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DOE OSTI2026

Knowledge Graph of RB-Tnseq Data from Fitness Browser (KP-DP1)

Motivation: Predicting microbial gene fitness across environmental conditions remains a central challenge for predictive phenomics and autonomous experimentation. Fitness assays generate large volumes of genotype–phenotype measurements difficult to integrate with experimental metadata and biological function in a form that supports mechanistic reasoning. Knowledge graphs offer a semantic framework for unifying modalities and enabling context-aware inference. Results: We build GIMME (Graph Inference for Microbial Metabolism Exploration), a semantically grounded knowledge graph that unifies gene fitness measurements spanning 10 Pseudomonas species with experimental metadata and biological context. Media are decomposed into chemical components and experiments carry structured links to natural-language descriptions. The resulting graph supports two inference modes: (1) symbolic graph traversal to surface candidate gene–environment and gene–chemical associations, and (2) learned inference using heterogeneous graph neural networks that propagate information across neighborhoods. We formulate link regression over (gene, media, experiment) triplets, combining learned gene embeddings with pretrained LLM sourced text embeddings of node descriptions to predict gene fitness. We then augment a baseline MLP with an auxiliary message-passing encoder (GraphSAGE/GAT) that propagates information over gene–protein–function and media–chemical subgraphs, and fuse the two pathways with a gated residual connection. This approach produces strong agreement with held-out fitness measurements (GraphSAGE Pearson r 0.74) while also highlighting inference challenges in extreme-fitness regimes. We aggregate GAT edge-attention weights by relation type and layer to estimate which biological and environmental relations most influence fitness predictions. Conclusion: This work explores using knowledge graphs as “context graphs” for microbial phenotype prediction. They provide a rich substrate which enables explainable retrieval of supporting evidence, and provides a natural bridge to autonomous workflows that prioritize the next experiment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

The Stars Kepler Missed: Investigating the Kepler Target Selection Function Using Gaia DR2

The Kepler Mission revolutionized exoplanet science and stellar astrophysics by obtaining highly precise photometry of over 200,000 stars over 4 yr. A critical piece of information to exploit Kepler data is its selection function, since all targets had to be selected from a sample of half a million stars on the Kepler CCDs using limited information. Here we use Gaia DR2 to reconstruct the Kepler selection function and explore possible biases with respect to evolutionary state, stellar multiplicity, and kinematics. We find that the Kepler target selection is nearly complete for stars brighter than Kp < 14 mag and was effective at selecting main-sequence stars, with the fraction of observed stars decreasing from 95% to 60% between 14 < Kp < 16 mag. We find that the observed fraction for subgiant stars is only 10% lower, confirming that a significant number of subgiants selected for observation were believed to be main-sequence stars. Conversely we find a strong selection bias against low-luminosity red giant stars (R ≈ 3–5R {sub ⊙}, T {sub eff} ≈ 5500 K), dropping from 90% at Kp = 14 mag to below 30% at Kp = 16 mag, confirming that the target selection was efficient at distinguishing dwarfs from giants. We compare the Gaia Re-normalized Unit Weight Error (RUWE) values of the observed and nonobserved main-sequence stars and find a difference in elevated (>1.2) RUWE values at ∼σ significance, suggesting that the Kepler target selection shows some bias against either close or wide binaries. We furthermore use the Gaia proper motions to show that the Kepler selection function was unbiased with respect to kinematics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Quantifying the Effect of Magnetic Field Line Curvature Scattering on the Loss of Ring Current Ions

During geomagnetic storms, the ring current ions sometimes exhibit rapid loss as suggested by the fast recovery of the Dst index on a time scale of a few hours. Here, the effects of magnetic field line curvature (FLC) scattering on the loss of ring current ions, which have not been well quantified, are studied here by test particle simulations under the T89c magnetic field model. Our simulation results show that the prediction of ion loss based on a single–value cutoff of the κ parameter or maximum of δμ/μ of a single FLC scattering is not accurate. Instead, the e–folding lifetime (τ) for the loss of ring current ions due to cumulative FLC scattering has been calculated for different initial ion energies, equatorial pitch angles, and L shells under different geomagnetic conditions. The results show that in general the FLC scattering loss is faster for ions of higher energy, higher mass, smaller pitch angle, higher L, and at high Kp level. Specifically, we find that at Kp = 6 the lifetime can be <10 h at L > 5 for 100 s keV protons and at L > 4 for 100 s keV O + , which demonstrates that FLC scattering can be an important mechanism for the observed fast loss (τ < 10 h) of ring current ions during geomagnetic storms. Furthermore, we formulate an empirical formula for τ as a function of ion energy, pitch angle, position, species, and Kp. The empirical formula can be directly included in ring current models to account for the FLC scattering effects.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Development and Experimental Validation of a Heat Transfer Model for Spilled Molten Salt Pools

