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DOE OSTI2022

Development of Porous Crystalline Materials for Selective Binding of O 2 from Air

Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Predictive modeling of NSTX discharges with the updated multi-mode anomalous transport module

Abstract The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.0.4 and those obtained through gyrokinetic simulations; and secondly, to showcase MMM’s ability to predict electron and ion temperature profiles in low aspect ratio, high beta NSTX discharges. MMM encompasses a range of transport mechanisms driven by electron and ion temperature gradients, trapped electrons, kinetic ballooning, peeling, microtearing, and drift resistive inertial ballooning modes. These modes within MMM are being verified through corresponding gyrokinetic results. The modes that potentially contribute to ion thermal transport are stable in MMM, aligning with both experimental data and findings from linear CGYRO simulations. The isotope effects on these modes are also studied and higher mass is found to be stabilizing, consistent with the experimental trend. The electron thermal power across the flux surface is computed within MMM and compared to experimental measurements and nonlinear CGYRO simulation results. Specifically, the electron temperature gradient modes (ETGM) within MMM account for 2.0 MW of thermal power, consistent with experimental findings. It is noteworthy that the ETGM model requires approximately 5.0 ms of computation time on a standard desktop, while nonlinear CGYRO simulations necessitate 8.0 h on 8 K cores. MMM proves to be highly computationally efficient, a crucial attribute for various applications, including real-time control, tokamak scenario optimization, and uncertainty quantification of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Real-fluid behavior in rapid compression machines: Does it matter?

Rapid compression machines (RCMs) have been extensively used to quantify fuel autoignition chemistry and validate chemical kinetic models at high-pressure conditions. Historically, the analyses of experimental and modeling RCM autoignition data have been conducted based on the adiabatic core hypothesis with ideal gas assumption, where real-fluid behavior has been completely overlooked, though this might be significant at common RCM test conditions. Here, this work presents a first-of-its-kind study that addresses two significant but overlooked questions for autoignition studies within RCMs in the fundamental combustion community: (i) experiment-wise, can unaccounted-for real-fluid behavior in RCMs affect the interpretation and analysis of RCM experimental data? and (ii) simulation-wise, can unaccounted-for real-fluid behavior in RCMs affect RCM autoignition modeling and the validation of chemical kinetic models? To this end, theories for real-fluid isentropic change are newly proposed and derived based on high-order Virial EoS, and are further incorporated into an effective-volume real-fluid autoignition modeling framework newly developed for RCMs. With detailed analyses, the strong real-fluid behavior in representative RCM tests is confirmed, which can greatly influence the interpretation of RCM autoignition experiments, particularly the determination of end-of-compression temperature and evolution of the adiabatic core in the reaction chamber. Furthermore, real-fluid RCM modeling results reveal that considerable error can be introduced into simulating RCM autoignition experiments when following the community-wide accepted effective-volume approach by assuming ideal-gas behavior, which can be as high as 64% in the simulated ignition delay time at compressed pressure of 125 bar and lead to contradictory validation results of chemical kinetic models. Therefore, we recommend the community to adopt frameworks with real-fluid behavior fully accounted for (e.g., the one developed in this study) to analyze and simulate past and future RCM experiments, so as to avoid misinterpretation of RCM autoignition experiments and eliminate the potential errors that can be introduced into the simulation results with the existing RCM modeling frameworks.

High-order Virial equation of state↗

DOE OSTI2023

Toward local core outlet temperature monitoring in gas-cooled nuclear reactors using distributed fiber-optic temperature sensors

Gas-cooled nuclear reactors operate at temperatures up to 950 °C with significant spatial variations in power generation and coolant flow through hundreds of parallel flow channels, resulting in complex mixing at the core outlet. The high temperatures and complex mixing can damage downstream components, challenge reactor calorimetry for power determination, and result in significant conservatism in calculated peak fuel temperatures, which ultimately limits the total power output. Directly measuring each gas stream individually is unrealistic using single point thermocouples, requiring more robust sensing techniques. Fiber-optic sensors are resilient to high temperatures (up to 1,000 °C) and radiation damage. Moreover, distributed measurements can be made along the length of one fiber, making them potential candidates for monitoring local core outlet temperatures to improve core calorimetry and identify hot channels. Here, to the authors’ knowledge, this manuscript is the first to report spatially distributed fiber optic temperature measurements to quantify mixing at the outlet of a relevant orifice plate under prototypic temperature and flow regimes to assess the feasibility of using fiber-optic sensors for distributed measurements of coolant temperature in gas-cooled reactors. A single optical fiber captured dynamic changes in local temperatures, whereas the mixed outlet temperature exhibited a muted response and could not identify which channels were responsible for the change in the mixed outlet temperature. The discussion focuses on potential challenges for deploying distributed optical fibers in gas-cooled reactors, including the effects of vibrations, radiation-induced signal attenuation and drift, and routing of the fiber while minimizing flow obstructions.

