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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Generation and characterization of carbon fiber microstructure in atomistic simulations

A clear understanding of carbon fiber (CF) microstructure is necessary for the development of high strength CFs. Here, we present an atomistic approach for generating and characterizing realistic mi- crostructures of CFs. Large-scale reactive molecular dynamics simulations are used to generate a set of distinct CF microstructures. Comprehensive characterization of the simulated microstructures is enabled by the development of a suite of computational structural analysis tools capable of evaluation of hy- bridization states of carbon atoms, populations and orientations of individual carbon rings, degree of graphitization, and pore size distribution. The calculation of X-ray diffraction profiles provides a direct link between the structural features of simulated samples and experimental data available for CFs. The CF generation algorithm is shown to produce microstructures with experimental densities and with structural characteristics matching those of PAN-based CFs. The key structural features affecting the properties of CFs, such as the relative fractions of graphitic, turbostratic and amorphous micro- constituents, degree of alignment, pore size distributions, and chemical cross-linking can be effectively controlled in simulations, thus enabling efficient exploration of structureeproperties relationships in CFs. The capabilities of the developed approach are illustrated by performing computational analysis of the mechanical deformation and fracture of CFs under axial tensile loading.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response

Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To predict the performance of particular microstructural configuration and thereby overall performance, constitutive models of materials with microstructure are needed. In this work we provide neural network architectures that provide effective homogenization models of materials with anisotropic components. These models satisfy equivariance and material symmetry principles inherently through a combination of equivariant and tensor basis operations. We demonstrate them on datasets of stochastic volume elements with different textures and phases where the material undergoes elastic and plastic deformation, and show that the these network architectures provide significant performance improvements.

anisotropy↗
DOE OSTI2021

Evolution of microstructures in radiation fields using a coupled binary-collision Monte Carlo phase field approach

The simulation of radiation effects in materials broadly falls into two categories. At short time and length scales lies the modeling of primary radiation damage, such as point defect creation, energy deposition, and ballistic mixing. This is followed by the modeling at longer time scales of thermally activated microstructure evolution and defect reactions, such as recombination, clustering, and coarsening. The binary collision Monte Carlo method is an established, numerically efficient method for the computation of primary radiation damage. Conversely, the phase field method is a state of the art method for microstructure evolution on longer time and length scales. Here we present a concurrent coupling of these two methods, overcoming the difference between the discrete object Monte Carlo paradigm for primary radiation damage and the continuum field variable approach for microstructure evolution. The coupling is bidirectional, in which the microstructure evolution in the MOOSE finite element frame- work provides the spatial scattering data set for the charged particle trans- port and receives point defect, mass transport, and heat source terms from the simulated collision cascades that contribute to the field variable evolution. The concurrent coupling scheme is implemented in the code Magpie and demonstrated by investigating patterning for a model irradiated immiscible binary alloy. The results from the coupled binary collision Monte Carlo/phase field simulations reproduce the results of analytical models for phase separation, phase mixing, and patterning, supporting the approach and indicating its utility for modeling real materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A scalable framework for efficient coupling of thermal and microstructural simulations in additive manufacturing

Predicting microstructure evolution in metal additive manufacturing (AM) is important for process optimization, but spatiotemporal scale disparities between thermal transport and microstructure evolution create significant challenges for efficient data transfer between simulation codes. To address this, we present Stork, a scalable framework for coupling thermal and microstructural simulations. Stork uses a sparse data representation to identify and store active solidification sub-volumes, enabling highly parallel quad-linear interpolation from coarse thermal grids to fine microstructure grids without large intermediate storage. We demonstrate the framework by coupling the semi-analytic heat transfer code 3DThesis with the time-parallel cellular automata code Toucan. This approach achieves over two orders of magnitude reduction in data generation time and file size compared to prior workflows. Numerical studies show that quad-linear interpolation preserves grain morphology and crystallographic texture in laser powder bed fusion (LPBF) simulations for coarsening ratios up to 16. Overall, Stork provides a scalable pathway for high-throughput, component-scale AM simulations on modern high-performance computing systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The effect of microstructure on the relationship between grain boundary sliding and slip transmission in high purity aluminum

