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At least 1,135 records · Page 63

Swamp Works Regolith Compaction Technologies

While the level of compaction below the lunar surface increases quickly after only a few cm of depth, in many cases during a construction mission there will be a need to excavate and transport regolith to a new location for cut-and-fill or horizontal construction of structures such as berms. In these cases to achieve high levels of bulk density, compaction must be per-formed. Additionally, in some cases surface technolo-gies such as systems that sinter/melt the surface may desire the maximum possible compaction at the sur-face to improve melting/heating performance and the final material strength properties. Kennedy Space Center’s (KSC) Swamp Works has developed two means of compaction, lunar and mar-tian compaction. Planetary Autonomous Compaction Technology (PACT) which is part of the Multifunction End Effector for Regolith Compaction Acquisition and Transfer (MEERCAT [1]) robotic arm end effector system’s capabilities and the Site Preparation Tooling for Operations on Mobility Platforms (STOMP [2]) vibratory roller compactor. PACT on MEERCAT has been demonstrated to a TRL 5 and STOMP to a TRL 4 in ambient testing. The results of PACT on MEERCAT and STOMP testing will be shared with results for various simulants including BP-1, ICN-LHT-1G (aka CSM-LHT-1G), RDW-LHT-1GH (a simulant developed for the Mason Tipping Point to match characteristics of ICN-LHT-1G), and Exolith LHS-1E. This will also include discus-sions on methods used to verify relative density before and after compaction and means to verify density effects below depth. To calculate relative density, maximum and minimum densities for simulants were taken from literature [3] [4] [5] and additional lab test-ing (publication in work).

vibration↗

Guarded Hot Cylinder Apparatus for Characterization of Thermal Insulation Systems and Materials at Liquid Hydrogen Temperatures

As interest in liquid hydrogen (LH2) continues to grow within the energy and mobility sectors, so does the demand for testing capabilities at deep cryogenics temperatures. However, cost-, complexity-, and safety-related challenges associated with handling LH2 effectively limit the landscape of possible options. As an alternative, LH2 temperatures can be accessed via a helium-based cryogenic refrigerator, or “cryocooler”. Recently, NASA and its partners CB&I and Shell began the development of a cryocooler-based calorimeter to characterize the thermal performance of insulations and other materials down to 20 K. Deemed the Guarded Hot Cylinder (GHC), the apparatus utilizes a small vacuum chamber in conjunction with a GM cryocooler and trim heater to control the cold boundary temperature. A sealed, cylindrical copper cup bolts to the cryocooler and houses the material specimen, with an internal, cylindrical test heater assembly to maintain the warm boundary. The steady-state heat load, traveling radially through the specimen, is measured via the electrical input power to the test heater and then used to evaluate the material’s absolute thermal performance. Initial checkout and validation of the GHC using a common bulk-fill insulation material showed close agreement with published data from standardized LN2 boiloff calorimetry testing. The instrument is now considered a lab standard, with the goal of incorporating it into the ASTM C1774 standard in the future, and it is in continuous use, examining insulation materials for next-generation LH2 applications.

Swanger, Adam (ORCID:000000021487592X)↗

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty [Brochure]

The four priority research directions outlined in this brochure represent a cohesive vision for advancing the science of inverse problems for complex systems under uncertainty. Together, they address the critical challenges of: discovering, exploiting, and preserving physical and problem structure; overcoming model limitations; integrating disparate, multimodal, and/or dynamic data; and tailoring the solution of inverse problems to downstream tasks. While each PRD focuses on a distinct aspect of inverse-problem research, their interconnected nature highlights the importance of a holistic approach that leverages progress across all areas to achieve transformative solutions. This agenda calls for research across mathematics, statistics, and computer science disciplines, which are guided and complemented by rapid advances in artificial intelligence, high-performance computing, and experimental facilities, to unlock new capabilities, maximize scientific impact, and meet the growing demands of inverse problems that arise across applications that are critical to DOE's mission.

