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At least 1,495 records · Page 83

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗

Recent In Situ/Operando Characterization of Lithium-Sulfur Batteries

To address the ever-increasing energy demand due to the increase in the population and at the same time depleting fossil fuel reserves, new energy storage systems, such as batteries, are being developed. Among various battery systems, Li-S batteries have comparatively high theoretical energy density and lower cost, making Li-S batteries very promising for next-generation secondary batteries. However, the current energy density and capacity decay with cycling of Li-S batteries do not fulfill the industrialization needs. To overcome the drawbacks of Li-S batteries and improve its performance, better mechanism understanding is necessary. A great deal of ex situ characterization research has been conducted making a lot of progress in the understanding of the working mechanism. Considering the complexity of the intermediate lithium polysulfides and the inherent multi-electron reaction pathways, advanced in situ/operando techniques are highly required. In this chapter, recent progress of a few typical in situ/operando characterization techniques used in Li-S battery studies is reviewed. These techniques provide more in-depth understanding of Li-S batteries in different aspects and could be enlightening for other energy storage systems too.

Yang, Yan↗

Sub-nanosecond single line-of-sight (SLOS) x-ray imagers (invited)

A new generation of fast-gated x-ray framing cameras have been developed that are capable of capturing multiple frames along a single line-of-sight with 30 ps temporal resolution. The instruments are constructed by integrating pulse-dilation electron imaging with burst mode hybrid-complimentary metal-oxide-semiconductor sensors. Two such instruments have been developed, characterized, and fielded at the National Ignition Facility and the OMEGA laser. These instruments are particularly suited for advanced x-ray imaging applications in Inertial Confinement Fusion and High energy density experiments. Here, we discuss the system architecture and the techniques required for tuning the instruments to achieve optimal performance. Characterization results are also presented along with planned future improvements to the design.

47 OTHER INSTRUMENTATION↗

Characterization of SuperLig® 639 rhenium and technetium resin with batch contact and column tests

Two new (2013) lots of SuperLig® 639 ion exchange resin (IBC Advanced Technologies, American Forks, UT) were tested for the first time above typical sodium concentrations (7.8 M sodium, along with typical 5 M concentration) in highly alkaline solutions. Batch contact and ion exchange column tests characterized rhenium (perrhenate) adsorption as a surrogate for pertechnetate. The work supports technetium removal options for Supplemental Low Activity Waste processing at the Hanford River Protection Project Waste Treatment Plant (WTP). The current work found that the resin performs well in the 7.8 M sodium simulant despite complete floating of the beads. A notable difference in performance between the two new resin lots was found. As a result, resin loading overall versus temperature, potassium concentration, and rhenium/nitrate ratios is consistent with previous data and expectations despite the high sodium concentration and floating of the resin beads.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CY2013 Annual Report for DOE-ITU INERI 2010-006-E

New concepts for nuclear energy development are considered in both the USA and Europe within the framework of the Generation-IV International Forum (GIF) as well as in various US-DOE programs (e.g. the Fuel Cycle Research and Development - FCRD) and as part of the European Sustainable Nuclear Energy Technology Platform (SNE-TP). Since most new fuel cycle concepts envisage the adoption of a closed nuclear fuel cycle employing fast reactors, the fuel behavior characteristics of the various proposed advanced fuel forms must be effectively investigated using state of the art experimental techniques before implementation. More rapid progress can be achieved if effective synergy with advanced (multi-scale) modeling efforts can be achieved. The fuel systems to be considered include minor actinide (MA) transmutation fuel types such as advanced MOX, advanced metal alloy, inert matrix fuel (IMF), and other ceramic fuels like nitrides, carbides, etc., for fast neutronic spectrum conditions. Most of the advanced fuel compounds have already been the object of past examination programs, which included irradiations in research reactors. The knowledge derived from previous experience constitutes a significant, albeit incomplete body of data. New or upgraded experimental tools are available today that can extend the scientific and technological knowledge towards achieving the objectives associated with the new generation of nuclear reactors and fuels. The objectives of this project will be three-fold: (1) to extend the available knowledge on properties and irradiation behavior of high burnup and minor actinide bearing advanced fuel systems; (2) to establish a synergy with multi-scale and code development efforts in which experimental data and expertise on the irradiation behavior of nuclear fuels is properly conveyed for the upgrade/development of advanced modeling tools; (3) to promote the effective use of international resources to the characterization of irradiated fuel through exchange of expertise and information among leading experimental facilities. The priorities in this project will be set according to the down selection procedure of U.S. and European development programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High-Mileage Courier Fleet Vehicle Laboratory Battery Pack Testing

