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Multilateral Testing Workshop on Relocatable Portal Monitors

The procurement and deployment of radiation detection equipment is a multi-faceted challenge across the globe. Knowledge sharing of the testing methods used to evaluate equipment for deployment scenarios helps improve the understanding of deployed systems by the global community. The United States Department of Energy’s Nuclear Smuggling Detection and Deterrence Office (NSDD) performed a series of characterization measurements in 2019, focused on radiation detection systems that could function as relocatable portal monitors. The capstone activity for this project was a multilateral and cross-disciplinary workshop demonstrating, performing, and refining the techniques used in the characterization measurements with International Atomic Energy Agency (IAEA) and global partners. A group of technical experts including representatives from nine countries, the IAEA, and NSDD gathered at Sandia National Laboratories in Albuquerque, NM during September of 2019 for the Operational and Performance Testing and Evaluation of Relocatable Portals Workshop. Over the course of a week, the group discussed the necessity for and process of developing operational and performance requirements, challenges related to deploying radiation detection systems for the countries in attendance, use cases for deploying relocatable radiation detection equipment, and considerations related to testing equipment for appropriate deployment scenarios. All participants were given the opportunity to have hands-on experience with eleven relocatable systems in executing a limited scope characterization test comprised of six test scenarios. At the conclusion of testing, participants reviewed and presented their findings, and the group as a whole compared and contrasted their experiences. Suggested revisions to the test methods and ideas for further collaborations were discussed. This report discusses the logistical and planning considerations for bringing together experts across disciplines in a multilateral workshop on testing of radiation detectors, as well as presenting the testing methods performed, results, and paths forward. Success of workshops related to technical knowledge transfer and improvement of test methods is key to global technical and scientific support of radiation detection deployments.

Erchinger, Jennifer L.↗

Filling the Gaps: A Bayesian Mixture Model for Imputing Missing Soil Water Content Data

ABSTRACT Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water‐limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well ( R 2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap‐fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

Ogle, Kiona [School of Informatics, Computing, and↗

Leveraging Artificial Intelligence to Predict Novel Eutectic Alloys

The goal of this project was to train an artificial neural network (ANN) to predict the fractional composition and melting point of eutectic alloys using fundamental atomic properties as inputs. The fundamental properties considered include atomic number, atomic weight, atomic radius, valence electron concentration, electronegativity, and electron affinity. The project involved several phases, starting with data preparation, where phase diagram data was harvested from the ASM International database. Approximately 1300 binary eutectics were collected and cleaned to ensure relevance and accuracy. A regression model was selected for training, utilizing a rectified linear unit as the activation function. Various model configurations were evaluated for predictive accuracy, with validation techniques employed to ensure robustness. The model demonstrated predictive capabilities above random guessing and was able to achieve up to 11% accuracy under certain conditions. An ablative test identified atomic radius and valence electron concentration as critical inputs for model performance. Incorporating the melting point of atomic constituents improved accuracy significantly, although ultimately the model’s predictive capability still fell short of the 80% target. This report details the methodology, results, and implications of the research, contributing to the understanding of employing artificial intelligence to predict the phase transition behavior of eutectic alloys.

36 MATERIALS SCIENCE↗

Biocatalytic Carboxylic Acid Reduction and Transamination in Cell‐Free Lysates at High Substrate Loading

Chemoselective reduction of stable carboxylic acids to reactive aldehydes is of interest across many industries. While carboxylic acid reductases (CARs) are promising biocatalysts for this chemistry, poor chemoselectivity and low yield are commonly obtained when using less expensive crude lysate preparations and prerequisite ATP and NADPH regeneration systems. Here, in this work, we developed a highly chemoselective multienzyme cascade featuring a CAR and an ω-transaminase (TA) in crude lysate format, with conversion of the dicarboxylic acid terephthalic acid (TPA) into the diamine para -xylylenediamine (pXDA) as the model chemistry. We improved chemoselectivity for pXDA using engineered aldehyde-stabilizing Escherichia coli strains, though desired product yields remained modest. We next found that CAR activity was limited at high substrate loadings and overcame this bottleneck by modulating the ratio of polyphosphate (polyP 6 ) to Mg 2+ , enabling volumetric scaling and increased substrate loading up to 50 mM TPA. We then showcased the portability of this platform across substrates, resulting in the synthesis of four other high-value amines from carboxylate precursors. The combination of high carboxyl group turnover, up to 93.5 mM under the tested conditions, and the simplicity of crude enzyme preparation is a promising platform for sustainable functional group interconversion.

