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At least 379 records · Page 21

System Integration of Rationally Designed Dilute Alloy Catalysts for Energy-Efficient Electrochemical CO 2 -To-Fuel Conversion

Energy effiecient electrochemical conversion of CO 2 to high-demand chemicals and transportation fuels using renewable solar and wind energy is a key technology needed for a high-productivity, low-carbon future. However, the development of scalable, low-cost, active, selective, and stable electrocatalysts remains a key challenge that needs to be overcome to enable high-volume conversion of CO 2 to feedstock chemicals for the chemical industry. In previous work, Lawrence Livermore National Laboratory (LLNL) has developed a rational design platform for dilute alloy transition metal electrocatalysts that promise to make electrochemical CO 2 conversion more energy efficient and selective. In this project, we worked with our industrial partners, Twelve and TotalEnergies, to improve scale up, integration, and stability of LLNL’s dilute alloy catalyst technology into an industry-relevant zero gap electrolyzer platform. Through virtual experiments and data analysis, we designed efficient and cost-effective copper-based catalysts. The catalyst was specifically designed to streamline the slowest and most energy-intensive step of the electrochemical chemical transformation of CO 2 to multi-carbon products – that is making the carbon-carbon bond by dimerization of the reaction intermediate carbon monoxide - resulting in up to 10% improvement in energy efficiency for C 2 products while simultaneously increasing the selectivity towards C 2 products. We tested two different scalable catalyst coating technologies and down-selected magnetron sputtering as the technique that provided the best control over catalyst loading, composition, and morphology. Using this technology, we successfully demonstrated integration of our dilute alloy catalysts into a 100 cm 2 electrolyzer platform with Faradaic efficiencies for ethylene production reaching 40% at a current density of 200 mA/cm 2 . We also developed the technology to integrate a well-defined nanoscale porosity by depositing alloy compositions that were compatible with dealloying, that is, selective leaching of an alloy component to generate nanoscale porosity. We observed that integration of the dealloying-derived nanoporosity improved catalyst performance and stability by leading to a more hydrophobic catalyst/anion exchange membrane interface. Unsolved problems that still need to be addressed are corrosion of the Cu catalyst -specifically if the used catalyst is exposed to air - as well as long term stability do to salt formation/deposition and flooding of the catalyst/electrolyzer flow channels, especially at higher current densities. As we only worked on optimization of catalyst composition, coating thickness, and morphology, further performance optimization will require a system level approach that includes optimization of electrolyzer design and membrane technology.

36 MATERIALS SCIENCE↗

A Spectroscopic Study of Mars-analog Materials with Amorphous Sulfate and Chloride Phases: Implications for Detecting Amorphous Materials on the Martian Surface

The Chemistry and Mineralogy X-ray diffraction (XRD) instrument aboard the Curiosity rover consistently identifies amorphous material at Gale Crater, which is compositionally variable, but often includes elevated sulfur and iron, suggesting that amorphous ferric sulfate (AFS) may be present. Understanding how desiccating ferric sulfate brines affect the spectra of Martian material analogs is necessary for interpreting complex/realistic reaction assemblages. Visible and near-infrared reflectance (VNIR), mid-infrared attenuated total reflectance (MIR, FTIR-ATR), and Raman spectra, along with XRD data are presented for basaltic glass, hematite, gypsum, nontronite, and magnesite, each at three grain sizes (<25, 25–63, and 63–180 μm), mixed with ferric sulfate (+/–NaCl), deliquesced, then rapidly desiccated in 11% relative humidity or via vacuum. All desiccated products are partially or completely XRD amorphous; crystalline phases include starting materials and trace precipitates, leaving the bulk of the ferric sulfate in the amorphous fraction. Due to considerable spectral masking, AFS detectability is highly dependent on spectroscopic technique and minerals present. This has strong implications for remote and in situ observations of Martian samples that include an amorphous component. AFS is only identifiable in VNIR spectra for magnesite, nontronite, and gypsum samples; hematite and basaltic glass samples appear similar to pure materials. Sulfate features dominate Raman spectra for nontronite and basaltic glass samples; the analog material dominates Raman spectra of hematite and gypsum samples. MIR data are least affected by masking, but basaltic glass is almost undetectable in MIR spectra of those mixtures. NaCl produces similar FTIR-ATR and Raman features, regardless of analog material.