For one of each of the AVTA's plug-in hybrid electric vehicles, battery electric vehicles, and some hybrid electric vehicles tested in high-mileage courier fleets, the high-voltage traction battery packs were removed from the vehicle and tested at the beginning and end of fleet testing. For some vehicles, batteries also were tested at periodic intervals during fleet testing. Standard reference performance tests were conducted to characterize battery degradation over time. This dataset contains results from two or more rounds of battery tests for 21 distinct year/make/model vehicles (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Each round of battery testing included the "Static Capacity Test" and the "Hybrid Pulse Power Characterization (HPPC) Test", conducted according to test procedures published in the United States Advanced Battery Consortium ["Battery Test Manual For Power-Assist Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=57), ["Battery Test Manual For Plug-In Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=168), and ["Electric Vehicle Battery Test Procedures Manual"](https://www.uscar.org/commands/files_download.php?files_id=5) prior to the time of testing. These tests were performed by Intertek Testing Services, North America. (This dataset will be shared by API; a small sample of the vehicle battery and test data has been extracted and is available for download while the API is being developed.)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-Mileage Courier Fleet Vehicle Laboratory Battery Pack Testing

For one of each of the AVTA's plug-in hybrid electric vehicles, battery electric vehicles, and some hybrid electric vehicles tested in high-mileage courier fleets, the high-voltage traction battery packs were removed from the vehicle and tested at the beginning and end of fleet testing. For some vehicles, batteries also were tested at periodic intervals during fleet testing. Standard reference performance tests were conducted to characterize battery degradation over time. This dataset contains results from two or more rounds of battery tests for 21 distinct year/make/model vehicles (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Each round of battery testing included the "Static Capacity Test" and the "Hybrid Pulse Power Characterization (HPPC) Test", conducted according to test procedures published in the United States Advanced Battery Consortium ["Battery Test Manual For Power-Assist Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=57), ["Battery Test Manual For Plug-In Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=168), and ["Electric Vehicle Battery Test Procedures Manual"](https://www.uscar.org/commands/files_download.php?files_id=5) prior to the time of testing. These tests were performed by Intertek Testing Services, North America. This dataset is shared by API; a small sample of the vehicle battery and test data has been extracted and is also available for download.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electrical Energy Storage for Renewable Energy Systems

This program focused on development of the fundamental understanding necessary to significantly improve advanced battery and ultra-capacitor materials and systems to achieve significantly higher power and energy density on the one hand, and significantly lower cost on the other. This program spanned all the way from atomic-level theory, to new nanomaterials syntheses and characterization, to system modeling and bench-scale technology demonstration. This program not only delivered significant advancements in fundamental understanding and new materials and technology, it also showcased the power of the cross-functional, multi-disciplinary teams at UT Dallas and UT Tyler for such work. These teams are continuing this work with other sources of funding from both industry and government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The NREL Sensor Laboratory: Status and Future Directions for Hydrogen Detection

