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DOE OSTI2025

Incorporating civilian radioxenon background estimates in anomaly detection

A nuclear explosion screening exercise in 2023 (Maurer et al., 2023) found challenges with discerning anomalous radioxenon activity concentrations relative to elevated background concentrations. Research has continued into methods to detect anomalous radioxenon concentrations by comparing samples to estimates of atmospheric radioxenon background concentrations caused by releases at nuclear reactors or medical isotope production facilities. A new approach estimates the sample concentrations using time-varying radioxenon release rates obtained using optimization techniques that constrain the facility release rates to plausible amounts based on historical data or facility knowledge. The purpose of the optimization is to determine whether any combination of plausible release rates from emitting facilities can explain a series of radioxenon measurements at one or more sampling stations. A case study uses radioxenon data collected at three locations in western Europe for a month in 2021 and considers releases from 77 locations. Fewer samples are identified as being anomalous using a simplistic flagging rule than from an application of the current International Monitoring System (IMS) activity concentration-level rule.

Environmental sciences↗

DOE OSTI2024

Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)

Extreme heat and drought conditions are affecting water availability in many regions worldwide, leading to negative impacts on human societies, agriculture, and ecosystems. However, current research lacks comprehensive spatiotemporal analysis examining the interplay between multiple hydrological factors and heatwave events, especially in the context of climate change. This research broadly pertains to understanding the dynamics of hydrological factors and their potential responses to heatwave during warm seasons across the contiguous United States for the period from 2003 to 2022. Utilizing data from the Global Land Data Assimilation System (GLDAS), we analyzed surface runoff, evapotranspiration (ET), precipitation, Groundwater Storage (GWS), Root Zone Soil Moisture (RZSM), and Total Water Storage (TWS) to discern annual patterns and the impacts of heatwave. Further, the spatial patterns of heatwave highlighted a higher occurrence in the western, central, and northeastern U.S., with longer average durations in the western and south-central regions. These events are predominantly dry, characterized by low Relative Humidity (RH), except in the southeastern U.S., where heatwave coincide with high RH levels. Post-heatwave analysis indicated a reduction in GWS, TWS, RZSM, and ET, alongside an increase in surface runoff, RH, and precipitation. An in-depth examination of rainfall and temperature dynamics during heatwave revealed weak correlations between rainfall and temperature, as well as between rainfall and heatwave duration, highlighting the complex nature of these interactions. The study also found an enhanced probability of rainfall following heatwave, particularly in the eastern regions, drawing attention to the potential for increased flood risks post-heatwave. Our findings contribute to the growing body of knowledge on the impacts of heatwave on hydrological factors, providing valuable insights for climate change adaptation and water resource management strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Lipid and lipoprotein metabolism in microglia: Alzheimer’s disease mechanisms and interventions

Alzheimer's disease (AD) presents a significant challenge owing to its widespread prevalence and complex neuropathogenesis, affecting millions worldwide. Current therapeutic strategies that predominantly target amyloid-beta accumulation are insufficient, particularly for ApoE4 carriers. Alterations in lipid composition are well documented in AD, characterized by reductions in phospholipids and sulfatides, along with increases in cholesterol, cholesteryl esters, and triglycerides (TGs). Microglia, the brain's resident immune cells, link dysfunctional lipid processing to AD neuropathogenesis. For example, genetic studies have pointed to microglial lipid and lipoprotein processing gene variants as some of the strongest risk factors for AD. In addition, microglial dysfunction, characterized by lipid droplet accumulation, increased cholesterol and TG levels, and altered lipid transport, may exacerbate the pathological hallmarks of AD, such as amyloid-beta and tau accumulation. Conversely, emerging studies have shown that strategies aimed at inhibiting lipid droplet accumulation in microglia, reducing TG synthesis, and promoting the activity of lipoprotein receptors expressed by microglia can improve cell functions and markers of AD pathology. This review dissects the interplay between microglial lipid metabolism and AD, highlighting the significance of lipid transport and trafficking within the CNS. Given the intrinsic link between microglial metabolism and AD progression, emerging and potential therapeutic strategies aimed at restoring lipid handling and improving microglial function are explored. This review provides a comprehensive examination of the emerging literature, detailing the current state of knowledge on microglial lipid metabolism, its genetic underpinnings, and the potential for novel interventions targeting these mechanisms to ameliorate AD pathology.

