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Optical transparency of LiF (100) shock compressed to ∼360 GPa

High-purity [100] lithium fluoride (LiF) is the most widely used optical window in dynamic compression experiments due to its wide bandgap and well-characterized mechanical response. Recent plate-impact experiments established the [100] LiF Hugoniot to ∼230 GPa and demonstrated shock-induced melting onset at 182 GPa with complete melting by 195 GPa; theoretical models predict LiF optical transparency to nearly 900 GPa. To experimentally examine the optical transparency of [100] LiF at higher pressures and in the liquid state, laser-driven shock experiments were performed at peak stresses ranging from 223 to 363 GPa. Optical response was examined by measuring the particle velocity histories at the Kapton/LiF interface using laser interferometry at 532 and 1550 nm wavelengths; in-material particle velocities were obtained using established refractive-index corrections. Continuous photonic Doppler velocimetry fringes were observed across the entire stress range, demonstrating that LiF remains transparent to 1550 nm light throughout the multi-megabar regime investigated. At 532 nm, fringe visibility depended on the reflector coating: aluminum mirrors provided signals to ∼235 GPa, while gold mirrors extended this limit to 270.5 GPa, indicating that the shorter-wavelength response is likely sensitive to experimental configuration rather than to the loss of LiF transparency. Continued optical transparency to at least 360 GPa indicates that shock-melted LiF does not display bandgap closure over the stress range explored. Furthermore, these results provide direct experimental constraints on the high-pressure optical response and establish LiF (100) as a robust optical window material for laser-driven dynamic compression experiments approaching 400 GPa.

Renganathan, P. [Argonne National Laboratory (ANL)

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Inlet

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Data Acquisition

Wide-ranging predictions of new stable compounds powered by recommendation engines

The computational search for new stable inorganic compounds is faster than ever, thanks to high-throughput density functional theory (DFT). However, stable compound searches remain highly expensive because of the enormous search space and the cost of DFT calculations. To aid these searches, recommendation engines have been developed. We conduct a systematic comparison of the performance of previously developed recommendation engines, specifically ones based on elemental substitution, data mining, and neural network prediction of formation enthalpy. After identifying ways to improve the recommendation engines, we find the neural network to be superior at recommending stable Heusler compounds. Armed with improved recommendation engines, we identify tens of thousands of compounds that are stable at zero temperature and pressure, now available in the Open Quantum Materials Database. We summarize this diverse pool of compounds, including the elusive mixed anion compounds, and two of their many applications: thermoelectricity and solar thermochemical fuel production.

Science & Technology - Other Topics

Composite Lithium Metal Structure to Mitigate Pulverization and Enable Long‐Life Batteries

In lithium metal batteries, non‐uniform stripping of lithium results in pit formation, which promotes subsequent non‐uniform, dendritic deposition. This viscous cycle leads to pulverization of lithium which promotes cell shorting or capacity degradation, symptoms further exaggerated by high electrode areal loading and lean electrolytes. Here, to address this challenge, a composite lithium metal anode is engineered that contains uniformly distributed, nanometer‐sized carbon particles. This composite lithium is shown to strip more uniformly since the growth of non‐uniform pits is intercepted by the carbon particles. This mechanism is corroborated by a continuum electrochemical model. Subsequent lithium deposition on carbon particles is also found to be more uniform than on the surface with irregular pits. Notably, the pulverization rate of composite lithium is 26 times slower than that of commercial lithium. Moreover, in a Li‐S battery with sulfurized polyacrylonitrile cathode, the use of the composite anode extends the cycle life by three times when the areal capacity is 8 mAh cm −2 . The approach of using an engineered lithium composite structure to address challenges during both stripping and plating can inform future designs of lithium metal anodes for high areal capacity operations.

high areal capacity

Microstructure, mechanical, and thermal properties of compositionally complex (Hf,Zr,Nb,Ti)B 2 ‒LaB 6 ceramics

Novel compositionally complex borides, (Hf,Zr,Nb,Ti)B 2 and (Hf,Zr,Nb,Ti)B 2 ‒LaB 6 , were fabricated using spark plasma sintering process. (Hf,Zr,Nb,Ti)B 2 ‒LaB 6 exhibits a dual-phase microstructure, in which (Hf,Zr,Nb,Ti)B 2 is a primary phase with the hexagonal structure and LaB 6 is a secondary phase with a cubic structure. The mechanical properties of both (Hf,Zr,Nb,Ti)B 2 and (Hf,Zr,Nb,Ti)B 2 ‒LaB 6 are comparable, with a combination of high hardness and moderate fracture toughness. Thermal diffusivity and conductivity of (Hf,Zr,Nb,Ti)B 2 are much lower than the individual transition metal borides but are significantly increased by the addition of LaB 6 . Herein, it is implied that the thermal properties of boride ceramics can be controlled through the appropriate design of principal metal element compositions.

borides

Detailed examination of LDEF's frame and the A0178 thermal blankets by the meteoroid and debris special investigations group

