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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating the Radiation-Induced Redox Chemistry of Plutonium Under Used Nuclear Fuel Reprocessing Conditions

Plutonium plays a critical role in the development of sustainable nuclear fuel cycles, and yet, our fundamental understanding of this element’s inherent radiation-induced redox chemistry and associated impacts on nuclear fuel cycle technologies is limited. Unanticipated changes in oxidation state distribution can influence the speciation and transport of plutonium in a given process. Control of these parameters is especially important for used nuclear fuel reprocessing technologies, wherein the separation and recovery of plutonium is typically achieved by the selective formation, maintenance, and complexation of specific oxidation states. Furthermore, plutonium’s inherent radiation-induced redox chemistry has the capacity to influence the radiolytic behavior of its complexes, the longevity of which are critical in the design of efficient and cost-effective advanced reprocessing technologies. These radiation-induced processes are unavoidable under fuel cycle conditions owing to the inherency of ionizing radiation fields to the decay of plutonium’s isotopes and to the various other radioisotopes generated by nuclear fission and neutron-capture process and the subsequent radioactive decay of their products. As such, mechanistically understanding the response of plutonium’s multiple oxidation states to multi-component ionizing radiation fields is essential for predicting the behavior of this critical element under used nuclear fuel reprocessing conditions. Here, through a combination of time-resolved (electron pulse) and steady-state (alpha and gamma) irradiation experiments complemented by quantitative, multiscale modeling calculations, we present advances in our understanding of radiation-induced plutonium redox chemistry!

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Janus Superiority of Membranes in Chemical Engineering and Beyond

Janus configurations, characterized by their inherent asymmetry, enable directional mass transfer in membrane materials that drive novel and energy-efficient chemical processes. This Janus superiority spans applications from nanoscale molecular and ionic transport to macro-scale separation systems with asymmetric spatial architectures. This review provides an analysis of the material foundations including design principles, structure regulation, and scalability challenges underlying Janus membranes. Here, we explore the physics that governs their unique behavior and examine their diverse applications across chemical engineering, including phase transfer, and molecular or ionic transport. Through a multiscale perspective, we provide a comprehensive understanding of the impact of Janus superiority in advancing chemical engineering technologies. Finally, we discuss the hurdles in translating theoretical advances into practical applications and propose promising avenues for future research to harness the full potential of Janus membranes and systems in addressing global challenges related to energy, sustainability, and beyond.

Yang, Hao‐Cheng [Zhejiang University, Hangzhou (Ch↗
DOE OSTI2024

CROCUS Air Quality Data at Argonne National Laboratory Prairie Site

The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a prairie field site at Argonne National Laboratory in Lemont, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. File naming convention includes the project (CROCUS), location (atmos), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Unravelling the radiation-induced redox chemistry of plutonium ions in aqueous solution

Plutonium plays a critical role in nuclear fuel cycle technologies, but our understanding of its fundamental radiation-induced redox chemistry is limited. Changes in oxidation states affect the speciation and transport of plutonium ions in solution. For example, solvent extraction techniques used to separate and recover plutonium from used nuclear fuel rely on the selective formation, maintenance, and complexation of specific plutonium oxidation states. However, radiolytically generated radicals, ions, and molecules can drive the oxidation state distribution of plutonium ions far from equilibrium, ultimately changing the physical and chemical properties of the bulk system. These radiation-induced processes are inevitable due to the ionizing radiation fields generated by the radioactive decay of plutonium and its daughter nuclides. Therefore, mechanistically understanding how plutonium's various oxidation states respond to ionizing radiation is essential for predicting its behavior in solution. Here, we present significant advances in our understanding of radiation-induced plutonium redox chemistry by using time-resolved (electron pulse) and dose accumulation (alpha and gamma) irradiation techniques, along with quantitative multiscale modeling methods.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Artificial Intelligence and Multiscale Modeling for Sustainable Biopolymers and Bioinspired Materials

Abstract Biopolymers and bioinspired materials contribute to the construction of intricate hierarchical structures that exhibit advanced properties. The remarkable toughness and damage tolerance of such multilevel materials are conferred through the hierarchical assembly of their multiscale (i.e., atomistic to macroscale) components and architectures. Here, the functionality and mechanisms of biopolymers and bio‐inspired materials at multilength scales are explored and summarized, focusing on biopolymer nanofibril configurations, biocompatible synthetic biopolymers, and bio‐inspired composites. Their modeling methods with theoretical basis at multiple lengths and time scales are reviewed for biopolymer applications. Additionally, the exploration of artificial intelligence‐powered methodologies is emphasized to realize improvements in these biopolymers from functionality, biodegradability, and sustainability to their characterization, fabrication process, and superior designs. Ultimately, a promising future for these versatile materials in the manufacturing of advanced materials across wider applications and greater lifecycle impacts is foreseen.

