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At least 775 records · Page 43

Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale

Abstract Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.

54 ENVIRONMENTAL SCIENCES↗

Carbon ablator areal density at fusion burn: Observations and trends at the National Ignition Facility

For inertial confinement fusion experiments, the pusher is composed of a high-density deuterium tritium cyrogenic fuel layer and an ablator, often made of carbon. In an ideal, no-mix implosion, increasing the areal density of the pusher transfers more pressure to the hot spot and increases the hot spot confinement time. There has been a lack of knowledge about the final compressed state of the ablator for implosions at the National Ignition Facility. 14 MeV fusion neutrons inelastically scattering on the remaining carbon ablator excites a nuclear metastable state that emits a prompt 4.4 MeV gamma ray. The gamma reaction history diagnostic data, when reduced by a new data analysis technique, can isolate and measure the carbon gamma rays, which are proportional to the areal density of the ablator during fusion burn. The trends over many National Ignition Facility campaigns show that the ablator areal density is weakly sensitive to the maximum shell velocity, the cold fuel radius, the ablator mass remaining, or the laser picket intensity. Controlled parameter scans reveal that, for specific campaigns, ablator compression has a strong dependence on laser coast time, high Z dopants, and the laser drive foot duration. Using a model of the compressed ablator density profile reveals that the greatest variation of the ablator areal density comes from its thickness, with highly compressed, thin layers having high areal density values. The compression and thickness of the ablator are other metrics that designers should understand to differentiate the types of capsule degradation and maximize the inertial confinement fusion performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cortical cell size regulates root metabolic cost

SUMMARY It has been hypothesized that vacuolar occupancy in mature root cortical parenchyma cells regulates root metabolic cost and thereby plant fitness under conditions of drought, suboptimal nutrient availability, and increased soil mechanical impedance. However, the mechanistic role of vacuoles in reducing root metabolic cost was unproven. Here we provide evidence to support this hypothesis. We first show that root cortical cell size is determined by both cortical cell diameter and cell length. Significant genotypic variation for both cortical cell diameter (~1.1‐ to 1.5‐fold) and cortical cell length (~ 1.3‐ to 7‐fold) was observed in maize and wheat. GWAS and QTL analyses indicate cortical cell diameter and length are heritable and under independent genetic control. We identify candidate genes for both phenes. Empirical results from isophenic lines contrasting for cortical cell diameter and length show that increased cell size, due to either diameter or length, is associated with reduced root respiration, nitrogen content, and phosphorus content.RootSlice, a functional‐structural model of root anatomy, predicts that an increased vacuolar: cytoplasmic ratio per unit cortical volume causes reduced root respiration and nutrient content. Ultrastructural imaging of cortical parenchyma cells with varying cortical diameter and cortical cell length confirms thein silicopredictions and shows that an increase in cell size is correlated with increased vacuolar volume and reduced cytoplasmic volume. Vacuolar occupancy and its relationship with cell size merits further investigation as a phene for improving crop adaptation to edaphic stress.

Plant Sciences↗

Evolution and Antigenic Advancement of N2 Neuraminidase of Swine Influenza A Viruses Circulating in the United States following Two Separate Introductions from Human Seasonal Viruses

Two separate introductions of human seasonal N2 neuraminidase genes were sustained in U.S. swine since 1998 (N2-98) and 2002 (N2-02). Herein, we characterized the antigenic evolution of the N2 of swine influenza A virus (IAV) across 2 decades following each introduction. The N2-98 and N2-02 expanded in genetic diversity, with two statistically supported monophyletic clades within each lineage. To assess antigenic drift in swine N2 following the human-to-swine spillover events, we generated a panel of swine N2 antisera against representative N2 and quantified the antigenic distance between wild-type viruses using enzyme-linked lectin assay and antigenic cartography. The antigenic distance between swine and human N2 was smallest between human N2 circulating at the time of each introduction and the archetypal swine N2. However, sustained circulation and evolution in swine of the two N2 lineages resulted in significant antigenic drift, and the N2-98 and N2-02 swine N2 lineages were antigenically distinct. Although intralineage antigenic diversity was observed, the magnitude of antigenic drift did not consistently correlate with the observed genetic differences. These data represent the first quantification of the antigenic diversity of neuraminidase of IAV in swine and demonstrated significant antigenic drift from contemporary human seasonal strains as well as antigenic variation among N2 detected in swine. These data suggest that antigenic mismatch may occur between circulating swine IAV and vaccine strains. Consequently, consideration of the diversity of N2 in swine IAV for vaccine selection may likely result in more effective control and aid public health initiatives for pandemic preparedness.

