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DOE OSTI2024

Predicting Anaerobic Membrane Bioreactor Performance Using Flow-Cytometry-Derived High and Low Nucleic Acid Content Cells

Having a tool to monitor the microbial abundances rapidly and to utilize the data to predict the reactor performance would facilitate the operation of an anaerobic membrane bioreactor (AnMBR). This study aims to achieve the aforementioned scenario by developing a linear regression model that incorporates a time-lagging mode. The model uses low nucleic acid (LNA) cell numbers and the ratio of high nucleic acid (HNA) to LNA cells as an input data set. First, the model was trained using data sets obtained from a 35 L pilot-scale AnMBR. The model was able to predict the chemical oxygen demand (COD) removal efficiency and methane production 3.5 days in advance. Subsequent validation of the model using flow cytometry (FCM)-derived data (at time t – 3.5 days) obtained from another biologically independent reactor did not exhibit any substantial difference between predicted and actual measurements of reactor performance at time t. Further cell sorting, 16S rRNA gene sequencing, and correlation analysis partly attributed this accurate prediction to HNA genera (e.g., Anaerovibrio and unclassified Bacteroidales) and LNA genera (e.g., Achromobacter, Ochrobactrum, and unclassified Anaerolineae). In summary, our findings suggest that HNA and LNA cell routine enumeration, along with the trained model, can derive a fast approach to predict the AnMBR performance.

42 ENGINEERING↗

DOE OSTI2022

A Novel Approach to Simulate Realistic Concrete Microstructures under Irradiation

The concrete biological shield of light water reactors is exposed to high neutron and gamma irradiation doses in the long term. Irradiation deteriorates the physical and mechanical properties of concrete. Such effects need to be investigated to predict the concrete’s performance in the event of a lifetime extension of a nuclear power plant. This work combines high-resolution characterization techniques with fast-Fourier transform (FFT)-based 2-D simulations to evaluate the radiation-induced volumetric expansion (RIVE) and damage in concrete microstructures under neutron irradiation. Two concrete microstructures from samples provided by the Japan Concrete Aging Management Program (JCAMP) were characterized using micro x-ray fluorescence (mXRF) to obtain elemental intensity maps, and energy-dispersive x-ray spectroscopy to complement mXRF with local elemental information for Na. Minerals and cement paste are then identified based on the elemental composition to produce high-resolution phase maps, resulting in a more accurate representation of the microstructures compared to previous work. Simulations of radiation-induced volumetric expansion (RIVE), creep, and damage in JCAMP concrete use the fast Fourier transform (FFT)-based code Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) combined with the irradiated minerals, aggregates, and concrete (IMAC) database, which contains mineral-specific RIVE models. Overall, the simulation results are in fair agreement with experimental data.

Cheniour, Amani↗

DOE OSTI2025

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Mechanisms and kinetics of citrate-promoted dissolution of a uranyl phosphate mineral

The formation of uranyl phosphate precipitates is a remediation strategy to limit the mobility of uranium in contaminated soils. However, exposure to organic ligands, like the plant exudate citrate, can remobilize the uranium. The purpose of this study is to provide a more thorough comprehension of citrate-promoted dissolution of a uranyl phosphate mineral, chernikovite [(H 3 O)(UO 2 )(PO 4 )·3H 2 O], by determining the extent of uranium release from chernikovite at a wide range of citrate concentrations. Here we have quantified the kinetics of dissolution and proposed potential mechanisms of chernikovite dissolution to gain a better understanding of the fate of uranyl phosphate precipitates in the environment. Batch dissolution and continuously stirred tank reactor (CSTR) experiments indicate that increasing citrate concentrations from 0.1 mM to 50 mM increases the concentration of dissolved uranium. However, at citrate concentrations of 10 mM and greater, the effectiveness of the ligand to enhance the dissolution decreases. Density functional theory modeling and Raman spectroscopy indicate a strong interaction between citrate and the uranyl ions at the surface of the uranyl phosphate. The interaction between citrate and uranyl suggests the formation of an alteration layer of uranyl-citrate surface complexes, which could impede uranium release at citrate concentrations of 10 mM or higher. Together, these results indicate that the citrate-promoted dissolution of chernikovite is a fast reaction that is hindered by a combination of surface saturation and a secondary-phase precipitation reaction at higher concentrations of citrate and reaction times greater than or equal to 72 min based on the hydraulic residence time of CSTR experiments. These findings improve our understanding of the stability of uranyl phosphate for use in sequestration of uranium groundwater plumes at contaminated sites.

