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DOE OSTI2022

On the thermal oxidation of nuclear graphite relevant to high-temperature gas cooled reactors

Thermal oxidation of nuclear graphite components is highly undesirable because it can cause structural and property degradation that negatively affect a reactor's intended operation. In this work, the body of knowledge of nuclear graphite oxidation is highlighted, including when O 2 , H 2 O, and/or CO 2 are the oxidant. Oxidation conditions relevant to high-temperature gas-cooled reactors (i.e., when oxidation could occur either as an acute or chronic phenomenon) are emphasized. Here, the objective is to summarize graphite oxidation data in a practical and accessible way to inform future research and regulatory requirements. Although each grade of nuclear graphite is different, the oxidation mechanism has underlying commonalities. Although oxidation behavior is grade dependent, the general temperature dependence is well described by a sequence of elementary steps which become rate limiting. Because the regime transition temperature depends on sample microstructure, size, and oxidant supply rate, extrapolating results beyond the experimental range should be done cautiously. Gravimetric oxidation rate measurements generally replicate well. However, caution must be exercised when rates are estimated by other methods or for samples that deviate significantly in size. Air oxidation data for IG-110, NBG-18, and PCEA graphite is critically reviewed to emphasize this point. Despite the amount of experimental data, gaps remain. Sample size and shape effects are not fully explained. Data on the oxidant penetration depth are insufficient. Analytical assessments demonstrate that lower temperature oxidation does not necessarily imply that oxidation is uniform throughout the bulk. Oxidation occurs faster at higher temperature but is more localized to the exposed surface. Paradoxically, at equal mass loss percentage, low temperature oxidation leads to greater property degradation than at high temperature. The isolated effect of oxidation is important; however, a gap remains in the systematic understanding of any potential effect of neutron irradiation on graphite structure and reactivity.

36 MATERIALS SCIENCE↗

DOE OSTI2025

An integrated approach to examine fuel-cladding chemical interaction in HT9/U-10Zr metallic fast reactor fuels: Coupling machine learning with electron microscopy and local mechanical properties analysis

The metallic U-Zr nuclear fuel alloy has garnered renewed interest as a promising candidate for next-generation sodium-cooled fast reactors. Recent studies and technology assessments have identified several areas requiring improvements, enhanced knowledge, and reliable data to strengthen the U-Zr fuel design basis for qualification and commercial applications. One of the most challenging phenomena impacting this fuel system’s performance is fuel-cladding chemical interaction (FCCI). This work aimed to harvest FCCI data by examining selected HT9/U-10Zr (wt. %) fuel samples of prototypic full-length fuel pins through an integrated approach. This approach integrated scanning electron microscopy (SEM) microstructure characterization with localized mechanical properties examination to deepen understanding of FCCI phenomenon in HT9/U-10Zr fuel system. Particularly, this study focused on MFF fuel pins irradiated at Fast Flux Test Facility (FFTF), which aimed to qualify metallic fuel as a driver fuel for FFTF and to assess its viability for larger-scale fast reactors. Electron microscopy provided high confidence in detecting and distinguishing the different FCCI layers, while small-scale mechanical testing (SSMT) probed the mechanical properties of these layers. SEM examination of a MFF-2 pin 192167, with a time averaged inner cladding temperature (TICT) slightly over 500°C, revealed minimal cladding-side FCCI (cladding wastage). In contrast, significantly thicker cladding wastage comprising two distinct sublayers was observed in samples from the thermally hot MFF-3 pin 193045 and MFF-5 pin 195011 where the TICT ranged from 610-635°C. SSMT indicated complete embrittlement in the sublayer adjacent to the fuel and a tendency toward embrittlement in the other sublayer. Additionally, a new machine learning method was developed, validated, and used to quantify cladding wastage thickness. The machine learning method reliably predicted the wastage thickness across various fuel pins and sample cross-sections. Furthermore, the available cladding wastage data from HT9/U-10Zr fuel system demonstrated a strong temperature dependency. However, the dataset remains small, and ongoing research activities are essential to further understand the FCCI phenomenon and develop a reliable FCCI model for enhanced fuel performance simulation under various conditions.

