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Investigation of Frozen Chemistry for Molten Salt Reactors (MSRs)

Understanding accident progression and the potential/conditions for fission product release from fuel is necessary to evaluate safety for any nuclear reactor system. Molten Salt Reactors (MSRs) under development need such analysis to support safety evaluations. Fission product chemistry specific to MSR concepts is a critical area that introduces distinct considerations relative to the current state-of-knowledge in reactor safety, primarily developed for water-moderated nuclear reactor systems. In Light Water Reactor (LWR) systems, it is necessary to capture the chemical interaction of fission products with the reactor evironment, containment and confinement systems. The overall effects at this point are relatively well understood for the purposes of performing safety evaluations. A key insight from LWR studies is that fission product chemical behavior can be reasonably captured by modeling approaches where the chemistry is "frozen". These modeling approaches assume that radionuclide reaction and speciation can be represented by chemical classes, each with characteristic transport behavior that is invariant under a broad range of thermochemical conditions. However, radionuclides can exhibit a range of behavior in the liquid salt-melt phase of the coolant used in MSRs. Radionuclides, salt, and the metal containment surfaces (i.e. pipes) can co-exist in dynamic equilibrium that could evolve with small system mass changes. A detailed investigation to the degree the equilibrium state can dynamically evolve with changes in the conditions of the molten salt mixture has not been previously conducted. It is currently not well understood where frozen chemistry assumptions are valid. Expanding the state-of-knowledge in this regard is relevant to better assessing the range of chemical effects that should be incorporated as part of MSR safety assessments. This investigation used the Oak Ridge Isotope GENeration (ORIGEN) module of the Standardized Computer-Analysis for Licensing Evaluation (SCALE) code to generate simulated radionuclide inventories for the MSR Experiment (MSRE) and then modeled reactor chemical speciation using the Molten Salt Thermodynamic Database – Thermochemical (MSTDB-TC) coupled with Thermochimica. The effect of composition variation during decay of fission product inventory in a molten salt over a period of 500 days prolonged post- at multiple temperatures was studied. Mass fractions for fluorine and berilium were varied in order to probe the effects of free fluorine control. Finally, speciation of fluoride reactors were showed by comparing MSRE readionuclide inventories with a FLiBe based molten salt breeder reactor (MSBR). The results showed that fission product mass change has little effect on phase mass changes and vapor pressures for fluoride species, but differ with varying carrier and fuel salt compositions. However, iodine species were found to have a vapor pressure not only dependent on temperature, but also the free fluorine potential, releasing iodine when the free fluorine potential is equal to the iodine inventory. This observation, however, arose under free fluorine potentials that are very unlikely to be realized in typical molten salt mixtures. Despite this observation, temperature was found to be the dominant parameter that drove phase change and fission product species vapor pressure. The results indicate that the current frozen chemistry approach is adequate for MSR analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Towards a data-driven model of hadronization using normalizing flows

We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimized Illuminance Operation-A Light-Driven Dilution Strategy to Improve Microalgae Biomass Productivity

Periodic dilution is a necessary operation to avoid light limitation due to self-shading as the culture grows dense. However, environmental conditions are constantly changing in outdoor cultivation systems, making it difficult to determine the optimal dilution rate. To address this challenge, this study evaluated a dilution approach based on light penetration to optimize illuminance (OptiLum) in the culture. Biomass concentration was controlled via sensor-feedback directed dilution to ensure that light reaching the bottom of the culture was maintained above the compensation intensity. Under replicated outdoor pond conditions, by keeping the entire culture within a net-positive photosynthetic zone, the OptiLum operation improved the biomass productivities of two top-performing strains, Picochlorum celeri and Tetraselmis striata, by 95 % and 86 %, respectively, compared to conventional semi-continuous batch cultivation. The dilution rate varied daily and was dynamically adjusted based on the light status within the culture, which is concurrently influenced by weather, culture density, and growth rate. The techno-economic analysis showed that the OptiLum operation could reduce biomass production cost by as much as 24 % and 33 % for P. celeri and T. striata, respectively, assuming a low-cost dewatering approach with initial gravity settling of biomass can be realized for both strains. However, a more costly two-stage dewatering strategy, comprising only membranes and centrifuges, may be necessary for non-settling strains, such as P. celeri, which would alternatively increase production costs by 23 % for the OptiLum case. The results demonstrated that the proposed OptiLum operation is a promising approach to improve biomass productivity and lower production cost via weather-responsive and self-adjusting dilution.