97 MATHEMATICS AND COMPUTING↗

Fire, dust, air and water: Improving aerosol biogeochemistry interactions in ACME. Final report

Aerosol-biogeochemistry interactions will have important consequences for human health, ecosystem services, and climate feedbacks over the next several decades. In this proposal we seek to link how human activities on land, including direct industrial emissions and landscape fires, impact the atmosphere and the biogeochemistry of the ocean and land. Our overall goal was to complement existing work at DOE labs to improve the capability and performance of the E3SM model in short-term, high-resolution projections of climate. Projections of ocean uptake of anthropogenic carbon are highly dependent on the details of the ocean physical and biogeochemistry parameterizations. Potentially equally important are the estimates of increases in iron and soluble nitrogen deposition in aerosols to the open ocean, but there are substantial uncertainties in these feedbacks. The E3SM land model simulates natural and anthropogenic fires, but improvement is needed to more accurately simulate fire responses to climate variability as well as fire contributions to terrestrial climate feedbacks. This proposal addressed four of the six priorities within the ACME/E3SM call by improving the representation of fire, industrial combustion sources, and desert dust and adding iron and soluble iron to the atmospheric chemistry (1). Our work focused on improving ocean biogeochemistry and the response of the oceans to anthropogenic atmospheric iron and nitrogen (3). We also improved the representation of land disturbance on fires and fire mediated carbon cycle feedbacks in the land model (4). Finally we had planned to couple the land, atmosphere and ocean biogeochemical systems (6) and explore how this coupling changes the feedbacks in the climate system. Our work under this proposal was separated into the following 5 tasks: i) improve representation of fire dynamics in both boreal and tropical ecosystems, ii) improve estimates of industrial emissions of iron and phosphorus, iii) improve representation of atmospheric iron, phosphorus and nitrogen transport, chemistry and deposition, iv) improve representation of iron, phosphorus and nitrogen deposition impacts on ocean biogeochemistry, and v) couple emissions into atmosphere, to deposition onto land and ocean biogeochemistry. For all 5 tasks, we conducted offline experiments of the historical period to enable comparison with available aerosol and land surface observations. We had planned to conduct fully coupled simulations, however, these will be conducted as part of the coupling in version 3 and 4 of the E3SM model, and thus have not been completed.

54 ENVIRONMENTAL SCIENCES↗

NASA Tech Briefs, February 2012

This issue contains the following briefs: (1) Optical Comb from a Whispering Gallery Mode Resonator for Spectroscopy and Astronomy Instruments Calibration (2) Real-Time Flight Envelope Monitoring System (3) Nemesis Autonomous Test System (4) Mirror Metrology Using Nano-Probe Supports (5) Automated Lab-on-a-Chip Electrophoresis System (6) Techniques for Down-Sampling a Measured Surface Height Map for Model Validation (7) Multi-Component, Multi-Point Interferometric Rayleigh/Mie Doppler Velocimeter (8) Frequency to Voltage Converter Analog Front-End Prototype (9) Dust-Tolerant Intelligent Electrical Connection System (10) Gigabit Ethernet Asynchronous Clock Compensation FIFO (11) High-Speed, Multi-Channel Serial ADC LVDS Interface for Xilinx Virtex-5 FPGA (12) Glovebox for GeoLab Subsystem in HDU1-PEM (13) Modified Process Reduces Porosity when Soldering in Reduced Gravity Environments (14) Use of Functionalized Carbon Nanotubes for Covalent Attachment of Nanotubes to Silicon (15) Flexible Plug Repair for Shuttle Wing Leading Edge (16) Three Dimensionally Interlinked, Dense, Solid Form of Single-Walled CNT Ropes (17) Axel Robotic Platform for Crater and Extreme Terrain Exploration (18) Site Tamper and Material Plow Tool - STAMP (19) Magnetic Interface for Segmented Mirror Assembly (20) Transpiration-Cooled Spacecraft-Insulation-Repair Fasteners (21) Fluorescence-Based Sensor for Monitoring Activation of Lunar Dust (22) Aperture Ion Source (23) Virtual Ultrasound Guidance for Inexperienced Operators (24) Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time (25) Interactive Schematic Integration Within the Propellant System Modeling Environment (26) Magnetic and Electric Field Polarizations of Oblique Magnetospheric Chorus Waves (27) Variable Sampling Mapping.

