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At least 1,063 records · Page 59

Assisted migration in a warmer and drier climate: less climate buffering capacity, less facilitation and more fires at temperate latitudes?

Assisted tree migration has been proposed as a conceptual solution to mitigate lags in biotic responses to anthropogenic climate change. The rationale behind this concept is that tree species currently growing under warmer and drier climates will be more resistant and resilient to the new climatic conditions than tree species naturally growing in currently wetter and colder climates. However, we hypothesize that, by being more stress‐tolerant to warmer and drier conditions, translocated species should exhibit different functional attributes, which could induce important ecological and societal costs and overcome the desired benefits of maintaining wood production and other ecosystem services. We used principal component analysis (PCA) to analyze variation in seven traits of 106 tree and tall shrub species from contrasting latitudinal distributions in western North America and Europe to predict the potential functional changes of forest ecosystems due to the translocation of tree species from low to high latitudes. We show that species from both continents differed primarily by their position on the leaf economy spectrum (LES) and their size traits. Even though, in Europe, differences in LES were significantly correlated to species southern latitudinal positions, in both continents differences in size traits were significantly correlated to latitude. These results suggest that assisted migration by translocating more conservative species of shorter stature in currently cooler climates should decrease the buffering capacity of forest canopies, decrease facilitation for understory species, and increase wildfire risks, whose effects have the potential to accelerate climate warming through negative atmospheric feedback processes. As an alternative solution to assisted migration that may accelerate rather than mitigate climate change, we recommend that foresters gradually diversify the vertical structure and layering of the existing forest canopy to maintain a sustainable water cycle and energy balance between the soil, the tree and the atmosphere without increasing the wildfire risk.

Environmental Sciences & Ecology↗

A transport-based framework for solidification cracking in Ni-based superalloys processed by laser powder bed fusion

Solidification cracking remains a persistent barrier to laser powder bed fusion (LPBF) processing of solid-solution-strengthened (SSS) Ni-based superalloys and is commonly attributed to carbide formation, liquation-type failure, or elemental segregation. In this work, the cracking behavior of three SSS Ni-based superalloys—Inconel 625 (625), Inconel 617 (617), and Haynes 230 (230)—is examined under comparable LPBF conditions to evaluate the origins of their cracking susceptibility. Carbides were present in both 625 and 230, yet cracking behavior differed significantly. MC-type carbides in 625 remain discrete and preserve liquid connectivity, whereas Cr-rich M23C6 carbides in 230 form at cellular triple junctions that bottleneck the interdendritic liquid network, influencing cracking through liquid connectivity rather than as an independent cause. Alloy 617 exhibited anomalous segregation without resolvable secondary phases yet cracked mildly, indicating that extensive carbide formation is not a prerequisite for cracking. To rationalize these observations, a transport-limited framework is proposed in which cracking occurs when terminal-liquid feeding cannot accommodate solidification-induced strain; among the mechanisms evaluated, this framework is most consistent with the physical constraints imposed by LPBF solidification. Transport-based crack-susceptibility indexes incorporating permeability, viscosity, and solidification kinetics distinguish the alloy hierarchy; permeability ratios Krat increased from approximately 7 (625) to 11.5 (617) and 14.5 (230), with corresponding increases in the μ-weighted mushy zone risk index (CSIMZRM). These results are consistent with transport-limited liquid feeding as a rate-limiting contributor to solidification cracking in LPBF-processed SSS Ni-based superalloys, providing a physically grounded basis for alloy and process design.

Hyer, Holden [ORNL] (ORCID:0000000343915561)↗

Shock-capturing parabolized Navier-Stokes model /SCIPVIS/ for the analysis of turbulent underexpanded jets

A new computational model, SCIPVIS, has been developed to predict the multiple-cell wave/shock structure in under or over-expanded turbulent jets. SCIPVIS solves the parabolized Navier-Stokes jet mixing equations utilizing a shock-capturing approach in supersonic regions of the jet and a pressure-split approach in subsonic regions. Turbulence processes are represented by the solution of compressibility corrected two-equation turbulence models. The formation of Mach discs in the jet and the interactive turbulent mixing process occurring behind the disc are handled in a detailed fashion. SCIPVIS presently analyzes jets exhausting into a quiescent or supersonic external stream for which a single-pass spatial marching solution can be obtained. The iterative coupling of SCIPVIS with a potential flow solver for the analysis of subsonic/transonic external streams is under development.