58 GEOSCIENCES↗

DOE OSTI2026

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

The daily as-run thermal analysis for the Advanced Gas Reactor (AGR)-5/6/7 experiment was documented in ECAR-5633 (Hawkes 2021). A finite element model was created for the entire test train, which consisted of five capsules. The fuel compacts, graphite holders, stainless-steel capsule walls, and all other major components were individually modeled, including all thermocouples (TCs). Daily heat rates for each compact and component in the model were input from daily as-run physics analyses. Daily gas compositions for each capsule were also input. The thermal conductivity of the compacts and graphite holders varied with fast neutron fluence. Gas mixture thermal conductivity was implemented using experimentally attained values from the literature. Fluence and temperature-dependent thermal conductivity was used for the graphite components and the fuel compacts. Radiation heat transfer was implemented. The model was tuned in an attempt to match the TC readings during the first cycle by adjusting the Neolube (graphite lubricant) thickness.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

BETO 2021 Peer Review - Thermochemical Platform Analysis WBS: 2.1.0.302

The objective of the NREL Thermochemical Platform Analysis (WBS 2.1.0.302) project is to inform and guide R&D priorities for thermal and catalytic conversion processes by providing process design and techno-economic analysis (TEA). This is achieved through close collaboration with researchers and external experts, along with the use of both commercially available modeling tools and the development or use of collaboration-derived domain-specific tools and resources, such as refinery integration, kinetic and reactor models, phase equilibrium models, and pertinent bio-products market studies. This project is directly aligned with DOE-BETO goals, with the enabling of technology advancements and cost reduction for biomass derived biofuels being one of its primary objectives. TEA-guided research facilitated by this project has helped achieve significant modeled cost reductions for the ex situ catalytic fast pyrolysis (CFP) pathway and the indirect liquefaction (IDL) pathway for the conversion of syngas to high-octane gasoline (HOG). Cost reduction through refinery integration, development of valuable co-products, and other options are being identified for future research to help reduce the modeled MFSP to $2.50/GGE by 2030. Additional priorities anticipated in the future, such as the use of renewable electricity for liquid fuels and products, and emphasis on waste utilization are also being explored in conjunction with research on catalytic utilization of syngas and other gases (including CO2). Industry-relevant parameters are given deliberate attention as part of the work done under this project to help answer questions important for future commercialization and address associated risks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Microwave catalytic conversion of acetylene for co-production of hydrogen and carbon nanotubes

Natural gas conversion to hydrogen and solid carbon can drastically reduce the carbon footprint. Microwave plasma pyrolysis is an emerging process for chemical industries to directly convert methane (CH 4 ), the major component of natural gas, to hydrogen and carbon, which offers benefits such as fast process dynamics, flexibility, and high product yield. However, the formation of unwanted by-products, like acetylene (C 2 H 2 ), will require extra cost for gas separation. Plasma pyrolysis of CH 4 produces large amount of acetylene at downstream, which is currently used mainly for welding. Here, to avoid gas separation and upgrade acetylene from the downstream of methane plasma reactor, a novel approach toward its transformation to carbon nanotubes (CNT) and pure hydrogen (H 2 ) over Ni-based bimetallic catalyst driven by microwave irradiation has been reported in this work. The dominant gas product was hydrogen. Low concentrations of methane, ethane, and ethylene were observed in the product stream. Catalytic acetylene decomposition was carried out at 400 °C over Al 2 O 3 supported Ni catalyst. The results showed that, at 400 °C, acetylene was dehydrogenated to CNT and hydrogen was the dominant gas in product stream over 10Ni-1Pd-Al 2 O 3 catalyst. Characterizations of spent catalysts was conducted using Raman spectroscopy and transmission electron microscopy (TEM) to investigate the properties of carbon deposited over the catalyst during the catalytic acetylene decomposition. The results highlight that methane can be efficiently converted to hydrogen and CNT through 2-step process, microwave plasma and microwave catalytic conversion of intermediate acetylene, operated in a single reactor system driven by microwave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Lowering the reactor breakeven requirements for proton–boron 11 fusion