Source record↗

Structural-Thermal-Optical-Performance (STOP) Model Development and Analysis of a Field-widened Michelson Interferometer

An integrated Structural-Thermal-Optical-Performance (STOP) model was developed for a field-widened Michelson interferometer which is being built and tested for the High Spectral Resolution Lidar (HSRL) project at NASA Langley Research Center (LaRC). The performance of the interferometer is highly sensitive to thermal expansion, changes in refractive index with temperature, temperature gradients, and deformation due to mounting stresses. Hand calculations can only predict system performance for uniform temperature changes, under the assumption that coefficient of thermal expansion (CTE) mismatch effects are negligible. An integrated STOP model was developed to investigate the effects of design modifications on the performance of the interferometer in detail, including CTE mismatch, and other three- dimensional effects. The model will be used to improve the design for a future spaceflight version of the interferometer. The STOP model was developed using the Comet SimApp'TM' Authoring Workspace which performs automated integration between Pro-Engineer®, Thermal Desktop®, MSC Nastran'TM', SigFit'TM', Code V'TM', and MATLAB®. This is the first flight project for which LaRC has utilized Comet, and it allows a larger trade space to be studied in a shorter time than would be possible in a traditional STOP analysis. This paper describes the development of the STOP model, presents a comparison of STOP results for simple cases with hand calculations, and presents results of the correlation effort to bench-top testing of the interferometer. A trade study conducted with the STOP model which demonstrates a few simple design changes that can improve the performance seen in the lab is also presented.

Scola, Salvatore J.↗

Revisiting the Role of Entropy for Charge Separation in 1D Pi-Conjugated Semiconductors

Free carrier generation in organic donor/acceptor heterojunctions and redox-doped organic semiconductors is poorly understood, since assumed tight electron-hole binding conflicts with observed high free carrier yields. Cornerstone analyses that have guided the field for over 15 years predict that entropy can stabilize free charges in 2D and 3D pi-conjugated semiconductors but not in 1D systems. Here, the impact of entropy on charge generation in 1D pi-conjugated semiconductors is revisited by exploiting a greatly simplified system where enthalpy considerations alone should not allow for free charge generation. Noncontact solution-phase microwave conductivity is used to investigate the carrier density-dependent conductivity and dielectric constant in isolated chemically doped semiconducting single-walled carbon nanotubes in a low-dielectric solvent. Dopant chemical structure dramatically influences the carrier density-dependent complex conductivity, with bulky dopants facilitating carrier escape even at carrier densities below one carrier per nanotube. Three distinct numerical calculations show that entropic stabilization dramatically lowers the Gibbs energy barrier for free charge generation, explaining the high yield of free carriers, even in 1D. This renewed understanding of entropy's role in carrier generation has important implications for designing organic electronic devices-such as solar cells and thermoelectric energy harvesters-for enhanced carrier yield, conductivity, and performance.

36 MATERIALS SCIENCE↗

Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data

Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.

54 ENVIRONMENTAL SCIENCES↗

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

Evolvable Cryogenics (ECRYO) Pressure Transducer Calibration Test

This paper provides a summary of the findings of recent activities conducted by Marshall Space Flight Center's (MSFC) In-Space Propulsion Branch and MSFC's Metrology and Calibration Lab to assess the performance of current "state of the art" pressure transducers for use in long duration storage and transfer of cryogenic propellants. A brief historical narrative in this paper describes the Evolvable Cryogenics program and the relevance of these activities to the program. This paper also provides a review of three separate test activities performed throughout this effort, including: (1) the calibration of several pressure transducer designs in a liquid nitrogen cryogenic environmental chamber, (2) the calibration of a pressure transducer in a liquid helium Dewar, and (3) the calibration of several pressure transducers at temperatures ranging from 20 to 70 degrees Kelvin (K) using a "cryostat" environmental chamber. These three separate test activities allowed for study of the sensors along a temperature range from 4 to 300 K. The combined data shows that both the slope and intercept of the sensor's calibration curve vary as a function of temperature. This homogeneous function is contrary to the linearly decreasing relationship assumed at the start of this investigation. Consequently, the data demonstrates the need for lookup tables to change the slope and intercept used by any data acquisition system. This ultimately would allow for more accurate pressure measurements at the desired temperature range. This paper concludes with a review of a request for information (RFI) survey conducted amongst different suppliers to determine the availability of current "state of the art" flight-qualified pressure transducers. The survey identifies requirements that are most difficult for the suppliers to meet, most notably the capability to validate the sensor's performance at temperatures below 70 K.

Diaz, Carlos E., Jr.↗

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗

Blueprint for DOE Quantum Supercomputing: Ensuring U.S. Leadership in the Quantum Decade

Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.

