. Furthermore, developing and implementing algorithms for real-time processing and analysis while correcting for any artifacts or distortions in images remains a complex task, given the computational requirements of the processing algorithms. In a collaborative effort across multiple Department of Energy national laboratories, the "MLExchange" project is focused on addressing these challenges. MLExchange is a Machine Learning framework deploying interactive web interfaces to enhance and accelerate data analysis. The platform allows users to easily upload, visualize, label, and train networks. The resulting models can be deployed on real data while both results and models could be shared with the scientists. The MLExchange web-based application for image segmentation allows for training, testing, and evaluating multiple machine learning models on hand-labeled tomography data. This environment provides users with an intuitive interface for segmenting images using a variety of machine learning algorithms and deep-learning neural networks. Additionally, these tools have the potential to overcome limitations in traditional image segmentation techniques, particularly for complex and low-contrast images.

Influence of Microporous Layers on Interfacial Properties, Oxygen Flow Distribution, and Durability of Proton Exchange Membrane Water Electrolyzers.

The efficient and cost-effective production of green hydrogen is essential to decarbonize heavily polluting sectors such as transportation and heavy manufacturing industries such as metal refining. Polymer electrolyte membrane water electrolysis (PEMWE) is the most promising and rapidly maturing technology for producing green hydrogen at a scale and on demand. However, substantial cost reduction by lowering precious metal catalyst loadings and efficiency improvement is necessary to lower the cost of the produced hydrogen. Porous transport layers (PTLs) play a major role in influencing the PEMWE efficiency and catalyst utilization. Several studies have projected that the use of microporous layers (MPLs) on PTLs can improve the efficiency of PEMWEs, but very limited literature exists on how MPLs affect anodic interfacial properties and oxygen transport in PTLs. In this study, for the first time, we use X-ray microtomography and innovative image processing techniques to elucidate the oxygen flow patterns in PTLs with varying MPL thicknesses. We used stained water to improve contrast of oxygen in PTLs and demonstrate visualization of time averaged oxygen flow patterns. The results show that PTLs with MPLs significantly improve interfacial contact by almost 20% as compared to single layer sintered PTL. For the single layer PTL without MPL, the pore volume utilization for oxygen flow is low and the oxygen follows a viscous fingering flow regime. With MPLs, the pore volume utilization is higher, and the number of oxygen transport pathways is increased significantly. MPLs were also shown to suppress capillary fingering and transition oxygen flow to the viscous fingering regime, which has been proven to decrease site masking effects. Finally, durability tests showed the least voltage degradation for thin MPL and thicker MPLs run into mass transport limitations. Based on these findings, PTL/MPL design optimization strategies are proposed for enabling low catalyst loadings and improving durability.

Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap-feeding insects illuminated with synchrotron-based 3D imaging.

Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect-mediated pathogen transmission efficiency have been identified among xylem sap-feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron-based X-ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap-feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue-green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy-winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.

Large Local Currents in a Lithium-Ion Battery during Rest after Fast Charging.

Increasing electric vehicle (EV) adoption requires lithium-ion batteries that can be charged quickly and safely. Some EV batteries have caught on fire despite being neither charged nor discharged. While the lithium that plates on graphite during fast charging affects battery safety, so do the internal ionic currents that can occur when the battery is at rest after charging. These currents are difficult to quantify; the external current that can readily be measured is zero. Here we study a graphite electrode at rest after 6C fast charging using operando X-ray microtomography. We quantify spatially resolved current density distributions that originate at plated lithium and end in underlithiated graphite particles. The average current densities decrease from 1.5 to 0.5 mA cm-2 in about 20 min after charging is stopped. Surprisingly, the range of the stripping current density is independent of time, with outliers above 20 mA cm-2. The persistence of outliers provides a clue as to the origin of catastrophic failure in batteries at rest.

X-ray Tomography Applied to Electrochemical Devices and Electrocatalysis.