60 APPLIED LIFE SCIENCES↗

How does drought affect residential water demand and price elasticity?

Urban water scarcity is an important social and economic concern, particularly as the intensity, duration, and frequency of droughts is increasing in many regions. We consider whether drought induces changes to water demand and the price elasticity of demand for water that may last beyond a drought’s official end date. If drought shocks prompt long-term changes in water demand behavior, and these changes occur at broad geographic scale, they could have important implications for modeling adaptive responses to water scarcity. We assemble a novel dataset on residential water demand and pricing in the western United States to test empirically for effects of drought on water demand and price elasticity. We perform our analysis with aggregate quantity, price, and drought data, accounting for endogenous prices under increasing-block water tariffs and using both average and marginal water fees in estimating water demand functions. Results are consistent with the hypothesis that households may become less price-sensitive after exposure to drought. However, we find no systematic evidence of long-run, drought-related reductions in water demand, itself.

demand hardening↗

Green solvent-processable poly(3-hexylthiophene) derivative maintains high hole mobility in diodes

The development of environmentally sustainable fabrication methods for organic solar cells (OSCs) is critical to enable their large-scale adoption. Conventional solution-processed OSCs often rely on halogenated, toxic solvents that pose health and environmental risks, limiting their scalability. This is because π-conjugated polymers tend to have a low solubility in non-halogenated solvents. A common strategy to enhance solubility in alternative solvents is through the incorporation of polar solubilizing groups, often on every repeat unit of at least one monomer. However, too many polar side chains tend to disrupt favorable morphology and decrease charge transport properties. In this study, we demonstrate that a minimal degree of side chain functionalization can improve green solvent processability while preserving electrical performance. We tested this hypothesis using our previously reported random copolymer derivative of poly(3-hexylthiophene) (P3HT) where ∼10 mol% of the side chains are 6-pentanoatehexyl side chains. We find that this low-level functionalization significantly broadens the solvents that can be used to process P3HT to less toxic solvents such as o-xylene and anisole. Furthermore, the copolymer processed from greener solvents showed high hole mobilities (∼10⁻ 3 cm 2 /Vs by the Space-Charge Limiting Current method in diodes), comparable to P3HT films cast from toxic chloroform. These findings suggest that minimal side-chain modification is a viable strategy for expanding green solvent compatibility while preserving electrical performance, paving the way toward more sustainable organic semiconductor designs.

36 MATERIALS SCIENCE↗

AMF diversity promotes plant community phosphorus acquisition and reduces carbon costs per unit of phosphorus

Plants may benefit from more diverse communities of arbuscular mycorrhizal fungi (AMF), as functional complementarity of AMF may allow for increased resource acquisition, and because a high AMF diversity increases the probability of plants matching with an optimal AMF symbiont. Here, we repeatedly radiolabeled plants and AMF in the glasshouse over c. 9 months to test how AMF species richness (SR) influences the exchange of plant C ( 14 C) for AMF P ( 32 P & 33 P) and resulting shoot nutrients and mass from a biodiversity–ecosystem functioning perspective. Plant P acquisition via AMF increased with sown AMF SR, as did shoot biomass, shoot P, and shoot N. The rate of plant C transferred to AMF for this P (C:P) decreased with sown AMF SR. Plants in plant communities benefit from inoculation with a variety of AMF species via more favorable resource exchange. Surprisingly, this effect did not differ among functionally distinct communities comprised entirely of either legumes, nonlegume forbs, or C3 grasses.