09 BIOMASS FUELS↗

Zirconium‐Based Metal–Organic Frameworks with Free Hydroxy Groups for Enhanced Perfluorooctanoic Acid Uptake in Water

Perfluorooctanoic acid (PFOA) is a highly recalcitrant organic pollutant, and its bioaccumulation severely endangers human health. While various methods are developed for PFOA removal, the targeted design of adsorbents with high efficiency and reusability remains largely unexplored. Here, in this work, the rational design and synthesis of two novel zirconium‐based metal‒organic frameworks (MOFs) bearing free ortho ‐hydroxy sites, namely noninterpenetrated PCN‐1001 and twofold interpenetrated PCN‐1002, are presented. Single crystal analysis of the pure ligand reveals that intramolecular hydrogen bonding plays a pivotal role in directing the formation of MOFs with free hydroxy groups. Furthermore, the transformation from PCN‐1001 to PCN‐1002 is realized. Compared to PCN‐1001, PCN‐1002 displays higher chemical stability due to interpenetration, thereby demonstrating an exceptional PFOA adsorption capacity of up to 632 mg g −1 (1.53 mmol g −1 ), which is comparable to the reported record values. Moreover, PCN‐1002 shows rapid kinetics, high selectivity, and long‐life cycles in PFOA removal tests. Solid‐state nuclear magnetic resonance results and density functional theory calculations reveal that multiple hydrogen bonds between the free ortho ‐hydroxy sites and PFOA, along with Lewis acid‐base interaction, work collaboratively to enhance PFOA adsorption.

36 MATERIALS SCIENCE↗

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗

Technoeconomic analysis of hydrogen storage using 1,4-butanediol (BDO)/γ-butyrolactone (GBL) as a stationary backup power system

Liquid organic hydrogen carriers (LOHCs) are compounds that store and release hydrogen in stable forms at high density. While one-way carriers such as methanol and ammonia have gained attention, their economic advantages are often realized from their use as an export product and direct use as a fuel. Liquid carrier materials that can instead be cycled for energy storage have promise for stationary power applications. In particular, the reversible LOHC system 1,4-butanediol (BDO, H 2 -rich) and gamma-butyrolactone (GBL, H 2 -lean) has a lower enthalpy of dehydrogenation compared to conventional cyclic hydrocarbons and can utilize non-precious metal copper-based catalysts. Here, in this study, BDO/GBL system capital and operating expenses are characterized for vapor phase versus liquid phase hydrogenation and dehydrogenation in a 10 MW backup power application corresponding to sizing of Tier 2 datacenters as well as other critical infrastructure such as hospitals. Costs are benchmarked against two incumbent technologies: a well-established methylcyclohexane/toluene carrier system and compressed gas storage. BDO/GBL storage costs are found to differ substantially between operating modes, with liquid phase hydrogenation coupled with liquid phase dehydrogenation leading to the lowest LCOS of $\$$4.58/kg H 2 in the absence of byproduct formation. In this bounding case, LCOS for the BDO/GBL system is lower than for MCH/TOL ($\$$6.97/kg H 2 ) and compressed gas ($\$$8.48/kg H 2 at 170 bara and $\$$12.05/kg H 2 at 350 bara). However, escalating costs of carrier replacement due to byproduct formation (ranging from an added $\$$6–11/kg H 2 ) illustrate the need for highly selective catalysts to ensure BDO/GBL carrier viability.

