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At least 307 records · Page 17

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.

Suchyta, Eric↗

Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure-based process monitoring of direct-ink write material extrusion additive manufacturing

As additive manufacturing (AM) has become a reliable method for creating complex and unique hardware rapidly, the quality assurance of printed parts remains a priority. In situ process monitoring offers an approach for performing quality control while simultaneously minimizing post-production inspection. For extrusion printing processes, direct linkages between extrusion pressure fluctuations and print defects can be established by integrating pressure sensors onto the print head. In this work, the sensitivity of process monitoring is tested using engineered spherical defects. Pressure and force sensors located near an ink reservoir and just before the nozzle are shown to assist in identification of air bubbles, changes in height between the print head and build surface, clogs, and particle aggregates with a detection threshold of 60–70% of the nozzle diameter. Visual evidence of printed bead distortion is quantified using optical image analysis and correlated to pressure measurements. Importantly, this methodology provides an ability to monitor the quality of AM parts produced by extrusion printing methods and can be accomplished using commonly available pressure-sensing equipment.

36 MATERIALS SCIENCE↗

Augmented Monitoring and Condition Assessment Program (AMCAP) - Proof-of-Principle (POP) Mockup for Non-Aluminum Spent Nuclear Fuel Container In-Situ Examinations

A disciplined engineering approach is being followed to develop an engineered system of tooling and sensors, characterization techniques, and deployment subsystems for in-situ inspection of the several container types used for the storage of non-aluminum spent nuclear fuel (NASNF) in L Basin under the Augmented Monitoring and Condition Assessment Program (AMCAP). Inspecting the containers to provide information on their structural condition helps ensure the safe handling and storage of the NASNF containers pending final disposition. This report describes the work performed in the initial two phases of this developmental work, namely the bench scale and proof-of-principle (POP) scale, which focus on sensor selection and the tooling design and fabrication for two remote non-destructive examination (NDE) methods. These methods include visual testing (VT) for a visual examination of the container surfaces and ultrasonic testing (UT) for a n examination to characterize container wall material thickness and flaws.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Revealing the Structural Evolution of Green Rust Synthesized in Ionic Liquids by In Situ Molecular Imaging

Abstract Ionic liquids are green solvents that have wide applications in material synthesis, catalysis, and separation. A model switchable ionic liquid (SWIL) consisting of 1,8‐diazabicycloundec‐7‐ene (DBU) and 1‐hexanol with carbon dioxide (CO 2 ) as the trigger gas is chosen to synthesize nanocrystalline green rust. Under anoxic conditions, by adding iron (II) acetate (Fe(C 2 H 3 O 2 ) 2 ) and methanol to the degassed SWIL, a nanoparticulate green rust with carbonate (nano‐GR) is synthesized. More importantly, the molecular structural change of the ionic liquid resulting in green rust crystallines is first characterized using in situ liquid using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) coupled with the system for analysis at the liquid vacuum interface (SALVI), a vacuum compatible microfluidic reactor in this work. Dimers and ionic clusters consisting ferric and ferrous ions are identified in liquid ToF‐SIMS spectra. Spectral principal component analysis is used to confirm that these ion pairs including dimers and cluster ions are different from nonionic liquids. The results show that liquid ToF‐SIMS can be a useful tool to study complex liquids at the molecular level providing insights into predicative synthesis of nanomaterials using environmentally friendly green solvents and giving unique visualization of the evolving material interface due to nucleation.

Shen, Yanjie↗

Precision Polishing of Spheres Via In-Situ Process Monitoring and Machine-Learning-Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High density carbon capsules made for ICF experiments on the National Ignition Facility (NIF) are precision polished to achieve the surface smoothness in the order of a few nm as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with goal of elevating the efficiency of this process. Our approach is to use MEMS-based sensors to capture the fine vibrational signals generated during the polishing process and combine it with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, we describe the multiple fronts that we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used for ensuring the progress of the run as well as a means for faster optimization.

36 MATERIALS SCIENCE↗

Visualizing electronic structure of twisted bilayer MoTe 2 in devices

The pursuit of emergent quantum phenomena lies at the forefront of modern condensed matter physics. A recent breakthrough in this arena is the discovery of the fractional quantum anomalous Hall effect (FQAHE) in twisted bilayer MoTe₂ (tbMoTe₂), marking a paradigm shift and establishing a versatile platform for exploring the intricate interplay among topology, magnetism, and electron correlations. While significant progress has been made through both optical and electrical transport measurements, direct experimental insights into the electronic structure – crucial for understanding and modeling this system – have remained elusive. Here, using spatially and angle-resolved photoemission spectroscopy (μ-ARPES), we directly map the electronic band structure of tbMoTe₂. We identify the valence band maximum, whose partial filling underlies the FQAHE, at the K points, situated approximately 150 meV above the Γ valley. By fine-tuning the doping level via in-situ alkali metal deposition, we also resolve the conduction band minimum at the K point, providing direct evidence that tbMoTe₂ exhibits a direct band gap – distinct from all previously known moiré bilayer transition metal dichalcogenide systems. These results offer critical insights for theoretical modeling and advance our understanding of fractionalized excitations and correlated topological phases in this emergent quantum material.