Dash, S. M.↗

Metasomatic alteration of coarse‐grained igneous calcium‐aluminum‐rich inclusions from CK3 carbonaceous chondrites

Abstract We report on the primary and secondary mineralogies of three coarse‐grained igneous calcium‐aluminum‐rich inclusions (CAIs) (Compact Type A [CTA], Type B [B], and forsterite‐bearing type B [FoB]) from the Northwest Africa (NWA) 5343 (CK3.7) and NWA 4964 (CK3.8) carbonaceous chondrites, compare them with the mineralogy of igneous CAIs from the Allende (CV3.6) chondrite, and discuss the nature of the alteration processes that affected the CK and CV CAIs. The primary mineralogy and mineral chemistry of the CK3 CAIs studied are similar to those from Allende; however, primary melilite and anorthite are nearly completely absent. Although the secondary minerals identified in CK CAIs (Al‐diopside, andradite, Cl‐apatite, clintonite, forsterite, ferroan olivine, Fe,Ni‐sulfides, grossular, ilmenite, magnetite, plagioclase, spinel, titanite, and wadalite) occur also in the Allende CAIs, there are several important differences: (i) In addition to melilite and anorthite, which are nearly completely replaced by secondary minerals, the alteration of CK CAIs also affected high‐Ti pyroxenes (fassaite and grossmanite) characterized by high Ti 3+ /Ti 4+ ratio and spinel. These pyroxenes are corroded and crosscut by veins of Fe‐ and Ti‐bearing grossular, Fe‐bearing Al,Ti‐diopside, titanite, and ilmenite. Spinel is corroded by Fe‐bearing Al‐diopside and grossular. (ii) The secondary mineral assemblages of grossular + monticellite and grossular + wollastonite, commonly observed in the Allende CAIs, are absent; the Fe‐bearing grossular + Fe‐bearing Al‐diopside ± Fe,Mg‐spinel, Fe‐bearing grossular + Fe,Mg‐olivine ± Fe,Mg‐spinel, and Ca,Na‐plagioclase + Fe‐bearing Al‐diopside + Fe‐bearing grossular assemblages are present instead. These mineral assemblages are often crosscut by veins of Fe‐bearing Al‐diopside, Fe,Mg‐olivine, Fe,Mg‐spinel, and Ca,Na‐plagioclase. The coarse‐grained secondary grossular and Al‐diopside often show multilayered chemical zoning with distinct compositional boundaries between the layers; the abundances of Fe and Ti typically increase toward the grain edges. (iv) Sodium‐rich secondary minerals, nepheline and sodalite, commonly observed in the peripheral portions of the Allende CAIs, are absent; Ca,Na‐plagioclase is present instead. We conclude that coarse‐grained igneous CAIs from CK3.7–3.8 s and Allende experienced an open‐system multistage metasomatic alteration in the presence of an aqueous solution–infiltration metasomatism. This process resulted in localized mobilization of all major rock‐forming elements: Si, Ca, Al, Ti, Mg, Fe, Mn, Na, K, and Cl. The metasomatic alteration of CK CAIs is more advanced and occurred under higher temperature and higher oxygen fugacity than that of the Allende CAIs.

