Shark vertebral bodies (centra) possess remarkable resistance to millions of cycles of large in vivo strains exceeding 4 to 8%. These strains are enormous for a mineralized tissue, and it appears that the centra evolved to achieve this performance through a hierarchy of structures spanning dimensions from centimeters to nanometers. At the 1μm scale, blocks cut from centra and imaged with synchrotron microCT demonstrate that the centra tissue consists of closely spaced, mineralized trabeculae. An outstanding question is: How do these trabeculae deform to accommodate these large strains. This paper presents recently obtained synchrotron microCT results on in situ loading of blocks of shark centra and examines the deformation modes of the interconnected array of trabeculae.
X-ray computed tomography (CT) is a promising technique for three-dimensional imaging of batteries, electrolyzers and fuel cells. Operando techniques rely significantly on reactor design, where the operando cell should approximate the actual device. Furthermore, nano- and micro-scale hierarchical materials are used to convert or store electrochemical energy. Imaging with the single scale or synchrotron beamline provides only sliver of information needed. Carbon and ionomer materials that are used as bulk materials in the electrochemical devices are soft and phase-contrast imaging is required.
We present our micro- and nano-X-ray CT reactors designs for polymer electrolyte fuel cells (PEFCs), electrolyzers, and micro X-ray CT operando pouch cell for battery. With the PEFC hardware we control temperature, relative humidity, pressure of gasses, as well as current density. By imaging the PEFCs at various current densities we are able to observe physical phenomena of membrane swelling with relative humidity increase and formation and removal of liquid water from the cell. With nano X-ray CT we are able to combine morphology with x-ray absorption near edge structure (XANES) to elucidate the oxidation state of the catalyst within the active porous layer. Using phase-contrast we are able to distinguish between liquid water and carbon phases. For electrolyzers, understanding formation and removal of oxygen bubbles, which is sub-second transport phenomena is critical. We combine X-ray CT with sub-second X-ray radiography to understand this transient process. For the batteries, we have developed a high throughput pouch cell design for x-ray CT imaging featuring 1 cm diameter active area.
Dilworth Parkinson, Joseph Pacold, Miela Gross, Tristan McDougall, Chandler Jones, John Bows, Ian Hamilton, Danil Smiles, Stefano De Santis, Alessandro Ratti, Daniël Pelt, James Sethian, Harold Barnard, Joshua Peterson, Alvaro Ramirez-Hong, Alastair MacDowell, David Shuh
Synchrotrons like the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory (LBNL) are an extremely bright source of X-rays. In recent years, this brightness has been coupled to large increases in detector speeds (including CMOS and sCMOS detectors) to enable microCT 3D imaging at unprecedented speeds and resolutions. The micro-CT Beamline at the ALS has been used by geologists simulating volcanic eruptions, engineers developing hierarchical materials that are tough at high temperature, and biologists studying water transport in plants experiencing drought stress. In each case, 3D processes occurring over seconds to minutes are studied with micrometer resolution-and in each case, advanced algorithms and data management have been critical in completing successful experiments. This article will describe the collaboration of the ALS with the National Energy Research Scientific Computing Center (NERSC) supercomputer to develop a super-facility, combining powerful X-rays with enormous computing power and describe the collaboration of the ALS with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at LBNL to develop algorithms that can not only handle the enormous data sizes now being collected, but do so fast enough to give scientists feedback during their experiments in real-time. A major focus of CAMERA has been to apply new machine learning approaches to tomography, to improve image reconstruction, automate feature detection, and allow image search.
Machine learning has revolutionized a number of fields, but many micro-tomography users have never used it for their work. The micro-tomography beamline at the Advanced Light Source (ALS), in collaboration with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at Lawrence Berkeley National Laboratory, has now deployed a series of tools to automate data processing for ALS users using machine learning. This includes new reconstruction algorithms, feature extraction tools, and image classification and recommen- dation systems for scientific image. Some of these tools are either in automated pipelines that operate on data as it is collected or as stand-alone software. Others are deployed on computing resources at Berkeley Lab–from workstations to supercomputers–and made accessible to users through either scripting or easy-to-use graphical interfaces. This paper presents a progress report on this work.
The Advanced Light Source (ALS) is a third-generation synchrotron X-ray source that operates as a user facility with more
than 40 beamlines hosting over 2000 users per year. Synchrotron sources like the ALS provide high quality X-ray beams,
with flux that is several orders of magnitude higher than lab-based sources. This is particularly advantageous for dynamic
applications because it allows for high-speed, high-resolution imaging and microscale tomography. The hard X-ray
beamline 8.3.2 at the Advanced Light Source enables imaging of samples at high temperatures and pressures, with
mechanical loading and other realistic conditions using environmental test cells. These test cells enable experimental
observation of samples undergoing dynamic microstructural changes in-situ. We present recent instrumentation
developments that allow for continuous tomography with scan rates approaching 1 Hz per 3D image. In addition, our use
of iterative reconstruction techniques allows for improved image quality despite fewer images and low exposure times
used during fast tomography compared to traditional Fourier reconstruction methods.