Chen, Cheng [Univ. of Oxford (United Kingdom)]↗

Favorable morphology and electronic conductivity of functional sublayers for highly efficient water splitting electrodes

Low electronic conductivities and improper morphologies of anode electrodes greatly limit the reaction area, catalyst utilization and efficiency in proton exchange membrane water electrolyzers. In this study, conductive sublayers with different conductivities and morphologies were introduced into anode electrodes in membrane-based water electrolyzers. In-situ and ex-situ investigation results showed that conductive sublayers (Au mesh and carbon nanotube (CNT) film) augmented the sheet conductivity of anode electrodes by up to 4000 times (from 2000 to 0.5 ohm square -1 ), and the ohmic resistance of water electrolyzers was reduced to 1/3 when inserting conductive sublayers. In addition, CNT film provided a higher electrochemical active area than Au mesh, because of favorable morphologies (large porosity and surface area) of CNT fibers on CNT films. Therefore, the current density of water splitting was increased by 3 times (from 4.55 mA cm -2 to 14.83 mA cm -2 ) at 2.5 V compared to a conventional anode electrode. Visualizations on bubble dynamics showed improved performances with conductive sublayers; this was mainly due to greatly increased number of reaction sites, highly spread reaction area (from 50 to 1000 um), and reduced activation overpotential. Therefore, a balance between high electronic conductivity and nanoporous morphology is essential to the anode electrode for larger reaction sites and areas in highly efficient water electrolyzers.

25 ENERGY STORAGE↗

Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fluorescent and Bioluminescent Reporter Mouse-Adapted Ebola Viruses Maintain Pathogenicity and Can Be Visualized in Vivo

Abstract Ebola virus (EBOV) causes lethal disease in humans but not in mice. Here, we generated recombinant mouse-adapted (MA) EBOVs, including 1 based on the previously reported serially adapted strain (rMA-EBOV), along with single-reporter rMA-EBOVs expressing either fluorescent (ZsGreen1 [ZsG]) or bioluminescent (nano-luciferase [nLuc]) reporters, and dual-reporter rMA-EBOVs expressing both ZsG and nLuc. No detriment to viral growth in vitro was seen with inclusion of MA-associated mutations or reporter proteins. In CD-1 mice, infection with MA-EBOV, rMA-EBOV, and single-reporter rMA-EBOVs conferred 100% lethality; infection with dual-reporter rMA-EBOV resulted in 73% lethality. Bioluminescent signal from rMA-EBOV expressing nLuc was detected in vivo and ex vivo using the IVIS Spectrum CT. Fluorescent signal from rMA-EBOV expressing ZsG was detected in situ using handheld blue-light transillumination and ex vivo through epi-illumination with the IVIS Spectrum CT. These data support the use of reporter MA-EBOV for studies of Ebola virus in animal disease models.

Immunology↗

Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming

The project Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Wyoming Carbon Underground Storage Project (WY-CUSP) consisted of CO2 storage site characterization and evaluation, focusing on Wyoming’s most promising CO2 storage reservoirs (the Pennsylvanian Weber/Tensleep Sandstone and Mississippian Madison Limestone) and premier CO2 storage site (Rock Springs Uplift). Results from the WY-CUSP project suggest the two reservoirs could store up to 17,000 million tons of CO2. The WY-CUSP team drilled a stratigraphic test well and acquired a 3-D seismic survey covering 25 square miles of the Rock Springs Uplift site. The team retrieved 916 feet of core from the 12,810-foot-deep well, along with a complete log suite, borehole images, fluid samples, and other data. Project partners (1) provided continuous visual documentation of the core, including grain size, mineralogy, facies distribution, and porosity; (2) performed continuous permeability and velocity scans of selected reservoir intervals; and (3) chemically analyzed the fluid samples. WY-CUSP scientists integrated seismic attributes with observations from log suites, a VSP survey, core, fluid samples, and laboratory analyses, including continuous permeability scans. From these integrations, researchers constructed 3-D spatial distribution volumes of reservoir and seal properties that represent geological heterogeneity at the targeted CO2 storage site. The WY-CUSP team used this data to perform new CO2 plume migration simulations. Baker Hughes, Inc., completed a series of small-scale, in-situ water injectivity measurements. A database was formed when observations, analyses, and experiments from the stratigraphic test well were integrated. Correlation of these data allowed petrophysical parameters to be extrapolated from the test well out into the storage domain (5x5 mile 3-D seismic survey volume). This resulted in an improved, realistic understanding of performance assessments for potential CO2 storage scenarios. The WY-CUSP team worked on (1) improving CO2 storage resource estimates, (2) establishing long-term integrity and permanence of confining layers, (3) designing a profitable strategy for pressure management, and (4) evaluating the utilization of stored CO2 at the Rock Spring Uplift. Finally, Baker Hughes developed a microseismic baseline for the test site using in-bore geophones to complete field operations.