Wang, Xing Quan [Department of Mechanical Engineer↗
DOE OSTI2025

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Integrated Hydro-terrestrial Modeling 2.0: Progress and Path Forward on Building a National Capability

It is the role of the U.S. federal government and its supporting agencies, including academia and future scientists, to ensure that its people have sustained and equitable freshwater services, as well as the critical knowledge necessary to make decisions about the future as it relates to freshwater services. Clear and consistent information and guidance from federal agencies is critical. Integrated Hydro-Terrestrial Modeling (IHTM), as a United States (U.S.) national capability, focuses on understanding, quantifying, and managing the replenishment of water supply through hydrologic cycle processes and their governing forces. To provide that information, we need enhanced IHTM capabilities that capitalize on the strengths of each U.S. governmental agency and its core mission. The first IHTM workshop was held in 2019, and its subsequent report was published in 2020. The U.S. Global Change Research Program (USGCRP) and member agencies held a second IHTM workshop (IHTM 2.0) from October 31 to November 2, 2023 in Reston, Virginia. The IHTM 2.0 workshop focused on the need to support a multiscale framework to accelerate research insights, better integrate operational and planning perspectives, and bridge national-to-regional capabilities to address major interdependent societal water challenges. The workshop was organized according to a “WHAT” and “HOW” framework, with the common underlying “WHY” being the integrated water resource challenges and the “WHO” defined through interagency and cooperating academic partners. The report provides a summary of plenary presentations and breakout discussions, and a road map that focuses on near-term activities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Prediction of α $IIb$ $β$ 3 integrin structures along its minimum free energy activation pathway

The adhesion protein integrin is a transmembrane heterodimer that plays a pivotal role in cellular processes such as cell signaling and cell migration. To execute its function, integrin undergoes extensive conformational changes from a bent-closed to an extended-open state. Resolving the structures across these changes remains a challenge with both experimental and computational methods, but it is crucial for understanding the activation mechanism of integrin. We address this challenge for the platelet integrin α IIb β 3 by employing finite temperature string method with structures of the images along the initial guess path generated by a multiscale data-driven framework. The full-length all-atom structures along the resulting minimum free energy path between the inactive bent-closed and active extended-open states of α IIb β 3 integrin are consistent with a variety of experimentally resolved structures. Changes in these predicted structures along the path show that the extension and separation of the α and β subunits from the bent-closed to the extended-open state require correlated movements between the subdomain pairs in α IIb β 3 . Furthermore, these results provide new insights into integrin activation mechanism, and the predicted structures have potential applications in guiding the design of integrin-targeting therapeutics.

Dasetty, Siva [University of Chicago, IL (United S↗
DOE OSTI2024

Radiation-Induced Plutonium Redox Chemistry

Plutonium plays a key role in global actinide research and nuclear fuel cycle technologies, and yet, our fundamental understanding of its inherent radiation-induced chemical behavior is limited. These radiation-induced processes cannot simply be switched off, as they are as fundamentally inherent to plutonium as the impact of relativistic effects on its f-electrons. In less chemically complex actinide systems, such as aqueous solutions of neptunium and americium, , radiolysis products play a significant role in the redox cycling of their oxidation states. However, plutonium's multiple, coexisting, and chemically active oxidation states, which comprise of bare ions and dioxo cations, provide additional redox pathways that complicate radiation-induced processes. Oxidation state control is critical for the manipulation of plutonium, especially in used nuclear fuel reprocessing technologies, where oxidation specific states are successfully extracted, and others rejected. Consequently, mechanistically understanding the behavior of plutonium’s multiple oxidation states in the presence of intense ionizing radiation fields is essential for predicting the behavior of this element under multiple conditions that support the development and innovation of nuclear fuel cycle technologies. Here, we present recent advances in our understanding of plutonium radiation chemistry, including the first-ever multiscale model for predicting gamma radiation-induced plutonium redox chemistry, and new chemical kinetics for the reaction of plutonium and its complexes of tributyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), and N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA) with transients radiolysis products, a measured using electron pulse radiolysis.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

The Role of Kinetic Instabilities and Waves in Collisionless Magnetic Reconnection

