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At least 325 records · Page 18

Computational study of TATB

We have performed a computational study of TATB. The study is composed of two parts, one where we perform static T = 0 K calculations with several different DFT functionals, to investigate structural properties and obtain a cold curve. Even though the functionals used in this study give poor results at ambient pressure, they perform much better at compression, when the dominance of the van der Waals’ forces in the binding is replaced by more normal interactions. In particular AM05 gives good results, mainly because it doesn’t include any “faulty” van der Waals’. Indeed the van der Waals’ corrected functional (PBE+D2) results shows the worst performance on structural properties. For the cold curve the PBE+D2 functional gives the best results compared to experiments (room temperature) but since the structural properties were bad with this functional we cannot for sure say that this is in any way a validation. It is shown that scaling the AM05 results with a common factor reproduces the experimental data. We leave the question on why to a follow up study but speculate that maybe the experiment and our calculations do not represent the same system set-up. From the structural properties we identify a site in the TATB lattice that contains a high concentration of oxygen and hydrogen. The consequences of this finding, if any, are left to a future project. In the second part of the study we perform extensive high-quality DFT-MD (molecular dynamics with DFT forces) calculations to obtain points on the Hugoniot. This part of the study did not get finished within this project and a more extensive summary of this part will be given in a follow up report at a future date. However, we show that obtaining calculated data is essential for equations of state development since the existing experimental Hugoniot data barely deviates from room temperature isotherm data and thus give no information of the high temperature dependency of materials properties. Our conclusion so far in the project is that being able to calculate materials properties is essential for high explosives since experiments are unable to give information in the high temperature part of phase space. While blind use of DFT cannot (yet) give unambiguous answers, we can still explore qualitatively and use such information to guide us in EOS development. However, the main conclusion is that we need better functionals in DFT to easily extract needed properties from calculations.

36 MATERIALS SCIENCE↗

Uncoupling Electrokinetic Flow Solutions

The continuum-scale electrokinetic porous-media flow and excess charge redistribution equations are uncoupled using eigenvalue decomposition. The uncoupling results in a pair of independent diffusion equations for “intermediate” potentials subject to modified material properties and boundary conditions. The fluid pressure and electrostatic potential are then found by recombining the solutions to the two intermediate uncoupled problems in a matrix-vector multiplication. Expressions for the material properties or source terms in the intermediate uncoupled problem may require extended precision or careful rewriting to avoid numerical cancellation, but the solutions themselves can typically be computed in double precision. The approach works with analytical or gridded numerical solutions and is illustrated through two examples. The solution for flow to a pumping well is manipulated to predict streaming potential and electroosmosis, and a periodic one-dimensional analytical solution is derived and used to predict electroosmosis and streaming potential in a laboratory flow cell subjected to low frequency alternating current and pressure excitation. The examples illustrate the utility of the eigenvalue decoupling approach, repurposing existing analytical solutions or numerical models and leveraging solutions that are simpler to derive for coupled physics.

58 GEOSCIENCES↗

Geometry-Dependent Solidification Regimes in Metal Additive Manufacturing

Recent modeling and experimental work in additive manufacturing has suggested that cross-sectional geometry may play a significant role in the local development of the solidification structure through its influence on the heat source path. This effect has been rationalized as the transition from a quasi-static point heat source regime, to a regime dominated by the quasi-static motion of an equivalent line source. This work provides a simple analytical framework for determining the conditions under which a system transitions between these regimes. Here, a transient semi-analytical heat transfer model is used to examine a wide range of process conditions and material properties. A simple analytical expression is derived and shown to accurately predict the transition between solidification regimes over these conditions. The functional form of this expression is then used to help understand the importance of various material properties, process parameters, and geometric factors on the characteristics of the solidification conditions. This approach may be used as a simple guideline for optimizing process conditions in response to variations in cross-sectional geometry to produce more consistent microstructural distributions in additively manufactured components.