The relationship between grain boundary sliding (GBS) and slip transmission is investigated experimentally at grain boundaries in 99.99% aluminum with a through-thickness, coarse grained microstructure deformed in tension at 190 °C. Using scanning electron microscope enabled digital image correlation (SEM-DIC) and electron backscatter diffraction (EBSD), high resolution strain fields and microstructural information were measured to examine the influence of microstructural neighborhoods on interactions between GBS and slip transmission and strain localization. Several distinct cases are presented that highlight important microstructural factors that govern deformation near grain boundaries. The findings include (1) direct transmission and GBS were anti-compatible and facilitated by opposing boundary types (low misorientation and high energy grain boundaries respectively); (2) increased GBS activity was correlated with decreased indirect transmission behavior; (3) GBS accommodation at triple junctions was enabled by intragranular plasticity; and (4) the local intragranular plastic strain discontinuity between grains determined the magnitude of GBS gradients. Finally, this work provides insight into the nature of these mechanisms and can be used to identify strain transfer criteria that can lead to improved GBS-sensitive crystal plasticity models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strength-ductility synergy through microstructural and compositional heterogeneity in directed energy deposition additive manufacturing of face-centered cubic materials

Directed energy deposition (DED) is an additive manufacturing (AM) process based on welding technology and offers the advantages of large build volume, high deposition rate, and ability to fabricate multi-material parts. Epitaxial continuous columnar grain growth is a characteristic microstructural feature of DED processed alloys. In this study, a bamboo-like microstructure (periodic alternation of equiaxed and columnar structure) was produced by adopting an intermittent deposition strategy in 316L stainless steel and Inconel 625. The formation of a bamboo-like alternating microstructure was confirmed through electron backscattered diffraction (EBSD) analysis. Hardness mapping showed that the columnar to equiaxed transition (CET) occurred at the region right below the fusion line. A finite element (FE) model was used to investigate the relationship between the temperature gradient (G) and the solidification rate (R). The FE model showed a low G/R ratio at the region right below the interface promoting the CET. The grain size and material-dependent deformation behaviors are analyzed using digital image correlation (DIC). The lower deformation on the fine-grain regions observed in DIC analysis is attributed to a higher strain hardening rate, which is confirmed through dislocation density analysis on a tensile-interrupted specimen. The periodically alternating grain size coupled with the microstructural changes caused by intermittent deposition strategy result in a better strength-ductility synergy in both single-material and bimetallic specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigating microstructural evolution in SolidStir™ extruded oxide dispersion strengthened 14YWT alloy fuel cladding tube

Structural components for extreme environments require advanced materials and manufacturing processes. One such advanced material is oxide dispersion strengthened (ODS) Fe–14 wt.%Cr–3W–0.4Ti–0.3Y 2 O 3 (14YWT), which is developed for components to be used in Gen IV and fusion nuclear reactors. However, the conventional manufacturing processes to produce components, such as fuel cladding tubes, either do not retain the desired microstructural attributes or are costly and less efficient. As a result, a more attractive option is a novel manufacturing process developed on the principle of friction stir welding or processing (FSW/P) and commercially referred to as SolidStir™ Extrusion (SSE). Here this study used the SSE technique to study the manufacturing and microstructural evolution of a fuel cladding tube made of ODS 14YWT alloy. The cladding extrusion by the SSE technique involved the use of ball-milled 14YWT powders with Y, Ti, and O in the solid solution and the use of a specially designed W-25Re-Hf tool for consolidation and extrusion of the powders. A scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and transmission electron microscope (TEM) were utilized for microstructural characterization. A Keyence microscope captured macrostructural photographs of the extruded tube. EBSD examination of the extruded tube on both transverse and longitudinal cross-sections showed the presence of dynamically recrystallized grains and revealed that the average grain size of the transverse cross-section was smaller than that of the longitudinal cross-section. The texture was weak and consisted of some amount of shear texture. The presence of nano-oxide clusters or precipitates of Y, Ti, and O (pyrochlores) in the extruded tube was determined by TEM. Aging heat treatment caused the average precipitate size to decrease and the density to increase compared to the as-processed condition. The results indicated that SSE is a viable tool for manufacturing fuel cladding tubes with the desired microstructural attributes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Identifying microstructures susceptible to pulverization in commercially irradiated high burnup UO2 under LOCA conditions