Recently, it has been shown that altering the natural collisional power flow of the proton–boron 11 (pB11) fusion reaction can significantly reduce the Lawson product of ion density and confinement time required to achieve ignition. However, these products are still onerous—on the order of 7×1015 cm−3 s under the most optimistic scenarios. Fortunately, a breakeven fusion power plant does not require an igniting plasma, but rather a reactor that produces more electrical power than it consumes. Here, we extend the existing 0D power balance analysis to check the conditions on power plant breakeven. We find that even for the base thermonuclear reaction, modern high-efficiency thermal engines should reduce the Lawson product to 1.2×1015 cm−3 s. We then explore the impact of several potential improvements, including fast proton heating, alpha power capture, direct conversion, and efficient heating. We find that such improvements could reduce the required Lawson product by a further order of magnitude, bringing aneutronic fusion to target ITER ion densities and confinement times.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Electrochemically modulated molten salt reactor

An electrochemically modulated molten salt reactor (EMMSR) that contains a vessel and a power source. The vessel houses a fuel salt, at least a portion of a neutron moderator, and at least a portion of an insulator. The fuel salt includes enough dissolved fissile isotopes to cause continued self-sustaining fission reactions during the operation of the EMMSR. The neutron moderator is configured to slow down fast neutrons produced by the dissolved fissile isotopes. The insulator is configured to electrically isolate the neutron moderator from the vessel. The power source has a positive potential and a negative potential. The positive potential is received by the neutron moderator and the negative potential is received by the vessel.

Jiang, Junhua↗

DOE OSTI2025

FIDES-II/P2M Simulation Exercise on AN3 and AN10 bump tests: main results

This paper presents simulations of bump tests conducted as part of the P2M (Power to Melt and Maneuverability) project within the OECD/NEA FIDES-II framework (Framework for Irradiation Experiments). To prepare fuel performance codes for analyzing the P2M experiments, an international Simulation Exercise (SE) was initiated under the P2M project. The objective of this exercise was to model the AN3 and AN10 bump tests carried out in the 1980s at the DR3 reactor (3rd RISØ Fission Gas Project), during which instrumented fuel rodlets (equipped with thermocouples and pressure sensors) were subjected to prolonged power transients and power dips. The ongoing simulation exercise involves seven organizations from industry, research, and regulatory bodies, each using different fuel performance codes. This paper provides detailed descriptions of the test cases and simulation results from six fuel performance codes (ALCYONE, BISON, FAST, FEMAXI, FRAPCON, and TRANSURANUS), with a particular focus on fission gas release kinetics.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

The high-yield direct synthesis of dimethyl ether from CO 2 and H 2 in a dry reaction environment

Direct dimethyl ether (DME) synthesis from CO 2 and H 2 is considered a promising production route. However, this process is thermodynamically and kinetically restricted by the presence of water as a byproduct. In this study, a water-conduction membrane was incorporated into the direct DME synthesis reactor to generate a dry reaction environment. In the absence of water, the activities of the CO 2 hydrogenation catalyst (CZA) and methanol dehydration catalyst (HZSM-5) were boosted 4- and 10-fold, respectively, and single-pass CO 2 conversion of up to 73.4%, far beyond equilibrium, and DME yields of up to 54.5% were obtained. Moreover, the good protection of the catalysts against fast deactivation was demonstrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