42 ENGINEERING↗

DOE OSTI2020

TDCOSMO. I. An exploration of systematic uncertainties in the inference of $H_0$ from time-delay cosmography

Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, H0. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on H0 from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in H0 values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the “bulge-halo” conspiracy, H0 is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields H0 = 74.0−1.8+1.7 km s−1 Mpc−1, while the power-law model yields 74.2−1.6+1.6 km s−1 Mpc−1. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Argon Pumpout by ICRF Waves in C-Mod L- and I-mode Plasmas

Pumpout of argon ions by ICRF waves has been observed in C-Mod deuterium L- and I-mode plasmas that had a substantial hydrogen fraction. The effect is manifested by a reduction of core argon x-ray brightness up to a factor of 90% on time scales of tens of milliseconds following injection of ICRF power. For Ar^16+, the pumpout is strongest for hydrogen minority concentrations between 0.25 and 0.4, when the ICRF waves are not expected to result in minority heating. Modeling with the TORIC code suggests that the pumpout process occurs when the H/D mode conversion layer overlaps with the 2nd harmonic impurity resonance layer. The magnitude of the argon pumpout is independent of ICRF power above an apparent threshold of ~500 kW, independent of electron density and appears to decrease as the plasma current is increased. Potential application as a heavy impurity control tool in reactors is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Argon pumpout by ICRF waves in C-Mod L- and I-mode plasmas

Pumpout of argon ions by ICRF waves has been observed in C-Mod deuterium L- and I-mode plasmas that had a substantial hydrogen fraction. The effect is manifested by a reduction of core argon x-ray brightness up to a factor of 90% on time scales of tens of milliseconds following injection of ICRF power. For Ar 16+ , the pumpout is strongest for hydrogen minority concentrations between 0.25 and 0.4, when the ICRF waves are not expected to result in minority heating. Modeling with the TORIC code suggests that the pumpout process occurs when the H/D mode conversion layer overlaps with the 2nd harmonic impurity resonance layer. Here, the magnitude of the argon pumpout is independent of ICRF power above an apparent threshold of ~500 kW, independent of electron density and appears to decrease as the plasma current is increased. Potential application as a heavy impurity control tool in reactors is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Advanced control sequences and FDD technology. Just shiny objects, or ready for scale?

Innovations in commercial building control sequences (ASHRAE guideline 36) and fault detection and diagnostics (FDD) technology have the potential to transform existing building operational efficiency by realizing whole-building level savings on the order of 15% and higher. However, several technical and market barriers related to up-front estimation of achievable savings, verifying implementation, and ensuring persistence are slowing down their adoption as a core offering through diverse owner-funded initiatives and rate-payer funded programs. This paper describes a suite of solutions to overcome these barriers to program delivery of advanced HVAC controls integrated with FDD energy management and information system (EMIS) technology. First, the Guideline 36 conformance test offers an automated method to confirm correct sequence implementation by the manufacturer, before field deployment. A successful test of a controller was conducted using a new manufacturer-independent hardware-in-the-loop testbed demonstrating the viability and scalability of this approach. Second, the Guideline 36 energy savings calculator uses modeling paired with high-level user inputs to estimate building-specific savings potential, target cost effective implementation and minimize uncertainty. Initial results indicate the baseline control sequences significantly impact energy savings, however, as much as 50% savings may be possible for the worst-case baseline scenario. Third, a functional specification provides minimum recommended EMIS-FDD capabilities, and best practices to integrate the technology into organizational practice and ensure that advanced control sequences provide persistent savings.

