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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗
DOE OSTI2020

Surface chemical trapping of optical cycling centers

Quantum information processors based on trapped atoms utilize laser-induced optical cycling transitions for state preparation and measurement. These transitions consist of an electronic excitation from the ground to an excited state and a decay back to the initial ground state, associated with a photon emission. While this technique has been used primarily with atoms, it has also recently been shown to work for some divalent metal hydroxides ( e.g. SrOH) and alkoxides ( e.g. SrOCH 3 ). Additionally, this extension to molecules is possible because these molecules feature nearly isolated, atomic-like ground and first-excited electronic states centered on the radical metal atom. We theoretically investigate the extension of this idea to a larger scale by growing the alkyl group, R, beyond the initial methyl group, CH 3 , while preserving the isolated and highly vertical character of the electronic excitation on the radical metal atom, M. Theory suggests that in the limit as the size of the ligand carbon chain increases, it can be considered a functionalized diamond (or cubic boron nitride) surface. Several requirements must be observed for the cycling centers to function when bound to the surface. First, the surface must have a significant band gap that fully encapsulates both the ground and excited states of the cycling center. Second, while the surface lattice imposes strict limits on the achievable spacing between the SrO– groups, at high coverage, SrO– centers can interact, and show geometric changes and/or electronic state mixing. We show that the coverage of the diamond surface with SrO– cycling centers needs to be significantly sub-monolayer for the functionality of the cycling center to be preserved. Having the lattice-imposed spatial control of SrO– placements will allow nanometer-scale proximity between qubits and will eliminate the need for atom traps for localized cycling emitters. Our results also imply that a functionalization could be done on a scanning microscope tip for local quantum sensing or on photonic structures for optically-mediated quantum information processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Photophysical Properties and Electronic Structure of Hydroporphyrin Dyads Exhibiting Strong Through-Space and Through-Bond Electronic Interactions

Electronic interactions between tetrapyrroles are utilized in natural photosynthetic systems to tune the light-harvesting and energy/charge-transfer processes in these assemblies. Such interactions also can be employed to tailor the electronic properties of tetrapyrrolic dyads and larger arrays for use in materials science and biomedical research. Here we have utilized static and time-resolved optical spectroscopy to characterize the optical absorption and emission properties of a set of chlorin and bacteriochlorin dyads with varied degrees of through-bond (TB) and through-space (TS) interactions between the constituent macrocycles. The dyads consist of two chlorins or two bacteriochlorins joined by a linker that utilizes a triple-double-triple bond (enediyne) motif in which the double bond portion is a ester-substituted ethylene or o-phenylene unit. The photophysical studies are coupled with density functional theory (DFT) calculations to probe the ground-state molecular orbital (MO) characteristics of the dyads and time-dependent calculations (TDDFT) to elucidate excited-state properties. The latter include electronic characteristics of the singlet excited state manifold and the absorption transitions to these states from the electronic ground state. Comparison of the MO and calculated spectral properties of each dyad with the linker present versus disrupted (by eliminating the double-bond portion) gives insight into the relative contributions of TB versus TS interactions to the electronic properties of the dyads. The results show that the TB and TS contributions are additive (constructively interfere), which is not always the case for molecular dyads. Most of the dyads have shorter lifetimes of the lowest singlet excited state compared to the parent monomer, which derives from increased S 1 → S 0 internal conversion. The enhancement is greater for the dyads in benzonitrile than in toluene. Furthermore, the studies provide insights into the nature of the electronic interactions between the constituents in the tetrapyrrole arrays and how these interactions dictate the spectral properties and excited-state decay characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

NH 4 OH Looping with Membrane CO 2 Absorber and Distributed Stripper for Enhanced Algae Growth