arbuscular mycorrhizal fungi↗

New Yield Estimates for Nuclear Detonations Over Water

One of the primary methods used by the United States to estimate the yields of atmospheric nuclear tests performed in the 1940’s, 50’s, and 60’s was to film each detonation with a high-speed camera, measure the blast radius as a function of time, and then use Taylor’s spherical blast wave equation to calculate the source energy (i.e., the yield). For surface detonations, the yield in Taylor’s equation was assumed to be twice as large as the actual yield to account for the energy reflected from the surface, assuming the ground was a perfect reflector. Recent simulations of surface detonations over water (referred to as barge shots) have shown that Taylor’s equation must be modified further to account for material entrainment and heat losses. We have computed this lost energy using a high-order radiation-hydrodynamics code to determine the reduction in blast radius vs. time. By analyzing simulation data in the same manner as film data, we have determined that a yield correction factor of 1.27± 0.04 should be applied to the barge shots.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Tabletop Testing for EV Charging Ecosystem PKI (Project T34PKI Final Report)

To test the communications and cybersecurity functionality, Electric Vehicle and charging station vendors have had to ship their products to in-person testing events. This is cumbersome, expensive, inefficient, and an impediment to rapid time-to-deployment. In this project Sandia used COTS hardware and Open-Source Software to develop and demonstrate a more agile, productive approach: testing low-voltage controllers independently from high-voltage power delivery sub-systems. This approach allows communications controllers to be transported easily (e.g. shipped at low cost, checked as airline baggage); set up on a table-top (“bench testing”); and use ordinary 120 VAC outlets to conduct agile testing. Table-top platforms become end nodes that can connect to laboratory and cloud-based servers to test communications and cybersecurity, specifically Public Key Infrastructure (PKI) functionality and interoperability, separately from EV battery charging (power/energy transfer) functionality.

33 ADVANCED PROPULSION SYSTEMS↗

MARVEL Instrumentation, Control, and Software Considerations

This paper details the various I&C considerations and design decisions made throughout the MARVEL (Micro-reactor Applications Research Validation and Evaluation) project, including sensor and actuator selection, safety-related functionality, digital control hardware and software, and testing methodologies. Key challenges such as managing radiation, temperature, and space constraints are discussed, along with the trade-offs between using standard equipment and custom solutions. The successful integration of off-the-shelf components, the emphasis on minimizing safety-related instrumentation, and the lessons learned from prototyping and testing are highlighted. The authors aim to provide insights that can benefit future micro-reactor designs and emphasize the importance of real-world testing in advancing reactor technology.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Biotic Interactions Are More Important than Propagule Pressure in Microbial Community Invasions

ABSTRACT Microbial probiotics are intended to improve functions in diverse ecosystems, yet probiotics often fail to establish in a preexisting microbiome. This is a species invasion problem. The relative importance of the two major factors controlling establishment in this context—propagule pressure (inoculation dose and frequency) and biotic interactions (composition of introduced and resident communities)—is unknown. We tested the effect of these factors in driving microbial composition and functioning following 12 microbial community invasions (e.g., introductions of many microbial invaders) in microcosms. Ecosystem functioning over a 30-day postinvasion period was assessed by measuring activity (respiration) and environment modification (dissolved organic carbon abundance). To test the dependence on environmental context, experiments were performed in two resource environments. In both environments, biotic interactions were more important than propagule pressure in driving microbial composition and community function, but the magnitude of effect varied by environment. Successful invaders comprised approximately 8% of the total number of operational taxonomic units (OTUs). Bacteria were better invaders than fungi, with average relative abundances of 7.4% ± 6.8% and 1.5% ± 1.4% of OTUs, respectively. Common bacterial invaders were associated with stress response traits. The most resilient bacterial and fungal families, in other words, those least impacted by invasions, were linked to antimicrobial resistance or production traits. Illuminating the principles that determine community composition and functioning following microbial invasions is key to efficient community engineering. IMPORTANCE With increasing frequency, humans are introducing new microbes into preexisting microbiomes to alter functioning. Example applications include modification of microflora in human guts for better health and those of soil for food security and/or climate management. Probiotic applications are often approached as trial-and-error endeavors and have mixed outcomes. We propose that increased success in microbiome engineering may be achieved with a better understanding of microbial invasions. We conducted a microbial community invasion experiment to test the relative importance of propagule pressure and biotic interactions in driving microbial community composition and ecosystem functioning in microcosms. We found that biotic interactions were more important than propagule pressure in determining the impact of microbial invasions. Furthermore, the principles for community engineering vary among organismal groups (bacteria versus fungi).

