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158 records · Page 9

Sound speed measurements in lithium fluoride single crystals shock compressed to 168 GPa along [100]

The shock wave response of [100] lithium fluoride (LiF) single crystals at high stresses is of long-standing interest due to their extensive use as optical windows in dynamic compression experiments. The report of melting in shock compressed LiF single crystals between 134 GPa and 152 GPa – based on a single sound speed datum [J. Appl. Phys. 117, 045901 (2015)] – was surprising because good optical transmission was previously demonstrated in LiF shock compressed to ~200 GPa [J. Appl. Phys. 116, 033515 (2014)]. To address these apparent differences, we report on plate impact experiments on [100] LiF single crystals shock compressed to 168 GPa. Wave profiles were measured using laser interferometry to determine Hugoniot states and longitudinal sound speeds in shock compressed LiF. The measured Hugoniot states are in good agreement with those measured in previous studies. However, the measured sound speeds presented here show no evidence of melting up to 168 GPa. In particular, the abrupt drop reported previously in sound speed at 152 GPa was not observed in the present work. Furthermore, our results establish a lower bound of 168 GPa for the onset of melting in shock compressed LiF single crystals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.

59 BASIC BIOLOGICAL SCIENCES↗

Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions

Many materials of interest to Sandia transition from fluid to solid or have regions of both phases coexisting simultaneously. Currently there are, unfortunately, no material models that can accurately predict this material response. This is relevant to applications that "birth stress" related to geoscience, nuclear safety, manufacturing, energy production and bioscience. Accurately capturing solidification and residual stress enables fully predictive simulations of the evolving front shape or final product. Accurately resolving flow of proppants or blood could reduce environmental impact or lead to better treatments for heart attacks, thrombosis, or aneurism. We will address a science question in this proposal: When does residual stress develop during the critical transition from liquid to solid and how does it affect material deformation? Our hypothesis is that these early phases of stress development are critical to predictive simulation of material performance, net shape, and aging. In this project, we use advanced constitutive models with yield stress to represent both fluid and solid behavior simultaneously. The report provides an abbreviated description of the results from our LDRD "Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions," since we have written four papers that document the work in detail and which we reference. We give highlights of the work and describe the gravitationally driven flow visualization experiment on a model yield stress fluid, Carbopol, at various concentrations and flow rates. We were able to collapse the data on a single master curve by showing it was self-similar. We also describe the Carbopol rheology and the constitutive equations of interest including the Bingham-Carreau-Yasuda model, the Saramito model, and the HB-Saramito model including parameter estimation for the shear and oscillatory rheology. We present several computational models including the 3D moving mesh simulations of both the Saramito models and Bingham-Carreau-Yasuda (BCY) model. We also show results from the BCY model using a 3D level set method and two different ways of handling reduced order Hele-Shaw modeling for generalized Newtonian fluids. We present some first ever two-dimensional results for the modified Jeffries Kamani-Donley-Rogers constitutive equation developed during this project. We include some recent results with a successful Saramito-level set coupling that allows us to tackle problems with complex geometries like mold filling in a thin gap with an obstacle, without the need for remeshing or remapping. We report on some experiments for curing systems where fluorescent particles are used to track material flow. These experiments were carried out in an oven on Sylgard 184 as a model polymerizing system. We conclude the report with a summary of accomplishments and some thoughts on follow-on work.