59 BASIC BIOLOGICAL SCIENCES↗

Feasibility Study for Disposal Control Rod Assemblies Using UNF-ST&DARDS As-Loaded Zion Dual Purpose Cask Models

This report documents an initial evaluation to support future use of disposal control rod assemblies (DCRAs) for post-closure criticality control in dual purpose canisters (DPCs). The work described herein is an extension of previous efforts performed by Walker using inputs generated by the Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNFST&DARDS) for the Zion site DPCs with as-loaded isotopic compositions. The results of this analysis demonstrate that there are multiple pathways to using DCRA for post-closure criticality control. Various configurations of DCRA material, diameter, number of rods per DCRA, and number and location of DCRAs within a DPC were shown to be effective in varying degrees for the set of DPCs analyzed by Walker. Because of the variations in DPC as-loaded isotopic compositions considered in an array of DCRA parametric sweeps, it can be concluded that a DPC-specific methodology is feasible (i.e., a one-size-fits-all approach may not be needed). Instead, the utility program created for this work can be expanded to develop capabilities to provide DPC-specific DCRA arrangements to limit cost and weight and to allow for operational considerations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment of Process Modeling Tools for Determining Variability in Additively Manufactured Parts

The Advanced Materials and Manufacturing Technologies (AMMT) program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy However, the unique aspects of additive manufacturing (AM) materials in terms of their processing history, microstructure, and properties, are a major barrier for qualification and certification of nuclear components. Much of this challenge may be attributed to component scale variations in microstructure and properties that are driven by local influences of process conditions and geometry on thermal history, melt pool dynamics, and corresponding microstructure evolution. Computational modeling tools may be helpful in this regard to aid in predicting and controlling this level of variability. The purpose of this report is to review the current state-of-the-art for process modeling with regards to metal AM. For this purpose, we consider specifically the case study of laser powder bed fusion (LPBF) processing of SS316, a family of alloys that are both commonly used in nuclear energy applications and suitable for AM processing. The report first introduces the necessary components of a process modeling workflow, followed by a review of the current status of each. At the end, application of these modeling tools to understanding variability in AM process given their current state are considered, and recommendations for future development are proposed

36 MATERIALS SCIENCE↗

Gaussian Process Modeling For Experimental Procedure Uncertainty

Many laboratory experiments generate data that are characterized by a form of uncertainty that differs from noise: experimental procedure uncertainty. The origin of this type of uncertainty is the difficulty in controlling a subset of experimental conditions in such a way that the experiment is perfectly reproducible within noise. In this report, we describe a Gaussian Process modeling-based method that accounts for experimental procedure uncertainty. The method accounts for variations in conditions from experiment to experiment that are independent between experiments, but correlated within each experiment, and incorporates the resulting uncertainty into predictions at future experimental settings. The method is discussed in the context of a specific chemistry application in which Raman scattering spectra are measured from three-component mixtures.