BDO/GBL↗

Electron density profile and associated fluctuation measurements using a microwave reflectometry diagnostic on Helically Symmetric eXperiment (HSX)

Abstract A dual-band frequency-modulated reflectometry is employed on the Helically Symmetric eXperiment (HSX) stellarator. This system equips a fast PIN switch to alternate the frequency source between two voltage-controlled oscillators, providing an operational frequency range from 14.5 GHz to 25.5 GHz. A monostatic antenna geometry and an ellipsoidal mirror are implemented in the vessel of HSX, where the polarization of the transmitted microwave can be switched between O- and X-mode to accommodate the magnetic field and plasma density. Although the original system was designed for density fluctuation measurement, significant efforts have been undertaken to improve the system performance and to realize the density profile inversion. Recent improvements of the system reported here include calibration of the dispersion in the transmission line, optimization of the waveform, and implementation of the Choi-Williams time–frequency distribution for spectral analysis. In this paper, we present the optimization of the reflectometry system along with first experimental measurements of the density profile and observations of fluctuations during gas puffing experiments.

Han, X. (ORCID:0000000184986433)↗

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O($10^8$) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the $n(z)$ uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. This analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

Giannini, G. [Chicago U., Astron. Astrophys. Ctr.;↗

Dark Energy Survey Year 6 results: Redshift calibration of the MagLim++ lens sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3 x 2pt cosmology analysis. The 3 x 2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection ( B alrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O(10 8 ) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the n(z) uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. Here, this analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

dark energy↗

Identifying Differential Equations in Fourier Domain (FourierIdent)

We investigate identifying differential equations in the frequency domain. Fourier analysis is an important tool in theoretical analysis and numerical solvers of differential equations, yet there is limited work in exploring this connection in the identification of differential equations. This paper aims to identify the underlying differential equation in the frequency domain, from a given single realization of the differential equation perturbed by noise. Such setting imposes difficulties which are different from other identification methods where computation is carried out in the physical domain. We propose several ways to mitigate the challenges arising from noise in data and large differences in the magnitudes of frequency responses. The main takeaways are that identifying differential equations solely in the frequency domain is challenging, the method we propose is based on a form of domain partitions in the frequency domain, and this method shows benefits for complex data even with high level of noise. We introduce a Fourier feature denoising, and define the meaningful data region and the core regions of features to reduce the effect of noise in the frequency domain and to enhance the accuracy in coefficient identification. The proposed method is tested on various differential equations with linear, nonlinear, and high-order derivative feature terms, and shows advantages on complex data with many frequency modes, even under high level of noise.

97 MATHEMATICS AND COMPUTING↗

The FastrSHWFS Project Development Motivation, Analysis, & Test Results

The recent 2020 Decadal Survey of Astronomy and Astrophysics listed habitable exoplanet imaging with future extreme adaptive optics (AO) on 30m-class telescopes as a key priority in the coming decade. However, there is a current 100x contrast gap between the best systems today and what is needed to enable this goal. Astronomical AO is a required approach to enable ground-based diffraction-limited imaging of exoplanets on future extremely large telescopes. Time lag between the end of an exposure and the application of deformable mirror commands is a major contributor to the error budget in many AO systems, and detector read time is often a large component of this lag. We present two designs for a modified Shack Hartmann wavefront sensor (SHWFS), named Focal plane Actualized Shifted Technique Realized for a SHWFS (fastrSHWFS), to reduce the time lag component. This design steers the spot pattern at the focal plane into a rectangular or linear array with a custom aspect ratio, reducing readout time. The mask with focus yields aberrated results while the mask with tip/tilt only yields some defined spots. This essay outlines the current SHWFS concept, our fastrSHWFS theoretical solution to addressing time lag, reflection and quality analysis of printed mask designs, and results from testing both masks on the High Contrast Testbed at Lawrence Livermore National Lab. This work follows the test of a previous fastrSHWFS design.