36 MATERIALS SCIENCE↗

Experimental Investigation of Low Cost, Low Thermal Conductivity Thermal Barrier Coating on HCCI Combustion, Efficiency, and Emissions

In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion since the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. A surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. At the same time, achieving a highly dynamic response sidesteps preheating of charge during intake and eliminates the volumetric efficiency penalty. The magnitude and temporal profile of the dynamic surface temperature swing is affected by the TBC material properties, thickness, morphology, engine speed, and heat flux from the combustion process. This study follows prior work of authors with Yttria Stabilized Zirconia, which systematically engineered coatings for HCCI combustion. Herein, a modeling study was used to assess the impacts of various TBC material properties, e.g. density, thickness, and thermal conductivity on the temperature swing effect. Reducing conductivity emerged as a most promising avenue, rather than reducing both the density and effective conductivity by increasing porosity, the current work emphasizes a material with natively low conductivity. A novel TBC formulation was developed, leverages a class of materials that, to the author’s best knowledge, have not been used as a thermal barrier coating previously. Here, a systematic experimental investigation was carried out using single-cylinder research engine. Experimental engine studies utilizing the novel ‘glassy’ low-K coating exhibit advanced ignition phasing and reduced combustion duration relative to the baseline engine. Heat transfer measurements indicate a net reduction in heat flux over the entire cycle, although main effect is felt during expansion, and the reduced heat transfer losses manifest in higher gross indicated thermal efficiency by approximately 5-6% on a relative basis.

42 ENGINEERING↗

Impact of Irradiation on Microstructure and Mechanical Properties of Materials Produced by Advanced Manufacturing

Advanced non-light water reactor designs, known as Generation IV (Gen IV) reactors, typically operate at higher temperatures and under more extreme radiation conditions than conventional light water reactors. A critical aspect of the successful deployment and advancement of Gen IV reactor designs is the selection of appropriate structural materials for specific applications, which necessitates the timely development of new materials and manufacturing processes. Advanced manufacturing (AM) offers numerous opportunities for innovative designs, enabling the production of high-performance components with potentially shorter development cycles compared to traditional manufacturing methods. However, a significant challenge in deploying AM technologies in the nuclear energy sector is the current lack of data on the irradiation performance of AM-produced components. This presentation will discuss neutron and ion irradiation results of AM materials, including stainless steel 316L, Grade 91, SA508, Inconel 718, and Inconel 625 materials. The materials were manufactured by AM, such as Powder Metallurgy Hot Isostatic Pressing (PM HIP), Laser Powder Bed Fusion (LPBF) and Directed Energy Deposition (DED). The effects of neutron irradiation on microstructure (e.g., dislocations, loops, and nanoclusters), tensile properties (e.g., strength and ductility), and ion irradiation on Irradiation-Assisted Stress Corrosion Cracking (IASCC) will be explored. Results are collected from several projects supported by the Nuclear Science User Facilities (NSUF) program.

36 - MATERIALS SCIENCE↗

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗

Mechanical Design of the MARCO Solenoid Detector Magnet

MARCO is the superconducting solenoid for ePIC, the new particle physics detector of the upcoming Electron Ion Collider (EIC) at the Brookhaven National Laboratory (NY, USA). The magnet has a 2.84 m warm bore diameter and is 3.85 m long. This 15 tons magnet provides a 2.0 T central field at the interaction point with a nominal current of about 4 kA at 4.5 K. The coil is composed of 6 layers of copper stabilized NbTi Rutherford in channel conductor (RIC) and it is wound internally to the brass mandrel. Here, this paper presents the detailed mechanical design of the magnet, starting with the magnet description, the material properties and the acceptance criteria considered. Then, the coil pack properties homogenization process is described. Subsequently, the 2D and 3D calculation models and their assumptions are described. At last, the computational results for the cool down and the energization are discussed. Index Terms—Superconducting Detector Magnet, material properties, homogenization, detector, EIC.