42 ENGINEERING↗

Planning for Material Control and Accountancy at Liquid Fueled Molten Salt Reactors

The purpose of this report is to provide molten salt reactor (MSR) developers and future US Nuclear Regulatory Commission (NRC) license applicants with recommendations for developing an effective and practical material control and accounting (MC&A) plan, focused primarily on MSR designs that use circulating liquid fuel. Because of the breadth of MSR designs, there is no single, generic, detailed MC&A plan that will work for every design. The wide variation of fresh fuel salts, the method and frequency of loading fresh fuel, the reactor system design components (e.g., tanks, filtration systems, chemical processing streams), and waste streams will determine the specific measurement locations and instrumentation that can best meet MC&A objectives throughout an MSR facility. Additionally, MSR designs are rapidly evolving, and new design features and deployment scenarios that will affect MC&A are being explored and pursued. This report defines a generic MC&A approach that was developed for terrestrial (as opposed to maritime) deployments to meet the intent of NRC domestic safeguards and MC&A. MSR license applicants should consider nuclear safeguards (both domestic and international) and security throughout the design, as early as the preconceptual design phase. MC&A of special nuclear material (SNM) is an aspect of the NRC’s domestic safeguards program, alongside physical protection. Because liquid-fueled MSRs are reactors with SNM in nondiscrete (or item) form, it is likely that the NRC may require liquid-fueled MSR license applicants to submit a formal MC&A plan as a part of their license application. Currently, the NRC licensing protocol presents a challenge because the NRC MC&A regulations have not been updated to accommodate advanced reactors, including types of MSRs. Because no liquid-fueled MSR has been licensed for operation at the time of this report, no template or precedence for a successfully licensed MSR MC&A plan exists. However, the MSR license applicant can take advantage of the NRC’s published commitments to performance-based regulations. The authors recommend that the license applicant, or MSR designers, develop an MC&A plan throughout the design lifecycle and plan to submit a detailed MC&A program description, or MC&A plan, to the NRC as a part of a license application. No MC&A plan template or guidance exists that is specific to liquid-fueled MSRs. The authors recommend that license applicants discuss the topic of MC&A during preapplication engagement. Because of the uniqueness of MC&A for liquid fueled MSRs, the authors recommend that liquid fueled MSR developers engage with the NRC on the topic of MC&A in the early phases of its design development and follow up any time there are significant modifications in design plans that would affect MC&A. For example, topics like modifications in fuel handling processes, changes in uranium enrichment, or additional chemical processing streams added to the design could be discussed with the NRC specifically on the topic of MC&A.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Metallurgical and mechanical characterization of ATP-5 aluminum alloys for minimizing machining distortion

ATP-5 aluminum alloy was considered as an alternative to 6061-T651 aluminum alloy to minimize machining distortion. ATP-5 is a proprietary cast alloy that is compositionally similar to 5083 aluminum and is purported to have excellent machinability, stability, and corrosion response. Dimensional stability tests, mechanical testing, chemical analysis, microstructural analysis, and fractography were completed to understand the metallurgy of the ATP-5 alloy and assess its potential as a 6061-T651 alloy alternative. Ultimately, the ATP-5 was found to retain dimensional stability issues, albeit to a lesser extent, relative to the 6061-T651 alloy. Combined with the residual cast structure observed microstructurally and lot-to-lot mechanical property variation, the alloy was deemed not suitable for a structural application. Alternative uses of ATP-5 include tooling, molds, vacuum chucks, fixtures, and jigs, where the material can shine in non-load bearing applications with a need for dimensional control and machinability.

36 MATERIALS SCIENCE↗

3D hydrogeophysical characterization of managed aquifer recharge basins

Aquifers are increasingly stressed. Managed aquifer recharge provides a potential solution to mitigate this stress and provide sustainable groundwater resources. Subsurface properties are known to have a strong control on the infiltration rates that can be achieved. However, these properties are often highly heterogeneous and difficult to assess with conventional probing techniques. Here, we show the application of 3D geophysical imaging to assess the recharge potential and its variation across several basins used for managed aquifer recharge. We link in-situ measurements of saturated hydraulic conductivity with the electrical resistivity of the subsurface to establish petrophysical relationships and use those relationships to estimate the distribution of hydraulic conductivity throughout the five recharge basins. Our results show a considerable variability in the hydraulic properties, i.e., soil texture and saturated hydraulic conductivity, that have a direct impact on potential infiltration rates. We use the 3D hydraulic property distributions to model groundwater recharge and provide estimates for infiltration rates and volumes, and use this approach to assess the impact of management activities on groundwater recharge performance. Having such data not only enables us to predict infiltration rates, but also provides means for optimizing such water infrastructure.