The University of Kentucky Center for Applied Energy (UK CAER) has devised a unique, integrated CO2 capture and utilization technology. CO2 from coal-fired power generation flue gas is first captured at half the operating cost of a typical aqueous CO2 capture system (CCS), distributed in an aqueous stream and then fixed by algae in bioreactors where the algae production is increased by 50% over that with a typical intermittent nutrient feeding system. Lower CCS operating cost is achieved by eliminating the flue gas pretreatment step for cooling and SO2 removal, eliminating steam extraction from the power generation steam cycle for solvent regeneration, and eliminating CO2 compression. Higher algae production is achieved by continuous, just-in-time nutrient feed to the bioreactors directly from a distributed solvent regenerator, which maintains the bioreactor pH for optimum growth. The process starts with a uniquely configured membrane absorber, where the flue gas is indirectly contacted with an ammonium hydroxide (NH4OH) solvent. Dissolved NH3 is attractive for both CO2 capture and as an algae nutrient. For CO2 capture it is inexpensive, has a low regeneration energy, is thermally- and oxidatively-stable and has a viscosity near that of water, which makes is easy to transport. Numerous studies have shown that the scrubbing capacity of NH3 is approximately 0.9-1.2 kg of CO2/kg of NH3, with a CO2 removal efficiency of ~99% and half the solvent regeneration energy than that of 30 wt% MEA[1, 2, 3]. NH3 is attractive as an algae nutrient due to its low cost. The rich NH4OH solvent is pumped to a set of distributed regenerators which are co-located with the algae bioreactors. Solvent pumping, transport and distribution reduces the balance of plant (BOP) cost compared to a typical aqueous CCS related to the flue gas duct and boost fan required to transport the flue gas. The energy required for the distributed solvent regeneration is supplied by solar-thermal panels eliminating the need for steam extraction from the power generation steam cycle. After solvent regeneration, the product stream contains both the CO2 captured from the flue gas and volatized NH3 from the solvent. This product stream is fed directly to the bioreactors, eliminating the need for compression of the CO2 stream. The relative amounts of CO2 and NH3 in the product stream are adjusted and controlled by a controlling the regeneration conditions (pressure and temperature). The continuous feed of the right ratio of nutrients overcomes the typical inhibition of algae growth resulting from frequent pH swings in the bioreactor due to unbalanced (intermittent) feeding systems for CO2 and N. Also, because the regenerators will operate at pressure and be located in close proximity to the bioreactors, there is no worry about pressure drop when sparging the gas into the algae. Sparging produces small bubbles which is beneficial for mass transfer efficiency. One known challenge when using an NH4OH solvent is high NH3 emission. Hydrophobic membranes are used for CO2 capture using an aqueous NH3 solution[4, 5] without the direct contact between flue gas and aqueous solution. Additionally, UK CAER CO2 capture and utilization process manages NH3 slip in three extra measures. First, NH3 slip is minimized by working with minimal species partial pressure, which is proportional to the concentration in the liquid. Hence, lowering the capture solvent concentration will lower the NH3 partial pressure. Second, UK CAER’s previous work has demonstrated that the addition of Zn2+ into NH3 solutions to chelate the NH3 can reduce NH3 volatility. Third, the configuration of the membrane CO2 absorber utilizes condensed water from the flue gas to continually wash the gas-side of the membrane to reduce fouling and recapture NH3 slip. Additional details about the UK CAER unique, integrated CO2 capture and utilization technology will be presented along with technology development plans. Diao, N., Q. Li, and Z. Fang. 2004. Heat transfer in ground heat exchangers with groundwater advection. International Journal of Thermal Sciences. 43: 1203-1211, He, Q., M. Chen, L. Meng, K. Liu, and W. Pan. 2004. Study on Carbon Dioxide Removal from Flue Gas by Absorption of Aqueous Ammonia. Western Kentucky University. Yeh, A.C., and H. Bai. 1999. Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse gas emissions. The Science of the Total Environment. 228: 121-133, Villeneuve, K., D. Roizard, J.C. Remigy, M. Iacono, and S. Rode. 2018. CO2 capture by aqueous ammonia with hollow fiber membrane contactors: Gas phase reactions and performance stability. Separation and Purification Technology, 199: 189-197, Toro Molina, C., and C. Bouallou. 2016. Carbon dioxide absorption by ammonia intensified with membrane contactors. Clean Techn Environ Policy 18, 2133–2146 (2016)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Optical-Gating of Spin-based Quantum States (Final Report)

This project developed a generalizable strategy for optical control of spin-based quantum states through the Photoisomerization-Induced Spin–Charge Excited State (PISCES) process, in which a photochromic spirooxazine ligand bound to an electronically bistable metal complex enables reversible, room-temperature optical switching of spin states in both dilute matrices and the solid state. A multidisciplinary team integrated synthesis, spectroscopy, theory, and surface science to establish design principles for opto-spintronic quantum materials. Systematic structure–property studies across four spirooxazine series revealed that donor–π–acceptor interactions govern thermal isomerization, which proceeds via a rotational pathway. Pulsed EPR measurements demonstrated millisecond-scale coherence times in cobalt-dioxolene-spirooxazine complexes, establishing their promise as optically addressable molecular qubits; the approach was extended to Cu(II), Ni(II), and lanthanide complexes, including optical modulation of zero-field splittings and clock transitions. Two-dimensional IR spectroscopy resolved picosecond ground-state population exchange dynamics, while ab initio calculations elucidated photoisomerization mechanisms and parametrized Hamiltonians for spin relaxation and decoherence. Toward device integration, the team fabricated 2D polymer scaffolds for covalent qubit organization, developed tip-enhanced Raman imaging of molecular monolayers, and demonstrated optical gating of gate voltage in spirooxazine-graphene field-effect transistors. The project produced numerous publications, dissertations, and presentations, and trained over 30 researchers.