NCERC-CL TREAT Free Field Characterization Foil Reaction Rate Results

This report summarizes the analysis and preliminary MCNP reaction rate modeling of free field characterization measurements performed in the Transient Reaction Test Facility (TREAT) at Idaho National Laboratory (INL) between 12/18/2023 and 2/22/2024. A series of seven irradiations were performed using the Big-BUSTER (Broad Use Specimen Transient Experiment Rig) core configuration. Foil sets including 19.5% LEU-Zr alloy wire, S, Au, Fe, Ni, Co, Ti, and Zr were deployed in each irradiation. Identical foil sets were supplied to Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and INL. All foils were supplied by INL. Additional details on the experiment can be found in [2]. The foil sets were shipped to the National Criticality Experiments Research Center Counting Laboratory (NCERC-CL) branch at LANL (NCERC-CL NISC) and were received on 3/25/2024. Additional details on receipt and counting are reported in [3]. All reactor dosimetry measurements were performed in adherence to the ASTM standards applicable to reactor dosimetry. Measured reaction rates from Au, Co, Fe, Ni, and Ti are reported. Select reaction rate ratios and simulated reaction rates and ratios are discussed. Reaction rates for all measured reaction products were modeled with MCNP 6.3.1 and a TREAT input deck supplied by Edward Lum. Neutron emission estimates calculated using the measured and simulated reaction rates show excellent agreement between the three fast-threshold n-p reactions with the percent differences being < 9% between the three reactions. The capture reactions had poorer, but still reasonable, agreement with < 20% percent differences between the neutron emission estimates of the three capture reactions. The percent difference between the fast-threshold and capture reactions is ∼ 100% for each reaction. This supports the TREAT model is not accurately modeling the neutron spectrum and additional measurements are required to characterize TREAT and match measurements to simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Investigation of irradiation damage and heat deposition: a comparative analysis for HEU-to-LEU conversion in HFIR

The planned conversion of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel requires detailed evaluation of experiment-relevant parameters to ensure continued performance for materials testing and isotope production. Here, this study presents the first comprehensive assessment of displacements per atom (dpa) and heat deposition rates in target materials within the HFIR flux trap with both HEU and candidate LEU core configurations. Seven analyses were conducted to evaluate key performance metrics, including fast neutron flux distribution, cross section response functions, cross section data, and local dpa and heat deposition rates using mesh- and cell-based tallies. Simulations employed Shift, Monte Carlo N-Particle (MCNP), and the HIFR Controller (HFIRCON) tool suite for high-fidelity transport and depletion modeling. The LEU designs—using U 3 Si 2 -Al dispersion fuel and operating at 95 MW—were compared to the current 85 MW HEU configuration. Results show that while the candidate LEU cores exhibit higher dpa rates due to a harder spectrum and extended cycle lengths, they also demonstrate reduced heat deposition rates in irradiation experiments, primarily due to increased gamma self-shielding from higher 238 U content in the core. These findings confirm that LEU conversion can maintain HFIR’s materials irradiation capabilities but may require redesigning existing experimental hardware.

HEU↗

DOE OSTI2023

Volume 4: Detection Systems and Ultra-Cold Neutrons

As part of the Sustaining and Enhancing Nuclear Science (SENSe) initiative at Oak Ridge National Laboratory (ORNL), the prospect of adding new detection systems to support High Flux Isotope Reactor (HFIR) operations and to advance scientific research has prompted many ideas and discussions regarding potential features, configurations, locations, and applications. A working group of ORNL staff members was organized to further develop the concepts and recommending one or more configurations to best support future HFIR operations and scientific capacities and to provide order-of-magnitude cost estimates and timing. The areas of investigation included fast access detection systems, non-scattering beamline instruments, shielded detection instruments, and an ultracold neutron source. In each case, the focus was to develop world leading capabilities that would be unmatched by any other facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Opening pathways for the conversion of woody biomass into sustainable aviation fuel via catalytic fast pyrolysis and hydrotreating