79 ASTRONOMY AND ASTROPHYSICS↗

High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor

Abstract 2D semiconductors offer a promising pathway to replace silicon in next-generation electronics. Among their many advantages, 2D materials possess atomically-sharp surfaces and enable scaling the channel thickness down to the monolayer limit. However, these materials exhibit comparatively lower charge carrier mobility and higher contact resistance than 3D semiconductors, making it challenging to realize high-performance devices at scale. In this work, we search for high-mobility 2D materials by combining a high-throughput screening strategy with state-of-the-art calculations based on the ab initio Boltzmann transport equation. Our analysis singles out a known transition metal dichalcogenide, monolayer WS 2 , as the most promising 2D semiconductor, with the potential to reach ultra-high room-temperature hole mobilities in excess of 1300 cm 2 /Vs should Ohmic contacts and low defect densities be achieved. Our work also highlights the importance of performing full-blown ab initio transport calculations to achieve predictive accuracy, including spin–orbital couplings, quasiparticle corrections, dipole and quadrupole long-range electron–phonon interactions, as well as scattering by point defects and extended defects.

Chemistry↗

Super-resolution stimulated X-ray Raman spectroscopy

Propagation of intense X-ray pulses through dense media has led to the observation of phenomena such as atomic X-ray lasing, self-induced transparency and stimulated X-ray Raman scattering (SXRS)4. SXRS has been long predicted as a means to launch and probe valence-electron wavepackets and as a building block for nonlinear X-ray spectroscopies. However, experimental observations of SXRS to date have not provided spectroscopic information, and theoretical modelling has largely implemented hard-to-realize phase-coherent attosecond pulses. Here we demonstrate SXRS with spectroscopic precision, that is, detection of valence-excited states in neon with a near Fourier-limited joint energy–time resolution of 0.1 eV–40 fs. We used a new covariance analysis between statistically spiky broadband incident X-ray and scattered X-ray Raman pulses. Using 18,000 single shots, we beat not only the incident (about 8 eV) bandwidth but also the approximately 0.2 eV instrumental energy resolution, thus creating super-resolution conditions, in analogy to super-resolved fluorescence microscopy. Our experimental results, supported by ab initio propagation simulations, reveal the competition between lasing in the ion and stimulated Raman scattering in the neutral. We demonstrate enhanced signal collection efficiency and a broad excitation window, surpassing spontaneous Raman efficiencies by orders of magnitude. This stochastic SXRS approach represents a first step towards tracking elementary events that determine chemical outcomes.

nonlinear x-ray spectroscopy↗

Validation of the DESI DR2 Ly⁢ 𝛼 BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-α (Ly α) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the baryonic acoustic oscillation (BAO) analysis using Ly α forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Lyα mocks that use a quasilinear input power spectrum to incorporate the nonlinear broadening of the BAO peak. Here, we have also increased the number of realizations used in the validation to 400, compared to the 150 realizations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask damped Lyman-α absorbers in our spectra. The BAO measurement from the Ly α dataset of DESI DR2 is presented in a companion publication.

Casas, L. [Institut de Física d’Altes Energies (IF↗

Mathematical methods for optimal polynomial recovery of high-dimensional systems from noisy data

The goal of our Early Career Research Project (ECRP) is to establish a modern mathematical foundation that will enable next-generation computational methods for polynomial approximation of high-dimensional systems, having a certain set of constraints, from a limited amount of noisy data. Such a foundation is critical to realizing the future potential of the DOE user facilities, and will ultimately empower scientists to address a fundamental question, namely, “how many realizations of a nonlinear manifold are required to recover the entire high-dimensional solution map, with optimal approximation guarantees and minimal computational cost?” The central theme of this effort aims to conquer this challenge by pioneering the development of extraordinarily innovative theoretical analysis and transformational non-intrusive computational methodologies. Such approaches will enable the reconstruction of the entire high-dimensional solution map, with accuracy comparable to the best approximation, while utilizing an optimal number of samples. During this reporting period we have made significant progress on four thrusts.