Alzheimer's disease↗

DOE OSTI2024

Physics-informed KNN milling stability model with process damping effects

This paper describes a k-nearest neighbors, or KNN, model for milling stability including process damping effects. A physics-based, frequency domain milling stability solution is used to generate the training data, but does not incorporate process damping effects. The data set is then updated using limited tests to capture the process damping behavior. A “stair step” approach is used to select the test points, where a first spindle speed-axial depth combination is selected based on the physics-based stability map, subsequent tests are defined using the previous test result, and data points are updated by knowledge of process damping behavior and the test results. Furthermore, the KNN modeling approach demonstrates the ability to predict both stable and unstable results, including process damping behavior.

42 ENGINEERING↗

DOE OSTI2025

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗

DOE OSTI2024

On the product phases and the reaction kinetics of carbothermic reduction of UO 2 +C at relatively low temperatures

The synthesis of UC using carbothermic reduction of UO 2 and C mixtures has been well studied at high temperatures. However, the product phase behavior of carbothermic reduction at low temperatures (≤1773 K) is not well studied. Such a study is important as low temperatures permit single phase UC synthesis without forming secondary higher carbides, and it further supports the knowledge base of the process that needs to be used for transuranic elements such as plutonium that have high vapor pressures at elevated temperatures. Therefore, a low temperature carbothermic reduction of two different C/UO 2 molar ratios under inert and reducing environments have been studied here. Two different sample holding crucibles, alumina (Al 2 O 3 ) and graphite, were also used here to differentiate the hypostoichiometric (UC 1-a ) and oxygen dissolved (UC 1-x O x ) uranium monocarbide phases adding more details on the two systems. Also, the reaction kinetics involved in the formation of UC via the carbothermic reduction of UO 2 +C using product phases instead of evolved gases such as carbon monoxide is reported here. Under inert atmospheres but with significant oxygen partial pressures, the low temperature carbothermic reduction of UO 2 +C produced up to 90 wt.% UC 1-x O x type oxycarbides as was confirmed by Xray powder diffraction. Reducing Ar-4%H 2 environments at these temperatures were not successful in synthesizing UC as it reduces the amount of C required for the carbothermic reduction, leaving UC phase at a non-equilibrium state. Inert atmospheres with low or negligible oxygen partial pressures on the other hand produced near stoichiometric UC at high phase purity, especially at 1673 – 1773 K temperature range. An activation energy of 377±75 kJmol -1 was also calculated using product phase concentrations of the carbothermic reduction of UO 2 +C under these inert Ar (g) atmospheres.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A model for trapping and re-solution regarding intra-granular bubbles in UO 2 , linked to atomic-scale simulations

In the literature, a clear definition of the irradiation re-solution frequency of gas from bubbles in the UO 2 fuel is absent. Moreover, for intra-granular bubbles, a detailed calculation of the cumulated displaced gas quantities in function of the distance from the radius of the bubble after a re-solution event has never been published. The assessment of these two elements is very useful if we want to increase the adherence of fission gas release codes to our present knowledge of the behavior of fission gases. Hence, we suggest to link the definition of the re-solution frequency to atomic-scale simulations. Furthermore, we present the cumulated displaced gas quantities obtained from Molecular Dynamics calculations, from which we have derived a re-solution profile that can be exploited to better consider the irradiation re-solution phenomenon inside Fission Gas Release codes. On top of that, we have built a new trapping/re-solution model for intra-granular bubbles linked to Molecular Dynamics simulations that can be easily incorporated into Fission Gas Release codes. In conclusion, we also check that the model is properly built through the comparison of the new model against a reference.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Impact of chemical ordering on thermodynamic properties of point defects and Xe substitutional in U-10Mo