Magnetic reconnection converts magnetic field energy into particle energy by breaking and reconnecting magnetic field lines. Magnetic reconnection is a kinetic process that generates a wide variety of kinetic waves via wave-particle interactions. Kinetic waves have been proposed to play an important role in magnetic reconnection in collisionless plasmas by, for example, contributing to anomalous resistivity and diffusion, particle heating, and transfer of energy between different particle populations. These waves range from below the ion cyclotron frequency to above the electron plasma frequency and from ion kinetic scales down to electron Debye length scales. This review aims to describe the progress made in understanding the relationship between magnetic reconnection and kinetic waves. We focus on the waves in different parts of the reconnection region, namely, the diffusion region, separatrices, outflow regions, and jet fronts. Particular emphasis is placed on the recent observations from the Magnetospheric Multiscale (MMS) spacecraft and numerical simulations, which have substantially increased the understanding of the interplay between kinetic waves and reconnection. Some of the ongoing questions related to waves and reconnection are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Multiscale geographically and temporally weighted regression (MGTWR): exploring the spatiotemporal heterogeneity of EV market adoption

As an innovative vehicle technology, electric vehicles are experiencing growing sales and have made significant inroads into the traditional automotive market in the United States and around the world. However, EV adoption rates vary significantly across space and over time, influenced by a complex interplay of socio-economic and infrastructural factors alongside federal and state policies. Here, this paper presents a comprehensive spatial–temporal investigation of EV market adoption within one city in the US, that of Chicago, utilizing Multiscale Geographically and Temporally Weighted Regression (MGTWR) alongside Multiscale Geographically Weighted Regression (MGWR). The aim is to unravel the spatial and temporal dynamics affecting EV adoption and to explore how the influence of various determinants of EV adoption, such as demographic factors and economic conditions, vary spatially. Moreover, by utilizing MGTWR, we provide insights into the evolution of these relationships over time, offering a predictive outlook on future EV market growth. Our findings, with an 86.6% prediction accuracy for EV market adoption, tailored policy measures to support accelerated EV adoption. Methodologically, this work advances MGWR frameworks by integrating temporal dynamics to examine nonstationary processes in spatially disaggregated contexts. These findings offer evidence–based guidance for policymakers, urban planners, and stakeholders in the automotive industry, supporting the transition toward a more sustainable and efficient transportation system.

EV Market Adoption↗
DOE OSTI2026

Improving Process Level Understanding of Boundary Layer Winds over the Northeast U.S. Shelf: The Third Wind Forecast Improvement Project (WFIP3)

The third Wind Forecast Improvement Project (WFIP3), a U.S. Department of Energy and National Oceanic and Atmospheric Administration sponsored investigation, sought to improve understanding of the physical phenomena in the atmosphere and ocean that dictate the structure and variability of wind and thermodynamic fields within the marine atmospheric boundary layer. WFIP3 focused on mesoscale and submesoscale flows -- including sea breezes, low-level jets, low-level clouds, and coastal storms -- and the ability of advanced numerical model parameterizations to represent them within fully coupled oceanic and atmospheric modeling systems and foundational weather forecast models. WFIP3 conducted a comprehensive 18-month observational study over the Northeast U.S. outer continental shelf, a high-use coastal zone, using a 3D multiscale sensor array to highly resolve the temporal, vertical, and horizontal structure of the coupled atmospheric and oceanic boundary layers. Multiple land-based study sites adjacent to the coastal ocean observed surface meteorology and vertical profiles of atmospheric properties via passive infrared and microwave radiometers, active lidars and radars, and radiosondes. At sea, an array of surface flux buoys and two vertical profiling lidar buoys observed both atmospheric and oceanic properties, augmented by land-based oceanographic radar systems and routine ship-based surveys. Intensive observations of the marine atmospheric boundary layer over the ocean was done from an air-sea interaction flux tower and extended deployments of a large autonomous barge platform. Numerous critical forecasting phenomena were observed that are being evaluated within regional coupled and uncoupled modeling systems, including the National Oceanic and Atmospheric Administration's foundational High-Resolution Rapid Refresh forecast model.