Geochemistry & Geophysics↗

Project Development of an Electrochemical Denitration and Caustic Generation System for HLW Pretreatment at Hanford - 26350

An engineering-scale electrochemical processing skid is proposed to perform the denitration of Hanford tank waste, which would help to mitigate a key process concern with the direct feed processing of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The reduction of nitrates and organic compounds in the waste feed will directly reduce hazardous NOx and ammonia gases generated during the vitrification process, which in turn will aid in addressing potential regulatory and safety challenges associated with processing large volumes of tank waste. This paper highlights the past legacy work, project layout, accomplishments from Phase 1 and research and development envisioned for Phase 2. An innovative electrochemical denitration and caustic generation (EDCGe) process was demonstrated for the pretreatment of tank waste at the Savannah River Site (SRS) in the early 2000s. The denitration electrolyzer, off-gas abatement system, and caustic generator electrolyzer are being developed with the intent that the denitration electrolyzer will convert nitrate and nitrite anions to nitrogen gas while also yielding other gaseous byproducts, which may include N2O, NH3, VOCs, and H2. The gaseous byproducts will be managed via a tandem off-gas catalyst-bed treatment system. The caustic generation electrolyzer will recycle NaOH from the feed to produce a clean caustic stream for use within the batching tanks at Hanford, aiding in the preparation of waste for WTP. The reduction in hazardous emissions and improved waste treatment processes provides a robust solution for nuclear waste management, contributing to environmental safety and regulatory compliance. The EDCGe technology is being adapted, modified, and updated for the preparation of the Direct Feed-High Level Waste (DF-HLW) flowsheet at Hanford. Phase 1 demonstrated a bench-scale proof-of-concept for reactions involving the denitration electrolyzer and gas phase abatement of ammonia. The electrochemical technology is drawing on the scientific outcomes that were reported in the legacy work. The results from Phase 1 demonstrated the viability of the EDCGe system in reducing the nitrogen species of simple non-radioactive waste simulants. Commercially available alloys used as electrode materials and membranes are being studied for the denitration and caustic generation electrolyzers. The continuation of this project holds promise for broader applications, such as energy-efficient ammonia production, and contributes significant advancements in nuclear waste management. Additional material discovery has been investigated into ceramic Na super ion conductive (NaSICON) materials and off-gas abatement catalyst discovery. NaSICON is of interest for selective transport of Na within the electrolyzers to make a clean caustic stream. Future integration and optimization efforts, informed by Phase 1 results and ongoing research, will continue to drive advancements in nuclear waste management technology. The technology developed for the EDCGe treatment of tank waste will also have broader potential to inform other fields, such as energy-efficient ammonia production, as well as ammonia abatement catalysis through the lessons learned in electrochemical nitrate reduction. The applications and benefits of this research extend beyond Hanford and the Savannah River Site, supported by a collaborative team of scientists and engineers from national labs, academia, and industry, ensuring a comprehensive approach to solving complex waste treatment challenges. The team is leveraging advanced electrochemical technologies, machine learning, novel catalysts tailored for gaseous nitrogen species, and cutting-edge reactor systems to enhance the process efficiency and effectiveness of the denitration process.

Rodene, Dylan [Savannah River National Laboratory ↗

Mechanical Properties of Aged A709

A709 plate is in the process of being developed and qualified through a collaboration by Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL). The goal is to qualify A709 plate in Section III, Division 5 of the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC). This would permit the construction of A709 plate for fast-reactor structural applications. A tradeoff between creep and creep-fatigue properties was established in prior work. A processing route was identified as providing the optimal balance between creep-rupture and elevated-temperature cyclic properties for the solution annealed condition. This condition, however, resulted in a shorter than desired creep-rupture life. Aging is probed to evaluate its potential at further improving mechanical properties. Aging statically precipitates the solutes in solution prior to service. The processing routes identified as providing the best creep-rupture properties and best balance in mechanical properties are investigated. This report discloses the results from tensile, creep, and elevated-temperature cyclic testing performed at INL on the aged material. The aged properties are compared to solution annealed properties. A709 offers improvement in performance compared to 316H particularly at high temperatures; 316H is a material qualified in Section III, Division 5 of the ASME BPVC. For certain high-temperature fast-reactor design conditions, 316H cannot be used while A709 can.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Improving the bioaccessibility of lipophilic ingredient in its oral intestinal delivery by ultrasound and biological cross‐linker