The NREL Hydrogen Sensor Laboratory was commissioned in 2010 as a resource for the national and international hydrogen community to ensure the availability and proper use of hydrogen sensors. Since then, the Sensor Laboratory has provided unbiased verification of hydrogen sensor performance for sensor developers, end-users, and regulatory agencies and has also provided active support for numerous code and standards development organizations. Although sensor performance assessment remains a core capability, the mission of the NREL Sensor Laboratory has expanded toward a more holistic approach regarding the role of hydrogen detection and its implementation strategy for both assurance of facility safety as well as for process control applications. Active monitoring for detection of unintended releases has been identified by the NFPA 2 Storage Task Group as a viable approach for improving facility safety and lowering setbacks. The current research program for the Sensor Laboratory addresses both conventional and advanced developing detection strategies in response to the emerging large-scale markets, such as those envisioned by H2@Scale. These emerging hydrogen applications may require alternative detection strategies that supplement and may ultimately supplant the use of traditional sensors for monitoring hydrogen releases. Research focus areas for the NREL Sensor Laboratory now encompasses the characterization of released hydrogen behavior to optimize detection strategies for both indoor and outdoor applications, advanced methods of hydrogen leak detection such as hydrogen wide area monitoring approaches for large scale and distributed applications, the incorporation of active monitoring as a risk reduction strategy to improve safety at hydrogen facilities, and continuing support of hydrogen safety codes and standards. In addition to assurance of safety, detection will be critical for process control applications, such as hydrogen fuel quality verification for fuel cell vehicle applications and for monitoring and controlling of hydrogen-natural gas blend composition.

codes and standards↗

Utilizing plant synthetic biology to accelerate plant-microbe interactions research

Plant-microbe interactions are critical to ecosystem resilience and substantially influence crop production. From the perspective of plant science, two important focus areas concerning plant-microbe interactions include: 1) understanding plant molecular mechanisms involved in plant-microbe interfaces and 2) engineering plants for increasing plant disease resistance or enhancing beneficial interactions with microbes to increase their resilience to biotic and abiotic stress conditions. Molecular biology and genetics approaches have been used to investigate the molecular mechanisms underlying plant responses to various beneficial and pathogenic microbes. While these approaches are valuable for elucidating the functions of individual genes and pathways, they fall short of unraveling the complex cross-talk across pathways or systems that plants employ to respond and adapt to environmental stresses. Also, genetic engineering of plants to increase disease resistance or enhance symbiosis with microbes has mainly been attempted or conducted through targeted manipulation of single genes/pathways of plants. Recent advancements in synthetic biology tool development are paving the way for multi-gene characterization and engineering in plants in relation to plant-microbe interactions. Here, we briefly summarize the current understanding of plant molecular pathways involved in plant interactions with beneficial and pathogenic microorganisms. Then, we highlight the progress in applying plant synthetic biology to elucidate the molecular basis of plant responses to microbes, enhance plant disease resistance, engineer synthetic symbiosis, and conduct in situ microbiome engineering. Lastly, we discuss the challenges, opportunities, and future directions for advancing plant-microbe interactions research using the capabilities of plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis

Abstract Point defects in hexagonal boron nitride (hBN) have attracted growing attention as bright single-photon emitters. However, understanding of their atomic structure and radiative properties remains incomplete. Here we study the excited states and radiative lifetimes of over 20 native defects and carbon or oxygen impurities in hBN using ab initio density functional theory and GW plus Bethe-Salpeter equation calculations, generating a large data set of their emission energy, polarization and lifetime. We find a wide variability across quantum emitters, with exciton energies ranging from 0.3 to 4 eV and radiative lifetimes from ns to ms for different defect structures. Through a Bayesian statistical analysis, we identify various high-likelihood charge-neutral defect emitters, among which the native V N N B defect is predicted to possess emission energy and radiative lifetime in agreement with experiments. Our work advances the microscopic understanding of hBN single-photon emitters and introduces a computational framework to characterize and identify quantum emitters in 2D materials.

Chemistry↗

Local plate/rod descriptors of 3D trabecular bone micro-CT images from medial axis topologic analysis

Purpose: Trabecular bone microarchitecture is made of a complex network of plate and rod structures evolving with age and disease. The purpose of this article is to propose a new 3D local analysis method for the quantitative assessment of parameters related to the geometry of trabecular bone microarchitecture. Methods: The method is based on the topologic classification of the medial axis of the 3D image into branches, rods, and plates. Thanks to the reversibility of the medial axis, the classification is next extended to the whole 3D image. Finally, the percentages of rods and plates as well as their mean thicknesses are calculated. The method was applied both to simulated test images and 3D micro-CT images of human trabecular bone. Results: The classification of simulated phantoms made of plates and rods shows that the maximum error in the quantitative percentages of plate and rods is less than 6% and smaller than with the structure model index (SMI). Micro-CT images of human femoral bone taken in osteoporosis and early or advanced osteoarthritis were analyzed. Despite the large physiological variability, the present method avoids the underestimation of rods observed with other local methods. The relative percentages of rods and plates were not significantly different between osteoarthritis and osteoporotic groups, whereas their absolute percentages were in relation to an increase of rod and plate thicknesses in advanced osteoarthritis with also higher relative and absolute number of nodes. Conclusions: The proposed method is model-independent, robust to surface irregularities, and enables geometrical characterization of not only skeletal structures but entire 3D images. Its application provided more accurate results than the standard SMI on simple simulated phantoms, but the discrepancy observed on the advanced osteoarthritis group raises questions that will require further investigations. The systematic use of such a local method in the characterization of trabecular bone samples could provide new insight in bone microarchitecture changes related to bone diseases or to those induced by drugs or therapy.