Pritoni, Marco↗

DOE OSTI2025

Role of perturbed parallel magnetic field effects in predicting turbulent transport in NSTX

This study presents analysis of gyrokinetic simulations on the National Spherical Torus Experiment (NSTX) to investigate the effects of electromagnetic fields on plasma turbulence and transport. The simulations, performed with varying levels of fidelity using the gyrokinetic CGYRO code, include electrostatic (ES), single-field electromagnetic (EM1), and two-field electromagnetic (EM2) models. A detailed comparison across the simulation database reveals that electromagnetic effects increase both predicted growth rates and quasilinear fluxes, with EM2 simulations producing stronger turbulence than ES and EM1 cases. Quasilinear modeling using QLGYRO demonstrates that while the perturbed parallel magnetic field (δB ∥ ) does not drastically affect the total flux at experimental gradients, it leads to a shift in the dominant instability, altering mode structures from microtearing to kinetic ballooning modes (KBMs). The proximity of the plasma profiles to the KBM threshold is explored, with the experimental conditions being near the onset of KBM-driven transport. The KBM, with its large growth rates, is identified as a potential driver of electron temperature flattening, as it can rapidly transport heat across flux surfaces. Performing stability analysis shows core-localized unstable a low- mode that could contribute to the flattening at the early times of the discharge. TGYRO predictive modeling, incorporating both TGLF and QLGYRO, indicates that the inclusion of δB ∥ significantly improves the accuracy of temperature profile predictions in NSTX high-beta plasmas, although challenges remain in modeling the sharp flux discontinuities caused by KBM-driven instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO 2 sequestration

Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Dynamical structure factors of warm dense matter from time-dependent orbital-free and mixed-stochastic-deterministic density functional theory

Abstract We present the first calculations of the inelastic part of the dynamical structure factor (DSF) for warm dense matter (WDM) using time-dependent orbital-free density functional theory (TD-OF-DFT) and mixed-stochastic-deterministic (mixed) Kohn Sham TD-DFT (KS TD-DFT). WDM is an intermediate phase of matter found in planetary cores and laser-driven experiments, where the accurate calculation of the DSF is critical for interpreting x-ray Thomson scattering measurements. Traditional TD-DFT methods, while highly accurate, are computationally expensive, motivating the exploration of TD-OF-DFT and mixed TD-KS-DFT as more efficient alternatives. We applied these methods to experimentally measured WDM systems, including solid-density aluminum and beryllium, compressed beryllium, and carbon–hydrogen mixtures. Our results show that TD-OF-DFT requires a dynamical kinetic energy potential in order to qualitatively capture the plasmon response. Additionally, it struggles with capturing bound electron contributions. In contrast, mixed TD-KS-DFT offers greater accuracy in distinguishing bound and free electron effects, aligning well with experimental data, though at a higher computational cost. This study highlights the trade-offs between computational efficiency and accuracy, demonstrating that TD-OF-DFT remains a valuable tool for rapid scans of parameter space, while mixed TD-KS-DFT should be preferred for high-fidelity simulations. Our findings provide insight into the future development of DFT methods for WDM and suggest potential improvements for TD-OF-DFT.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Analysis of Distributed Energy Storage as a Core Grid Infrastructure via Production Cost Modeling

Energy storage plays a pivotal role in enabling power system operation with more flexibility and resilience. Unlike current practice that considers energy storages as attached ancillary devices, this paper focuses on storages as a core infrastructure by looking at their spatial distribution in the system. A sensitivity analysis based on production cost modeling is conducted to demonstrate the benefits of distributed energy storages. First, the modeling of energy storages in production cost modeling is presented. Second, potential optimal locations of distributed energy storages in a power system are discussed. Finally, multiple scenarios with various numbers and locations of additional distributed energy storages in the WECC 2030 model are created. The production cost modeling results of these scenarios show that distributed energy storages have higher utilization compared to the centralized ES units and therefore provide significantly more benefits in terms of reduction in generation cost, emission cost, and volatility of location marginal prices. A saturation effect is observed suggesting the selection of optimal locations will further improve the benefits.

Nguyen, Quan H.↗

DOE OSTI2025

High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME's core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform's ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME's potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck.