High burnup fuel fragmentation (HBFF) has been a concern in the nuclear industry for many years. When UO2 reaches and exceeds pellet average burnups around 55 GWd/tU, microstructural changes in the fuel pellet begin to occur that render the pellet susceptible to fine fragmentation under loss-of-coolant accident (LOCA) conditions. During a LOCA event, the cladding balloons and bursts, potentially releasing part of these fine fuel fragments into the reactor pressure vessel. This process is known as fuel fragmentation, relocation, and dispersal (FFRD). Presently, the US nuclear industry is developing a safety basis for FFRD with the goal of increasing burnups and pressurized water reactor cycle lengths. Increased cycle lengths would push the burnup limits of the fuel rods past the known threshold for HBFF susceptibility. In this work, the microstructural impact on HBFF was investigated by comparing the microstructures of as-irradiated rod segments to their post-LOCA tested counterparts. This investigation found that varied operational histories result in different microstructural evolutions across the pellet radius, which impacts the fragmentation behavior and radial location of the fragmentation. It is noted that regions with a high bubble density and a high density of grain boundaries fragment under LOCA-relevant conditions. In addition to the fragmentation that has been previously reported at the periphery of the fuel, fragmentation was also noted in the dark zone toward the fuel center. Analysis of the power histories of the fuel samples suggests that the dark zone forms in the central regions of the pellet between temperatures of approximately 740 and 960 °C.

McKinney, Casey [ORNL] (ORCID:0000000335383614)↗
DOE OSTI2026

Irradiation of UC1+x kernels using the MiniFuel vehicle: Microstructure, phase analysis, and initial post-irradiation examination

Uranium carbide is a candidate fuel form for a wide range of advanced reactors, including larger Generation IV reactors as well as small modular reactors and microreactors. However, its commercial deployment timeline faces challenges via traditional qualification approaches. To address this issue, an accelerated fission rate irradiation test was performed to collect basic fuel performance data to inform fuel performance models and potential future integral tests. Hyperstoichiometric UC (UC1+x) kernels were irradiated in the High Flux Isotope Reactor using the MiniFuel irradiation vehicle. The test matrix spanned two temperature regimes (700 °C and 800 °C) and burnup levels (1.8 % FIMA and 2.8 % FIMA). Between 21 and 63 kernels were tested at each unique temperature and burnup condition. As-fabricated microstructural analysis revealed a multiphase composition with UC, UC2, UC2−y, and U-C-O bearing phases for the irradiated kernels. Following irradiation, fission gas release, swelling, and microstructures were analyzed. Measured fission gas release was below 5 % for all irradiation conditions, reaching a maximum at the highest temperature and burnup condition. A binary swelling response was observed; the lower burnup and temperature conditions resulted in negligible swelling, but the higher burnup and temperature conditions produced significant anisotropic swelling and densification in a subset of kernels. The basic microstructural exams of kernels following irradiation were not capable of showing a correlation between kernels that exhibited excessive swelling and those that did not. Characterization of a subset of samples using the Advanced Photon Source and more detailed microstructural examination of unirradiated kernels revealed that a subset of kernels contained very high UC2 phase fractions. The anomalous swelling response is hypothesized to have been driven by this chemical variation. The results of this irradiation highlight the potential of accelerated fission rate irradiation testing to explore such behaviors and inform the development of fuel specifications.

Adorno Lopes, Denise [ORNL] (ORCID:000900023705987↗
DOE OSTI2019

Data clustering for the high-resolution alignment of microstructure and strain fields

The emergence of small-scale deformation mapping by a combination of scanning electron microscopy and digital image correlation (SEM-DIC) has enabled full-field investigations into the complex roles of microstructure on microscale deformation mechanisms. However, these investigations are hindered by errors in alignment between the microstructure data, generally acquired by electron backscatter diffraction (EBSD), and the microscale strain data obtained by SEM-DIC. Distortions, stitching artifacts, and spatial resolution differences between microstructure and strain fields can lead to misalignments on the order of μms. This alignment uncertainty introduces error into microstructure-strain localization analyses and precludes the examination of deformation mechanisms near grain boundaries. To improve alignment between EBSD-obtained grain boundaries and SEM-DIC strain data, an approach was created wherein a mantle was first established around the EBSD-acquired grain boundaries. Strain data was then clustered within this mantle using a k-means algorithm to identify grain boundary strain localization, and these boundary points were fit to obtain a continuous curve for each individual boundary. Clustered point outliers, such as those due to grain boundary-local dislocation slip, were statistically identified by using an absolute error threshold and removed from the grain boundary fit. The ending identification of grain boundaries in the microscale strain data is significantly improved from EBSD-identified boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strain rate sensitivity, microstructure variations, and stress-assisted β → α" phase transformation investigation on the mechanical behavior of dual-phase titanium alloys