97 MATHEMATICS AND COMPUTING↗

Magneto-optical study of Nb thin films for superconducting qubits

Among the recognized sources of decoherence in superconducting qubits, the spatial inhomogeneity of the superconducting state and the possible presence of magnetic-flux vortices remain comparatively underexplored. Niobium is commonly used as a structural material in transmon qubits that host Josephson junctions, and excess dissipation anywhere in the transmon can become a bottleneck that limits overall quantum performance. The metal/substrate interfacial layer may simultaneously host pair-breaking loss channels (e.g., two-level systems, TLS) and control thermal transport, thereby affecting dissipation and temperature stability. Here, we use quantitative magneto-optical imaging of the magnetic-flux distribution to characterize the homogeneity of the superconducting state and the critical current density, $j_{c}$, in niobium films fabricated under different sputtering conditions. The imaging reveals distinct flux-penetration regimes, ranging from a nearly ideal Bean critical state to strongly nonuniform thermo-magnetic dendritic avalanches. By fitting the measured magnetic-induction profiles, we extract $j_{c}$ and correlate it with film physical properties and with measured qubit internal quality factors. Our results indicate that the Nb/Si interlayer can be a significant contributor to decoherence and should be considered an important factor that must be optimized.

Datta, Amlan [Ames Lab; Iowa State U.]↗

Deep-learning-based domain adaptation for cavity fault prediction at Jefferson Laboratory

Superconducting radio-frequency (SRF) cavities are the core components of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab, providing high-power electron beams for nuclear physics experiments. The facility comprises 418 SRF cavities, and any fault in these cavities can lead to interruptions in the electron beam supply. Cavity faults are the leading cause of beam trips in CEBAF. Predicting and mitigating those faults before onset can help maintain normal operation. Existing models face challenges in distinguishing between normal and fault signals when changes occur in the underlying time-series data, from changes in control software, operational parameters, or the environment. This work proposes a deep learning domain adaptation model that leverages transfer learning to address fault prediction challenges by improving accuracy. The model is trained and fine-tuned using a dataset collected for faulty and normal operation using a data acquisition system in CEBAF. Our deep learning-based domain adaptation model achieves a prediction accuracy of 89.61% of the fault and normal signals. The developed model effectively predicts normal running signals compared to the baseline approach without domain adaptation. This capacity is essential for the fault prediction task in the CEBAF because of heavily imbalanced data containing vast amounts of normal signals. The model performs well for predicting faults several hundred milliseconds before the fault onset compared to other models where no adaptation is applied. Incorporating deep learning-based domain adaptation techniques will significantly improve the fault prediction performance.

Rahman, Md Monibor [Old Dominion Univ., Norfolk, V↗

NASA’s Orbital Debris JAO/ES-MCAT Optical Telescope Facility on Ascension Island

The NASA Orbital Debris Program Office has a long-standing optical program begun over three and a half decades ago in 1984, designed to observe the Earth-orbiting environment with optical telescopes. Photometrically calibrated optical data provides a statistical sample for input to NASA models of the debris population for understanding the current and future debris environment around the Earth. Tracked objects and orbits allow for analysis of break-up events. Both known (correlated target in the SSN catalogue, or CT) and unknown (uncorrelated target, or UCT) objects are of interest to better understand how to protect current spacecraft and design more robust future operational satellites, and advise on how policies and practices can lead to protecting the environment itself for future generations. In 2015, a joint NASA JSC – Air Force Research Labs (AFRL) project culminated in the installation of the 1.3-meter Eugene Stansbery Meter Class Autonomous Telescope, ES-MCAT (a.k.a. MCAT) on Ascension Island. This DFM Engineering designed telescope provides nearly five-times greater light-collecting power than its predecessor, the 0.6-m MODEST telescope, and faster tracking capabilities by both the telescope and the 7-m ObservaDome. This allows for all orbital regimes to be easily within reach, ranging from low Earth to geosynchronous orbits. Extensive testing and commissioning activities of this custom system led to successfully reaching Initial Operational Capability in 2018, and the facility is currently on track to reach Full Operational Capability. The John Africano Observatory (JAO) comprises the primary 1.3-m ES-MCAT facility, the adjacent tower platform with a 0.4-m telescope, a sophisticated suite of weather instruments, and custom software by Euclid Research for autonomously running the entire system, including monitoring the weather and hardware, tasking all components, and collecting, processing, and analyzing the data. The mission of JAO and MCAT will be discussed, including survey and tracking tasking, a full discussion of data calibration, and both optics and weather-dependent performance.