Abstract BACKGROUND Great efforts have been made to improve the oral bioaccessibility of lipophilic ingredients with multi‐functionalities. Achieving intestinal delivery of lipophilic ingredients and their encapsulation in micelles composed of bile salts and lipid hydrolysates (i.e. fatty acids) is critical for improving oral bioaccessibility. Therefore, oil‐core microcapsules are considered ideal carriers of lipophilic ingredients. Previous studies have reported oil‐core/zein‐shell microcapsules constructed by a one‐step anti‐solvent process. Still, its efficacy as an intestinal delivery system was limited because if the porous shell structure. RESULTS Zein solution was pretreated with ultrasound and tannic acid (TA) cross‐linking. Composite oil‐core microcapsule (COM) with a compact shell structure was successfully prepared by using modified zein solution in the anti‐solvent process. Fourier‐transform infrared spectroscopy and circular dichroism analyses indicated that ultrasound and TA synergistically promote the conformational transition of zein from α‐helix to β‐sheet and enhance the hydrophobic interactions among protein chains. The above changes contribute to the strengthen of shell zein network. Correspondingly, COM presents superior encapsulation efficiency and environmental stability over the simple oil‐core microcapsule (SOM) prepared without the use of ultrasound and TA. Furthermore, antioxidant activity of β‐carotene was well retained during the encapsulation process. In vitro studies indicated that COM was more resistant to digestibility and acid‐induced swelling. More than 87% of β‐carotene could be released in the intestine in a sustainable way. The controllable release behavior thus promoted a significant increase in bioaccessibility of β‐carotene encapsulated in COM compared to SOM (85.9% versus 48.5%). CONCLUSION The COM generated here shows potential for bioaccessibility improvement of lipophilic ingredients. © 2022 Society of Chemical Industry.

Wei, Yun‐Shan↗

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗

Effect of CMAS viscosity on the infiltration depth in thermal barrier coatings of different microstructures

Calcium magnesium aluminum silicate (CMAS) is one of the leading concerns for the gas turbine industry. The effects of CMAS viscosity and the coating microstructure on CMAS infiltration depth were explored by conducting a time dependent interaction study. Three CMAS compositions were used from literature, and their viscosities predicted through FactSage viscosity module were drastically different. The interaction was carried out on three different TBCs synthesized using the solution precursor plasma spray process (SPPS): two of the TBCs were made of yttrium aluminum garnet (YAG) having different microstructures that promote different modes of CMAS infiltration, and one TBC was made of gadolinium zirconate (GZO). All samples had stress relieving vertical cracks and different intensities of horizontally banded porosity, (inter pass boundaries IPBs). A concentration of 100 mg/cm 2 of CMAS was applied on the TBCs which were then subjected to a 5-minute interaction at 1300 °C. Samples were analyzed using scanning electron microscopy (SEM), electron dispersive X-ray spectroscopy (EDXS), and transmission electron microscopy (TEM). Low viscosity CMAS readily penetrated the TBCs while more viscous CMAS showed less penetration. The depth of CMAS infiltration depended on the coating microstructure. In the YAG with IPBs, the CMAS spread horizontally in the IPBs before infiltrating deeper, resulting in reduced infiltration depth compared to other samples in spite of having wider vertical cracks. TEM and EDXS analysis were performed to investigate the phases present in the CMAS-TBC interaction region in YAG. Two regions were chosen, the top TBC surface in direct contact with the sea of CMAS, and the region at the CMAS penetration ended within the coating. Finally, the results showed that no secondary phases like apatite were observed in YAG, thus it can be concluded that the arrest of CMAS happened solely because of CMAS viscosity and the short infiltration time.

36 MATERIALS SCIENCE↗

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.