In this study, the microstructures of three widely used dual-phase titanium alloys: Ti-6Al-4V, Ti-6Al-2Sn-4Zr-2Mo, and Ti-6Al-2Sn-4Zr-6Mo are characterized using backscatter electron imaging and the deformation behaviors in their individual α and β phases are investigated using in situ high-energy X-ray diffraction during uniaxial tension experiments. This is accompanied by calculation of the strain rate sensitivity (SRS) in these alloys, as a function of applied loading. The results of the calculated SRS and the mechanical response (in terms of lattice strains and hardening behaviors) are rationalized based on the local microstructure, composition, and texture of the alloy. A stress-induced β (BCC) to α" (orthorhombic) phase transformation is observed during the in-situ diffraction experiment, which permitted analysis of the lattice strain evolution during the phase transformation. Results from this study provide insights into the relationship between microstructure, composition, applied loading, and the deformation behavior, including effects on loading with time holds. Specifically, the results show that the microstructure, and not necessarily the chemical composition (Mo content), along with the applied loading have a dominant role in the observed SRS variation in titanium alloys. Further, the evolution of the α" (orthorhombic) phase is observed for the first time during deformation of an industrially relevant titanium alloy, Ti-6246.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Microstructural stability of irradiated yttrium hydride under thermal cycles

Hydrides that retain their hydrogen in service are critical for advanced microreactor and space nuclear systems. Hydrogen retention is affected by evolving microstructure under temperature and irradiation extremes. This study investigated microstructural features in neutron-irradiated yttrium hydride and the stability of these features under thermal cycles. Differential scanning calorimetry was used to determine hydrogen desorption and temperatures at which significant phase changes are occurring, and transmission electron microscopy was used for microstructural analysis after each thermal cycle. Cyclic heating led to crystallization and epitaxial growth of surface oxidation and dehydriding of the matrix. Other features such as the bulk matrix crystal structure, irradiation-induced cavities, and matrix precipitation remained constant after thermal cycling. Results allow us to design better hydride alloys through microstructure tailoring and potential irradiation conditioning treatments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructure and mechanical properties of hypoeutectic Al–6Ce–3Ni-0.7Fe (wt.%) alloy

Here, a hypoeutectic, Fe-modified Al–Ce–Ni alloy (Al–6Ce–3Ni-0.7Fe, wt.%) is studied in terms of microstructure, thermal stability, ambient temperature strengthening, and creep resistance. The as-cast microstructure consists of primary Al dendrites and interdendritic binary eutectic regions (Al–Al11Ce3 and/or Al–Al9(Fe,Ni)2), with micron/submicron lamellar spacing, depending on the location along the height of the ingot. The cast alloy exhibits excellent coarsening resistance at 400 °C, with mostly unchanged microstructure and microhardness after 6 weeks of aging, indicating good thermal stability of Al11Ce3 and Al9(Fe,Ni)2. Orowan strengthening and load transfer are identified as strengthening mechanisms at ambient and elevated temperature. A high volume fraction of the intermetallic phases (providing load transfer) and relatively coarse eutectic spacing (for modest Orowan strengthening) result in a moderate as-cast microhardness of 566 ± 32 MPa. Creep resistance at 300 and 350 °C is similar to a binary Al-12.5Ce eutectic alloy (with twice the Ce content) because of two countering effects: Al–6Ce–3Ni-0.7Fe shows a higher volume fraction of strengthening intermetallic phases, but it also exhibits a large fraction of primary Al dendrites which weaken the alloy. By contrast, the alloy, when laser-remelted at the surface, has a fully eutectic microstructure without primary aluminum dendrites achieved by high undercooling on solidification, with a refined network of eutectic phases that doubles the microhardness as compared to the cast alloy. Whereas coarsening is faster due to the shorter diffusion distances between the eutectic phases, hardness remains ~30% higher than the as-cast alloy after ~6 weeks aging at 400 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructural evolution in shear-punch tests: A comparative study of pure Cu and Cu-Cr alloy