Reymond, Hugo [Commissariat a l'Energie Atomique e↗

A better understanding of the mechanics of borehole breakout utilizing a finite strain gradient-enhanced micropolar continuum model

Borehole breakout denotes the failure in rock mass subjected to drilling, caused by stress concentrations exceeding the material strength. Depending on the material properties, the preexisting in situ stress state, and the borehole dimensions, different types of borehole breakout, such as spiral-shaped breakout or v-shaped breakout, are distinguished in the literature. In the present work, we address the influence of the material properties on the predicted borehole breakout mode in a comprehensive finite element study. To this end, herein we employ a gradient-enhanced micropolar damage-plasticity model based on the Mohr–Coulomb strength criterion, formulated in the finite strain regime, which is calibrated based on experimental results from plane strain compression tests on Red Wildmoor sandstone. In the numerical study, the influence of the in situ stress state, the material friction angle, plastic dilation, post peak residual strength, and the inherent material length scale parameters are investigated. Thereby, we demonstrate that depending on the material parameters, substantially different failure modes, characterized by strongly localized shear bands or diffuse failure zones, are predicted. It is shown that in particular the brittleness of the material in the post peak regime has a major influence on the predicted breakout type. Moreover, a statistical validation of the results is obtained by considering different random field distributions of the initial material strength.

58 GEOSCIENCES↗

Controlling the Crystal Packing and Morphology of Metal–Organic Macrocycles through Side-Chain Modification

Supramolecular nanotubes constructed from the self-assembly of conjugated metal–organic macrocycles provide a unique collection of materials properties, including solution processability, porosity, and electrical conductivity. Here we show how small modifications to the macrocycle periphery subtly alter the noncovalent interactions governing self-assembly, leading to large changes in crystal packing, crystal morphology, and materials properties. Specifically, we synthesized five distinct copper-based macrocycles that differ in either the steric bulk, polarity, or hydrogen-bonding ability of the peripheral side chains. We show that the electrical conductivity of these macrocycles is highly sensitive to steric bulk, decreasing by 3 orders of magnitude upon introduction of peripheral neopentyl substituents. Here, we further show that the introduction of hydrogen-bonding groups leads to more ordered packing and a dramatic increase in crystallite size. Together, these results establish side-chain engineering as a rich toolkit for controlling the packing structure, particle morphology, and bulk properties of conjugated metal–organic macrocycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phosphorylation toggles the SARS-CoV-2 nucleocapsid protein between two membrane-associated condensate states

Abstract The Nucleocapsid protein (N) of SARS-CoV-2 plays a critical role in the viral lifecycle by regulating RNA replication and by packaging the viral genome. N and RNA phase separate to form condensates that may be important for these functions. Both functions occur at membrane surfaces, but how N toggles between these two membrane-associated functional states is unclear. Here, we reveal that phosphorylation switches how N condensates interact with membranes, in part by modulating condensate material properties. Our studies also show that phosphorylation alters N’s interaction with viral membrane proteins. We gain mechanistic insight through structural analysis and molecular simulations, which suggest phosphorylation induces a conformational change in N that softens condensate material properties. Together, our findings identify membrane association as a key feature of N condensates and provide mechanistic insights into the regulatory role of phosphorylation. Understanding this mechanism suggests potential therapeutic targets for COVID infection.

Science & Technology - Other Topics↗

Integrated Process Optimization for Biochemical Conversion

This research is motivated by the challenges faced during biomass processing in bioenergy plants. It has been observed that variations in biomass characteristics, such as moisture, ash, and carbohydrate contents cause variations in feeding of the system which led to underutilization of equipment and the reactor. The objective of this research is to ensure a continuous flow of biomass to the reactor in plants that use the biochemical conversion process to generate liquid fuels. The overall goal is to lower the cost of producing biofuels, which could lead to improving US’s energy independency and growing US’s rural economy. The research team developed analytical models, such as discrete element method (DEM) models and mathematical models. The DEM models are unit-level models that explicitly capture biomass characteristics and quantify the impacts of biomass characteristics on bulk material properties and the performance of specific equipment. The mathematical models are system-level models that capture the impacts of system infeed rate, equipment processing rate, storage location and capacity, and biomass characteristics on system throughput. The functional relations predicting the bulk material properties from DEM models are incorporated to the mathematical models. The models developed were validated and evaluated using data collected at Idaho National Laboratory’s biomass processing facility. Via these models, we identified process control strategies that ensure a continuous flow of biomass to the reactor, while meeting the requirements of biochemical conversion process. Our analysis indicates that sequencing of biomass bales based on moisture level, and carbohydrate contents could have a positive impact on reducing processing time and inventory level and increasing throughput rate. Short bale sequences that repeat frequently, seem to have the greatest impact on improving system’s performance. Based on our experiments, the total annual system operating costs reduced by 20-30%, and the maximum inventory level reduced by 3 to 4 times. The operating costs include the annual equipment amortization cost and processing cost. The implementation of the models developed requires the use of standardized bale format, Radio Frequency Identification technology, sensing and real time monitoring of material attributes, automated material handling equipment, and automated process control. The scope of the model proposed can be extended to include the whole supply chain. The supply chain models help identify how many bales of different biomass feedstock to purchase given biomass availability in the region, biomass price and quality, and the biomass processing capabilities of the biorefinery. Thus, the outcomes of supply chain models can be used to inform the design of long-term contracts among farmers and the biorefinery.