X-ray computed tomography (CT) is a nondestructive three-dimensional (3D) imaging technique used for studying morphological properties of porous and nonporous materials. In the field of electrocatalysis, X-ray CT is mainly used to quantify the morphology of electrodes and extract information such as porosity, tortuosity, pore-size distribution, and other relevant properties. For electrochemical systems such as fuel cells, electrolyzers, and redox flow batteries, X-ray CT gives the ability to study evolution of critical features of interest in ex situ, in situ, and operando environments. These include catalyst degradation, interface evolution under real conditions, formation of new phases (water and oxygen), and dynamics of transport processes. These studies enable more efficient device and electrode designs that will ultimately contribute to widespread decarbonization efforts.

Failure Mechanisms at the Interfaces between Lithium Metal Electrodes and a Single-Ion Conducting Polymer Gel Electrolyte.

Polymer electrolytes have the potential to enable rechargeable lithium (Li) metal batteries. However, growth of nonuniform high surface area Li still occurs frequently and eventually leads to a short-circuit. In this study, a single-ion conducting polymer gel electrolyte is operated at room temperature in symmetric Li||Li cells. We use X-ray microtomography and electrochemical impedance spectroscopy (EIS) to study the cells. In separate experiments, cells were cycled at current densities of 0.1 and 0.3 mA cm-2 and short-circuits were obtained eventually after an average of approximately 240 cycles and 30 cycles, respectively. EIS reveals an initially decreasing interfacial resistance associated with electrodeposition of nonuniform Li protrusions and the concomitant increase in electrode surface area. X-ray microtomography images show that many of the nonuniform Li deposits at 0.1 mA cm-2 are related to the presence of impurities in both electrolyte and electrode phases. Protrusions are globular when they are close to electrolyte impurities but are moss-like when they appear near the impurities in the lithium metal. At long times, the interfacial resistance increases, perhaps due to additional impedance due to the formation of additional solid electrolyte interface (SEI) at the growing protrusions until the cells short. At 0.3 mA cm-2, large regions of the electrode-electrolyte interface are covered with mossy deposits. EIS reveals a decreasing interfacial resistance due to the increase in interfacial area up to short-circuit; the increase in interfacial impedance observed at the low current density is not observed. The results emphasize the importance of pure surfaces and materials on the microscopic scale and suggest that modification of interfaces and electrolyte may be necessary to enable uniform Li electrodeposition at high current densities.

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google's Colaboratory.

X-ray micro-computed tomography (X-ray µCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray µCT images, using low-cost resources in Google's Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

Unveiling characteristic proteins for the structural development of beetle elytra.

Beetles possess a set of highly modified and tanned forewings, elytra, which are lightweight yet rigid and tough. Immediately after eclosion, the elytra are initially thin, pale and soft. However, they rapidly expand and subsequently become hardened and often dark, resulting from both pigmentation and sclerotization. Here, we identified changes in protein composition during the developmental processes of the elytra in the Japanese rhinoceros beetle, Trypoxylus dichotomus. Using mass spectrometry, a total of 414 proteins were identified from both untanned and tanned elytra, including 31 cuticular proteins (CPs), which constitute one of the major components of insect cuticles. Moreover, CPs containing Rebers and Riddiford motifs (CPR), the most abundant CP family, were separated into two groups based on their expression and amino acid sequences, such as a Gly-rich sequence region and Ala-Ala-Pro repeats. These protein groups may play crucial roles in elytra formation at different time points, likely including self-assembly of chitin nanofibers that control elytral macro and microstructures and dictate changes in other properties (i.e., mechanical property). Clarification of the protein functions will enhance the understanding of elytra formation and potentially benefit the development of lightweight materials for industrial and biomedical applications. STATEMENT OF SIGNIFICANCE: The beetle elytron is a light-weight natural bio-composite which displays high stiffness and toughness. This structure is composed of chitin fibrils and proteins, some of which are responsible for architectural development and hardening. This work, which involves insights from molecular biology and materials science, investigated changes in proteomic, architectural, and localized mechanical characteristics of elytra from the Japanese rhinoceros beetle to understand molecular mechanisms driving elytra development. In the present study, we identified a set of new protein groups which are likely related to the structural development of elytra and has potential for new pathways for processing green materials.