3-D seismic↗

High-temperature thermal imaging to inform the arc-melt synthesis of nuclear materials

The advancement of nuclear energy technology necessitates the development of novel materials and synthesis methods to produce materials which enable new fuel cycles. Alongside the maturation of R&D scale technologies to produce these materials, there is an ongoing effort to develop in situ monitoring capabilities to reduce the time to the discovery and development of these fuels. Monitoring data can be leveraged in artificial intelligence platforms to detect phenomena which lead to varied macro- and microstructural features which impact the application and performance of samples synthesized. The present study presents early-stage findings of the implementation of high-temperature, high-frame-rate infrared thermal imaging to monitor the arc-melt synthesis of novel fuels and compounds relevant to advanced nuclear reactors. The study illustrates both the challenges and opportunities of this methodology, highlighting the importance of internal standards while determining emissivity and transmission values as well as visualizing volatilization during melt synthesis.

Stone, Jordan↗

Direct Visualization of Current-Stimulated Oxygen Migration in YBa 2 Cu 3 O 7–δ Thin Films

The past years have witnessed major advancements in all-electrical doping control on cuprates. In the vast majority of cases, the tuning of charge carrier density has been achieved via electric field effect by means of either a ferroelectric polarization or using a dielectric or electrolyte gating. Unfortunately, these approaches are constrained to rather thin superconducting layers and require large electric fields in order to ensure sizable carrier modulations. In this work, we focus on the investigation of oxygen doping in an extended region through current-stimulated oxygen migration in YBa 2 Cu 3 O 7–δ superconducting bridges. The underlying methodology is rather simple and avoids sophisticated nanofabrication process steps and complex electronics. Here, a patterned multiterminal transport bridge configuration allows us to electrically assess the directional counterflow of oxygen atoms and vacancies. Importantly, the emerging propagating front of current-dependent doping δ is probed in situ by optical microscopy and scanning electron microscopy. The resulting imaging techniques, together with photoinduced conductivity and Raman scattering investigations, reveal an inhomogeneous oxygen vacancy distribution with a controllable propagation speed permitting us to estimate the oxygen diffusivity. These findings provide direct evidence that the microscopic mechanism at play in electrical doping of cuprates involves diffusion of oxygen atoms with the applied current. The resulting fine control of the oxygen content would permit a systematic study of complex phase diagrams and the design of electrically addressable devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering exopolysaccharide functional specificity via visualization of chemical motifs that mediate microbial-microenvironment interactions in soil micromodels

Exopolysaccharides (EPS) are carbohydrate-based matrices of microbial biofilms that microbes use to adapt to their surroundings. Microbial EPS also promotes soil aggregate stability and contributes toward soil health by reducing erosion caused by continued land use. The chemical structure of EPS, even within single species biofilms, can vary greatly: from repeating units and branching patterns to the non-carbohydrate decorations. Despite the wealth of knowledge on EPS chemistry, many unresolved questions regarding the biological implications of EPS chemical variations remain. Here, we develop a mass spectrometry imaging toolbox that reveal how EPS chemistry enables microbial adaptation to different microenvironments such as specific moisture, soil-biofilm interfaces, and food source proximity. First, we developed emulated soil micromodels (ESMs), microfluidic channels that simulate the physical properties of soil, for biofilm formation in different microenvironments. Then, in order to map chemical features of EPS in these micromodels, we develop strategies for in-situ releasing of oligosaccharides using specific enzymes. Lastly, we optimized matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) to spatially analyze the released compounds in ESMs.

54 ENVIRONMENTAL SCIENCES↗

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Zheng, Weijian↗

Produced Water DNA Database (PW-DNA): Utilizing KBase to generate an environmental specific curated molecular database

The deep subsurface is estimated to host the majority of Earth’s microbial biomass yet remains one of the most challenging environments to access and study. One common approach to investigate these microbial communities is through the analysis of produced water from subsurface reservoirs, where researchers can assess water and gas chemistry along with molecular (DNA/RNA) sequence data. Advances in high-throughput sequencing have greatly expanded our understanding of these environments and their biotechnological potential. However, further progress requires large-scale, integrative meta-analyses across diverse datasets. To address this need, we developed the Produced Water-DNA (PW-DNA) Database, a curated, publicly available resource that consolidates microbial DNA/RNA sequences, geochemical data, and relevant metadata from in situ hydrocarbon environments such as coal beds, oil reservoirs, and natural gas systems. The PW-DNA database delivers three core benefits to the research community: (1) it improves data sharing by linking environmental microbial datasets with corresponding geochemical parameters, enabling more robust filtering and analysis; (2) it connects with complementary research databases to promote broader dissemination and interoperability; and (3) it supports technological innovation by serving as a resource for identifying microbial trends and exploring genetic potential. While individual studies have highlighted basin-specific microbial communities and functional redundancy in biogeochemical cycling, a comprehensive, system-wide perspective is needed to better understand connectivity and novelty across subsurface ecosystems. By designing the PW-DNA in the KBase platform, we provide a reproducible, visual framework for integrating large-scale genomic and geochemical data, enabling researchers to perform more informed analyses and experimental design. Ultimately, this resource enhances the ability to identify, characterize, and interpret microbial functions across diverse subsurface environments, thereby accelerating discovery in subsurface microbiology and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