36 MATERIALS SCIENCE↗

HFIR SiC Bowing Test Ready to Insert

This report describes the successful assembly of a High Flux Isotope Reactor (HFIR) irradiation experiment designed to assess radiation-induced lateral bowing of silicon carbide fiber–reinforced, silicon carbide matrix composite (SiC/SiC) components under a radial fast neutron flux gradient. Excessive bowing of a SiC/SiC channel box in a boiling water reactor could potentially interfere with control blade movements. Similar concerns exist for SiC/SiC fuel cladding in light water reactors. The experiment described herein will provide experimental validation of the structural response of a miniature SiC/SiC channel box and tube specimens with pressurized water reactor diameters during irradiation. The significant radial fast neutron flux gradients that exist in the permanent reflector of HFIR were characterized using detailed three-dimensional neutronic calculations. The three-dimensional displacement damage dose rate profile and the resulting volumetric swelling in SiC were used as inputs to structural analyses that predicted the deformation and stresses in the channel box specimen. The specimens were thoroughly characterized prior to irradiation using traditional dimensional inspection and surface profilometry so that these measurements can later be compared with similar measurements that will be made post-irradiation to determine radiation-induced deformations. Furthermore, fine engraving markers were inscribed along all outer surfaces of the specimen and mapped using a digital microscope and a three-dimensional stage. This technique allowed for accurate measurements of the marker spacings, which can be compared with similar measurements that will be made post-irradiation to provide local radiation-induced strain mapping. The experiment was successfully assembled and is scheduled for insertion during HFIR cycle 492, which is currently scheduled to run from May 25, 2021 to June 18, 2021.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Anomalous elastic softening in ferroelectric hafnia under pressure

his study employs first-principles density-functional theory (DFT) calculations to explore the elastic and mechanical properties of ferroelectric hafnia (HfO 2 ) in its polar orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase under varying hydrostatic pressure conditions up to 30 GPa. Utilizing a plane-wave basis set and Perdew-Burke-Ernzerhof generalized-gradient approximation for solids in our DFT calculations, we investigate both pure and yttrium-substituted HfO 2 . Our findings reveal an anomalous reduction in the 𝐶 33 component of the elastic tensor with increasing pressure, which becomes significant above 15 GPa and signals a potential pressure-driven structural phase transition at higher pressure. The analysis of atomic displacements under pressure sheds light on the unusual mechanical behavior and phase stability of this material. Additionally, we observe a transition from an indirect band gap to a direct band gap with increasing pressure, which could have significant implications for optical applications. Here, the effects of yttrium substitution on the mechanical and electronic properties are further examined, revealing that yttrium substitution softens the elastic response of this material and reduces the electronic band gap. These results enhance our understanding of elastic and mechanical responses of ferroelectric hafnia and its potential for applications in microelectronics, piezoelectric devices, and nonvolatile ferroelectric random-access memories. Further experimental validation is recommended to confirm our predictions and explore the practical implications of the observed phase transitions and electronic behavior of the ferroelectric hafnia under high-pressure conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fish scale-loss caused by simulated hydraulic shear stress

Riverine fishes found within streams impacted by hydropower also often pass through hydropower turbines during annual downstream migrations. During turbine passage events, fish may experience a suite of stressors including rapid pressure changes, impacts from turbine blades, and exposure to hydraulic shear. Scale-loss is often observed in fish collected below dams and hydraulic shear is the most likely cause of this trauma. While exposure to shear may cause other injuries, scale-loss appears to be the most common non-lethal injury observed to date. We sought to quantify how hydraulic shear may cause scale-loss in rainbow trout, gizzard shad, and hybrid striped bass by precisely controlling the exposure level (velocity) and duration (seconds) of a water jet. We targeted the same area for all three species found between the operculum and dorsal fin on the left, lateral surface. Exposure velocities ranged from 0 (controls) to 11.0 meters/second but fish were only exposed to the water jet for 1.5 seconds. A 0.2 milligram/milliliter solution of fluorescein was used to stain the areas of scale-loss by submerging each fish in this solution for at least 6 minutes. Fluorescein was used because it interacts with epithelial tissue that has been damaged and it fluoresces under ultraviolet lighting. Fish were photographed under short- and longwave ultraviolet lighting in a dark chamber to capture fluorescence. Fish photographs were analyzed using ImageJ and the proportion of descaled area was estimated for each fish within a 35 by 35-millimeter square. In general, these data highlight how exposure to hydraulic shear may lead to significant levels of descaling in riverine fishes.