09 BIOMASS FUELS↗

Long-Term Thermal Aging of Modified Sylgard 184 Formulations

Primarily used as an encapsulant and soft adhesive, Sylgard 184 is an engineered, high-performance silicone polymer that has applications spanning microfluidics, microelectromechanical systems, mechanobiology, and protecting electronic and non-electronic devices and equipment. Despite its ubiquity, there are improvements to be considered, namely, decreasing its gel point at room temperature, understanding volatile gas products upon aging, and determining how material properties change over its lifespan. In this work, these aspects were investigated by incorporating well-defined compounds (the Ashby–Karstedt catalyst and tetrakis (dimethylsiloxy) silane) into Sylgard 184 to make modified formulations. As a result of these additions, the curing time at room temperature was accelerated, which allowed for Sylgard 184 to be useful within a much shorter time frame. Additionally, long-term thermal accelerated aging was performed on Sylgard 184 and its modifications in order to create predictive lifetime models for its volatile gas generation and material properties.

36 MATERIALS SCIENCE↗

A model to assess Zircaloy’s mechanical property changes following a transient beyond critical heat flux

Maintaining the integrity of nuclear fuel rods is essential for ensuring public health and safety in nuclear power generation. During reactor operation, this integrity is confirmed by demonstrating compliance with established regulatory acceptance criteria. For moderate-frequency events, such as limiting transients and anticipated operational occurrences (AOOs), the current fuel integrity criterion is based on preventing boiling transition. This criterion assumes that prevention of boiling transition will prevent excessive cladding heating and, thus, fuel failure during normal operations. While conservative, this approach places significant constraints on core design, fuel cycle economics, and a plant’s ability to perform major power uprates, leading to suboptimal fuel utilization and inefficient carbon-free energy production. A more efficient approach could be achieved by revising the failure criterion to a material-specific limit rather than strictly preventing the boiling transition, since boiling transition per se is not a cause of fuel cladding failure. Here, as a result, a new licensing framework based on material properties, termed time-at-temperature (t@T), is needed. This approach would allow for brief periods of post–critical heat flux operation during an AOO without compromising safety. Implementing the t@T licensing strategy requires a robust technical foundation in material properties, which must be established through comprehensive data collection on both unirradiated and irradiated fuel and cladding materials. This foundation would enable the development of a safety basis that ensures safe operation while providing greater flexibility and efficiency for reactor operation. This paper documents a thorough review of the available data to establish a baseline knowledge that can inform the development of cladding mechanical models, as well as identify experimental data gaps that need to be addressed in future research. Machine learning and data informatics were utilized to extract the importance of parameters on the t@T parameter. Industry tools were used to perform baseline analyses to define the relevant transient conditions for data analysis. The subsequent review successfully identified applicable experimental data, as well as sufficient data to evaluate changes in cladding mechanical properties following an AOO transient. Rather than developing new models, this work coupled existing irradiation annealing and recrystallization models to calculate changes in hardness, yield stress, and ultimate tensile stress following an AOO event. The findings from this review were summarized to highlight the experimental data needs required to fill remaining gaps and support the development of future t@T licensing methodologies.