2D polymers↗
DOE OSTI2021

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗
DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2026

Direct observation of the superallowed α-decay of 104 Te

The radioactivity of the α particle is among the most compelling evidence for the existence of cluster structures in atomic nuclei. During the decay process, a pre-existing α particle tunnels through the potential barrier formed by the residual nucleus1,2. The degree of preformation of the α particle, a strongly bound system of two protons and two neutrons, is extracted from the data by dividing the α-decay probability by the barrier penetrability for a given particle energy. The preformation probability changes rapidly near nuclear shell closures, which is direct evidence that clustering is connected to nuclear structure3. Enhanced preformation was observed in the lightest α-particle emitters, spherical tellurium and xenon isotopes decaying to magic isotopes of tin. Here we show the most extreme case of α-particle preformation from the measurement of the decay of tellurium-104 (104Te). With a half-life of , 104Te is the fastest ground-state α-emitting nucleus known so far. The deduced preformation demonstrates that the enhancement is greater for 104Te than for any other nucleus. One nuclear model that can explain our observation postulates that the α particle can exist only in the low-nuclear-matter-density regions on the surface of the nucleus. The uniquely high preformation for 104Te is attributed to its relation to doubly magic tin-100 (100Sn), creating conditions conducive to form an α particle.

Cox, Ian↗
DOE OSTI2024

Diffusion quantum Monte Carlo approach to the polaritonic ground state

Making and using polaritonic states (i.e., hybrid electron-photon states) for chemical applications has recently become one of the most prominent and active fields that connects the communities of chemistry and quantum optics. Modeling of such polaritonic phenomena using ab initio approaches calls for new methodologies, leading to the reinvention of many commonly used electronic structure methods, such as Hartree-Fock, density functional, and coupled cluster theories. Here in this work, we explore the formally exact diffusion quantum Monte Carlo approach to obtain numerical solutions to the polaritonic ground state during the dissociation of the H 2 molecular system. Here, we examine various electron-nuclear-photon properties throughout the dissociation, such as changes to the minimum of the cavity Born-Oppenheimer surface, the localization of the electronic wave function, and the average mode occupation. Finally, we directly compare our results to that obtained with state-of-the-art, yet approximate, polaritonic coupled cluster approaches.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Study of alpha-resonances in ¹¹B via the ⁷Li(⁷Li, t ) reaction

The near-threshold proton resonance in ¹¹B, recently identified and characterized through independent experi-ments, plays a crucial role in understanding the unexpectedly high decay branch observed in the β-delayed proton emission (β− p) from the neutron halo nucleus ¹¹Be. Critical to interpreting this process is the determination of whether or not this state has any significant α-decay width (rα). A coincidence measurement was conducted to study the alpha-transfer reaction ⁷Li(⁷Li, t ) ¹¹B∗ → ⁷Li +α employing the Super-Enge Split Pole Spectrograph coupled with a silicon detector at Florida State University. This experiment aimed to investigate the structure of α resonances in ¹¹B in the Eₑₓ = 9.0 MeV–14 MeV energy region. In particular, to explore and constrain the α-decay branch of the near-threshold proton resonance at Eₑₓ = 11.44 MeV. No significant α-decay strength was observed from this state. Additionally, the experimental results provided insights into the state at Eₑₓ = 12.55 MeV, previously proposed as the T = 3/2 isobaric analog state of the ¹¹Be ground state. The observed decay pattern, dominated by α + ⁷Li, suggests a strong T = 1/2 component, indicating the need for further experimental measurements.

Lopez-Saavedra, E.↗
DOE OSTI2023

Impact of Erbium Doping in the Structural and Magnetic Properties of the Anisotropic and Frustrated SrYb 2 O 4 Antiferromagnet