The accurate knowledge of defect energetics is critical to understanding the aging and irradiation behavior of U-10Mo nuclear fuel, which is selected as the fuel type for conversion of the United States High-Performance Research Reactors (HPRRs). Furthermore, using hybrid molecular dynamics and Monte Carlo (MDMC) simulation, we studied the impact of chemical ordering on the formation energies of vacancies, interstitials, and the solution energy of the Xe substitutionals. Instead of forming a random solid solution (RSS), substantial short-range-order (SRO) develops in U-10Mo, particularly at low temperatures. Mo atoms are found to repel each other and prefer U-rich local atomic environments within the 1st nearest neighbor (1NN) cutoff. Compared to the case of a RSS, the state with equilibrated Mo ordering shifts the distributions of vacancy and interstitial formation energies due to the dependence of defect energies on the local atomic environment, without a clear effect on Xe solution energy. In the operation temperature range (100–250 °C) of U-Mo fuels, neglecting SRO can lead to an inaccurate estimate of thermal equilibrium point defect concentrations by over an order of magnitude and incorrectly predict the preference among different types of dumbbells, highlighting the critical importance of accounting for the impact of chemical ordering for accurate atomistic calculations of defect properties.

Molecular dynamics and Monte Carlo (MDMC)↗

DOE OSTI2025

In-situ irradiation of uranium carbide

Uranium carbide (UC) is a leading candidate fuel for Generation IV reactors due to its high uranium density and thermal conductivity. However, its irradiation performance—particularly gas bubble swelling and defect dynamics—remains poorly characterized. Using in-situ transmission electron microscopy (TEM), we irradiated UC with 300 keV Xe + and 1 MeV Kr 2+ ions at temperatures up to 900 °C to quantify swelling behavior and dislocation loop evolution. The swelling remained below 0.6 % across all temperatures, suggesting the dimensional stability of UC under irradiation at these temperatures. Dislocation loops grew faster in UC than in UO 2 or UN, correlating with its lower homologous temperature. Notably, nanograin structures emerged in thin regions of the lamellar, mirroring phenomena previously observed in UO 2 and ZrC. These results address critical knowledge gaps in the radiation tolerance of UC and provide insight into its suitability for advanced reactor systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

An integrated approach to examine fuel-cladding chemical interaction in HT9/U-10Zr metallic fast reactor fuels: Coupling machine learning with electron microscopy and local mechanical properties analysis

The metallic U-Zr nuclear fuel alloy has garnered renewed interest as a promising candidate for next-generation sodium-cooled fast reactors. Recent studies and technology assessments have identified several areas requiring improvements, enhanced knowledge, and reliable data to strengthen the U-Zr fuel design basis for qualification and commercial applications. One of the most challenging phenomena impacting this fuel system’s performance is fuel-cladding chemical interaction (FCCI). This work aimed to harvest FCCI data by examining selected HT9/U-10Zr (wt. %) fuel samples of prototypic full-length fuel pins through an integrated approach. This approach integrated scanning electron microscopy (SEM) microstructure characterization with localized mechanical properties examination to deepen understanding of FCCI phenomenon in HT9/U-10Zr fuel system. Particularly, this study focused on MFF fuel pins irradiated at Fast Flux Test Facility (FFTF), which aimed to qualify metallic fuel as a driver fuel for FFTF and to assess its viability for larger-scale fast reactors. Electron microscopy provided high confidence in detecting and distinguishing the different FCCI layers, while small-scale mechanical testing (SSMT) probed the mechanical properties of these layers. SEM examination of a MFF-2 pin 192167, with a time averaged inner cladding temperature (TICT) slightly over 500°C, revealed minimal cladding-side FCCI (cladding wastage). In contrast, significantly thicker cladding wastage comprising two distinct sublayers was observed in samples from the thermally hot MFF-3 pin 193045 and MFF-5 pin 195011 where the TICT ranged from 610-635°C. SSMT indicated complete embrittlement in the sublayer adjacent to the fuel and a tendency toward embrittlement in the other sublayer. Additionally, a new machine learning method was developed, validated, and used to quantify cladding wastage thickness. The machine learning method reliably predicted the wastage thickness across various fuel pins and sample cross-sections. Furthermore, the available cladding wastage data from HT9/U-10Zr fuel system demonstrated a strong temperature dependency. However, the dataset remains small, and ongoing research activities are essential to further understand the FCCI phenomenon and develop a reliable FCCI model for enhanced fuel performance simulation under various conditions.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