Gaillard, William R↗

DOE OSTI2025

E3SM‐GCAM: A Synchronously Coupled Human Component in the E3SM Earth System Model Enables Novel Human‐Earth Feedback Research

Abstract Modeling human‐environment feedbacks is critical for assessing the effectiveness of climate change mitigation and adaptation strategies under a changing climate. The Energy Exascale Earth System Model (E3SM) now includes a human component, with the Global Change Analysis Model (GCAM) at its core, that is synchronously coupled with the land and atmosphere components through the E3SM coupling software. Terrestrial productivity is passed from E3SM to GCAM to make climate‐responsive land use and CO 2 emission projections for the next 5‐year period, which are interpolated and passed to E3SM annually. Key variables affected by the incorporation of these feedbacks include land use/cover change, crop prices, terrestrial carbon, local surface temperature, and climate extremes. Regional differences are more pronounced than global differences because the effects are driven primarily by differences in land use. This novel system enables a new type of scenario development and provides a powerful modeling framework that facilitates the addition of other feedbacks between these models. This system has the potential to explore how human responses to climate change impacts in a variety of sectors, including heating/cooling energy demand, water management, and energy production, may alter emissions trajectories and Earth system changes. Plain Language Summary Earth system models help us understand how humans are changing the climate. Currently, these models do not include human systems, so predetermined greenhouse gas, aerosol, and land use change data are input to these models. These data do not reflect human responses to changes projected by Earth system models. We have added a human component to an Earth system model to represent human responses to environmental change and calculate corresponding greenhouse gas and land use change data instead of using predetermined data. Including this human component changes projections of land use, land carbon storage, and regional climate. Key Points We have incorporated a novel, advanceable human component in an Earth system model to simulate human‐Earth feedbacks Including terrestrial productivity feedbacks from the Earth to the human systems affects land change, crop prices, carbon, and climate Regional effects of including terrestrial productivity feedbacks are greater than global effects because land change is the main driver

E3SM↗

DOE OSTI2023

Expansion of Hazards and Probabilistic Risk Assessments of a Light-Water Reactor Coupled with Electrolysis Hydrogen Production Plants

This report builds upon the body of work sponsored by the Department of Energy (DOE) Light-Water Reactor Sustainability (LWRS) Flexible Power Operation and Generation (FPOG) program that presented generic probabilistic risk assessments (PRAs) for the addition of a heat extraction system (HES) to light-water reactors to support the co-location of a high temperature hydrogen electrolysis facility (HTEF). Probabilistic and deterministic hazards assessments and risk analyses are leveraged throughout this report. Several improvements and new analyses are included in this report. First, higher amounts of detail in the specifications of the generic HTEFs are used to produce scaled results for a 100, 500, and 1000 MW nominal hydrogen production facility. An additional hazard assessment of 1000 kg of hydrogen storage is performed. The facility hazards and footprint are assessed to determine the safe distance required for placement near the nuclear power plant (NPP). Second, specific designs for corresponding HESs for the different levels of support required by the HTEFs are analyzed in the PRA model. Third, a hazards analysis of the specified HTEFs leads not only to effects of the quantified risk assessment for the NPP, but also qualitative hazards assessment for the community. Finally, a seismic analysis and a high winds analysis have each been added to the PRA. The results investigate the applicability of the potential licensing approaches which do not require a full United States (U.S.) Nuclear Regulatory Commission (NRC) licensing review. The PRAs are generic and include listed assumptions. The HTEF design built for this project has further eliminated many conservative assumptions from the prior PRAs in this series. The PRA results indicate that the 10 CFR 50.59 licensing approach is justified due to the minimal increase in initiating event frequencies for all design basis accidents, with none exceeding 7.7%. The PRA results for core damage frequency and large early release frequency support the use of NRC Regulation Guide 1.174 as further risk information that supports a change without a full licensing amendment review. The hazard analyses and PRA confirm the need for engineered blast barriers of storage tanks and the common production header leaving the HTEF. The hazards analyses and PRA also confirm with high confidence that using the assumptions of design in this report that the safety case for licensing an HES addition and an HTEF sited with its unprotected high-pressure stage components 187 meters from the NPP’s transmission towers (the most fragile structure, system, and component) is strong.