We present a systematic study of the structural and magnetic properties of a series of powder samples of SrYb 2-x Er x O 4 with different Yb/Er concentrations. Magnetometry and neutron diffraction have been used to study the magnetic ground states of the compound series, while inelastic neutron scattering was used to investigate the crystal field excitations for a chosen concentration. These results show that the crystal structure remains the same for all compositions, while the lattice parameters increase linearly with the Er content. All compounds showed some type of magnetic transition below 1 K, however, both the magnetic structure and nature of the phase transition vary throughout the series. The samples present a non-collinear magnetic structure with the moments lying on the ab plane for low Er content. For high Er content, the magnetic structure is collinear with the moments aligned along the c-axis. A critical concentration is found where there is a bifurcation between zero-field and field-cooled magnetic susceptibility. This irreversible process could be due to the random mixture of single-ion magnetic anisotropies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Updates to a Preliminary Probabilistic Performance Assessment Model for Radiological and Chemical Contamination at the West Valley Site, New York - 20420

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351-ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States at the WNYNSC. NFS built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg (640 metric tons) of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations halted in 1972 and never restarted, leaving behind radioactive and chemical wastes. The U.S. Department of Energy (DOE) was required to complete certain waste management activities under the West Valley Demonstration Project (WVDP) Act of 1980 including decommissioning of WVDP facilities. As collaborating agencies, NYSERDA and the DOE are tasked with making decisions about decommissioning and risk reduction for the West Valley Site. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) model to assist the agencies in their decision making process for decommissioning the WVDP and WNYNSC. One important tool that is needed in order to inform the decision-making process is a science-based model of the West Valley Site that evaluates potential future consequences for human health and the environment. This forms the core of the spatial domain of the West Valley PPA Model. The PPA Model, developed using the GoldSim system modeling software, is a tool intended to provide support for decision making that evaluates uncertainty, in a manner that is transparent, defensible, and robust. The PPA Model includes contaminant transport and health effects components, and is organized around geographically-grouped contaminated facilities. These include the waste disposal areas licensed by the U.S. Nuclear Regulatory Commission and the State of New York, a waste tank farm for storage of high level radioactive waste resulting from reprocessing operations, and several areas contaminated with radioactive and chemical constituents. The PPA Model evaluates contaminant transport from these sources to points of exposure across the site and into receiving surface waters and sediments. Hypothetical people and wildlife could be exposed to contamination at these locations, and the effects of these exposures are evaluated. Contaminant transport processes to be evaluated in the PPA Model include groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The evaluation of exposures to people in this preliminary model is limited to a resident farmer scenario, and ecological assessment is performed at the level of a screening analysis. The results of these preliminary evaluations inform future model developments. PPA Model results are subjected to sensitivity analysis in order to determine those pathways and parameters that are most significant in influencing the results. This information allows analysts and decision makers to focus on those aspects of Site behavior and processes. With this information, the decision makers can drive informed, defensible decisions regarding decommissioning of the Site. This paper includes an update of the information presented at WM2019 [1]. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Elucidating Processes Controlling Arctic Atmospheric Aerosol Sources, Aging, and Mixing States (Final Report)

Atmospheric aerosols play critical roles in the Earth’s energy budget, directly by scattering or absorbing solar and terrestrial radiation and indirectly by serving as seeds (nuclei) for cloud droplet and ice crystal formation and by depositing on snow and ice surface, thereby changing the surface albedo. These effects are dependent on aerosol particle size and chemical composition and impact the hydrological cycle as well. This project provided single-particle size and chemical composition measurements across the entire annual cycle in the high Arctic and in the Alaskan Arctic during fall – winter, addressing the most significant gaps in Arctic aerosol observational data. These needs were based on recent rapid sea ice loss across the entire Arctic, as well as the major annual delays in sea ice freeze-up during fall in the Chukchi Sea and increased wintertime sea ice fracturing in the Beaufort Sea, both off the North Slope of Alaska. Two DOE Atmospheric Radiation Measurement (ARM) field campaigns were conducted for atmospheric aerosol sampling. The Aerosols during the Polar Utqiagvik Night (APUN – ‘snow on ground’ in Iñupiaq) ARM field campaign at Utqagivik, Alaska was conducted from Oct. 28 – Dec. 22, 2018. Aerosol sizing instrumentation and a single-particle mass spectrometer were successfully deployed for size-resolved number concentration measurements and measurements of individual particle size and chemical composition, respectively. These results show the influence of locally-produced sea spray aerosol, with high cloud-forming potential, due to delayed sea ice freeze-up in the fall. During the 2019‐2020 international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, daily atmospheric aerosol particles were collected aboard the German icebreaker Polarstern in the Central Arctic from Nov. 2019 – Oct. 2020. Sea salt aerosol and marine organics were observed year-round during MOSAiC with varying morphologies and sources. These findings are important because most Arctic models do not include a sea spray aerosol source, despite this source increasing with declining sea ice extent. In addition to collecting new samples and data, this project also conducted further analysis of previously collected single-particle chemical composition measurements within the North Slope of Alaska oil fields and at Utqiaġvik, AK, during Aug. – Sep. 2015 and 2016 field campaigns. This work resulted in the discovery of chemical reactions of oil field combustion emissions occurring within fog droplets across the North Slope of Alaska and forming secondary aerosol, showing the impact of Arctic oil field emissions beyond black carbon aerosol and greenhouse gases. In addition, the distribution of chemical species across the aerosol population within the oil fields was quantified, using these data and a previously development framework. We also presented the first ambient evidence of the collision of two atmospheric particles resulting in formation of an organic-coated ammonium sulfate particle of marine origin, which has implications for cloud formation with declining sea ice extent. Overall, this project has elucidated connections between seawater biogeochemistry, resource extraction activities, atmospheric composition, clouds, and the energy budget of the Arctic region. The results of this project are expected to improve weather and sea ice forecasting for security and development in the Arctic and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Seismoacoustic Signatures Observed During a Long-Term Deployment of Infrasound Sensors at the Nevada National Security Site