Meeting aggressive decarbonization targets set by the International Civil Aviation Organization (ICAO) will require the rapid development of technologies to produce sustainable aviation fuel (SAF). Catalytic fast pyrolysis (CFP) can support these efforts by opening pathways for the conversion of woody biomass into an upgraded biogenic oil that can be further processed to SAF and other fuels. However, the absence of end-to-end experimental data for the process leads to uncertainty in the yield, product quality, costs, and sustainability of the pathway. The research presented here serves to address these needs through a series of integrated experimental campaigns in which real biomass feedstocks are converted to a final SAF product using large bench-scale continuous reactor systems. For these campaigns, the degree of catalytic upgrading during CFP was varied to produce CFP-oils with oxygen contents of 17 and 20 wt% on a dry basis. The CFP-oils were then hydrotreated and distilled into gasoline, diesel, and SAF fractions. Detailed yield and compositional data were obtained for each step of the process to inform technoeconomic and lifecycle analyses, and the fuel properties of the SAF fraction were evaluated to provide first-of-its-kind insight into the quality of the final product. This research reveals opportunities to optimize process carbon efficiency by tuning the degree of catalytic upgrading during the CFP step and highlights routes to produce a high-quality cycloalkane-rich SAF with 85–92% reduction in greenhouse gas emissions compared to fossil-based pathways.

09 BIOMASS FUELS↗

DOE OSTI2021

Initial use of Nek5000/Cardinal to improve closure models in Pronghorn

Heat transfer coefficient closure models for pebble bed reactors are built using a data-driven approach by leveraging the capabilities of an Evolutionary Algorithm entitled Particle Swarm Optimization (PSO). In the present work, the Computational Fluid Dynamics code nekRS was used in order to collect the high-fidelity flow data for a core with 1,568 pebbles. To characterize the heat transfer, multiple concentric regions were considered to extract the physical quantities of interest, e.g./ the Reynolds number. The PSO algorithm is employed as part of an inverse problem targeting determine what are the coefficients for a Nusselt number correlation to match the collected data. Such correlation should follow any given format that is defined a priori. Finally, two correlations are proposed, one with an implicit dependence on the pebbles’ wall temperatures and another expressed as a fully explicit correlation depending on the flow conditions and the position within the core. Anyway, given the generic nature of the proposed approach, correlations following different formats could be tested. Preliminary results for the high-fidelity simulation of a fast MSR core are presented. The target Reynolds number is currently 20K, with the expectation that this will increase, pending the availability of further computational resources. These simulations will be used to inform lower fidelity models, including a coarse CFD turbulence model in Pronghorn. Additionally, they will serve as a reference for the RANS models in Nek5000/NekRS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Integrated modeling of alpha particle losses in JET DT plasmas

Alpha particle confinement is crucial for sustaining burning plasmas and designing future reactor concepts. Along with classical/prompt losses, various magnetohydrodynamic instabilities can lead to wave-particle interactions which can transport alpha particles outward from the plasma. This can result in a reduction in plasma heating/performance, and, at worst, damage in-vessel components. Joint European Torus’s recent deuterium–tritium campaigns in 2021–2023 have produced numerous alpha particle loss measurements with its scintillator probe and Faraday cup array fast ion loss detectors as discussed in Bonofiglo et al (2024 Nucl. Fusion 64 096038). This paper will report on integrated energetic particle transport modeling in support of those measurements. The modeling is accomplished with the TRANSP and ORBIT-kick codes with the use of recently developed reduced models which calculate mode structure, amplitude, and the evolving dynamics. When possible, constraints and comparisons to experiment are conducted. Case studies are performed on a variety of magnetohydrodynamic activity, including: fishbones, tearing modes (TMs), and sawtooth crashes. Additionally, a special case of an alpha-driven toroidal Alfvén eigenmode is briefly discussed, where modeling showed marginally weak alpha losses and was unable to support experimental observations. Coupled effects between a TM and toroidal field ripple are presented and were unable to replicate the observations in lost particle pitch but did duplicate the localized flattening of the measured neutron profile. Additional modeling results compare the magnitude of losses and energy/velocity-space sensitivities against experimental observations/measurements for each scenario. This work corroborates numeric alpha transport modeling while also identifying model deficiencies. While this report details alpha transport, it also presents open issues for discussion in assessing the validity of our numerical models towards burning plasmas.

Bonofiglo, Phillip J. [Princeton Plasma Physics La↗