Kirincich, Anthony↗
DOE OSTI2024

Impact of the Earthquake Rupture on Ground-Motion Variability of the 24 August 2016 M w 6.2 Amatrice, Italy, Earthquake

Here, the devastating 24 August 2016 M w 6.2 earthquake that struck Amatrice, Italy, marked the beginning of a prolonged seismic sequence dominated by three subsequent M w ≥6.0 events in the central Apennines region. The earthquake destroyed Amatrice’s historic center, claiming the lives of 299 individuals and causing widespread damage in the neighboring villages. The severity of the ground shaking, with a recorded maximum acceleration of 850 cm/s 2 on the east–west component at the Amatrice station, was far greater than the predicted acceleration based on the Italian ground-motion model (GMM). As pointed out by several investigations, the observed ground-motion amplitude and its spatial variability during the earthquake can be linked to specific rupture characteristics, including slip distribution and rupture directivity effects revealed by the observed data (Tinti et al., 2016; Pischiutta et al., 2021). In this study, we conducted physics-based 3D numerical simulations of ground motion for the Amatrice earthquake for frequencies up to 3 Hz. We employed a series of kinematic rupture models and a well-constrained local 3D velocity model incorporating surface topography. The kinematic rupture realizations were generated using multiscale hybrid and fully stochastic models, following the technique proposed by Graves and Pitarka (2016). We focused on assessing the sensitivity of near-fault ground-motion amplitudes to earthquake rupture characteristics, in particular, the spatial slip pattern. To evaluate the quality of our simulations, we employed goodness-of-fit measurements performed in comparisons of simulated and recorded ground motions. The simulated ground motions compare well with the recorded data and predictions from GMMs for Italy, ITA18 (Lanzano et al., 2019). However, we found that the simulated interevent ground-motion variability (randomness in the source process) of peak ground velocity, σ (PGV) is higher than the constant σ (PGV) predicted by conventional GMMs. Our simulations using several rupture scenarios demonstrate that the near-fault ground-motion amplification pattern is directly related to the slip distribution pattern.

3D Ground Motions Simulations↗
DOE OSTI2025

Data-driven equation-free dynamics applied to many-protein complexes: The microtubule tip relaxation

Microtubules (MTs) constitute the largest components of the eukaryotic cytoskeleton and play crucial roles in various cellular processes, including mitosis and intracellular transport. The property allowing MTs to cater to such diverse roles is attributed to dynamic instability, which is coupled to the hydrolysis of GTP (guanosine-5'-triphosphate) to GDP (guanosine-5'-diphosphate) within the β-tubulin monomers. Understanding the equilibrium dynamics and the structural features of both GDP- and GTP-complexed MT tips, especially at an all-atom level, remains challenging for both experimental and computational methods because of their dynamic nature and the prohibitive computational demands of simulating large, many-protein systems. This study employs the “equation-free” multiscale computational method to accelerate the relaxation of all-atom simulations of MT tips toward their putative equilibrium conformation. Using large MT lattice systems (14 protofilaments × 8 heterodimers) comprising ~21-38 million atoms, we applied this multiscale approach to leapfrog through time and nearly double the computational efficiency in realizing relaxed all-atom conformations of GDP- and GTP-complexed MT tips. Commencing from an initial 4 μs unbiased all-atom simulation, we interleave coarse projective “equation-free” jumps with short bursts of all-atom molecular dynamics simulation to realize an additional effective simulation time of 1.875 μs. Our 5.875 μs of effective simulation trajectories for each system expose the subtle yet essential differences in the structures of MT tips as a function of whether β-tubulin monomer is complexed with GDP or GTP, as well as the lateral interactions within the MT tip, offering a refined understanding of features underlying MT dynamic instability. Furthermore, the approach presents a robust and generalizable framework for future explorations of large biomolecular systems at atomic resolution.

Wu, Jiangbo [University of Chicago, IL (United Sta↗
DOE OSTI2026

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗
DOE OSTI2025

Reaction-induced departures from continuum Navier–Stokes turbulence

Reactive hydrodynamic turbulence is an inherently multiscale phenomenon, characterized by the separation between energy-containing, viscous, and molecular length and time scales. The separation between the viscous scale (the Kolmogorov scale) and the molecular mean free path ostensibly justifies a macroscopic description of reactive turbulence via the Navier–Stokes (NS) equations. However, here we use molecular-level simulations to demonstrate that exothermic bimolecular reactions can cause the NS description of turbulence to break down in the near-continuum regime. Sufficiently energetic heat-releasing reactive collisions strongly distort the Maxwell–Boltzmann velocity distribution function, modifying not only the macroscopic chemical rate law but the kinetic-energy-transfer processes as well. This translational nonequilibrium ultimately introduces significant departures from the NS description in the kinetic energy spectra at scales orders of magnitude larger than both the molecular mean free path and the Kolmogorov length scale. These departures prove substantial enough to meaningfully alter integrated quantities, including the overall turbulence kinetic energy itself.

molecular gas dynamics↗
DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