36 - MATERIALS SCIENCE↗

DOE OSTI2020

Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system

Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. As such, in this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. 137 Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Nuclear waste attributes of near-term deployable small modular reactors

The nuclear waste attributes of near-term deployable SMRs were assessed using established nuclear waste metrics, which are the DU mass, SNF mass, volume, activity, decay heat, radiotoxicity, and decommissioning LLW volumes. Metrics normalized per unit electricity generation were compared to a reference large PWR. Three SMRs, VOYGR, Natrium, and Xe-100, were selected because they represent a range of reactor and fuel technologies and are active designs deployable by the decade’s end. The SMR nuclear waste attributes show both some similarities to the PWR and some significant differences caused by reactor-specific design features. The DU mass is equivalent to or slightly higher than the PWR. Back-end waste attributes for SNF disposition vary, but the differences have a limited impact on long-term repository isolation. SMR designs can vary significantly in SNF volume (and thus heat generation density). However, these differences are amenable to design optimization for handling, storage, transportation, and disposal technologies. Nuclear waste attributes from decommissioning vary depending on design and decommissioning technology choices. Given the analysis results in this study and assuming appropriate waste management system and operational optimization, there appear to be no major challenges to managing SMR nuclear wastes compared to the reference PWR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Nondestructive measurements of residual 235 U mass of Israeli Research Reactor-1 fuel using the Advanced Experimental Fuel Counter

In 2018, a measurement campaign took place with participants from Los Alamos National Laboratory (LANL), the Nuclear Research Centre-Negev (NRCN) and Soreq Nuclear Research Center (SNRC) at the Israeli Research Reactor-1 (IRR-1) in which 14 of the reactor’s used fuel assemblies (FAs) with varied amount of depletion were measured with the nondestructive assay instrument Advanced Experimental Fuel Counter (AEFC). Designed for safeguards purposes, the AEFC measures both neutrons emitted from the FA (passive neutrons) and fission neutrons induced by an external neutron source (in this experiment, 252 Cf). Signals recorded with the AEFC include total neutron count rates (Singles), time-correlated neutron count rates (Doubles), and total gamma-ray count rates. The 235 U content of the FAs was previously assessed by two independent methods: (1) measurement of the transparency of the FA to low-energy gamma rays from an activated rhenium source (rhenium gamma transmission, or the RGT method) and (2) calculation of the 30-year burnup history of the core using detailed three-dimensional Monte-Carlo core depletion calculations. The results from the FAs that had been measured via the RGT method were used to construct the calibration curves, which translate the AEFC count rates to 235 U mass. Then, the calibration was evaluated using AEFC measurements of six additional FAs that were not measured via the RGT method. From the results, it was determined the Doubles calibration curve was more reliable than that of the Singles and follows a simple second-order polynomial fit for the whole range of residual 235 U mass content, albeit with larger statistical uncertainty. Detailed uncertainties quantification was conducted for both the AEFC Singles and Doubles. This includes the analysis of statistical uncertainties, calibration uncertainty, and random uncertainties due to the sensitivity of the AEFC to several sources of uncertainty, namely the FA position, FA orientation, interrogation source position, and ambient pool temperature. Finally, an overall total uncertainty of 6 g of 235 U is estimated for the Singles and Doubles, which is mainly due to calibration uncertainty (for the Singles) and statistical uncertainty (for the Doubles), and which constitutes 3%–6% of the 235 U total mass in the FAs, depending on their level of depletion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Development of the reactor core isolation cooling system model for the extended station black-out accident

In order to accurately predict the behavior of the Reactor Core Isolation Cooling System (RCIC) in the context of the FLEX strategies under the extended station black-out accident (SBO), we present a mechanistic model of the RCIC in this work. The control volume formulation of angular momentum conservation is employed to model the Terry turbine in the RCIC system. The two-phase nozzle flow model developed in the previous work is utilized to simulate the convergent-divergent nozzles in the Terry turbine. A nozzle flow table is generated to cover the operation range of the RCIC during beyond design basis accidents (BDBAs). The mechanistic RCIC turbine-pump model and the nozzle flow table are incorporated in a TRACE BWR model. Simulations of short-term and long-term SBO transients are performed to demonstrate dynamic RCIC responses. A system analysis code with the proposed mechanistic model of the RCIC system will have a better prediction of system safety response during SBO accidents. With the addition of such more realistic models, the system code will be capable of providing expanded understanding of safety margin, which can help help to form the technical basis for the successful implementation of the FLEX and SAMG measures under Extended Loss of AC Power (ELAP) conditions for BWR or PWR reactor designs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Failure investigation and mitigation after experimental research reactor fuel plate deformation in an irradiation device