13 HYDRO ENERGY↗

Report on RIA Relevant Modified Burst Testing of ATF Cladding Materials

The mechanical performance of accident-tolerant fuel (ATF) cladding candidates in light-water reactors (LWRs) must be similar to or better than that of current conventional nuclear fuel claddings to reduce dose to the public and ensure a that the core coolable geometry is maintained during a postulated reactivity-initiated accident (RIA) in light-water reactors (LWRs). During an RIA event, the rapid thermal expansion of nuclear fuel can deform the cladding once the fuel–cladding gap closes. In some cases, the pellet–cladding mechanical interaction (PCMI) can induce mechanical failure in ATF candidates. Thus, the mechanical response of ATF cladding must be investigated by mimicking the conditions of RIA and potentially performing Transient Reactor Test (TREAT) experiments to establish or verify the safety envelope. The work presented in this report investigated the failure behavior of as-received, hydrided, and chromium-coated (Cr-coated) Zircaloy-4 (Zry-4) cladding tube under strain-driven mechanical conditions, mimicking postulated RIA loading conditions. Mechanical testing was performed at 300°C via modified burst test (MBT) equipment with pulse width control previously developed under the Department of Energy’s (DOE’s) Advanced Fuel Campaign (AFC). The mechanical strains were determined using 2D digital image correlation (DIC) techniques. The base Zry-4 acquired by Cameco Inc. was in stress-relieved annealed (SRA) condition. Because of the observed large deformation of the cladding tubes, the failure strain definition was updated for the MBT, which can also be applied to other tube tests where significant bulging (out-of-plane deformation) is present. The failure strain was determined to be affected by the speed of the test or the RIA event. As the RIA-like event duration decreased from 75 to 15 ms, the failure strain decreased 5, 7 and 1% for as-received, hydrided, and Cr-coated specimens, respectively. Fractography on the Cr-coated specimens indicated the presence of two failure mechanisms: (i) crenulation at the outer surface of the coating due to the tensile tractional forces along with coatings grain microstructure and (ii) formation of critical defect at the coating/cladding interface that initiated coating rupture after severe plastic deformation of the Zry- 4 substrate. Based on the MBT results and fractography observations, performing mechanical property testing at high strain rates—in particular on Cr-coated tubes—and semi-integral TREAT experiments are required future efforts to ensure ATF cladding performance during transients. The testing recommended would also inform the development of long-term generalized cladding technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer–Meshkov instability

Capturing the dynamic response of a material under high strain-rate deformation often demands challenging and time consuming experimental effort. While shock hydrodynamic simulation methods can aid in this area, a priori characterizations of the material strength under shock loading and spall failure are needed in order to parameterize constitutive models needed for these computational tools. Moreover, parameterizations of strain-rate-dependent strength models are needed to capture the full suite of Richtmyer–Meshkov instability (RMI) behavior of shock compressed metals, creating an unrealistic demand for these training data solely on experiments. Herein, we sweep a large range of geometric, crystallographic, and shock conditions within molecular dynamics (MD) simulations and demonstrate the breadth of RMI in Cu that can be captured from the atomic scale. In this work, yield strength measurements from jetted and arrested material from a sinusoidal surface perturbation were quantified as Y RMI = 0.787 ± 0.374 GPa, higher than strain-rate-independent models used in experimentally matched hydrodynamic simulations. Defect-free, single-crystal Cu samples used in MD will overestimate Y RMI , but the drastic scale difference between experiment and MD is highlighted by high confidence neighborhood clustering predictions of RMI characterizations, yielding incorrect classifications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Predicting the viscoplastic response of a crystallizing fluoropolymer using transient network theory

We employ a molecular theory of dynamic polymer networks to describe the viscoplastic response of rubbery FK-800, a thermoplastic copolymer of chlorotrifluoroethylene and vinylidene fluoride, over a broad range of thermal histories. The kinetics of crystallization at different annealing temperatures was modeled using a modified Avrami equation, whose parameters were found to evolve through simple relationships over the full temperature range of the rubbery state. By fitting experimental compression data, we discovered predictable trends for the physical parameters in our mechanical model over its full range of crystallinities (up to ≈20%) and provided insights based on molecular-level physics to justify them. Using this, an end-to-end model was developed to predict the yielding and post-yield behavior of rubbery FK-800 for arbitrary thermal histories. The model successfully predicted the highly nonlinear evolution of characteristic mechanical signatures (stiffness, yield point, post-yield drop) throughout the crystallization process. A statistical analysis of variance test was employed to determine that the measured variations in the mechanical behavior of rubbery FK-800 are primarily dictated by its fractional crystallinity, regardless of its exact thermal history.