Long, Jason D.↗

Direct Air Capture of CO 2 via Reactive Crystallization

Atmospheric CO 2 removal using engineered chemical processes, aka direct air capture (DAC), has become an essential component of our available portfolio for mitigating climate change. Here we describe a promising approach to DAC based on reactive crystallization of atmospheric CO 2 (RC-DAC) with aqueous guanidine and amino acid. Compared to the previously studied phase-changing DAC processes involving initial CO 2 absorption by an aqueous alkaline solvent followed by carbonate crystallization in a second step, RC-DAC combines the CO 2 absorption and carbonate crystallization into a single step. Thus, as the insoluble carbonate salts are removed from solution by crystallization, more CO 2 is pulled from the air into solution, further driving the DAC process. The RC-DAC was performed in a household humidifier as the air–liquid contactor, which can handle solid–liquid slurries effectively. The crystallization was monitored in situ by pH measurements, real-time imaging with a microscope probe, and by Raman spectroscopy, and ex situ by NMR spectroscopy, powder X-ray diffraction, and total inorganic carbonate analysis. Further, the investigation provided a detailed mechanistic picture of the RC-DAC process, involving formation of carbamate and carbonate anions in solution, followed by sequential crystallization of different guanidinium carbonate phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing Reactive Transport Behavior in a Three-Dimensional Discrete Fracture Network

While several studies have linked network and in-fracture scale properties to conservative transport behavior in subsurface fractured media, studies on reactive transport cases remain relatively underdeveloped. In this study, we explore the behavior of an irreversible kinetic reaction during the interaction of two solute plumes, one consisting of species A and the other species B. When the plumes converge, these species react kinetically to form a new species C via A+B→kC. This reactive system is studied using a three-dimensional discrete fracture network (DFN) model coupled with reactive Lagrangian particle tracking. We find that the interplay of network topology and chemical properties of the reactive solutes controls reactive transport processes. The network topology drives species A and B together, and the chemical properties dictate whether and how quickly a reaction occurs. Results demonstrate that reactions are most likely to occur in high-velocity fractures that make up the network backbone. The interplay between species’ chemical properties and transport is characterized by a non-dimensional Damköhler (Da) number. We show that the spatial distribution of reactions is sensitive to Da, which subsequently influences late-time tailing behavior in outlet breakthrough time distributions. The results of this study provide initial insights into how an irreversible reaction occurs during transport in a fracture network, using a methodology that can be applied to study reactive transport in a wide range of fractured media environments and contexts.

58 GEOSCIENCES↗

Impact of coolant temperature on the combustion characteristics and emissions of a stratified-charge direct-injection spark-ignition engine fueled with E30

The direct injection spark ignition (DISI) engine has received considerable attention due to its potential to increase the power density of traditional spark ignition engines while significantly improving fuel economy through lean, unthrottled combustion. However, the market introduction of DISI engines operated in a lean combustion mode is inhibited by their unsatisfactory emissions, especially during cold start conditions that make proper mixture formation more challenging. Ethanol-blended gasoline, now a widely used fuel, makes the cold start of a DISI engine more difficult, leading to higher HC and soot emissions because of the high latent heat of vaporization of ethanol relative to gasoline. This work investigated the impact of coolant temperature on the characteristics of combustion and emissions in a stratified-charge DISI engine fueled with an E30 fuel (i.e. 30% ethanol in gasoline), while the coolant temperature was alternated between four levels (45, 60, 75, and 90 °C) to simulate different conditions throughout the warm-up process. The experiments showed that the coolant temperature affected the post-spark inflammation time, as well as the speed, intensity, and stability of the combustion process in the engine. When the coolant temperature rose, the engine produced more NOX and less CO, PM and HC. In addition, high-speed direct photography was used to obtain crank-angle resolved images of fuel sprays and flames in the cylinder. As the coolant temperature rose, the liquid spray lengths became shorter, reducing the possibility of wall wetting, and reduced irradiance from soot particles also indicated less nonpremixed combustion. The in-cylinder imaging results are consistent with the observed combustion and emission characteristics and shed light on the underlying processes. Finally, some potential solutions to the emissions challenges faced here could be either raising in-cylinder temperatures by using trapped residuals or modifying the injection schedule, for example by increasing the number of injections or to inject later in the cycle into a higher-density environment.

42 ENGINEERING↗

Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues

In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.