Experimental research reactor fuel testing is conducted in the Belgian Reactor 2 (BR2) of the Belgian Nuclear Research Centre (SCK CEN) in dedicated irradiation vehicles or rigs. One such vehicle allows flat full-size fuel plates to be irradiated by inserting them into slotted baskets that captures a narrow portion of the longitudinal edges of the plates. The motion of the fuel plates within the baskets is possible within the narrow slots and thus, the plate is considered to be unattached. The design intentionally omits fixing mechanisms of the fuel plates to the baskets to facilitate the inspection and repositioning of the plates between the irradiation cycles and the accommodation of thermal expansion of the plates in the lateral direction. However, loosely inserted fuel plates have weak structural boundary conditions allowing for larger out-of-plane deflections caused by hydrodynamic loads exerted by the flowing coolant, as compared to those of fixed plates. Unexpected large deformations of plates occurred in several irradiation cycles that further resulted in a loss of cladding integrity. These deformations could not be attributed to a single source. This triggered a series of thermal hydraulic, structural, and fluid-structure interaction analyses aiming at understanding the observed phenomenon. The analyses revealed that, for a certain combination of unfavorable manufacturing and assembly tolerances, fuel plate edges could escape out of the slots in the irradiation basket due to the hydrodynamic load. Subsequently, the plate could become wedged inside the basket coolant channel opening. This resulted in reduced coolant flow and accelerated temperature increase and thermal expansion of the plate while under irradiation. This unfavorable feedback loop could then lead to excessive plate surface temperatures, deformed plates and cladding failure, as was observed in the experiments. These analyses not only provided a probable cause of the fuel plate failures, but also resulted in a new and improved design of the irradiation basket to avoid these issues in the future. In conclusion, a series of recent successful irradiations confirm that the sources of failures were identified correctly, and the implemented mitigations were adequate.

BR2↗

DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

DOE OSTI2020

Experimental evaluation of direct current magnetron sputtered and high-power impulse magnetron sputtered Cr coatings on SiC for light water reactor applications

Two types of physical vapor deposition Cr coatings were deposited on chemical vapor deposited SiC coupons using conventional direct current magnetron sputtering (DCMS) and high-power impulse magnetron sputtering (HiPIMS) to mitigate the corrosion of SiC, an advanced fuel and structural material in light water nuclear reactor cores. Coating microstructure was characterized using scanning electron microscopy and scanning transmission election microscopy. X-ray diffraction analysis was conducted for phase identification and qualitative analysis of residual stresses. The mechanical integrity of the coatings was evaluated using scratch testing, micro-indentation, and nano-indentation tests. Additionally, the microstructure of the DCMS coating consisted of fine columnar grains with nanoscale intercolumnar channels, while the HiPIMS microstructure was denser and free of any columnar defects. The DCMS coating showed a small tensile residual stress, while the HiPIMS coating was under compressive stress. Both types of coatings showed good mechanical integrity in terms of ductility and adhesion to the substrate. Corrosion performance of the coatings was assessed with a 30-day high temperature water autoclave test. Both types of coatings formed a protective Cr 2 O 3 surface layer 20-30 nm thick during the autoclave test. In the DCMS coating, the columnar defects provided permeation pathways for water penetration resulting in oxide formation in the intercolumnar regions in the interior of the coating. Overall, both types of Cr coatings offer promise for the mitigation of hydrothermal corrosion of SiC in light water reactor operating environments.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Integration of pH Control into Chi.Bio Reactors and Demonstration with Small-Scale Enzymatic Poly(ethylene terephthalate) Hydrolysis

Small-scale bioreactors that are affordable and accessible would be of major benefit to the research community. In previous work, an open-source, automated bioreactor system was designed to operate up to the 30 mL scale with online optical monitoring, stirring, and temperature control, and this system, dubbed Chi.Bio, is now commercially available at a cost that is typically 1–2 orders of magnitude less than commercial bioreactors. In this work, we further expand the capabilities of the Chi.Bio system by enabling continuous pH monitoring and control through hardware and software modifications. For hardware modifications, we sourced low-cost, commercial pH circuits and made straightforward modifications to the Chi.Bio head plate to enable continuous pH monitoring. For software integration, we introduced closed-loop feedback control of the pH measured inside the Chi.Bio reactors and integrated a pH-control module into the existing Chi.Bio user interface. We demonstrated the utility of pH control through the small-scale depolymerization of the synthetic polyester, poly(ethylene terephthalate) (PET), using a benchmark cutinase enzyme, and compared this to 250 mL bioreactor hydrolysis reactions. The results in terms of PET conversion and rate, measured both by base addition and product release profiles, are statistically equivalent, with the Chi.Bio system allowing for a 20-fold reduction of purified enzyme required relative to the 250 mL bioreactor setup. Through inexpensive modifications, the ability to conduct pH control in Chi.Bio reactors widens the potential slate of biochemical reactions and biological cultivations for study in this system, and may also be adapted for use in other bioreactor platforms.