58 GEOSCIENCES↗

Corrosion of Zinc Cold Spray Coatings in a Wet Sweet and Sour Gas Environment

Internal corrosion is a problem for steel pipelines transporting natural gas or CO 2 containing water and partial pressures of H 2 S higher than 0.3 kPa (0.05 psi). This work aims to mitigate internal corrosion in steel pipelines transporting natural gas containing H 2 S using cold spray coatings. Two types of the cold spray binary metallic coatings (zinc chromium [ZnCr]. zinc niobium [ZnNb]) were studied using electrochemical techniques: potentiodynamic polarization, linear polarization resistance, and electrochemical impedance spectroscopy. The corrosion resistance of cold spray coatings (ZnCr, ZnNb) was evaluated in an environment containing 4 bar CO 2 pressure, simulating the partial pressures found in gas transmission lines over a solution of 3.5 wt% NaCl heated to 40°C. A concentration of 0.003 M Na 2 S 2 O 3 ·5H 2 O, corresponding to H 2 S partial pressures around 0.079 bar (1.146 psi), was used to simulate sour conditions. Postcorrosion surface characterization was performed using a scanning electron microscope (SEM) equipped with an energy-dispersive x-ray spectroscope (EDS) and x-ray diffraction analysis. The data showed that the presence of 0.003 M Na 2 S 2 O 3 ·5H 2 O shifted the corrosion potential to more anodic values and decreased the corrosion current density. Both coatings showed similar behavior after 1 h of exposure in the CO 2 /H 2 S environment, indicating that similar electrochemical reactions were occurring on ZnNb and ZnCr. SEM images and EDS surface analyses for specimens showed a significant change in the surface chemical composition of carbon steel coated with ZnNb and ZnCr after 24 h of immersion. In the presence of thiosulfate (under sour conditions), the formation of corrosion product layers (ZnCO 3 and ZnS) on top of ZnNb and ZnCr coatings increased their corrosion resistance, which helped to reduce their corrosion by a factor of 2. Under a sweet environment, the corrosion rates for steel coated with cold spray coatings after 14 d of exposure are lower than that for galvanized steel by a factor of 5 due to the ZnCO 3 layer formed on top of the coatings. The ZnCO 3 layer formed on the steel surface acts as a physical barrier against corrosion by blocking the diffusion of corrosive species to the surface. No localized attack was observed. ZnCr Cold spray coating with defect showed promising corrosion protection against CO 2 corrosion (sweet corrosion) after 14 d of exposure to a CO 2 environment. Here, the scratch on the coating simulated damage created in service, and it was deep enough to expose the substrate material (steel). The formation of zinc oxide (ZnO) and zinc carbonate (ZnCO 3 ) on the scratch confirmed the cathodic protection of the steel by ZnCr and ZnNb coatings.

36 MATERIALS SCIENCE↗

Measurement of f1(1285) production in pp collisions at $\sqrt{s}$ = 13 TeV

This study presents the first measurement of the f 1 (1285) resonance using the ALICE detector in inelastic proton–proton collisions at a center-of-mass energy of 13 TeV. The resonance is reconstructed at midrapidity (|y| < 0.5) through the hadronic decay channel f 1 (1285)→ K$^0_S$K ± π ± . Key measurements include the determination of its mass, transverse-momentum integrated yield, and average transverse momentum. Additionally, the ratio of the transverse-momentum integrated yield of f 1 (1285) to pion is compared with calculations from the canonical statistical hadronization model. The model calculation, assuming a zero total strangeness content for f 1 (1285), reproduces the data within 1σ deviation, shedding light on the quark composition of f 1 (1285).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Product consistency test results for the LAW Phase 4 gases