A spill of radionuclide-bearing molten salt is one of the major postulated events that needs to be analyzed for liquid fluorine salt-cooled high-temperature reactor (FHR) or molten salt reactor licensing purposes. In this postulated event, radioactive source term materials (RSTMs) in the molten salt are discharged from the reactor vessel to the reactor building. The release of RSTMs from the spilled salt pool to the gas space in the reactor building is expected to be controlled by the cooling behavior of the spilled salt, including the growth and shrinkage of the solid crust on the surface of the spilled salt pool. This paper presents a simulation model for spilled salt pool heat transfer and validation efforts. The validation data come from two molten salt spill tests that were performed recently: the PELE2 test by the Rapid Experimental Laboratory of Kairos Power LLC (KP) and the Argonne salt cooling test conducted by Argonne National Laboratory. The former was a large-scale test involving kilograms of molten spilled FLiNaK salt, and the latter was a relatively smaller-scale test targeting various processes associated with a salt spill event. Both tests generated valuable data sets that can be used to assess salt cooling and validate evaluation models. This paper provides a new one-dimensional model that can simulate the cooling process of a spilled salt pool as well as the thermal responses of heat structures, such as the stainless steel liner and the concrete below the salt. The model has been implemented as part of KP-SAM code, which is a branch of the systems code SAM specific to KP FHR. In conclusion, the simulation results of the model are compared with the data of the PELE2 and Argonne tests, and reasonable agreements are observed between the model and test data.

heat transfer model↗

DOE OSTI2021

SAM Co-Development to Support Fluoride-salt-cooled High-temperature Reactor Design and Licensing (CRADA 2018-18177 Final Report)

This project aims to raise the SAM code's technical and commercial maturity level to enable the Kairos Power ("Kairos") to use SAM to support its KP-FHR design analysis and licensing application. Argonne National Laboratory ("Argonne") has actively developed and maintained SAM, a modern system-level analysis tool for advanced nonlight water reactors safety analysis. Kairos is currently actively pursuing development of an FHR design and associated technology, and consequently requires a pedigreed safety analysis tool. The purpose of this project is to increase the maturity of the SAM code for the modeling and simulation of the KP-FHR design, thus enabling its use in safety analyses that support licensing application. Argonne will primarily be responsible for software design, development, and testing; while Kairos will be responsible for software requirements, assessment of software capabilities, needs, gaps, and priorities, and development of proprietary models. The research and development activities for the joint SAM development project include: a series of identification and prioritization studies on design characteristics, event sequences, relevant phenomena, and software capabilities; SAM capability enhancements for specific KP-FHR systems and components; performing code verification and validations; integrating uncertainty quantification (UQ), model calibration, and sensitivity analysis (SA) techniques in safety analyses; and raising the software quality rigor level for commercial-grade applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Ultraviolet Photoemission Spectroscopy and Kelvin Probe Measurements on Metal Halide Perovskites: Advantages and Pitfalls

In this essay, a case study is presented on the electronic structure of several metal halide perovskites (MHP) using Kelvin probe (KP)-based surface photovoltage (SPV) measurements and ultraviolet photoemission spectroscopy (UPS) to demonstrate the advantages, but also the pitfalls, of using these techniques to characterize the surfaces of these materials. The first part addresses the loss of halide species from perovskite surfaces upon supragap illumination in vacuum. This has the potential to cause both a long-term alteration of the sample work function and a modification of the KP tip during SPV measurements. If undetected, this leads to a misinterpretation of the MHP surface potential. The second part illustrates the difficulties in determining the valence band maximum (VBM) of MHP surfaces with UPS and stresses the importance of taking into account the low density of states at the VBM edge. Given this circumstance, specific care must be taken to eliminate measurement artifacts in order to ascertain the presence or absence of low densities of electronic gap states above the VBM. This essay also highlights issues such as film degradation, nonequilibrium situations (e.g., SPV), and satellite emissions, which occur during photoemission spectroscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Development of LpxH Inhibitors Chelating the Active Site Dimanganese Metal Cluster of LpxH