97 MATHEMATICS AND COMPUTING↗

Multinuclear PFGSTE NMR description of 39 K, 23 Na, 7 Li, and 1 H specific activation energies governing diffusion in alkali nitrite solutions

While pulsed field gradient stimulated echo nuclear magnetic resonance (PFGSTE NMR) spectroscopy has found widespread use in the quantification of self-diffusivity for many NMR-active nuclei, extending this technique to uncommon nuclei with unfavorable NMR properties remains an active area of research. Potassium-39 ( 39 K) is an archetypical NMR nucleus exhibiting an unfavorable gyromagnetic ratio combined with a very low Larmor frequency. Despite these unfavorable properties, this work demonstrates that 39 K PFGSTE NMR experiments are possible in aqueous solutions of concentrated potassium nitrite. Further, analysis of the results indicates that 39 K NMR diffusometry is feasible when the nuclei exhibit spin–lattice and spin–spin relaxation coefficients on the order of 60–100 ms and 50–100 ms, respectively. The diffusivity of 39 K followed Arrhenius behavior, and comparative 23 Na, 7 Li, and 1 H PFGSTE NMR studies of equimolal sodium nitrite and lithium nitrite solutions led to correlations between the enthalpy of hydration with the activation energy governing self-diffusion of the cations and also of water. Realizing the feasibility of 39 K PFGSTE NMR spectroscopy has a widespread impact across energy sciences because potassium is a common alkali element in energy storage materials and other applications.

74 ATOMIC AND MOLECULAR PHYSICS↗

Floquet engineering of polaritonic amplification in dispersive photonic time crystals

In this study, we investigate the dynamics of dispersive photonic time crystals (PTCs) and their potential applications for controlling light-matter interaction. Using the Lorentz-Drude as dispersive material model, we analyze the effects of periodic modulation of dispersion parameters through both theoretical and numerical analysis, revealing the emergence of hybrid bandgaps from the interaction of polaritonic branches with distinctive characteristics. Our study demonstrates that dispersive PTCs offer novel excitation channels and amplification possibilities, that require lower modulation frequencies compared to nondispersive systems thus alleviating experimental challenges for the realization of PTCs in the optical regime. These findings pave the way for advancements in polaritonic lasing and resonant Raman scattering.

Classical optics↗

Impacts of Model Building Energy Codes

The Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates national and state-level impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, conducted an assessment of the prospective impacts of national model building energy codes from 2010 through 2040. A previous PNNL study evaluated the impact of the Building Energy Codes Program. A 2016 study looked more broadly at overall code impacts and this report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced emissions at the state level and at aggregated levels. In 2021, DOE conducted an interim and limited update to its 2016 study to evaluate potential building code updates using the 2016 methodology. That interim update includes estimated savings resulting from updates to the model energy codes, including the ANSI/ASHRAE/IES Standard 90.1-2016 (ASHRAE 90.1-2016) and 2019 editions, as well as the 2018 and 2021 International Energy Conservation Code (IECC). In 2023, DOE developed a fully updated report that includes code updates (ASHRAE 90.1-2019 and 2021 IECC), as well as additional enhancements and updates, including updated energy prices, annual floorspace additions, state code adoption dates, and emission factors, among others. This current version is another fully updated report that includes code updates (ASHRAE 90.1-2022 and 2024 IECC), as well as additional enhancements and updates, including updated energy prices, state code adoption dates, emission factors, and renewable energy contribution among others. Energy codes follow a three-phase cycle that starts with the development of a new model code, proceeds with the adoption of the new code by states and local jurisdictions, and finishes when the new code is implemented and builders, architects, and engineers are required to comply with the new provisions. The development of new model code editions creates the potential for increased energy savings. After a new model code is adopted, potential savings are realized in the field when new buildings (or additions and alterations) are constructed to comply with the new code. The contributions of all three phases are crucial to the overall impact of codes and are considered in this assessment. Figure ES.1 schematically describes the analysis framework. Energy savings are expressed in terms of energy use intensity (EUI) in the figure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