A Kinetic Model of the Long-Term Corrosion of Glass-Ceramic Materials

Multiphase waste forms show promise for increased waste loading and for the ability to dispose of contaminated solid and particulate waste through direct densification. However, achieving predictive capability for long-term durability of multiphase waste forms, and thus assessing their possible deployment, requires expanding the current, limited knowledge base. Here, we describe the development of a corrosion model of a two-phase waste form consisting of crystals of known volume fraction embedded in a glass matrix. This model accounts for the dissolution of both the crystalline and glass phases as well as the hydration of the glass phase through an ion exchange reaction. Because of the large difference in solubility between the two phases, the reactive surface of the crystalline phase is a function of the extent of dissolution of the glass phase in this model. Model parameterization was performed using corrosion data, such as from single-pass flow-through tests, for the individual phases. The parameterized corrosion model was evaluated against static dissolution test data for a glass-ceramic multiphase waste form. This evaluation demonstrated the model’s ability to reproduce the time-dependent release of key tracers of glass and crystalline phase dissolution. Hence, the development of a kinetic model provides a pathway for long-term durability predictions and thus the use of multiphase waste forms in nuclear cleanup missions.

Kerisit, Sebastien N.↗

DOE OSTI2025

Systematic feature design for cycle life prediction of lithium-ion batteries during formation

Optimization of the formation step in lithium-ion battery manufacturing is challenging due to limited physical understanding of solid-electrolyte interphase formation and the long testing time (∼100 days) for cells to reach the end of life. We propose a systematic feature-design framework that requires minimal domain knowledge for accurate cycle life prediction during formation. By only using two simple Q (V) features designed from our framework, extracted from formation data without any additional diagnostic cycles, we achieved an average of 9.87% error for cycle life prediction. Here, the physics-based investigation guided by the two designed features shows that the voltage ranges identified by our framework capture the effects of formation temperature and microscopic-particle resistance heterogeneity. By designing highly predictive, robust, and interpretable features, our approach can accelerate industrial battery formation research, leveraging the interplay between data-driven feature design and mechanistic understanding.

25 ENERGY STORAGE↗

DOE OSTI2025

Dynamics of disordered intermediates during the two-electron alkaline MnO 2 conversion reaction for grid-scale batteries

Battery technologies beyond Li-ion are likely needed for extensive integration of grid-scale storage. The rechargeable Zn-MnO 2 chemistry has the potential for high sustainability, high safety, and low cost, using Earth-abundant basis materials. In an alkaline electrolyte, the MnO 2 cathode can cycle reversibly if modified by including a Bi-containing additive, although the cycling mechanism remains mostly unknown. This work presents an account of the intermediate species involved in the electrochemical transformation from layered δ-MnO 2 to Mn(OH) 2 and back. During charge, a disordered intermediate with a structure resembling layered β-MnOOH exists stably for an extended period, corresponding to a regime known to have unexpected electrochemical activity of Bi. During discharge, β-MnOOH exists only briefly and is never the majority material, revealing that the cycling mechanism is asymmetric. In conclusion, these findings represent a significant advance in mechanistic knowledge and can enable engineering to develop the system for commercial use.

36 MATERIALS SCIENCE↗

DOE OSTI2025

The influence of kinematics of deformation on polycrystalline halite dynamic recrystallization: Full-field simulation of simple shear versus pure shear