Understanding the mechanisms behind microstructural evolution during shear deformation has been a long-standing area of interest. However, establishing a connection between microstructure, mechanical properties, and extent of shear deformation is challenging and requires refined experimental approaches. Shear-punch testing (SPT) provides a controlled method to introduce shear into small volumes of material that later can be subjected to detailed microstructural characterization. In this study, we utilize an SPT device to induce shear deformation to pure copper and a binary copper-chromium alloy. Electron backscatter diffraction and transmission electron microscopy were used to study the mechanisms of plastic deformation after SPT. Our results indicate that shear deformation of pure Cu produces a dense network of intercepting microshear bands upon sustained deformation. Twin boundaries undergo degradation into high angle grain boundaries due to simultaneous deviation from the axis-angle pair condition of 60° misorientation on [111] direction. The presence of 50% volume Cr particles in the soft Cu matrix fundamentally altered the shear deformation mechanism. Preferential deformation of the Cu matrix led to accelerated shear-induced formation of low and high angle grain boundaries, and subsequent grain refinement. Comparatively, no grain refinement occurred in pure Cu at a strain ~10 times larger (ϵ = 4.73) than that of the copper-chromium case (ϵ = 0.42). Overall, our study sheds light on the microstructural evolution during shear deformation and highlights the significant influence of particle reinforcements on the shear deformation mechanisms of metals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of post-deposition heat treatment on microstructure and mechanical properties of NASA HR-1 cold spray coatings

The primary goal of this work was to examine the impact of heat treatment on the evolution of microstructure and mechanical properties of NASA HR-1 cold spray coatings. Coatings were produced employing a high pressure cold spray system using N2 and He process gases and the effect of process gas and deposition temperature on the microstructure and mechanical properties of the coatings was examined. Microstructural characterization was performed using optical microscopy, scanning electron microscopy, micro X-ray computed tomography, and electron backscatter diffraction. NASA HR-1 coatings produced with He process gas exhibited improved plastic deformation and resulted in the lowest porosity compared to those deposited with N2 process gas. All coatings showed brittle failure with limited ductility in the as-deposited condition. Heat treatment of the NASA HR-1 cold spray coatings was performed at 550°C and 950°C for 1 h to improve the mechanical strength of the coatings. Heat treatment improved the particle bonding and enhanced the mechanical properties of the cold spray coatings. Heat treatment performed at 550°C resulted in higher mechanical strength of coatings, whereas the heat treatment performed at 950°C resulted in recrystallized microstructure and improved ductility of the coatings. However, heat treatment at 950°C resulted in forming the Eta (η) phase and Ni-Ti intermetallics in all the NASA HR-1 cold spray coatings. Here, the overall results suggest that using He as process gas contributed to reduced porosity and enhanced mechanical properties of the cold spray coatings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Modeling Framework to Predict Melting Dynamics at Microstructural Defects in TNT-HMX High Explosive Composites

Many high explosive (HE) formulations are composite materials whose microstructure is understood to impact functional characteristics. Interfaces are known to mediate the formation of hot spots that control their safety and initiation. Here, to study such processes at molecular scales, we developed all-atom force fields (FFs) for Octol, a prototypical HE formulation comprised of TNT (2,4,6-trinitrotoluene) and HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine). We extended a FF for TNT and recasted it in a form that can be readily combined with a well-established FF for HMX. The resulting FF was extensively validated against experimental results and density functional theory calculations. We applied the new combined TNT-HMX FF to predict and rank surface and interface energies, which indicate that there is an energetic driver for coarsening of microstructural grains in TNT-HMX composites. Finally, we assess the impact of several microstructural environments on the dynamic melting of TNT crystal under ultrafast thermal loading. We find that both free surfaces and planar material interfaces are effective nucleation points for TNT melting. However, MD simulations show that TNT crystal is prone to superheating by at least 50 K on subnanosecond time scales and that the degree of superheating is inversely correlated with surface and interface energy. The modeling framework presented here will enable future studies on hot spot formation processes in accident scenarios that are governed by strong coupling between microstructural interfaces, material mechanics, momentum and energy transport, phase transitions, and chemistry.

36 MATERIALS SCIENCE↗