In this report, the Savannah River National Laboratory provides chemical analysis of Product Consistency Test (PCT) leachates from a series of simulated nuclear waste glasses fabricated at the Pacific Northwest National Laboratory (PNNL). The series included quenched and canister-centerline cooled (CCC) versions of the glasses. The resulting data will be used in the development of enhanced property/composition models for waste vitrification at Hanford. For some of the glass leachates, minor scatter among the triplicate values of some analytes were observed. For other leachates, there were more significant differences among the triplicate values. A review of the PCT data noted that there was little difference between the normalized values based on targeted or measured glass composition. Several of the study glasses have normalized concentration of element “i” (NCi) values that are greater than the Hanford Tank Waste Treatment and Immobilization Plant immobilized low-activity waste constraint of 4 g/L for boron (B), sodium (Na), and silicon (Si). The results of these glasses will help ensure the ability of advanced glass performance models to appropriately predict acceptable compositions. For the study glasses with NCi values exceeding 4 g/L, the CCC heat treatment samples had generally lower NCi values than quenched samples. The samples of the Environmental Assessment (EA) reference glass included with each PCT set had generally consistent NCi values. The release rates for boron (B), potassium (K), lithium (Li), sodium (Na), and silicon (Si) were highly correlated for the study glasses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Product Consistency Test Results for the LAW HPVR Glasses

This report summarizes the chemical analysis of Product Consistency Test (PCT) leachates received from Pacific Northwest National Laboratory (PNNL). The leachates are from a series of simulated nuclear waste glasses designated Low-Activity Waste High PCT and VHT Response (LAW HPVR) glasses that were designed and fabricated at PNNL. The glasses included both quenched and canister centerline cooled glasses. The reported data will be used in the development, validation, and implementation of enhanced property/composition models for waste glass vitrification at Hanford. The elemental release for the study glasses is reported as normalized concentration (NC i ). NC i of several elements was computed for both the target and measured glass compositions, which were similar, resulting in no significant differences when computing the NC i values. The majority of the glasses exhibited NC B , NC Na , and NC Si values that were greater than the Hanford Tank Waste Treatment Plant (WTP) low-activity waste constraint of 4 g/L. Several blank solutions included with the study glasses had K, Na, and Si concentrations above the analytical detection limit. Additionally, several of the reference glasses that were included with the study glasses had Na concentrations that were higher than expected. The unexpected analyte concentrations in the reference glass and blank solutions were insignificant with respect to the reported NC i values, and are noted for completeness and their experimental relevance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GRIDCERF - Geospatial Raster Input Data for Capacity Expansion Regional Feasibility

The Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package is a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers hundreds of individual suitability layers for use with both renewable and non-renewable power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions. GRIDCERF data can be directly used with the CERF (Capacity Expansion Regional Feasibility) model to site power plants at a 1km resolution. GRIDCERF includes composite technology siting suitability raster layers for the following utility scale technology configurations. Note that, in addition to technology sub-types shown below, various cooling types are also included (recirculating, pond, once-through, recirculating-seawater, dry-hybrid, or dry) for various technologies. Biomass Conventional (with or without CCS) IGCC (with or without CCS) Coal Conventional (with or without CCS) IGCC (with or without CCS) Natural Gas Combined-cycle (CC) (with or without CCS) Turbine Geothermal Enhanced Geothermal Systems (EGS) - Class 1 through Class 5 resource potential Nuclear Gen 2 Light Water Reactor (LWR) Gen 3 Small Modular Reactor (SMR) Gen 3 AP1000 Refined Liquids Combined-cycle (CC) (with or without CCS) Turbine Solar Photovoltaic (PV) - for capacity factors in the range of 6-18% Utility-scale Concentrating Solar Power (CSP) - for capacity factors in the range of 24-46% Tower Wind (Onshore) - for capacity factors in the range of 5-50% 80m hub height 100m hub height 120m hub height 140m hub height Wind (Offshore) - for capacity factors in the range of 25-60% 100m hub height 140m hub height 160m hub height

capacity expansion↗

GRIDCERF - Geospatial Raster Input Data for Capacity Expansion Regional Feasibility

The Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package is a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers hundreds of individual suitability layers for use with both renewable and non-renewable power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions. GRIDCERF data can be directly used with the CERF (Capacity Expansion Regional Feasibility) model to site power plants at a 1km resolution. GRIDCERF includes composite technology siting suitability raster layers for the following utility scale technology configurations. Note that, in addition to technology sub-types shown below, various cooling types are also included (recirculating, pond, once-through, recirculating-seawater, dry-hybrid, or dry) for various technologies. Biomass Conventional (with or without CCS) IGCC (with or without CCS) Coal Conventional (with or without CCS) IGCC (with or without CCS) Natural Gas Combined-cycle (CC) (with or without CCS) Turbine Geothermal Enhanced Geothermal Systems (EGS) - Class 1 through Class 5 resource potential Nuclear Gen 2 Light Water Reactor (LWR) Gen 3 Small Modular Reactor (SMR) Gen 3 AP1000 Refined Liquids Combined-cycle (CC) (with or without CCS) Turbine Solar Photovoltaic (PV) - for capacity factors in the range of 6-18% Utility-scale Concentrating Solar Power (CSP) - for capacity factors in the range of 24-46% Tower Wind (Onshore) - for capacity factors in the range of 5-50% 80m hub height 100m hub height 120m hub height 140m hub height Wind (Offshore) - for capacity factors in the range of 25-60% 100m hub height 140m hub height 160m hub height