09 BIOMASS FUELS↗

DOE OSTI2025

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗

DOE OSTI2026

Surface-Initiated Atom Transfer Radical Polymerization Using Hydrogel Reactors

Atom transfer radical polymerization (ATRP) is a controlled radical polymerization method that enables the synthesis of tailored polymeric materials with low dispersity, highlighting its immense potential for green fabrication of advanced materials. However, its broader implementation is limited by challenges in product isolation, maintaining catalyst activity, and mitigating atmospheric sensitivity arising from oxygen-sensitive metal catalysts. Here, gelatin hydrogels (GHs) are introduced as a soft “reactor” matrix for interfacial ATRP, operating with minimal metal-catalyst loading while exhibiting possibly an organoreductive behavior. This strategy leverages activator regeneration via electron transfer through a ligand–metal charge-transfer (LMCT) mechanism to reduce oxidized metal catalysts within the GH network. Polymerization is evaluated by growing polymer brushes at an active interface formed between GHs swollen in monomer solution and an initiating surface, and sequential growth experiments confirmed that GH-mediated ATRP preserves living character. Under UV illumination, LMCT is activated, producing polymers both at the desired interface and within the GH bulk. UV–Vis spectroscopy revealed active reduction of Cu(II) to Cu(I) along with concentration-dependent complex formation, indicating dynamic coordination chemistry within the hydrogel. The redox-active arginine- and glutamic acid-rich gelatin backbone coordinates and reduces the metal center, enabling ATRP at ppm-level catalyst concentrations. While polymerization proceeds in GH-Cu(II) reactors, adding external mobile ligands to the GH results in longer polymer brushes. Here, the results reported here are exploratory. More experiments are needed to characterize polymer brush growth in GHs and compare it to conventional surface-initiated polymerization in solution.

Absorption↗

DOE OSTI2026

Development of Data-Driven Models for Performance Prediction and Chemical Dosing of a Full-Scale Controlled Phosphorus Precipitation Reactor

This study evaluated the use of data-driven models to improve control of a struvite precipitation reactor that removes phosphorus from wastewater while producing a fertilizer product. The researchers developed predictive models for influent orthophosphate concentration, effluent orthophosphate concentration, and phosphorus removal using operational data from a full-scale MagPrex™ reactor at a water resource recovery facility in Denver, Colorado. Model predictions were used to recommend magnesium chloride dosing adjustments needed to achieve a target effluent phosphorus concentration. Several machine learning approaches were tested, with ridge regression providing the best predictions for influent orthophosphate concentration and phosphorus removal, and XGBoost providing the best predictions for effluent orthophosphate concentration. Simulation results indicated that the decision-support approach could correctly identify dosing adjustments in most cases and reduce chemical use. Full-scale implementation achieved lower accuracy due to changing operating conditions and limited historical data in some operating ranges. Here, the results demonstrate the potential of data-driven tools to support phosphorus recovery process control while also identifying practical limitations that affect deployment in full-scale systems.

42 ENGINEERING↗

DOE OSTI2020

Probing the Radial Chemistry of Getter Components in Light Water Reactors via Controlled Electrochemical Dissolution

Getters are among the key functional components in the Tritium Producing Burnable Absorber Rods (TPBARs) of Light Water Reactors, and are used to capture the released tritium gas. They are cylindrical tubes comprised of the alloy zircaloy-4 which is coated with nickel plating both internally and externally. Their exposure to tritium as well as the irradiation environments in the light water reactors changes their structure, chemical composition and chemistry. Understanding the radial tritium distribution is key to gaining insight into the evolution of new chemistry upon irradiation in order to predict getter performance. Consequently, efforts are underway to devise a method that can allow selective probing into the getter core radially to probe the chemistry akin to carefully and selectively peeling of the layers of an onion. We have recently devised an electrochemical dissolution technique for controlled radial dissolution of zirconium based liners; this work describes the first proof-of-concept demonstration of the applicability of this technique on the controlled radial dissolution of nickel plated getters. The technique is complemented with periodic analysis of the electrolyte solution to measure the rates of release of the various elemental components and therefore glean information on their radial distribution across the getter; further complementary microscopy on the exposed surfaces allows us insight into the chemistry at the getter core.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Constraining the impact of chlorine as a neutron absorber in next-gen fast reactor designs

