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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗
DOE OSTI2026

Electromagnetic Analysis of ITER Electron Cyclotron Emission Model

The ITER electron cyclotron emission (ECE) diagnostic system is located at diagnostics shielding module 2 (DSM2), equatorial port 9 (EP9), to measure electron temperature profile and electron temperature fluctuations, and also assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two hot sources for calibration and two couples of mirrors for two different optical views. It shall receive that the large electromagnetic (EM) loads up to 100-MN/m3 force density due to the eddy currents on the copper mirrors generated by the short transient plasma disruption. The simplified EM analysis model using magnetic field ( B ) data and flux variations (dB/dt) method based on the worst case of plasma disruption, MD_DW_EXP16MS_CATIII, has been developed to calculate the force and moments for each ECE component and support structure for EP9 DSM2 Bay2 and Bay3. The B and dB/dt methods use the constant B and dB/dt assumed for each local bay space, but the real B and dB/dt are basically varied along the radial direction of each bay. The complex global model with the local ECE components and support structure using Maxwell transient has been developed to do EM analysis to compare the results of the B and dB/dt models. The volumetric EM force density of the whole ECE components and support structure can be used for the subsequent structural analysis. In conclusion, combined with the thermal and nuclear loads and seismic and initial loads, the ECE integration analysis can be finalized for the operation case.

Fang, J. [Princeton Plasma Physics Laboratory (PPP↗
DOE OSTI2025

Fast and Invertible Simplicial Approximation of Magnetic‐Following Interpolation for Visualizing Fusion Plasma Simulation Data

We introduce a fast and invertible approximation for fusion plasma simulation data represented as 2D planar meshes with connectivities approximating magnetic field lines along the toroidal dimension in deformed 3D toroidal spaces. Scientific variables (e.g., density and temperature) in these fusion data are interpolated following a complex magnetic-field-line-following scheme in the toroidal space represented by a cylindrical coordinate system. This deformation in the 3D space poses challenges for root-finding and interpolation. To this end, we propose a novel paradigm for visualizing and analyzing such data based on a newly developed algorithm for constructing a 3D simplicial mesh within the deformed 3D space. Our algorithm generates a tetrahedral mesh that connects the 2D meshes using tetrahedra while adhering to the constraints on node connectivities imposed by the magnetic field-line scheme. Specifically, we first divide the space into smaller partitions to reduce complexity based on the input geometries and constraints on connectivities. Then, we independently search for a feasible tetrahedralization of each partition, considering nonconvexity. We demonstrate our method with two X-Point Gyrokinetic Code (XGC) simulation datasets on the International Thermonuclear Experimental Reactor (ITER) and Wendelstein 7-X (W7-X), and use an ocean simulation dataset to substantiate broader applicability of our method. An open source implementation of our algorithm is available at https://github.com/rcrcarissa/DeformedSpaceTet.

Ren, Congrong [The Ohio State Univ., Columbus, OH ↗
DOE OSTI2022

Constraints on ion velocity distributions from fusion product spectroscopy

Abstract Recent inertial confinement fusion experiments have shown primary fusion spectral moments which are incompatible with a Maxwellian velocity distribution description. These results show that an ion kinetic description of the reacting ions is necessary. We develop a theoretical classification of non-Maxwellian ion velocity distributions using the spectral moments. At the mesoscopic level, a monoenergetic decomposition of the velocity distribution reveals there are constraints on the space of spectral moments accessible by isotropic distributions. General expressions for the directionally dependent spectral moments of anisotropic distributions are derived. At the macroscopic level, a distribution of fluid element velocities modifies the spectral moments in a constrained manner. Experimental observations can be compared to these constraints to identify the character and isotropy of the underlying reactant ion velocity distribution and determine if the plasma is hydrodynamic or kinetic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Same-sided successive-shock HED instability experiments