capacity expansion↗

Electricity use in big area additive manufacturing of fiber-reinforced polymer composites

In recent years, additive manufacturing (AM), especially large-format additive manufacturing (LFAM), has gained momentum in the manufacturing industry. While LFAM offers benefits over conventional manufacturing processes, such as minimizing material waste and providing vast geometric freedom, assessing its sustainability remains challenging due to limited data, particularly on energy consumption. Most existing data pertain to small-scale or desktop AM and are not directly applicable to LFAM. In this study, we conducted real-time measurements of electricity usage for a type of LFAM known as big area additive manufacturing (BAAM), which typically uses fiber-reinforced polymer pellets as feedstock. We collected electricity usage data from fifteen printing jobs over two months in an industrial production setting. These data fill the existing gap and can be reused to enhance the community’s understanding of LFAM electricity usage, support further research, and promote sustainable development in advanced manufacturing technologies.

ecology↗

Recent and future developments in pultrusion technology with consideration for curved geometries: A review

Herein this paper examined the current state and future developments in pultrusion with particular emphasis on its application in curved part manufacturing. The relationship between factors such as resin chemistry, fiber characteristics, and die geometry that influences the properties of pultruded product were highlighted. Moreover, the specific challenges associated with pultruding curved parts such as the complexities in achieving uniformity and structural integrity in such geometries were discussed. The review emphasized mold design, process improvement, adaptive control systems for precise resin impregnation and material selection to address these challenges. Additionally, the paper suggests the integration of real-time monitoring and data analytics as ways to enhance quality control during curved parts pultrusion. These advancements will help to overcome challenges specific to curved pultrusion and make the process more efficient. Other manufacturing techniques such as filament winding, thermoforming, pulforming were mentioned as alternatives to curved parts pultrusion. The review also explores pultruded variable curvature processes, highlighting some notable patents and article related to this subject matter. Production of pultruded variable curvature parts was seen as a key driver that can shape the future of pultrusion. Finally, the paper anticipates future trends, with sustainability, customization, integration of advanced materials, and development of techniques for pultrusion of composites parts.

42 ENGINEERING↗

Uncertainty analysis of Raman spectra for measuring ortho-parahydrogen compositions

Determining ortho-parahydrogen compositions at cryogenic temperatures is an important quality control for liquid hydrogen custody exchange. High orthohydrogen compositions lead to an exothermic reaction resulting in increased boil off and increased venting losses of liquid hydrogen product by either the supplier or consumer. Traditional methods for measuring ortho-parahydrogen compositions such as hot-wire anemometry, nuclear magnetic resonance, and infrared spectroscopy are typically inconvenient at best. As the number of cryogenic hydrogen systems continue to increase, there is an increased need for flexible, standardized techniques for post processing composition measurements. A Raman spectrometer implemented in the Cryo-Catalysis Hydrogen Experimental Facility (CHEF) has demonstrated incredible flexibility for composition measurements of cryogenic hydrogen flows through a wide range of temperatures and pressures with the Raman probe in-situ at cryogenic temperatures. This article analyzes the uncertainty of Raman spectroscopy data of cryogenic hydrogen equilibrated at temperatures in IONEX catalyst. Spectra from hydrogen catalyzed to the equilibrium ortho-parahydrogen composition are processed and compared to expected statistical distributions for method verification.