Abstract Despite the widespread emergence of multidrug‐resistant nosocomial Gram‐negative bacterial infections and the major public health threat it brings, no new class of antibiotics for Gram‐negative pathogens has been approved over the past five decades. Therefore, there is an urgent medical need for developing effective novel antibiotics against multidrug‐resistant Gram‐negative pathogens by targeting previously unexploited pathways in these bacteria. To fulfill this crucial need, we have been investigating a series of sulfonyl piperazine compounds targeting LpxH, a dimanganese‐containing UDP‐2,3‐diacylglucosamine hydrolase in the lipid A biosynthetic pathway, as novel antibiotics against clinically important Gram‐negative pathogens. Inspired by a detailed structural analysis of our previous LpxH inhibitors in complex with K. pneumoniae LpxH ( Kp LpxH), here we report the development and structural validation of the first‐in‐class sulfonyl piperazine LpxH inhibitors, JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ), that achieve chelation of the active site dimanganese cluster of Kp LpxH. The chelation of the dimanganese cluster significantly improves the potency of JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ). We expect that further optimization of these proof‐of‐concept dimanganese‐chelating LpxH inhibitors will ultimately lead to the development of more potent LpxH inhibitors for targeting multidrug‐resistant Gram‐negative pathogens.

Pharmacology & Pharmacy↗

DOE OSTI2023

Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification

An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Modeling the Effects of Drift Orbit Bifurcation on Radiation Belt Electrons

Abstract Drift orbit bifurcation (DOB) has been suggested to play a major role in the loss and transport of radiation belt electrons since it violates the second adiabatic invariants of particles and makes the third invariant undefined. Results from our guiding‐center test particle simulations using the Tsyganenko‐1989c magnetic field model show that the DOB could affect a broad region of the outer radiation belt, which can penetrate inside the geosynchronous orbit at Kp ≥ 3, and its effects are more significant further away from the Earth, at a higher Kp and for higher electron energies. Specifically, the short‐term simulation results after one electron drift show both traditional and nontraditional DOB transport of electrons, with the nontraditional DOB, caused by a third minimum of the magnetic field strength near the equator, reported here for the first time. Moreover, our results show large ballistic jumps in the second invariant and radial distance for electrons at high equatorial pitch angles after one drift. In addition, long‐term DOB transport coefficients of electrons over many drifts are calculated based on our simulation results. We find that the pitch angle and radial diffusion coefficients of electrons due to DOB could be comparable to or even larger than those caused by electron interactions with chorus and Ultra‐Low‐Frequency waves, respectively. In sum, our results demonstrate that DOB could cause effective loss and transport of radiation belt electrons even in the absence of waves.

Astronomy & Astrophysics↗

DOE OSTI2021

Quantifying the reaction mechanisms of a high-capacity CuP 2 /C composite anode for potassium ion batteries

Introducing metals into phosphorus to form metal phosphide materials as anodes for potassium ion batteries (PIBs) is an effective strategy to improve the electronic conductivity and alleviate the volume change during cycling, although with a compromise of capacity. Here in this paper, we explore a CuP 2 /C composite as a novel anode for PIBs, which delivers a high reversible capacity of >450 mA h g -1 . Unexpectedly, our results reveal that the POx components existing in the prepared composite are reversible, through a quantitative analysis via high-resolution solid-state 31 P NMR and synchrotron X-ray diffraction tests. Their potassiation products K 3 PO 4 and K 4 P 2 O 7 can react with K–P alloys and turn back to PO x during depotassiation, which probably accounts for the high capacity of the prepared material. The results also illustrate a crystallization–amorphization evolution process during cycling involving nanocrystalline α-K 4 P 6 , K 4 P 3 and KP, and amorphous K 4 P 6 , KP and K 3 P phases, among which, the amorphous phases are identified for the first time.