The role of chlorine as a neutron poison and as a seed for producing radioactive waste in nuclear systems has driven a renewed interest to improve its nuclear data uncertainties. Additionally, basic and applied science programs that use CLYC (Cs 2 LiYCl 6 :Ce) detectors for neutron spectroscopy and monitoring are also very sensitive to any change in chlorine nuclear data for simulations of the detector response. In this work, sensitivities relevant for these different applications are addressed through simulations of the efficiency of CLYC detectors in a fast fission spectrum when applying new chlorine nuclear data as input. These simulations are validated by an experimental measurement using CLYC detectors coupled to an ionization chamber loaded with a 252 Cf spontaneous fission source. The results are then used to obtain the first reliable direct measurement of the 35 Cl(n,p 0 ) and summed Cl(n,p+n,α) fission spectrum average cross sections, found to be 54.7(32) and 105.0(98) mb, respectively. The results are within uncertainty of calculated fission spectrum averaged cross sections based on recently re-evaluated chlorine nuclear data, which confirm recent impact studies performed for the Molten Chloride Reactor Experiment. Meanwhile, there currently exists only one published criticality benchmark experiment that is sufficiently sensitive to chlorine nuclear data. Discrepancies are found with this set of criticality safety benchmarks, which are more sensitive to thermal and epithermal neutron energies than the energies, above 100 keV, tested in this current work. Hence, there is still a need to re-evaluate the chlorine nuclear data at lower energies to assess these discrepancies. Interpretation of the data from future “faster” criticality benchmarks, which are needed for next-gen fast reactor designs, benefit from the improved constraints on the chlorine nuclear data validated in this work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Production of renewable alcohols from maple wood using supercritical methanol hydrodeoxygenation in a semi-continuous flowthrough reactor

Biomass conversion to alcohols using supercritical methanol depolymerization and hydrodeoxygenation (SCM-DHO) with CuMgAl mixed metal oxide is a promising process for biofuel production. Here, we demonstrate how maple wood can be converted at high weight loadings and product concentrations in a batch and a semi-continuous reactor to a mixture of C 2 –C 10 linear and cyclic alcohols. Maple wood was solubilized semi-continuously in supercritical methanol and then converted to a mixture of C 2 –C 9 alcohols and aromatics over a packed bed of CuMgAlO x catalyst. Up to 95 wt% of maple wood can be solubilized in the methanol by using four temperature holds at 190, 230, 300, and 330 °C. Lignin was solubilized at 190 and 230 °C to a mixture of monomers, dimers, and trimers while hemicellulose and cellulose solubilized at 300 and 330 °C to a mixture of oligomeric sugars and liquefaction products. The hemicellulose, cellulose, and lignin were converted to C 2 –C 10 alcohol fuel precursors over a packed bed of CuMgAlO x catalyst with 70–80% carbon yield of the entire maple wood. The methanol reforming activity of the catalyst decreased by 25% over four beds of biomass, which corresponds to 5 turnovers for the catalyst, but was regenerable after calcination and reduction. In batch reactions, maple wood was converted at 10 wt% in methanol with 93% carbon yield to liquid products. The product concentration can be increased to 20 wt% by partially replacing the methanol with liquid products. The yield of alcohols in the semi-continuous reactor was approximately 30% lower than in batch reactions likely due to degradation of lignin and cellulose during solubilization. These results show that solubilization of whole biomass can be separated from catalytic conversion of the intermediates while still achieving a high yield of products. However, close contact of the catalyst and the biomass during solubilization is critical to achieve the highest yields and concentration of products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

DBD plasma-thermal tandem reactors for converting biogas to carbon nanofibers

Sequestering greenhouse gases (CO 2 and CH 4 ) in biogas into carbon nanofibers (CNF) offers a promising route to mitigate carbon emissions and create value-added solid carbon materials. Coupling non-thermal plasma with a thermocatalytic reactor in a tandem setup is a promising approach for tandem reactions of dry reforming of methane to synthesis gas and its subsequent conversion to CNF. Various parameters were studied to determine their effects on CNF growth. Decreasing the total flow rate resulted in an increase in CNF growth. Increasing the plasma power input or the plasma zone length also enhanced the production of CNF. These results illustrate that plasma-thermal tandem reactors can be used to synthesize CNF from biogas with tunable parameters that may be further optimized in future studies.

03 NATURAL GAS↗