08 HYDROGEN↗

Transmission electron microscopy investigation of phase transformation and fuel constituent redistribution in neutron irradiated U-10wt.%Zr fuel

Uranium-10wt.%zirconium (U-10wt.%Zr) is a primary candidate for fast reactor nuclear fuels. However, there is a lack of data characterizing neutron irradiated crystallographic phases and chemistry. In the current study, the microstructural evolution of a U-10wt.%Zr fuel neutron irradiated to a burnup of 5.7 at.% was investigated by scanning transmission electron microscopy, energy dispersive spectroscopy, and selected area electron diffraction to determine the major phases, alterations in microstructure, and variations in local chemical composition at different localities of a fuel cross-section. The current study revealed that the irradiated U-10wt.%Zr fuel was comprised of various major phases, including a-U, ß-U, and d-UZr2, as well as amorphous and crystalline solid fission product (FP) precipitates within different regions of the fuel cross-section. Regions A and A/B in the center of the fuel were comprised of U-rich, U-intermediate, and U-lean localities with a-U and d-UZr 2 composing the major phases. Regions B and C in the intermediate and peripheral fuel localities, respectively, were comprised of a-U grains, U-rich (ß-U) grains with Zr-rich precipitates, U-intermediate grains (d-UZr2), and solid FP precipitates. The major phases identified were associated with the nanoscopic chemical concentrations, the phase diagram, and the as-characterized specimen temperature, with the exception of the non-equilibrium ß-U phase identified in region B. The U-lean localities in regions A, A/B, B, and C were Zr-enriched pathways along subgrain/grain boundaries. This phenomenon suggests that Zr is susceptible to radiation-induced segregation in U-Zr fuels and indicates a new mechanism for constituent redistribution.

36 MATERIALS SCIENCE↗

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗

Photoaging of phenolic secondary organic aerosol in the aqueous phase: evolution of chemical and optical properties and effects of oxidants

Abstract. While gas-phase reactions are well established to have significant impacts on the mass concentration, chemical composition, and optical properties of secondary organic aerosol (SOA), the aqueous-phase aging of SOA remains poorly understood. In this study, we performed a series of long-duration photochemical aging experiments to investigate the evolution of the composition and light absorption of the aqueous SOA (aqSOA) from guaiacyl acetone (GA), a semivolatile phenolic carbonyl that is common in biomass burning smoke. The aqSOA was produced from reactions of GA with hydroxyl radical (•OH-aqSOA) or a triplet excited state of organic carbon (3C∗-aqSOA) and was then photoaged in water under conditions that simulate sunlight exposure in northern California for up to 48 h. The effects of increasing aqueous-phase •OH or 3C∗ concentration on the photoaging of the aqSOA were also studied. High-resolution aerosol mass spectrometry (HR-AMS) and UV–Vis spectroscopy were utilized to characterize the composition and the light absorptivity of the aqSOA and to track their changes during aging. Compared to •OH-aqSOA, the 3C∗-aqSOA is produced more rapidly and shows less oxidation, a greater abundance of oligomers, and higher light absorption. Prolonged photoaging promotes fragmentation and the formation of more volatile and less light-absorbing products. More than half of the initial aqSOA mass is lost, and substantial photobleaching occurs after 10.5 h of prolonged aging under simulated sunlight illumination for 3C∗-aqSOA and 48 h for •OH-aqSOA. By performing positive matrix factorization (PMF) analysis of the combined HR-AMS and UV–Vis spectral data, we resolved three generations of aqSOA with distinctly different chemical and optical properties. The first-generation aqSOA shows significant oligomer formation and enhanced light absorption at 340–400 nm. The second-generation aqSOA is enriched in functionalized GA species and has the highest mass absorption coefficients in 300–500 nm, while the third-generation aqSOA contains more fragmented products and is the least light absorbing. These results suggest that intermediately aged phenolic aqSOA is more light absorbing than other generations, and that the light absorptivity of phenolic aqSOA results from a competition between brown carbon (BrC) formation and photobleaching, which is dependent on aging time. Although photoaging generally increases the oxidation of aqSOA, a slightly decreased O/C of the •OH-aqSOA is observed after 48 h of prolonged photoaging with additional •OH exposure. This is likely due to greater fragmentation and evaporation of highly oxidized compounds. Increased oxidant concentration accelerates the transformation of aqSOA and promotes the decay of BrC chromophores, leading to faster mass reduction and photobleaching. In addition, compared with •OH, photoaging by 3C∗ produces more low-volatility functionalized products, which counterbalances part of the aqSOA mass loss due to fragmentation and evaporation.