The main advantage of Bragg reflection from a multilayer mirror as a monochromator for hard X-rays, is the higher
photon flux density because of the larger spectral bandpass compared with crystal lattice reflection. The main
disadvantage lies in the strong modulations of the reflected beam profile. This is a major issue for micro-imaging
applications, where multilayer-based monochromators are frequently employed to deliver high photon flux density. A
subject of particular interest is the origin of the beam profile modifications, namely the irregular stripe patterns, induced
by the reflection on a multilayer. For multilayer coatings in general it is known that the substrate and its surface quality
significantly influence the performance of mirrors, as the coating reproduces to a certain degree the roughness and shape
of the substrate. This proceedings article reviews recent experiments that indicate potential options for producing wave
front-preserving multilayer mirrors, as well as new details on the particular mirrors our group has extensively studied in
the past.
Justin Blair, Richard Canon, Jack Deslippe, Abdelilah Essiari, Alexander Hexemer, Alastair MacDowell, Dilworth Parkinson, Simon Patton, Lavanya Ramakrishnan, Nobumichi Tamura, Brian Tierney, Craig Tull
KEYWORDS: Databases, Tomography, Data archive systems, Visualization, Data storage, Computing systems, Reconstruction algorithms, Light sources, Hard x-rays, Data processing
The Advanced Light Source (ALS) is a third-generation synchrotron X-ray source that operates as a user facility with more
than 40 beamlines hosting over 2000 users per year from around the world. Users of the Hard X-ray Micro-Tomography
Beamline (8.3.2) often collect more than 1 Terabyte of raw data per day that in turn generates additional Terabytes of
processed data. The data rate continues to increase rapidly due to faster detectors and new sample automation capabilities.
We will present the development and deployment of a computational pipeline, fed by data from the ALS, and powered by
the storage, networking, and computing resources of the local National Energy Research Scientific Computing Center
(NERSC) and the Energy Sciences Network (ESNET). After one year of operation, the system contained 70,000 datasets
and 350 TB of data from 85 users. All datasets now collected at the Hard X-ray Tomography Beamline are automatically
reconstructed using parameters set by users and/or that are automatically detected from the data acquisition control system.
Results are presented to users for visualization through a secure web portal. Users can then download their data or launch a
(currently limited but) growing number of operations based on the data-such as filtering, segmentation, and simulation.
The massive computational resources of NERSC are thus made available on a level that is easily accessible to the full range
of micro-tomography users.
The X-ray micro-Tomography Facility at the Advanced Light Source has been in operation since 2004. The source is a superconducting bend magnet of critical energy 11.5 keV; photon energy coverage is 8-45 KeV in monochromatic mode, and a filtered white light option yields useful photons up to 50 keV. A user-friendly graphical user interface allows users to collect tomographic and radiographic data sets with options including tiled and time series data sets. We will focus on recent projects that utilize sample environments for in-situ imaging. These environments include a high pressure triaxial flow cell which has allowed study of supercritical CO2 transport through brine-saturated sandstone at pressures typical of in-situ conditions for subsurface CO2 sequestration and water transportation within live plants.
We employ a coded aperture pattern in front of a charge couple device (CCD) pixilated detector to image fluorescent xrays (6-25KeV) from samples irradiated with synchrotron radiation. Coded apertures encode the angular direction of xrays, and given a known source plane, allow for a large Numerical Aperture x-ray imaging system. The algorithm to develop the free standing coded aperture pattern of the Non-Two-Holes-Touching (NTHT) was developed. The algorithms to reconstruct the x-ray image from the encoded pattern recorded are developed by means of modeling and confirmed by experiments on standard samples. Spatial resolution and efficiency are determined for the next development stage whereby an energy resolving pixilated CCD will be deployed allowing for elemental imaging.
High-resolution x-ray micro-tomography is used for imaging of solid materials at micrometer scale in 3D. Our
goal is to implement nondestructive techniques to quantify properties in the interior of solid objects, including
information on their 3D geometries, which supports modeling of the fluid dynamics into the pore space of the
host object. The micro-tomography data acquisition process generates large data sets that are often difficult to
handle with adequate performance when using current standard computing and image processing algorithms.
We propose an efficient set of algorithms to filter, segment and extract features from stacks of image slices of
porous media. The first step tunes scale parameters to the filtering algorithm, then it reduces artifacts using a
fast anisotropic filter applied to the image stack, which smoothes homogeneous regions while preserving borders.
Next, the volume is partitioned using statistical region merging, exploiting the intensity similarities of each
segment. Finally, we calculate the porosity of the material based on the solid-void ratio. Our contribution is to
design a pipeline tailored to deal with large data-files, including a scheme for the user to input image patches
for tuning parameters to the datasets. We illustrate our methodology using more than 2,000 micro-tomography
image slices from 4 different porous materials, acquired using high-resolution X-ray. Also, we compare our
results with standard, yet fast algorithms often used for image segmentation, which includes median filtering
and thresholding.
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