36 MATERIALS SCIENCE↗

A Novel Spatio-Temporal Regime Tracking Method for Impact Simulations

In this proposal, we present a novel method of tracking the rheological regimes activated during impact cratering events that will allow researchers to gain new insights into cratering mechanics. Rheology describes the stress-strain response of rocks to different conditions. Planetary impact cratering events often occur on too large of a scale to be feasibly captured in controlled experiments. Instead, these dynamic events are primarily studied using multi-physics codes equipped with complex material models that enable calculations of the impact event at scale. However, determining which physical processes are required for the problem of interest is challenging. Because the dominant rheological regimes change with space and time during crater formation, it is difficult to link numerical simulations with observable features of craters at the end of the event. The basis of this work is the implementation of numerical flags that track the activation of each rheological regime throughout impact simulations. We demonstrate this with the ‘Rock Model’ implemented in the CTH shock-physics code. We will use this rheology tracking method to ’zoom in’ on a specific region within an event and track the conditions the rock experiences over time. This work will develop community benchmarks to validate and distribute our implemented rheological models. We will focus on improving the melt models used by the planetary impact modeling community by developing an EOS-aware rheological transition from solid to melt. Through analysis of cell and tracer-particle based tracking data, we will study the effects of different rheologies on modeled outcomes, particularly on the volume and distributions of impacts melts. We will also use this method to link observable features with the rheological mechanisms responsible for them. The deliverables (peer-reviewed papers) from the proposed work are (i) tests of the implemented rheologic processes and demonstrations of the tracking flags; (ii) the first calculations of the spatio-temporal evolution of the dominant rheologies during impact cratering events; and (iii) application to delivery of impactor iron during basin-scale impacts.

58 GEOSCIENCES↗

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Current approaches to analyzing metabolomic data often rely on matching MS/MS fragmentation data to sparse libraries or databases. This approach results in limited identification of features, often with less than 10% of the dataset being annotated. A complementary approach is to assign molecular formula to features based on accurate mass measurements, but the platforms commonly used for metabolomics do not have the needed accuracy or resolving power to do this robustly, particularly for larger molecules. Using our newly modified analysis tool, CoreMS, we generated a library of molecular formula from pooled samples analyzed with LC-21T FT-ICR MS. This library successfully annotated approximately 53.2% of features identified from the exometabolome of marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 5.9% annotation rate achieved using a conventional MS/MS library matching approach. Using this FT-ICR MS library approach, we were able to differentiate differences in the exometabolome of P. tricornutum in iron replete and iron limited conditions, with 668 metabolites being differentially expressed (p < 0.05, 2 x intensity difference) under these conditions. The traditional MS/MS fragmentation-based annotation approach only annotated 61 of these metabolites, while our novel pipeline annotated 450 metabolites and revealed 12 metabolites that were significantly more abundant under low iron conditions. Our results demonstrate the utility of ultrahigh resolution mass spectrometry for generating more comprehensive and confident molecular annotations.