54 ENVIRONMENTAL SCIENCES↗

Towards a Benchmark Experiment with the Compact Nuclear Power Source

The Compact Nuclear Power Source (CNPS) was a high-assay low enriched uranium (HALEU) tristructural isotropic (TRISO)-fueled, graphite-moderated microreactor constructed in 1987 at Los Alamos National Laboratory. The reactor, conceived as a power source for short-range radar stations, was designed to be "walk-away safe," and was cooled by heat pipes and ambient air. Though the project was formally cancelled after the fuel and moderator material had been received, its potential to meaningfully advance the body of critical and integral data was evident, and critical experiments with a mock-up of the reactor proceeded at TA-18 until its disassembly in 1991. The reflector and some components of the core would later go on to see service as part of the New Production Reactor Modular High-Temperature Gas-Cooled Reactor (NP-MHTGR) critical experiments. In light of the progress made by groups like Westinghouse and X-Energy towards contemporary graphite-moderated microreactors, the system remains an attractive candidate for the basis of a benchmark experiment even today. Uncertainties remain, however, in some features of the system–inconsistencies in the dimensions and composition of the reactor’s components as described in literature and implemented in current computational models. The identification, quantification, and to the extent possible, the minimization of these uncertainties is a crucial task on the path towards creating a benchmark based on the CNPS system. The present work seeks to initiate this process with a survey of available documentation and improvements to the accuracy of CNPS neutronics models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗

Bayesian discovery of optimal reduced order models from mechanistic and experimental data: A case study of Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles rely on a silicon carbide (SiC) layer as the primary structural material and barrier to metallic fission products (FPs) release. Accurate prediction of palladium (Pd) transport and penetration is therefore critical for qualifying TRISO fuels for advanced reactors. The empirical correlation for Pd penetration in BISON is derived from historical particle-fuel data, but cannot explain the large scatter in the experimental data that arises from varying experimental conditions. To aid fuel qualification, we previously developed a mechanistic reduced order model (ROM) using BISON that resolves these dependencies. Here, in this work we build on that mechanistic ROM and perform validation and quantify its uncertainty using Bayesian uncertainty quantification (UQ). calibration against a suite of in-pile and out-of-pile experiments spanning particle compositions, geometries, and operating conditions, and we benchmark it against the empirical correlation. Bayesian UQ identifies influential parameters, calibrates them to data, and yields predictive intervals. Results show that while the empirical correlation can be tuned to fit a single experiment type, it transfers poorly; the mechanistic ROM sustains accuracy with credible uncertainty across disparate conditions. This demonstrates a practical path—via Bayesian UQ applied to mechanistic ROMs—to leverage single-effect experiments for inferring in-reactor behavior and supporting TRISO fuel qualification.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Genetic characterization of a Sorghum bicolor multiparent mapping population emphasizing carbon-partitioning dynamics

Sorghum bicolor, a photosynthetically efficient C4 grass, represents an important source of grain, forage, fermentable sugars, and cellulosic fibers that can be utilized in myriad applications ranging from bioenergy to bioindustrial feedstocks. Sorghum’s efficient fixation of carbon per unit time per unit area per unit input has led to its classification as a preferred biomass crop highlighted by its designation as an advanced biofuel by the U.S. Department of Energy. Due to its extensive genetic diversity and worldwide colonization, sorghum has considerable diversity for a range of phenotypes influencing productivity, composition, and sink/source dynamics. To dissect the genetic basis of these key traits, we present a sorghum carbon-partitioning nested association mapping (NAM) population generated by crossing 11 diverse founder lines with Grassl as the single recurrent female. By exploiting existing variation among cellulosic, forage, sweet, and grain sorghum carbon partitioning regimes, the sorghum carbon-partitioning NAM population will allow the identification of important biomass-associated traits, elucidate the genetic architecture underlying carbon partitioning and improve our understanding of the genetic determinants affecting unique phenotypes within Poaceae. We contrast this NAM population with an existing grain population generated using Tx430 as the recurrent female. Genotypic data are assessed for quality by examining variant density, nucleotide diversity, linkage decay, and are validated using pericarp and testa phenotypes to map known genes affecting these phenotypes. We release the 11-family NAM population along with corresponding genomic data for use in genetic, genomic, and agronomic studies with a focus on carbon-partitioning regimes.

multiparental populations↗