Whole-organism 3D quantitative characterization of zebrafish melanin by silver deposition micro-CT.

We previously described X-ray histotomography, a high-resolution, non-destructive form of X-ray microtomography (micro-CT) imaging customized for three-dimensional (3D), digital histology, allowing quantitative, volumetric tissue and organismal phenotyping (Ding et al., 2019). Here, we have combined micro-CT with a novel application of ionic silver staining to characterize melanin distribution in whole zebrafish larvae. The resulting images enabled whole-body, computational analyses of regional melanin content and morphology. Normalized micro-CT reconstructions of silver-stained fish consistently reproduced pigment patterns seen by light microscopy, and further allowed direct quantitative comparisons of melanin content across wild-type and mutant samples, including subtle phenotypes not previously noticed. Silver staining of melanin for micro-CT provides proof-of-principle for whole-body, 3D computational phenomic analysis of a specific cell type at cellular resolution, with potential applications in other model organisms and melanocytic neoplasms. Advances such as this in whole-organism, high-resolution phenotyping provide superior context for studying the phenotypic effects of genetic, disease, and environmental variables.

Quantitative X-ray tomographic analysis reveals calcium precipitation in cataractogenesis.

Cataracts, named for pathological light scattering in the lens, are known to be associated with increased large protein aggregates, disrupted protein phase separation, and/or osmotic imbalances in lens cells. We have applied synchrotron phase contrast X-ray micro-computed tomography to directly examine an age-related nuclear cataract model in Cx46 knockout (Cx46KO) mice. High-resolution 3D X-ray tomographic images reveal amorphous spots and strip-like dense matter precipitates in lens cores of all examined Cx46KO mice at different ages. The precipitates are predominantly accumulated in the anterior suture regions of lens cores, and they become longer and dense as mice age. Alizarin red staining data confirms the presence of calcium precipitates in lens cores of all Cx46KO mice. This study indicates that the spatial and temporal calcium precipitation is an age-related event associated with age-related nuclear cataract formation in Cx46KO mice, and further suggests that the loss of Cx46 promotes calcium precipitates in the lens core, which is a new mechanism that likely contributes to the pathological light scattering in this age-related cataract model.

3D Detection of Lithiation and Lithium Plating in Graphite Anodes during Fast Charging.

A barrier to the widespread adoption of electric vehicles is enabling fast charging lithium-ion batteries. At normal charging rates, lithium ions intercalate into the graphite electrode. At high charging rates, lithiation is inhomogeneous, and metallic lithium can plate on the graphite particles, reducing capacity and causing safety concerns. We have built a cell for conducting high-resolution in situ X-ray microtomography experiments to quantify three-dimensional lithiation inhomogeneity and lithium plating. Our studies reveal an unexpected correlation between these two phenomena. During fast charging, a layer of mossy lithium metal plates at the graphite electrode-separator interface. The transport bottlenecks resulting from this layer lead to underlithiated graphite particles well-removed from the separator, near the current collector. These underlithiated particles lie directly underneath the mossy lithium, suggesting that lithium plating inhibits further lithiation of the underlying electrode.

Evolution of Protrusions on Lithium Metal Anodes Stabilized by a Solid Block Copolymer Electrolyte Studied Using Time-Resolved X-ray Tomography.

Growing demand for rechargeable batteries with higher energy densities has motivated research focused on enabling the lithium metal anode. A prominent failure mechanism in such batteries is short circuiting due to the uncontrolled propagation of lithium protrusions that often have a dendritic morphology. In this paper, the electrodeposition of metallic lithium through a rigid polystyrene-b-poly(ethylene oxide) (PS-b-PEO or SEO) block copolymer electrolyte was studied using hard X-ray microtomography. In this system, protrusions were approximately ellipsoidal globules: we take advantage of this simple geometry to quantify their growth as a function of polarization time and electrolyte salt concentration. The growth of 47 different globules was tracked with time to obtain average velocities of globule growth into the electrolyte. The globule diameter was a linear function of globule height in the electrolyte with a slope of about 6, independent of time and electrolyte salt concentration.

Evolution of eggshell structure in relation to nesting ecology in non-avian reptiles.