08 HYDROGEN↗

DOE OSTI2023

Sticky roots--implications of widespread, cryptic, viral infection of plants in natural and managed ecosystems for soil carbon processing in the rhizosphere

Plants strongly influence soil properties through rhizodeposition, in which exudates diffuse from roots, additional secretions are actively released, and root cells are sloughed into the soil. This contribution by plants of carbon compounds belowground is at the core of soil health, water holding capacity, and the soil carbon storage that pulls carbon dioxide out of the atmosphere. Once in soil, organic matter can bind with minerals such as iron hydroxides, where it can be protected from microbial attack for millenia, preserving very large terrestrial soil carbon pools. However, those same compounds contributed by roots to soil may also destabilize the long-term protective associations of SOM with minerals, making that soil organic matter (SOM) more vulnerable to microbial attack and decomposition. Plant roots thus influence both the buildup and breakdown of soil carbon pools. DOE’s E3SM Land Model (ELM) includes a representation of soil carbon storage on minerals, but the potential vulnerability of SOM–mineral associations to effects of rhizodeposition is not yet represented in ELM. To begin testing for this effect of rhizodeposition on soil carbon storage and decomposition, we worked to develop a novel approach during this TES Exploratory project DE-SC0019142 – we harnessed the power of plant viral infection. We examined whether plant virus infection can serve as a tool to intensify rhizodeposition at the root surface, and therefore possibly intensify mobilization of SOM from minerals making it visible to our analytical techniques. Viral infection is widespread in terrestrial ecosystems; 25-70% of plants have virus infection, yet the influence of such infection on root traits and terrestrial soil carbon dynamics remains largely unexplored. We used two plant hosts: the annual Avena sativa (oats) and the genetically tractable, model grass Brachypodium distachyon. These grasses were infected with the broad host range virus Barley Yellow Dwarf Virus (BYDV) via aphids (Rhopalosiphum padi). BYDV infects at least 150 grass species in agricultural and natural ecosystems, and in previous experiments, oats infected with BYDV had roots that were very sticky to the touch, strongly suggesting that infection altered rhizodeposition. We developed this new experimental approach mostly in a one virus (Barley Yellow Dwarf Virus)–one plant (Avena sativa) system. (Several effects of infection in a Brachypodium-BYDV system were similar in nature to effects on Avena sativa, but were more variable.) In the BYDV-Avena system, we developed protocols for consistently infecting target plants (and avoiding infection of control plants) using aphid caging on leaves. We measured that infected plants exhibited reduced photosynthesis, plant (including root) biomass, and root:shoot ratio, as well as simplified root system architecture. We established procedures for sampling the organic compounds carried specifically in phloem (vascular tissue) of leaves and roots, using aphid stylectomy. We used FTICR-MS, Orbitrap GC-MS, and LC-MS/MS to analyze organic compounds in phloem, liquid around roots of plants grown hydroponically, and pore water around roots in soil, and found differences in the compounds in solution bathing roots when infected and uninfected plants were grown hydroponically. Finally, we synthesized isotopically-labeled mineral–organic matter (MAOM) associations in the lab and developed assays using them in solution and in soil. Assays quantified the extent and rate of mineralization of labeled MAOM that was mobilized by functionally distinct rhizodeposits and then attacked by microbes. Two mechanisms for MAOM mobilization emerged, with distinct dynamics. During “direct” mobilization, rhizodeposits such as the strong ligand oxalic acid could drive rapid dissolution of minerals, mobilizing MAOM. During “indirect” mobilization, rhizodeposits such as the simple sugar glucose did not attack minerals directly but instead intensified microbial activity, which led to mobilization via changes in e.g. pH, Eh, and microbial metabolite production (Li et al. 2021). Mechanistic understanding derived from these data and our ongoing experiments using these techniques will inform future development of ELM. Plant roots not only contribute newly fixed organic compounds to soils, but also root activities can drive mineralization of the carbon and nutrients mobilized off minerals via “indirect” or “direct” mechanisms. Using viral infection as a new tool, ongoing combined experimentation and modeling will explore the strength and larger-scale significance of the cascade of processes from rhizodeposition to MAOM mobilization for soil carbon storage and nutrient cycling in terrestrial ecosystems. And if viral infection leads quite generally to “sticky roots”, our perception of the potential importance of prevalent virus infection in terrestrial landscapes will be transformed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