Earthquakes have repeatedly been shown to produce inaudible acoustic signals (<20 Hz), otherwise known as infrasound. These signals can propagate hundreds to thousands of kilometers and still be detected by ground-based infrasound arrays depending on the source strength, distance between source and receiver, and atmospheric conditions. Another type of signal arrival at infrasound arrays is the seismic induced motion of the sensor itself, or ground-motion-induced sensor noise. Measured acoustic and seismic waves produced by earthquakes can provide insight into properties of the earthquake such as magnitude, depth, and focal mechanism, as well as information about the local lithology and atmospheric conditions. Large earthquakes that produce strong acoustic signals detected at distances greater than 100 km are the most commonly studied; however, more recent studies have found that smaller magnitude earthquakes ($M$ w <2.0) can be detected at short ranges. In that vein, this study will investigate the ability for a long-term deployment of infrasound sensors (deployed as part of the Source Physics Experiments [SPE] from 2014 to 2020) to detect both seismic and infrasonic signals from earthquakes at local ranges (<50 km). Methods used include a combination of spectral analysis and automated array processing, supported by U.S. Geological Survey earthquake bulletins. Further, this investigation revealed no clear acoustic detections for short range earthquakes. However, secondary infrasound from an $M$ w 7.1 earthquake over 200 km away was detected. Important insights were also made regarding the performance of the SPE networks including detections of other acoustic sources such as bolides and rocket launches. Finally, evaluation of the infrasound arrays is performed to provide insight into optimal deployments for targeting earthquake infrasound.

58 GEOSCIENCES↗
DOE OSTI2026

In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Seward Peninsula, Alaska, 2022

The in-situ soil moisture and thaw depth measurements provided in this dataset were collected coincident with airborne overflights of L-band synthetic aperture radar (SAR) instruments at the Teller, Kougarok, and Council study sites on the Seward Peninsula, Alaska. Overflights occurred on August 19, 2022. Soil moisture data at Teller and Kougarok was collected on August 19, and at Council on August 20. Thaw depth, soil pits, and any additional measurements were recorded on August 20 and 21. Field measurements and flights were conducted during the summer of 2022 as a collaboration between the National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE) Project’s Airborne SAR Campaign and the Next-Generation Ecosystem Experiments (NGEE) Arctic Project. This dataset includes a data file (*.csv), a data dictionary (*_dd.csv) and a file-level metadata (*_flmd.csv). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

EARTH SCIENCE > LAND SURFACE > FROZEN GROUND↗
DOE OSTI2024

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗
DOE OSTI2025

Search for excited tau leptons in the ττγ final state in proton-proton collisions at $\sqrt{\text{s}}$ = 13 TeV

Results are presented for a test of the compositeness of the heaviest charged lepton, τ, using data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC. The data were collected in 2016–2018 and correspond to an integrated luminosity of 138 fb −1 . This analysis searches for tau lepton pair production in which one of the tau leptons is produced in an excited state and decays to a ground state tau lepton and a photon. The event selection consists of two isolated tau lepton decay candidates and a high-energy photon. The mass of the excited tau lepton is reconstructed using the missing transverse momentum in the event, assuming the momentum of the neutrinos from each tau lepton decay are aligned with the visible decay products. No excess of events above the standard model background prediction is observed. This null result is used to set lower bounds on the excited tau lepton mass. For a compositeness scale Λ equal to the excited tau lepton mass, excited tau leptons with masses below 4700 GeV are excluded at 95% confidence level; for Λ = 10 TeV this exclusion is set at 2800 GeV. This is the first experimental result covering this production and decay process in the excited tau mass range above 175 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