Rock salt, composed mainly of halite, flows viscoplastically over a wide range of geological conditions, strongly impacting the dynamic evolution of sedimentary basins and orogens. Understanding how dislocation creep, which involves dislocation glide, intracrystalline recovery and dynamic recrystallization, influences the microstructure and rheology of halite under various deformation kinematics and temperatures is crucial for enhancing knowledge of salt flow dynamics. Here, this study employs a full-field numerical simulation method to compare the viscoplastic deformation of polycrystalline halite under simple shear and pure shear conditions up to a natural strain of ε = 1.5 at temperatures ranging from 100 °C to 300 °C. The results are presented in terms of crystallographic preferred orientation (CPO), grain shape preferred orientation (SPO), subgrain boundary direction, grain size and strain rate distribution. The results indicate that the crystallographic anisotropy of individual halite crystals is transferred to the polycrystalline scale, resulting in strain localization, particularly in simple shear simulations. The kinematics of deformation affect the evolution and distribution of high strain-rate bands, determining the direction of intragranular substructures and the morphology of strain-induced grain boundaries, with minimal impact on grain size. The intensity of grain boundary migration increases with temperature, significantly influencing grain morphology and size, thereby obscuring strain localization, while having little effect on CPOs. At low strain (ε < 1.0), CPOs relative to both the maximum shortening direction and the grain SPO are similar regardless of the deformation kinematics. At high strain (ε > 1.0), simple shear CPOs exhibit three stronger {100} maxima with a monoclinic symmetry relative to the grain SPO compared to the six {100} maxima with an orthotropic symmetry relative to the grain SPO generated under pure shear. Therefore, microstructures and CPOs can serve as indicators of the strain path in polycrystalline halite under various conditions, aiding in determining the shear sense and elucidating the deformation kinematics of salt structures.

58 GEOSCIENCES↗

DOE OSTI2026

Identification of drug repurposing candidates for amyotrophic lateral sclerosis using electronic health records: a retrospective cohort study

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with a life expectancy of only 3–5 years and few approved treatments. To identify drug repurposing candidates for the treatment of ALS, we analysed the electronic health records (EHRs) of a large cohort of military veterans with ALS. We analysed the EHRs of individuals in the US Veterans Health Administration (VHA) database who were diagnosed with ALS between Jan 1, 2009 and Dec 31, 2019 to assess medication effects. Individuals without recorded prescriptions after the date of diagnosis were excluded. Two sets of criteria were applied to ascertain exposure. Exposure criteria A were met if the dispense date or the end date of the medication was within 12 months of ALS diagnosis and the end date was at least 6 months after the dispense date. Exposure criteria B were met if there were at least two dispenses within 6 months before diagnosis and 12 months after diagnosis. Propensity score-matched control groups were generated on the basis of confounders included in the EHR, with methodology of potential outcomes used to infer treatment effects. The primary outcome was death. A standard Cox proportional hazards analysis was done to assess association with survival. Survival was defined as the time from diagnosis date recorded in the EHR to death reported in the Department for Veterans Affairs Vital Status File. Follow-up survival time was censored on Dec 31, 2020, for those alive on this date. Downstream protein targets of drugs with clinically significant effects were analysed using the protein–protein interaction networks-based algorithm PathFX. The EHRs of 11 003 individuals with ALS in the VHA database were appropriate for analysis. 162 medications with treatment groups of 30 or more individuals were identified. Among these 162 medications, 27 were associated with statistically significant changes (≥0·1) in the hazard ratio (HR) for death. 18 of the medications were associated with a reduced HR for death (prolonged survival), and nine were associated with an increased HR for death (reduced survival). Drugs associated with reduced HR included HMG-CoA reductase inhibitors (simvastatin, pravastatin, lovastatin, and atorvastatin), PDE5 inhibitors (vardenafil and sildenafil), and α-adrenergic antagonists (tamsulosin and terazosin). The medications associated with an increased HR were drugs used either in the management of clinical features of ALS associated with poor outcomes or in end-of-life care. PathFx analysis identified a complex of proteins interacting with several of the identified drugs. To our knowledge, this analysis is the largest EHR-based study for identifying drug repurposing candidates for ALS. We identified several drugs that warrant further assessment as therapeutic options in ALS, as well as a protein network complex that might serve as a therapeutic target for ALS.