54 ENVIRONMENTAL SCIENCES↗

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

54 ENVIRONMENTAL SCIENCES↗

A Novel Thermodynamical Predictor of Tropical High‐Cloud Area Coverage: Estimated Anvil‐Outflow Stability

The stability at the lapse-rate tropopause (LRT) was previously defined as the upper-tropospheric stability (UTS and SUT) but might underestimate the stability control on high-level clouds, since there is little direct connection between convective processes and the thermal stratification at the LRT. Here, a novel estimated anvil-outflow stability (EAS) based on the minimum stability in the upper troposphere is proposed. At the Manus site, the results show that small and large values of the LRT-based UTS and SUT both correspond to strong divergence and frequent occurrence of high-level ice clouds. In contrast, smaller EAS corresponds to stronger convective outflows to produce likely more high-level ice clouds, with a strong negative correlation. In tropics, EAS better explains the geographic distribution of high-level cloud coverage (HCC) and its temporal variations than UTS and SUT. With a strong linear correlation, EAS is likely a simple useful predictor of HCC.

54 ENVIRONMENTAL SCIENCES↗

Preliminary results in using Deep Learning to emulate BLOB, a nuclear interaction model

Purpose: A reliable model to simulate nuclear interactions is fundamental for Ion-therapy. We already showed how BLOB (“Boltzmann-Langevin One Body”), a model developed to simulate heavy ion interactions up to few hundreds of MeV/u, could simulate also 12 C reactions in the same energy domain. However, its computation time is too long for any medical application. For this reason we present the possibility of emulating it with a Deep Learning algorithm. Methods: The BLOB final state is a Probability Density Function (PDF) of finding a nucleon in a position of the phase space. We discretised this PDF and trained a Variational Auto-Encoder (VAE) to reproduce such a discrete PDF. As a proof of concept, we developed and trained a VAE to emulate BLOB in simulating the interactions of 12 C with 12 C at 62 MeV/u. To have more control on the generation, we forced the VAE latent space to be organised with respect to the impact parameter (b) training a classifier of b jointly with the VAE. Results: In this work, the distributions obtained from the VAE are similar to the input ones and the computation time needed to use the VAE as a generator is negligible. Conclusions: We show that it is possible to use a Deep Learning approach to emulate a model developed to simulate nuclear reactions in the energy range of interest for Ion-therapy. We foresee the implementation of the generation part in C++ and to interface it with the most used Monte Carlo toolkit: Geant4.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Realizing symmetry-guaranteed pairs of bound states in the continuum in metasurfaces

Abstract Bound states in the continuum (BICs) have received significant attention for their ability to enhance light-matter interactions across a wide range of systems, including lasers, sensors, and frequency mixers. However, many applications require degenerate or nearly degenerate high-quality factor ( Q ) modes, such as spontaneous parametric down conversion, non-linear four-wave mixing, and intra-cavity difference frequency mixing for terahertz generation. Previously, degenerate pairs of bound states in the continuum (BICs) have been created by fine-tuning the structure to engineer the degeneracy, yielding BICs that respond unpredictably to structure imperfections and material variations. Instead, using a group theoretic approach, we present a design paradigm based on six-fold rotational symmetry ( C 6 ) for creating degenerate pairs of symmetry-protected BICs, whose frequency splitting and Q -factors can be independently and predictably controlled, yielding a complete design phase space. Using a combination of resonator and lattice deformations in silicon metasurfaces, we experimentally demonstrate the ability to tune mode spacing from 2 nm to 110 nm while simultaneously controlling Q -factor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Monovalent ion–graphene oxide interactions are controlled by carboxylic acid groups: Sum frequency generation spectroscopy studies