21T-FTICR-MS, CoreMS↗

Dislocation Patterning in Deforming Crystals: Theory, Computational Predictions and Validation (Final Technical Report)

This project was awarded for an initial period of three years, followed by a no-cost extension for one year and a funded one-year renewal. During the first four years, the project focused on investigating the role of dislocation reactions and dislocation correlation in dislocation patterning in FCC metals. During the fifth year, the scope of research was expanded to investigate the effects of composition inhomogeneity on the mesoscale plastic response of Body-Centered Cubic (BCC) alloys. In addition to its impact on metal hardening during deformation, dislocation patterning provides the microstructure information required to understand phenomena like fracture and recrystallization in metals. The Continuum Dislocation Dynamics (CDD) framework was the methodology used during the first four years, followed by the use of Discrete Dislocation Dynamics (DDD) during the fifth year. CDD is a density-based formalism of dislocation dynamics in which the plastic deformation of crystals is predicted together with the mesoscale dislocation patterns by tracking the space-time evolution of dislocations as driven by the applied stress, short-range and long-range interactions of dislocations, and cross slip. CDD is a crystal mechanics approach in which the plastic constitutive part is replaced with the equations of dislocation dynamics, which is driven by the internal stress via a mobility laws, while the evolution of the density gives the eigenstrain required to update the internal stress itself. The governing equations are thus those of crystal mechanics cast as an eigenstrain problem and those of dislocation transport and reactions. Our investigations during the first four years were driven by the hypothesis that that dislocation patterning is triggered by spatiotemporal dislocation density and internal stress fluctuations, and that such fluctuations influence the collective dislocation dynamic through their effects on the short-range reaction rates and the collective dislocation mobility. This hypothesis was tested by modeling the influence of the dislocation reactions and dislocation correlations on collective dislocation dynamics. The main research components during the first four years were: 1) Reformulation of the CDD framework to integrate the dislocation correlations and dislocation reactions. 2) Simulation of the dislocation correlations and quantifying their contribution to the long-range stress of complex dislocation systems. 3) Computational implementation of the updated CDD model for FCC single crystals and development of an efficient CDD code. 4) Investigation of dislocation patterning in FCC crystals based on the updated CDD model. Some key findings from these investigations were: 1) The patterning of dislocations is initiated by cross slip and internal stress fluctuations, and the refinement of the pattern results from junction formation. 2) Patterning is more prominent under high stress. 3) The correlation stress was found to be a significant part of the mean field stress in continuum representations of dislocation dynamics. During the last year of the project, we have established a method for performing dislocation dynamics in inhomogeneous alloys and demonstrated the impact of composition inhomogeneity on the characteristics of initial yielding and dislocation character in BCC alloys. We also tested this method using an irradiated ferritic alloy in which the composition and dislocation loops effects are both present. In doing so, we have considered two aspects of the role of inhomogeneity, the creation of internal coherency stress due to the dependence of the lattice parameter on the local composition, and the dependence of the dislocation mobility on the local composition. These two aspects resulted in an unexpected behavior of the dislocation system, and, in turn, the yielding behavior of BCC alloys. Key findings include: 1) The composition inhomogeneity in BCC alloys alters the well-known role of screw dislocations by forcing a level of waviness on the average dislocation character, thus destroying the screw character dominance in the yielding observed in pure or homogeneous BCC metals. 2) In the case of irradiated alloys, while composition inhomogeneity by itself and dislocation loops by themselves result in some hardening, the superposition of the two mechanisms does not result in the sum of the two contributions via any known rule. The latter result contradicts the classical works related hardening via multiple mechanisms, which state that various hardening mechanisms can be added linearly or using some Pythagorean additive rule. We were able to rationalize this unexpected result by a closer loop at the origin of the hardening mechanisms themselves, which both involved long-range elastic interactions with dislocations. We reached the conclusion that the hardening resulting from the total stress associated with these two mechanisms (current work) differs from the sum of the effects of the individual stress fields (classical literature). We have also found a major flaw in the classical theory of spinodal hardening. The latter theory never considered the impact of composition undulation on the solute hardening. We have built a new general theory accounting for the effect of solute friction together with the composition undulations on the dislocation configuration at Critical Resolved Shear Stress (CRSS), which is yielding a new definition of the spinodal hardening and new different results. This work is the first to recognize the lack of the role of solute in spinodal hardening theory of alloys.

36 MATERIALS SCIENCE↗