60 APPLIED LIFE SCIENCES↗

X-ray-diffraction and electrical-transport imaging of superconducting superhydride (La,Y)H 10

Understanding how microscopic structural domains govern macroscopic electronic properties is central to advancing hydride superconductors, yet such correlations remain poorly resolved under pressure. We report the synthesis and characterization of (La 0.9 Y 0.1 )H 10 superhydrides exhibiting coexisting cubic $Fm\bar{3}m$ and $P6_3/mmc$ hexagonal clathrate phases observed over the pressure range from 168 GPa down to 136 GPa. Using synchrotron-based X-ray diffraction imaging at the upgraded Advanced Photon Source, we spatially resolved μm-scale distributions of these phases, revealing structural inhomogeneity across the sample. Four-probe resistance measurements confirmed superconductivity with two distinct transitions: an onset at 244 K associated with the cubic phase and a second near 220 K linked to the hexagonal phase. Notably, resistance profiles collected from multiple current and voltage permutations showed variations in transition width and onset temperature that correlated with the spatial phase distribution. These findings demonstrate a direct connection between local structural domains and superconducting behavior.

Materials science↗

Advanced Collaborative Emissions Study (ACES)

The objective of the Advanced Collaborative Emissions Study (ACES) was to determine before widespread commercial deployment whether or not the new, energy-efficient, heavy duty diesel engines (2007 and 2010 EPA Emissions Standards Compliant) may generate anticipated toxic emissions that could adversely affect the environment and human health. ACES was planned to take place in three phases. In Phase 1, extensive emissions characterization of four production-intent prototype engine and control systems designed to meet 2007 standards for nitrogen oxides (NOx) and particulate matter (PM) was conducted at an existing emissions characterization facility: Southwest Research Institute (SwRI). One of the tested engines was selected (at random, after careful comparison of results) for health testing in Phase 3. In Phase 2, extensive emission characterization of three production-intent prototype engine and control systems meeting the 2010 standards (including more advanced NOx controls to meet the more stringent 2010 NOx standards) was conducted at the same test facility. In Phase 3, one engine/aftertreatment system selected from Phase 1 was further characterized during health effects studies (at an existing inhalation toxicology laboratory: Lovelace Respiratory Research Institute, [LRRI]) to form the basis of the ACES safety assessment. The Department of Energy (DOE) award provided funding for emissions characterization in Phases 1 and 2 as well as exposure characterization in Phase 3. The main health analyses in Phase 3 were funded separately and are not reported here.

54 ENVIRONMENTAL SCIENCES↗

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. Additionally, the end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

42 ENGINEERING↗

Frontiers of in situ electron microscopy

In situ transmission electron microscopy (TEM) has become an increasingly important tool for materials characterization. It provides key information on the structural dynamics of a material during transformations and the correlation between structure and properties of materials. With the recent advances in instrumentation, including aberration corrected optics, sample environment control, the sample stage, and fast and sensitive data acquisition, in situ TEM characterization has become more and more powerful. In this article, a brief review of the current status and future opportunities of in situ TEM is included. It also provides an introduction to the six articles covered by in this issue of MRS Bulletin explore the frontiers of in situ electron microscopy, including liquid and gas environmental TEM, dynamic four-dimensional TEM, nanomechanics, ferroelectric domain switching studied by in situ TEM, and state-of-the-art atomic imaging of light elements (i.e., carbon atoms) and individual defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