Amniotic eggs are multifunctional structures that enabled early tetrapods to colonize the land millions of years ago, and are now the reproductive mode of over 70% of all terrestrial amniotes. Eggshell morphology is at the core of animal survival, mediating the interactions between embryos and their environment, and has evolved into a massive diversity of forms and functions in modern reptiles. These functions are critical to embryonic survival and may serve as models for new antimicrobial and/or breathable membranes. However, we still lack critical data on the basic structural and functional properties of eggs, particularly of reptiles. Here, we first characterized egg shape, shell thickness, porosity, and mineralization of eggs from 91 reptile species using optical images, scanning electron microscopy, and micro computed tomography, and collected data on nesting ecology from the literature. We then used comparative analyses to test hypotheses on the selective pressures driving their evolution. We hypothesized that eggshell morphology has evolved to protect shells from physical damage and desiccation, and, in support, found a positive relationship between thickness and precipitation, and a negative relationship between porosity and temperature. Although mineralization varied extensively, it was not correlated with nesting ecology variables. Ancestral state reconstructions show thinning and increased porosity over evolutionary time in squamates, but the opposite in turtles and crocodilians. Egg shape, size, porosity and calcification were correlated, suggesting potential structural or developmental tradeoffs. This study provides new data and insights into the morphology and evolution of reptile eggs, and raises numerous questions for additional research.

Tomography of 3D-Printed Lattice Structured Aluminum-Silicon Alloy and Its Deformation.

Additive manufactured light components are desirable for airspace and automobile applications where failure resistance under contact is important. To date, understanding the nature of subsurface damage in contact is still lacking. In this research, we investigated 3D-printed aluminum-silicon (Al-Si) alloys in the lattice structure under a rolling contact condition. Using the microtomography technique, we were able to construct a 3D image of the lattice structure being plastically deformed. Finite element analysis was conducted about the strain and stress on struts of different dimensions. Results showed that morphology dominated the deformation. The significant factors affecting the deformation were the strut aspect ratio, and their relative diameter. When the aspect ratio of a strut is smaller than 0.5, the plastic deformation is distributed in the subsurface region and when it is larger than 0.5, the deformation concentrates on the top layer of struts. This research indicates that the dimensional parameters of lattice structures can be designed for optimization to achieve higher resistance to deformation.

Observation of Preferential Pathways for Oxygen Removal through Porous Transport Layers of Polymer Electrolyte Water Electrolyzers.

Understanding the relationships between porous transport layer (PTL) morphology and oxygen removal is essential to improve the polymer electrolyte water electrolyzer (PEWE) performance. Operando X-ray computed tomography and machine learning were performed on a model electrolyzer at different water flow rates and current densities to determine how these operating conditions alter oxygen transport in the PTLs. We report a direct observation of oxygen taking preferential pathways through the PTL, regardless of the water flow rate or current density (1-4 A/cm2). Oxygen distribution in the PTL had a periodic behavior with period of 400 µm. A computational fluid dynamics model was used to predict oxygen distribution in the PTL showing periodic oxygen front. Observed oxygen distribution is due to low in-plane PTL tortuosity and high porosity enabling merging of oxygen bubbles in the middle of the PTL and also due to aerophobicity of the layer.

Scalable method for micro-CT analysis enables large scale quantitative characterization of brain lesions and implants.

Anatomic evaluation is an important aspect of many studies in neuroscience; however, it often lacks information about the three-dimensional structure of the brain. Micro-CT imaging provides an excellent, nondestructive, method for the evaluation of brain structure, but current applications to neurophysiological or lesion studies require removal of the skull as well as hazardous chemicals, dehydration, or embedding, limiting their scalability and utility. Here we present a protocol using eosin in combination with bone decalcification to enhance contrast in the tissue and then employ monochromatic and propagation phase-contrast micro-CT imaging to enable the imaging of brain structure with the preservation of the surrounding skull. Instead of relying on descriptive, time-consuming, or subjective methods, we develop simple quantitative analyses to map the locations of recording electrodes and to characterize the presence and extent of hippocampal brain lesions.