25 ENERGY STORAGE↗

DOE OSTI2025

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt-cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. Here, to address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor's size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. In conclusion, the Reger direct numerical simulation-driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Mixed Convection↗

DOE OSTI2025

Source function from two-particle correlation function through entropy-regularized Richardson-Lucy deblurring

Source functions are obtained from p – p and d – α correlation functions by applying the Richardson-Lucy (RL) deblurring to the Koonin-Pratt (KP) equation. To prevent fitting of noise in the correlation function, total-variation (TV) regularization is employed that has been effective in ordinary image restoration. TV alone cannot ensure normalization of the source functions. To ensure the latter, we propose a maximum-entropy regularized RL algorithm (MEM-RL). We outline the MEM-RL formalism and optimization strategy for the KP equation, demonstrating its effectiveness on both simulated and experimental data, including the p – p and d – α correlation functions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Sensitivity Analysis of Tunable Equation of State Material Model In Pulsed Mercury Target Simulation

A pulsed neutron spallation target is subjected to very short but intense loads from repeated proton pulses. Approximately 60% of the energy from each proton pulse is deposited into the mercury target material and the stainless-steel target structure, leading to a high-pressure region in both the stationary target structure and the flowing mercury. The high-pressure region propagates and leads to fluid-structure interaction. The resultant loading on the target structure containing liquid mercury is difficult to predict, although various simulation approaches and material models for the mercury have been tried. To date, the best match of simulation to experimental data is obtained by using an equation of state (EOS) material model with a specified tensile cutoff pressure, which simulates the cavitation threshold. The inclusion of a threshold to represent cavitation is key to the successful predictions of stress waves triggered by the high-energy pulse striking the mercury and vessel. However, recent measurements of target structure strain show that significant discrepancies remain between the measured and simulated strain values in the EOS mercury model. These differences grow when noncondensable helium gas is intentionally injected into the flowing mercury to reduce the loading on the structure. An EOS-based proportional–integral–derivative (PID) mercury model has been proposed to reduce the gap between the measured and simulated vessel strain responses for targets with gas injection. The conceptual and numerical description and initial investigation of the PID model are presented in previous work. Further studies of this PID model — including the sensitivity of the structure’s strain response to model parameters (the tensile cutoff, PID parameters Kp, Ki, and Kd) — are reported in this article. Results show the strain response is more sensitive to changes in the tensile cutoff value than to changes in the model parameters Kp, Ki, and Kd. These results will aid in future work where the model parameters will be optimized to match simulation data to strain measurements.

Lin, Lianshan↗

DOE OSTI2020

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Volume of distribution at steady state (V D,ss ) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62%–71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted V D,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss but was limited in estimating the compounds with low V D,ss .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Setup and verification of a SCALE/KENO platform for generic FHR benchmark calculations

The work presented in this article is preliminary to downstream analysis of a generic fluoride salt-cooled high-temperature reactor (gFHR) core performed by the University of Tennessee in collaboration with Kairos Power (KP). A Monte Carlo transport model of the publicly available gFHR equilibrium core is developed in SCALE/KENO with multigroup energy treatment. Several output quantities of interest are used to verify the simulations against a benchmark model developed by KP using the continuous energy Monte Carlo code Serpent 2. Good agreement is seen in flux and fission rate profiles with a maximum relative difference of 1.4% and 2.8% respectively. Furthermore, an effective multiplication factor bias of 44 pcm was observed between the two simulations. The fuel temperature reactivity coefficient calculated with SCALE is within uncertainty to the reference model. This verification acts as a publicly reproducible benchmark for the gFHR in SCALE/KENO. A simplified depletion model is also presented where a single fuel pebble is depleted to discharge burnup through the equilibrium core while the equilibrium core is assumed to be invariant. This method produces results that intercept the equilibrium core concentrations in every case, however, an interesting artifact of this particular depletion model is uncovered. The phenomenon is shown to be a fundamental feature of the differential rate equations and inspires questions about how this system behaves when the time evolution of the equilibrium core is considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Alginate–Amorphous Calcium Carbonate Hydrogels for Controlled Therapeutic Release