59 BASIC BIOLOGICAL SCIENCES↗

Energy Technology Proving Ground FY-2026 Program Plan (Rev.1)

New methods of energy production and distribution are required to meet clean energy goals and demands across all U.S. energy sectors. Idaho National Laboratory’s (INL) Integrated Energy Systems (IES) initiative is enabling clean energy research, development, and demonstration (RD&D) activities. To date, IES demonstration programs have been limited by distributed infrastructure and a lack of large-scale facilities to accommodate industry-scale research of Technical Readiness Level (TRL) 6-8 technologies. The IES initiative plans to eliminate these constraints by establishing a new research complex at INL known as the Energy Technology Proving Ground (Proving Ground) to be led by the Energy and Environment Science and Technology Directorate. The Energy and Environment Science and Technology (EES&T) directorate, one of five Idaho National Laboratory (INL) RD&D organizations, focuses on clean energy technologies that anchor the industry-enabling research of the Proving Ground. The Proving Ground will combine diverse clean energy systems into lean integrated test bed of independent multiscale capabilities available to the government and commercial industries to perform research; and will enable INL’s goal of becoming a Net-Zero entity by 2031. This program encompasses existing and new research space at both the in-town Research and Education Campus (REC) and the Arco desert site (the Site). The Proving Ground will support the maturation of IES technologies from TRL 1 through 8 by providing the infrastructure and capabilities needed to sustain a continuum of RD&D from basic science to industry-scale. To establish The Proving Ground and meet INL’s net-zero goals by 2031, nine research program areas have been identified within the IES initiative that require expanded and new capital infrastructure. This program plan provides guidance for establishing the Proving Ground at the Site for plug-and-play pilot testing and proofing of integrated energy system functionality including fission and renewable energy sources for industry driven application platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A method to fuse multiphysics waveforms and improve predictive explosion detection: theory, experiment and performance

Natural and human-made sources of transient energy often emit multiple geophysical signatures that include mechanical and electromagnetic waveforms. We present a constructive method to fuse and evaluate statistics that we derive from such multiphysics waveforms that improves our capability to detect small, near-ground explosions over similar methods that consume single signature waveforms. Our method advances Fisher's Combined Probability Test (Fisher's Method) to operate under both hypotheses of a binary test on noisy data and provide researchers with the density functions required to forecast the ability of Fisher's Method to screen fused explosion signatures from noise. We apply this method against 12 d, multisignature explosion and noise records to show (1) that a fused multiphysics waveform statistic that combines radio, acoustic and seismic waveform data can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability and (2) that we can quantitatively predict how this fused, multiphysics statistic performs with Fisher's Method. Our work thereby offers a baseline method for predictive waveform fusion that supports multiphenomenological explosion monitoring (multiPEM) and is applicable to any binary testing problem in observational geophysics.

58 GEOSCIENCES↗

Entity—Hardware-agnostic Particle-in-cell Code for Plasma Astrophysics. I. Curvilinear Special Relativistic Module

Entity is a new-generation, fully open-source particle-in-cell (PIC) code developed to overcome key limitations in astrophysical plasma modeling, particularly the extreme separation of scales and the performance challenges associated with evolving, GPU-centric computing infrastructures. It achieves hardware-agnostic performance portability across various GPU and CPU architectures using the Kokkos library. Crucially, Entity maintains a high standard for usability, clarity, and customizability, offering a robust and easy-to-use framework for developing new algorithms and grid geometries, which allows extensive control without requiring edits to the core source code. This paper details the core general-coordinate special relativistic module. Entity is the first PIC code designed to solve the Vlasov–Maxwell system in general coordinates, enabling a coordinate-agnostic framework that provides the foundational structure for straightforward extension to arbitrary coordinate geometries. The core methodology achieves numerical stability by solving particle equations of motion in the global orthonormal Cartesian basis, despite using generalized coordinates like Cartesian, axisymmetric spherical, and quasi-spherical grids. Charge conservation is ensured via a specialized current deposition technique using conformal currents. The code exhibits robust scalability and performance portability on major GPU platforms (AMD MI250X, NVIDIA A100, and Intel Max Series), with the 3D particle pusher and the current deposition operating efficiently at about 2 ns per particle per time step. Functionality is validated through a comprehensive suite of standard Cartesian plasma tests and the accurate modeling of relativistic magnetospheres in curvilinear axisymmetric geometries.