Reimer, Richard J. [Stanford Univ., CA (United Sta↗

DOE OSTI2025

Thin film combinatorial sputtering of TaTiHfZr refractory compositionally complex alloys for rapid materials discovery

Many applications from advanced nuclear reactors to aerospace and automotive industries require materials to operate in extreme environments. In search of new materials that can operate in these extremes, the present work explores this space whereby: (1) guided by atomistic and thermodynamic calculations we utilize thin film combinatorial synthesis to rapidly explore mechanical and thermal properties in a broad range of refractory compositionally complex alloys, and (2) observe transformation induced plasticity via oscillations in the thin film nanoindentation load depth curves that are attributed to, (3) a stress-induced HCP-to-BCC phase transformation in the resulting nanogranular microstructure, which to our knowledge has not been observed before in this alloy system; and finally (4) scale to bulk materials to compare the thin film results.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Identifying multiple synergistic factors on the susceptibility to stress relaxation cracking in variously heat-treated weldments

The 347H austenitic stainless steel has been widely used for pressure vessels and pipeline (PVP) applications due to its excellent creep and corrosion resistance, which fit ideally to the harsh conditions in petrochemical industries, fossil fuel or nuclear power plants, and modern energy storages. However, a failure mode has been commonly observed with cracks emerging at the heat affected zone (HAZ) of weldments during post-weld heat treatment (PWHT) or under intermediate to high temperature service conditions. This phenomenon is termed as Stress Relaxation Cracking (SRC) since the purpose of PWHT is to relieve the welding-induced residual stress fields, or as Stress Age Cracking (SAC) if failure happens during service. A leading literature explanation of this failure suggests that the residual stress relaxation and the precipitation dissolution and/or re-precipitation occur in the same temperature range, which can lead to locally high strains and thus to crack at the grain boundaries. Since in situ spatial measurements of residual stress fields, microstructural evolution, and failure processes are nearly infeasible, this work recourses to a micromechanical finite element framework that models the high temperature failure as the nucleation and growth of grain boundary cavities, whereas various parameters such as thermomechanical loading history and its evolution, the competition of grain-interior dislocation creep and grain-boundary diffusion in failure lifetime, and microstructural heterogeneities (such as the precipitate free zone near grain boundaries) can be quantitatively incorporated. It can be concluded from these microstructure-explicit simulations that an accurate knowledge of residual stress evolution and a carefully calibrated set of material constitutive parameters are the essential prerequisites for lifetime predictions. The understanding of individual governing factors also leads to a mechanistic interpretation of the observed SRC susceptibility C-curves. In conclusion, these results suggest that the criticality of residual stress evolution, but not the precipitation-induced local strains, be the leading factor for SRC.

347H stainless steel weldments↗

DOE OSTI2025

Fully implicit crystal plasticity models representing orientations with modified Rodrigues parameters

Here, this work describes a crystal plasticity formulation combining several mathematical, numerical, and implementation choices to produce a highly efficient model. Specifically, the key choices in the implementation are (1) representing orientations with modified Rodrigues parameters, (2) implementing a fully coupled implicit time integration for the elastic stretch, the crystal orientations, and the model internal variables, (3) implementing the model in the NEML2 constitutive modeling framework, based on PyTorch, to vectorize the calculations and port the computation to GPUs and other hardware accelerators, and (4) an exact implementation of the consistent tangent matrix, even for arbitrary coupling to other field variables beyond the displacements, like temperature, neutron fluence, etc. The first two features of the model are, to our knowledge, novel. The paper considers each of these choices individually as well as the final model as a whole. This includes a full description of modified Rodrigues parameters, their advantages over other representations of orientations, the mathematical formulae and tools required to implement a model with modified Rodrigues parameters, and a detailed description of the geometry of the space of modified Rodrigues parameters (in an appendix). It also includes a description of a fully implicit time integration scheme for the orientations and the advantages in representing orientations with modified Rodrigues parameters in implementing such a model. The work then assess, via numerical examples, the advantages of fully coupled implicit time integration versus more common decoupled and explicit time integration schemes. These studies demonstrate the computational advantages of fully coupled integration versus other time integration algorithms, though the performance of the competing models depends on the complexity of the underlying single crystal model. The study concludes by demonstrating that the choice of time integration method affects the sharpness of the predicted texture, with explicit methods for integrating the orientations overestimating texture sharpness and implicit methods underestimating texture sharpness.

Crystal plasticity↗