Graphene oxide (GO) is a two-dimensional, mechanically strong, and chemically tunable material for separations. Elucidating GO–ion–water interactions at the molecular scale is highly important for predictive understanding of separation systems. However, direct observations of the nanometer region by GO surfaces under operando conditions are not trivial. Therefore, thin films of GO at the air/water interface can be used as model systems. With this approach, we study the effects of alkali metal ions on water organization near graphene oxide films at the air/water interface using vibrational sum frequency generation (SFG) spectroscopy. Here, we also use an arachidic acid Langmuir monolayer as a benchmark for a pure carboxylic acid surface. Theoretical modeling of the concentration-dependent sum frequency signal from graphene oxide and arachidic acid surfaces reveals that the adsorption of monovalent ions is mainly controlled by the carboxylic acid groups on graphene oxide. An in-depth analysis of sum frequency spectra reveals at least three distinct water populations with different hydrogen bonding strengths. The origin of each population can be identified from concentration dependent variations of their SFG signal. Interestingly, an interfacial water structure seemed mostly insensitive to the character of the alkali cation, in contrast to similar studies conducted at the silica/water interface. However, we observed an ion-specific effect with lithium, whose strong hydration prevented direct interactions with the graphene oxide film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resistivity phase diagram of cuprates revisited

The phase diagram of the cuprate superconductors has posed a formidable scientific challenge for more than three decades. This challenge is perhaps best exemplified by the need to understand the normal-state charge transport as the system evolves from Mott insulator to Fermi- liquid metal with doping. Here in this paper, we report a detailed analysis of the temperature (T) and doping (p) dependence of the planar resistivity of simple-tetragonal HgBa 2 CuO 4+δ (Hg1201), the single- CuO 2 -layer cuprate with the highest optimal superconducting transition temperature, T c . The data allow us to test a recently proposed phenomenological model for the cuprate phase diagram that combines a universal transport scattering rate with spatially inhomogeneous (de)localization of the Mott-localized hole. We find that the model provides a good description of the data. We then extend this analysis to prior transport results for several other cuprates, including the Hall number in the overdoped part of the phase diagram, and find little compound-to-compound variation in (de)localization gap scale. The results point to a robust, universal structural origin of the inherent gap inhomogeneity that is unrelated to doping-related disorder. They are inconsistent with the notion that much of the phase diagram is controlled by a quantum critical point, and instead indicate that the unusual electronic properties exhibited by the cuprates are fundamentally related to strong nonlinearities associated with subtle nanoscale inhomogeneity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Starting-point-independent quantum Monte Carlo calculations of iron oxide

Quantum Monte Carlo (QMC) methods are useful for studies of strongly correlated materials because they are many body in nature and use the physical Hamiltonian. Typical calculations assume as a starting point a wave function constructed from single-particle orbitals obtained from one-body methods, e.g., density functional theory. However, mean-field-derived wave functions can sometimes lead to systematic QMC biases if the mean-field result poorly describes the true ground state. In this study, we examine the accuracy and flexibility of QMC trial wave functions using variational and fixed-node diffusion QMC estimates of the total spin density and lattice distortion of antiferromagnetic iron oxide (FeO) in the ground state B1 crystal structure. We found that for relatively simple wave functions the predicted lattice distortion was controlled by the choice of single-particle orbitals used to construct the wave function, rather than by subsequent wave function optimization techniques within QMC. By optimizing the orbitals with QMC, we then demonstrate starting-point independence of the trial wave function with respect to the method by which the orbitals were constructed by demonstrating convergence of the energy, spin density, and predicted lattice distortion for two qualitatively different sets of orbitals. The results suggest that orbital optimization is a promising method for accurate many-body calculations of strongly correlated condensed phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