Cladding performance↗

Solidification dynamics in metal additive manufacturing: analysis of model assumptions

Solidification characteristics in the meltpool drive the process-microstructure relationship which helps dictate the material properties of as-built parts in additive manufacturing; therefore, being able to accurately and quickly simulate the size, shape, and solidification characteristics in the melt pool is of great interest to the field. In this study, we investigate various important physical phenomena (dynamic material properties, fluid-flow, radiation and vaporization) which can either be included or neglected in a continuum finite volume model (FVM) and their effect on the solidification conditions. Additionally, since the simplest form of such a model (conduction only) has an analytic solution which is much faster, its viability is also considered. Since the inclusion of some of these physical phenomena will inherently change the net energy input as well as the amount of energy needed to achieve melting of a control volume, each set of included phenomena had an effective absorption efficiency which was calibrated to closely match the dimensions of the melt pool to that of the ground truth data. The ground truth data for this study was defined to be the output of the FVM which included all the physical phenomena (OF). This study then goes on to compare the effects on solidification conditions each of these calibrated models has. It was found that most of the change in solidification conditions comes from the inclusion of latent heat. A posterior correlation factor (PCF) is then introduced to enable an analytic model to predict similar solidification conditions to OF model.

36 MATERIALS SCIENCE↗

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗

A spherical crystal diffraction imager for Sandia’s Z Pulsed Power Facility

Sandia’s Z Pulsed Power Facility is able to dynamically compress matter to extreme states with exceptional uniformity, duration, and size, which are ideal for investigating fundamental material properties of high energy density conditions. X-ray diffraction (XRD) is a key atomic scale probe since it provides direct observation of the compression and strain of the crystal lattice and is used to detect, identify, and quantify phase transitions. Because of the destructive nature of Z-Dynamic Material Property (DMP) experiments and low signal vs background emission levels of XRD, it is very challenging to detect a diffraction signal close to the Z-DMP load and to recover the data. We have developed a new Spherical Crystal Diffraction Imager (SCDI) diagnostic to relay and image the diffracted x-ray pattern away from the load debris field. The SCDI diagnostic utilizes the Z-Beamlet laser to generate 6.2-keV Mn–He α x rays to probe a shock-compressed material on the Z-DMP load. Finally, a spherically bent crystal composed of highly oriented pyrolytic graphite is used to collect and focus the diffracted x rays into a 1-in. thick tungsten housing, where an image plate is used to record the data.

47 OTHER INSTRUMENTATION↗

High temperature annealing of irradiated nuclear grade graphite

Previous work has shown that the material properties of nuclear grade graphite are substantially affected by the atomic and microstructural changes that occur during neutron-irradiation. The parameters that play a role in these changes are irradiation dose, temperature, graphite composition and the initial microstructure of the graphite. Understanding the details of how these material changes occur and exactly what the changes consists of will enable the prediction of the material property changes as a function of these variables. Other work has shown these atomic level and microstructural changes can be healed or annealed out by raising the irradiated graphite above its irradiation temperature. Here in this work, experiments were carried out to investigate how the properties of irradiated graphite recover when heated. By showing property recovery as a function of annealing temperature or energy, insight is provided into the type of damage that occurred during neutron-irradiation. The data presented here shows recovery of thermal diffusivity, coefficient of thermal expansion, Young's modulus and electrical resistivity between annealing temperatures of 500 °C and 2380 °C. Graphite grades NBG-18, IG-110 and PCEA are considered that were both stressed and unstressed during irradiation.

36 MATERIALS SCIENCE↗

Exploring the Mineral Composition, Structure, and Function of a Freshwater Bivalve Adhesive

Abstract Etheria elliptica is a freshwater oyster that produces an adhesive that hardens underwater, allowing them to attach to other oysters, rocks, wood, and other natural substrates, producing complex oyster bed communities. Despite the importance of the adhesive in oyster bed formation, little is known about its chemical composition, structure, or mechanical properties. Through a combination of scanning electron microscopy (SEM), x‐ray photoemission electron microscopy (X‐PEEM), infrared (IR) spectroscopy, microhardness testing, and nanoindentation, it is found that the oyster adhesive consists entirely of aragonite nanoparticles that clump together into crystallites of varied shape, size, and orientation. The crystallite clumping density varies from the exterior of the adhesive to the interior, with the adhesive closest to the prismatic layer generally being denser. With this variation in density comes a variation in material properties with the exterior adhesive layer being softer and more flexible and the interior adhesive layer being harder and less elastic, or more similar to the prismatic and nacre shell structures produced by the E. elliptica . The resultant material exhibits varied materials properties, despite similar mineral composition.

Chemistry↗