97 MATHEMATICS AND COMPUTING↗

Verification of Bison fission product species conservation under TRISO reactor conditions

When assessing the reliability and predictive capabilities of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. During this process, numerical results in a discrete solution are compared to the analytical solution of the mathematical model. Here, in this paper, the code verification process is applied to one-dimensional spatiotemporal problems that exercise partial differential equation governing the conservation of fission product species (or mass diffusion). Numerical experiments were performed in the Bison fuel performance code to evaluate its predictive capability under various TRISO reactor conditions such as base irradiation and safety heating test conditions for either short- or long-lived fission product species, as well as a case concerning evaporation from the outer surface of a particle. The code predictions were compared with the expected exact results obtained from the analytical expressions, and the fact that they demonstrate the correct analytical behavior provides strong evidence of proper numerical algorithm implementation.

07 ISOTOPE AND RADIATION SOURCES↗

Concentration-Dependent Solvation Structure and Dynamics of Aqueous Sulfuric Acid Using Multinuclear NMR and DFT

Sulfuric acid is a ubiquitous compound for industrial processes and aqueous sulfate solutions also play a critical role in electrolytes for many prominent battery chemistries. While the thermodynamic literature for it is quite well-developed, comprehensive studies of the solvation structure, and particularly molecular-scale dynamical and transport properties, are less available. This study applies a multinuclear NMR approach to the elucidation of the solvation structure and dynamics over a wide temperature (-10 – 50?C) and concentration (0 – 18 M) range, combining 17O shift, linewidth, and T1 relaxation measurements, 33S shift and linewidth measurements, and 1H PFG-NMR measurements of the proton self-diffusivity. In conjunction, these results indicate a crossover between two regimes of solvation structure and dynamics, occurring above the concentration associated with the deep eutectic point (~ 4.5 M), with the high-concentration regime dominated by strong water-sulfate correlation. This description was borne out in detail by the activation energy trends with increasing concentration derived from the relaxation of both the H2O/H3O+ and H2SO4/HSO4-/SO42- 17O resonances and the 1H self-diffusivity. However, the 17O chemical shift difference between the H2O/H3O+ and H2SO4/HSO4-/SO42- resonances across the entire temperature range is nevertheless strikingly linear. A computational approach coupling MD simulations and DFT NMR shift calculations to reproduce this trend is presented, which will be the subject of further development. This combination of multinuclear, dynamical NMR and computational methods, and the results furnished by this study, will provide a platform for future studies on battery electrolytes where aqueous sulfate chemistry plays a central role in the solution structure.

Bazak, Jonathan D.↗

Effect of Graft Molecular Weight and Density on the Mechanical Properties of Polystyrene-Grafted Cellulose Nanocrystal Films

In this work, polymer-grafted nanoparticle (PGN) films were prepared from polystyrene (PS) grafted to rodlike cellulose nanocrystals (MxG-CNC-g-PS) with a controllable grafting density (0.03–0.25 chains/nm 2 ) and molecular weight (5–60 kg/mol). These nanorod-based PGNs are solution- and melt-processible, permitting access to one-component composite films with high nanofiller loadings (with up to 55 wt %). The impact of both grafted polymer density and molecular weight on the mechanical properties of the films was investigated and related to the polymer brush conformation: concentrated polymer brush (CPB), semidilute polymer brush (SDPB), or CPB core with SDPB corona (CPB/SDPB). The rubbery regime storage modulus (above $T_g$) showed 2 orders of magnitude increase, maximizing at a low degree of polymerization (N) and low grafting density (σ). Fracture toughness was maximized in samples with the grafted polymer in the SDPB or CPD/SDPB (higher N and relatively low σ) regime and showed enhancement relative to PS of molecular weight similar to the graft. In line with prior computation predictions, optimizing for both rubbery modulus and fracture toughness in such nanorod-based PGN films requires the polymers in the SDPB regime and CNC loading levels (ca. 50–60 wt %) that are difficult to attain in more traditional two-component CNC composites.

36 MATERIALS SCIENCE↗