Lederer, S. M.↗

Re-establishment of Sandia National Labs super-critical carbon dioxide testing autoclave capability for exposure of metal alloys and polymers (Level 4 Milestone Report)

The sCO 2 system located in 916/160A, Sandia National Laboratories, CA, was constructed in 2014, for testing of materials in the presence of supercritical carbon dioxide (sCO 2 ) at high pressures (up to 3500 psi) and temperatures (up to 650°C). The basic design of the system consists of a thermally insulated IN625 autoclave, a high-pressure supercritical CO 2 compressor, autoclave heaters, temperature controllers, gas manifold, and temperature and pressure diagnostics. This system was modified in 2016 (sCO 2 compressor was removed) to enable corrosion studies with metal alloys in gaseous CO 2 at lower pressure (up to 300 psi) at 500°C. The capability was not used much afterwards until 2020, when preliminary tests using this capability (again without the supercritical CO 2 compressor) involved the exposure of fatigue and tensile specimens of HN 230 and 800H alloys to CO 2 gas for 168 hours in gaseous CO 2 . Using this capability, we finished experiments with low pressure (450 psi/ 3 MPa), high temperature (650°C) exposure of fatigue and tensile specimens of HN 230 and 800H alloys to CO 2 gas for 168 hours. The data from these experiments will be compared to that gathered from experiments performed in 2020 using the tube furnace and presented in a future report. It is to be noted that the tube furnace experiments ran 500-1500 hours, unlike the 168 hours of exposure in the recent experiment. This can help validate the use of the sCO 2 autoclave for both CO 2 and sCO 2 experiments.

36 MATERIALS SCIENCE↗

Data for: Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events

This dataset contains data and code associated with the paper Patel et al. "Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events".The coastal terrestrial-aquatic interface (TAI) is a highly dynamic system characterized by strong physical, chemical, and biological gradients. In particular, shifting soil redox conditions and consumption of terminal electron acceptors, due in part to dynamic hydrologic conditions, is a strong driver of carbon availability and transformations across TAIs. However, while redox dynamics are well described, our ability to quantitatively forecast rates of oxic to anoxic shifts in soils with different characteristics and inundation regimes is limited. We integrated field measurements, laboratory incubations, and model simulations to improve mechanistic understanding of oxygen consumption dynamics in coastal soils. Continuous in situ monitoring unexpectedly revealed that flooding caused temporary spikes in subsurface dissolved oxygen followed by rapid consumption in the wetlands. To further investigate these mechanisms in a controlled setting, we performed laboratory incubations using surface and subsurface soils from a TAI gradient (defined here as upland forest to transitional forest to wetland) in Western Lake Erie to measure oxygen consumption rates in TAI soils during flood events. In our experiments, wetland soils reached anoxia the fastest, in ∼ 9 h on average, whereas upland soils turned anoxic in ∼ 18 h. Subsurface upland soils did not turn anoxic even after two weeks of saturation in the lab, and their oxygen consumption patterns suggested carbon and/or nutrient limitation. These results are consistent with in-situ groundwater redox and oxygen measurements in the field, where wetland soils exhibited the highest rates of oxygen consumption along the TAI. Model simulations of oxygen consumption suggested that oxygen consumption had stronger abiotic controls in wetland soils but stronger biotic controls in upland soils, providing a useful framework for future incubation experiments. Microbial activity is a strong driver of oxygen consumption in TAI soils, although it is constrained by the availability of dissolved carbon in subsurface soils.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/COMPASS-DOE/cmps-time_to_anoxia (DOI: 10.5281/zenodo.10815374).

54 ENVIRONMENTAL SCIENCES↗

Dirac Magnon in Honeycomb Lattice Magnet NiTiO 3

We performed inelastic neutron scattering experiments on single-crystal samples of the honeycomb lattice magnet, ilmenite NiTiO 3 . Below the Néel temperature of 22 K, spin wave excitations with a band energy of 3.7 meV were observed. Further, the neutron energy spectra were well-reproduced by modeling the system as a ferromagnetic honeycomb lattice with antiferromagnetic interlayer coupling, using linear spin wave theory. Similar to another ilmenite CoTiO 3 , a crossing structure was observed at the K point, suggesting the presence of Dirac magnons in NiTiO 3 . Further calculations suggested the formation of Dirac nodal line.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