A responsibility of the group is to define the hypervelocity particle environment encountered by LDEF during its stay in low Earth orbit. LDEF's 6061-T6 aluminum frame and the 'Teflon silver-inconel paint' thermal blankets represent large surface areas that were widely distributed around the spacecraft. The results are reported of high resolution scans of approx. 0.36 and approx. 0.31 sq m for the intercostals and thermal blankets, respectively. The findings are in qualitative agreement with existing model predictions that suggest high differential bombardment histories for surfaces pointing into specific directions relative to the velocity vector of a non-spinning platform in LEO. The production rate for craters greater than or = 50 microns in diameter in aluminum and penetration holes greater than or = 100 microns in diameter in thin foil materials differ by more than a factor of 10 between forward and rearward facing surfaces. These are substantial differences that must be considered during the design of future long duration space platforms in LEO.

Thomas H. See

Powering the Lunar Surface: Managing Dust, Extreme Environments, and Power Needs

Power availability remains one of the primary constraints for lunar surface science. This talk reviews power requirements from previously flown instruments to help prepare future payloads for upcoming CLPS opportunities and highlights the testing and environmental simulation capabilities at NASA JSC that enable reliable lunar payload development. It also outlines the power needs, environmental challenges, and emerging technologies required to support sustained human and robotic operations on the lunar surface as part of NASA’s Moon to Mars strategy. Key challenges include variable solar illumination at polar and equatorial regions, extreme thermal environments, and dust driven degradation that limit current surface power systems. The science data needed for resource identification and landing site planning will allow for the successful preparation of crewed Artemis activities and long-term presence. Building on recent missions, current test infrastructure, and emerging power technology pathways, this presentation equips industry, academia, and government teams with the information needed to design robust lunar payloads, reduce development risk, and fully leverage the increasing cadence of CLPS missions. These developments will form a critical technical foundation for long duration lunar presence and future Mars exploration.

Anastasia Ford

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.

High Energy Hydroforming Friction Stir Welded 2050 Al-Li Blanks for Aerospace Domes and Cones

Friction stir welded (FSW) aluminum blanks offer larger preform sizes than available from the mill in single width plates. Large blanks made from aerospace-grade aluminum alloys are essential for making large domes and cones for launch vehicles and crew vehicles. Previous research efforts have demonstrated >5m FSW blanks can be formed into large domes or cones using spin forming, but the subsequent solution heat treatment consistently led to abnormal grain growth (AGG). The AGG phenomenon occurs because the FSW blanks must be spin formed in the -O annealed temper to withstand the high strain process without cracking. Subsequently, the solution heat treatment process leads to the onset of AGG, whereby a small number of grains grow much larger than the surrounding matrix. Ultimately, the large grains and bimodal grain-size distribution leads to unacceptable ductility in the short-transverse direction of the part. Alternatively, explosive hydroforming is a nascent process that can be applied to large and thick aerospace-grade aluminum alloy blanks in the -T3 temper and only require a post-forming artificial aging process to a -T8. Avoiding the solution heat treatment (SHT) process mitigates AGG, and also eliminates the need for very rare drop-furnace quench baths that can accommodate a part size larger than 5m in diameter. This presentation summarizes a Lockheed Martin-led effort that demonstrated explosive hydroforming of a 1.9m diameter, 39mm thick 2050 aluminum lithium FSW blank. Details will be provided on the process flow, mechanical properties, and metallographic analyses. This work was performed in partnership with NASA Langley Research Center (LaRC) under a NASA Announcement of Collaboration Opportunities program.

Friction stir welded blank

Rapid Assessment of Sulfate Resistance in Mortar and Concrete

Extensive research has been conducted on the sulfate attack of concrete structures; however, the need to adopt the use of more sustainable materials is driving a need for a quicker test method to assess sulfate resistance. This work presents accelerated methods that can reduce the time required for assessing the sulfate resistance of mixtures by 70%. Class F fly ash has historically been used in concrete mixtures to improve sulfate resistance. However, environmental considerations and the evolving energy industry have decreased its availability, requiring the identification of economically viable and environmentally friendly alternatives to fly ash. Another challenge in addressing sulfate attack durability issues in concrete is that the standard sulfate attack test (ASTM C1012) is time-consuming and designed for only standard mortars (not concrete mixtures). To expedite the testing process, accelerated testing methods for both mortar and concrete mixtures were adopted from previous work to further the development of the accelerated tests and to assess the feasibility of testing the sulfate resistance of mortar and concrete mixtures rapidly. This study also established criteria for interpreting sulfate resistance for each of the test methods used in this work. A total of 14 mortar mixtures and four concrete mixtures using two types of Portland cement (Type I and Type I/II) and various supplementary cementitious materials (SCMs) were evaluated in this study. The accelerated testing methods significantly reduced the evaluation time from 12 months to 21 days for mortar mixtures and from 6 months to 56 days for concrete mixtures. The proposed interpretation method for mortar accelerated test results showed acceptable consistency with the ACI 318-19 interpretations for ASTM C1012 results. The interpretation methods proposed for the two concrete sulfate attack tests demonstrated excellent consistency with the ASTM C1012 results from mortar mixtures with the same cementitious materials combinations. Metakaolin was shown to improve sulfate resistance for both mortar and concrete mixtures, while silica fume and natural pozzolan had a limited impact. Using 15% metakaolin in mortar or concrete mixtures with Type I/II cement provided the best sulfate resistance.