Hakobyan, Hayk [Flatiron Institute, New York, NY (↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Least H 2 norm updating of quadratic interpolation models for derivative-free trust-region algorithms

One particular class of derivative-free optimization algorithms is trust-region algorithms based on quadratic models given by the under-determined interpolation. Different techniques in updating the quadratic model from iteration to iteration will give different interpolation models. We propose a new way to update the quadratic model by minimizing the $H^{2}$ norm of the difference between neighboring quadratic models. The motivation for applying the $H^{2}$ norm is given. The theoretical properties of our new updating technique are also presented. We propose the projection in the sense of $H^{2}$ norm and the interpolation error analysis of our model function. We obtain the coefficients of the quadratic model function using the Karush–Kuhn–Tucker (KKT) conditions. Numerical results show the advantages of our model on the test set considered, and the derivative-free algorithms based on our least $H^{2}$ norm updating quadratic model functions can solve test problems with fewer function evaluations than the algorithm based on the least Frobenius norm updating model and the other compared methods.

derivative-free optimization↗

Hooks versus Pedicle Screws at the Upper Instrumented Level: An In Vitro Biomechanical Comparison

Study Design. Controlled laboratory study Objective. To compare motions at the upper instrumented vertebra (UIV) and supra-adjacent level (UIV+1) between two fixation techniques in thoracic posterior spinal fusion (PSF) constructs. We hypothesized there would be greater motion at UIV+1 after cyclic loading across all constructs and bilateral pedicle screws (BPS) with posterior ligamentous compromise would demonstrate the greatest UIV+1 range of motion (ROM). Summary of Background Data. Proximal junctional kyphosis (PJK) is a well-recognized complication following long thoraco-lumbar PSF, however its mechanism is poorly understood. Methods. Twenty-seven thoracic functional spine units (FSU) were randomly divided into three UIV fixation groups (n=9): (1) BPS, (2) bilateral transverse process hooks (TPH), and (3) BPS with compromise of the posterior elements between UIV and UIV+1 (BPS-C). Specimens were tested on a servohydraulic materials testing system in native state, following instrumentation, and after cyclic loading. FSUs were loaded in flexion-extension (FE), lateral bending (LB), and axial rotation (AR). Results. After cyclic testing, the TPH group had a mean 29.4% increase in FE ROM at UIV+1 versus 76.6% in the BPS group ( P <0.05). The BPS-C group showed an increased FE of 49.9% and 62.19% with sectioning of the facet joints and interspinous ligament respectively prior to cyclic testing. Conclusion. Bilateral pedicle screws at the UIV led to greater motion at UIV+1 compared to bilateral TPH after cyclic loading. This is likely due to the increased rigidity of BPS compared to TPH leading to a “softer” transition between the TPH construct and native anatomy at the supra-adjacent level. Facet capsule compromise led to a 49.9% increase in UIV+1 motion, underscoring the importance of preserving the posterior ligamentous complex. Clinical studies that account for fusion rates are warranted to determine if constructs with a “soft transition” result in less PJK in vivo.

Neurosciences & Neurology↗

Virtual Agents-Based Attack-Resilient Distributed Control for Islanded AC Microgrid

Due to its dependence on a communication network, distributed secondary control of microgrids is susceptible to denial-of-service (DoS) attacks in channel shutdown mode, which may negatively impact the network connectivity and thus deteriorate the coordination and power sharing among distributed generators (DGs). Honeypot is a common method for cyber deception by introducing fake targets. However, in the context of microgrid, the misleading information spread by honeypots will also impact the system performance. This paper proposes an attack-resilient distributed control for AC microgrids utilizing virtual agents (VAs) to counteract both DoS edge and node attacks. The VAs are designed to not impact the system’s steady state during normal operation but to share information among neighboring real agents and serve as dummy targets for DoS attacks. The control with VAs is implemented by a primal-dual gradient based distributed algorithm to efficiently obtain a practical solution for voltage/frequency regulation and power sharing. The simulation results on a 4-DG test system and a modified IEEE 34-bus system show that 1) VAs do not impact the normal functionality of the test system, and 2) deploying VAs can enhance the resilience of the microgrid control against DoS edge and node attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