Alginate hydrogels are widely explored as biocompatible matrices for transdermal delivery of therapeutic compounds but burst release and mechanical stability remain persistent challenges in drug delivery systems. This experimental study investigated alginate–amorphous calcium carbonate (ACC) hydrogel composites designed to regulate release of model anti-inflammatory compound, ibuprofen. Hydrogels containing 1.6–2.0 wt% sodium alginate were crosslinked with CaCl₂ and combined with ACC through two incorporation pathways: (i) separate addition of ACC and ibuprofen or (ii) co-precipitation of ACC onto ibuprofen prior to hydrogel incorporation. Hydrogels without ACC served as Control. Biocomposite structure and properties were characterized and release profiles quantified using Korsmeyer–Peppas (KP) model.Burst release was curbed as crosslinking time increased, highlighting importance of network density in diffusion control. Co-precipitating ACC with ibuprofen prior to incorporating into the hydrogel suppressed burst release and sustained release for > ~72 h. Rheological measurements indicate ACC reinforces hydrogel network, increasing storage modulus while maintaining hydration and flexibility. KP model indicates release is diffusion-controlled, with deviations reflecting contributions from diffusion barriers and morphologic/structural changes near the ACC coated ibuprofen. ACC within alginate hydrogels provides a strategy for tuning drug release while preserving mechanical properties relevant to transdermal applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Analysis and Design for Irradiation of High Power TRISO Fuel Compact Specimens in HFIR

Tristructural isotropic (TRISO) fuel is being proposed for use in several high-temperature advanced reactor concepts because of its structural integrity under high operating temperatures and burnup. One of these advanced reactor concepts is the Kairos Power fluoride salt-cooled high-temperature reactor (KP- FHR) under development by Kairos Power, LLC. Previous TRISO irradiation experiments were focused on qualification for high-temperature gas reactors (HTGRs), which have higher operating temperatures but lower particle powers than the KP-FHR design. To study the performance of TRISO fuel designed for HTGRs under prototypical FHR conditions, a set of experiments was designed using the MiniFuel irradiation vehicle at the Oak Ridge National Laboratory’s (ORNL) High Flux Isotope Reactor (HFIR). The experiments will irradiate 30 TRISO-containing carbon matrix compacts at inner small vertical experiment facilities in HFIR. Each compact will contain 20 TRISO particles (600 particles total) developed for HTGRs, consisting of either 14% enriched uranium dioxide uranium carbide, naturally enriched uranium dioxide, uranium carbide, or 9.6% enriched uranium dioxide fuel kernels with time- and volume-averaged silicon carbide layer temperatures between 500 and 900°C. This report summarizes the vehicle designs that have been developed, as well as the neutronic and thermal analyses completed for these irradiation experiments. These analyses show that MiniFuel compact irradiation is a versatile experiment that can be used to study a range of TRISO particle powers and fuel types while providing reasonable separation of burnup and temperature effects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Thermochemical Modeling in Molten Fluoride Salts for Radionuclide Speciation

An important aspect of the licensing process for nuclear reactors is providing a reasonable assurance of safety to the general public. This includes modeling potential radionuclide releases from the reactor during normal operations and accident scenarios, which is known as the reactor’s source term. A new class of advanced (non-LWR) reactors are being developed which use molten salts as the coolant fluid. Because the molten salt coolant represents a credited barrier for radionuclide transport between the fuel and the environment, a necessary aspect of mechanistic source term (MST) analysis for the KP-FHR is modeling the thermochemistry of molten salts. Provided here is a review of the theory of the thermodynamic principles governing multicomponent phase equilibria, the background of molten salt thermochemistry research, and a summary of the thermochemical data relevant to the KP-FHR coolant salt, Li 2 BeF 4 , commonly referred to as “FLiBe”. A review of literature is followed by a brief introduction to methods that can be used to model the thermochemical behavior of molten salt mixtures. The methodology outlined is based on the use of a commercial thermodynamic modeling software called FactSage, which is one of only a few available softwares based on the modified quasichemical model(MQM), which is the recommended solution model for molten salts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