Chemistry

Quantifying Primary Arc-Induced Degradation of Perovskite Solar Cells

Primary arcing induced by spacecraft charging presents a significant hazard to thin film solar cells if left unchecked. Here, we present the results of a preliminary effort to quantify the impacts of primary arcing to perovskite solar cells. Solar cells operating in a charged environment are susceptible to electrostatic discharges known as arcing. While primary arcs are not generally considered a major concern for traditional space PV, for thin film cells, these can induce significant heating and subsequent damage. We conducted ESD testing in a LEO-like plasma in the National Plasma Interaction Facility at NASA Glenn Research Center to quantify impacts to cell performance by arcing. The perovskites tested saw a decrease of short circuit current with an increased number of arcs, averaging a relative change of 73.89 ± 15.90% after 60 total arcs supplied a cumulative energy dose of 76.12 mJ to the string. Ongoing work entails testing with larger perovskite data sets and expanding to include additional thin film cell technologies to demonstrate the risk unmitigated primary arcing presents.

primary arcing

The Cassini/Huygens Doppler Wind Experiment: Results from the Titan Descent

The primary objective of the Doppler Wind Experiment (DWE), one of the six scientific investigations comprising the payload of the ESA Huygens Probe, is a determination of the wind velocity in Titan's atmosphere. Measurements of the Doppler shift of the S-band (2040 MHz) carrier signal to the Cassini Orbiter and to Earth were recorded during the Probe descent in order to deduce wind-induced motion of the Probe to an accuracy better than 1 m s-1. An experiment with the same scientific goal was performed with the Galileo Probe at Jupiter. Analogous to the Galileo experience, it was anticipated that the frequency of the Huygens radio signal could be measured on Earth to obtain an additional component of the horizontal winds. Specific secondary science objectives of DWE include measurements of: (a) Doppler fluctuations to determine the turbulence spectrum and possible wave activity in the Titan atmosphere; (b) Doppler and signal level modulation to monitor Probe descent dynamics (e.g., spinrate/spinphase, parachute swing); (c) Probe coordinates and orientation during descent and after impact on Titan.

M K Bird

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION

Tetrel Bond-Mediated Photophysical Modulation and Fluoride Recognition in Carbazole-Organosilanes

Silicon-centered orbitals are typically regarded as electronically inert in donor–acceptor systems. Here, we show that silole-based carbazole–silane architectures can render these orbitals electronically relevant, enabling modulation of excited-state behavior and anion-responsive photophysics. Two carbazole–Dipp–silanes exhibit identical carbazole-localized LE singlet emission in solution yet diverge markedly in the solid state: one compound displays a broad long-wavelength emission band in the prompt spectrum and enhanced long-lived emission consistent with a triplet-derived excited state, likely arising from a combination of intramolecular structural locking and solid-state packing effects, whereas the more flexible analogue remains predominantly LE-emissive. Fluoride coordination further differentiates the two systems, producing ratiometric red-shifted emission in one case and fluorescence quenching in the other through a fully reversible coordination process. These results identify σ*(Si–Ar) orbitals as tunable contributors to excited-state landscapes in organosilane luminophores and suggest a broader design strategy for controlling excited-state behavior in tetrel-based photofunctional systems.

Haque, Md Hasanul

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]

First Principles Study of Aluminum Doped Polycrystalline Silicon as a Potential Anode Candidate in Li‐ion Batteries

Addressing sustainable energy storage remains crucial for transitioning to renewable sources. While Li‐ion batteries have made significant contributions, enhancing their capacity through alternative materials remains a key challenge. Micro‐sized silicon is a promising anode material due to its tenfold higher theoretical capacity compared to conventional graphite. However, its substantial volumetric expansion during cycling impedes practical application due to mechanical failure and rapid capacity fading. A novel approach is proposed to mitigate this issue by incorporating trace amounts of aluminum into the micro‐sized silicon electrode using ball milling. Density functional theory (DFT) is employed to establish a theoretical framework elucidating how grain boundary sliding, a key mechanism involved in preventing mechanical failure is facilitated by the presence of trace aluminum at grain boundaries. This, in turn, reduces stress accumulation within the material, reducing the likelihood of failure. To validate the theoretical predictions, capacity retention experiments are conducted on undoped and Al‐doped micro‐sized silicon samples. In conclusion, the results demonstrate significantly reduced capacity fading in the doped sample, corroborating the theoretical framework and showcasing the potential of aluminum doping for improved Li‐ion battery performance.

25 ENERGY STORAGE