Inertial confinement fusion (ICF) and high-energy density (HED) physics experiments experience complicated forcing for instability growth and mix due to the ubiquitous presence of multiple shocks interacting with perturbations on multiple material interfaces. One common driver of instability growth is successive shocks from the same direction. However, there is a severe lack of analytic work and modeling validation for same-sided successive shocks since they are extremely difficult to achieve with conventional (non-HED) drivers. Successive shocks access a large instability parameter space; idealized fluid theory [K. O. Mikaelian, Phys. Rev. A 31, 410 (1985)] predicts 15 different interface evolution scenarios for a sinusoidal perturbation. Growth becomes more complex for multi-mode, compressible HED systems. The Mshock campaign is the first experiment in any fluid regime to probe a wide portion of successive shock parameter space. This is enabled by our development of a hybrid direct/indirect drive platform capable of creating independently controllable successive shocks on the National Ignition Facility. These experiments have delivered the first data capable of rigorously challenging our models and their ability to accurately capture Richtmyer–Meshkov growth under successive shocks. Single-mode and two-mode experiments have successfully demonstrated the ability to access and control the various growth scenarios of the shocked interface, including re-inversion, freeze out, and continued growth. Simulations and theoretical modeling are shown to accurately capture the experimental observations in the linear growth phase, giving us confidence in our ICF/HED design codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Closure models for the feedback of energetic particles on plasma turbulence

Energetic particles interact with the plasma surrounding them, resonating with certain types of plasma waves to stabilize them while destabilizing others, and changing the character of the background turbulence in ways that have not been fully quantified or understood. Interaction with the turbulent background plasma is key to the acceleration of many types of energetic particles including high-energy cosmic rays, solar energetic particles, and pick-up ions. The acceleration of particles is a process that would ideally be described by a kinetic model, a type of model that follows a probability distribution function (PDF) for all particles in 7-dimensional (x, y, z, v x , v y , v z , t) space. Because of the high dimensionality of a kinetic model, simulations that solve kinetic equations use the largest computational resources currently available, and are yet unable to simulate a realistic number of particles, reach the large scales necessary for astrophysical problems, and use high-precision numerical methods. Two available alternatives to kinetic plasma models have been explored for this problem, with limited success. One is a multi-fluid model produced by a cumulant discarding closure, which evolves coupled equations for the velocity, magnetic field, and internal energy for both the background plasma and the fluid of energetic particles. However, simulations that solve multi-fluid magnetohydrodynamic (MHD) equations are able to include the interaction with energetic particles only in crude ways, typically as an add-on pressure term. The second alternative is to use a hybrid method to couple a fluid description of the background plasma to a kinetic model or a Fokker–Planck model for the energetic particles. These methods are hampered by the physical modeling of the coupling. In this work, we develop a new model, which follows the PDF for all particles; this can be viewed as a step toward physical realism above a multi-fluid MHD model, while also being more computationally efficient than a kinetic model. The equations we develop model both the background plasma and the energetic particles self-consistently. Over the last decade, similar PDF methods have been developed to a high level of sophistication to model reactive flows and turbulent combustion for engineering applications. For treatment of the feedback of the energetic particles on a background plasma, a PDF closure approach should evaluate the mean characteristics, including the density, with better statistical quality than will particle-sampling procedures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the violation of the zeroth law of turbulence in space plasmas

The zeroth law of turbulence states that, for fixed energy input into large-scale motions, the statistical steady state of a turbulent system is independent of microphysical dissipation properties. This behaviour, which is fundamental to nearly all fluid-like systems from industrial processes to galaxies, occurs because nonlinear processes generate smaller and smaller scales in the flow, until the dissipation – no matter how small – can thermalise the energy input. Using direct numerical simulations and theoretical arguments, we show that in strongly magnetised plasma turbulence such as that recently observed by the Parker Solar Probe spacecraft, the zeroth law is routinely violated. Namely, when such turbulence is ‘imbalanced’ – when the large-scale energy input is dominated by Alfvénic perturbations propagating in one direction (the most common situation in space plasmas) – nonlinear conservation laws imply the existence of a ‘barrier’ at scales near the ion gyroradius. This causes energy to build up over time at large scales. The resulting magnetic-energy spectra bear a strong resemblance to those observed in situ , exhibiting a sharp, steep kinetic transition range above and around the ion-Larmor scale, with flattening at yet smaller scales. The effect thus offers a possible solution to the decade-long puzzle of the position and variability of ion-kinetic spectral breaks in plasma turbulence. The existence of the ‘barrier’ also suggests that, how a plasma is forced at large scales (the imbalance) may have a crucial influence on thermodynamic properties such as the ion-to-electron heating ratio.

Physics↗
DOE OSTI2022

Physical mechanisms for the transition from type-III to large ELMs induced by impurity injection on EAST

Transition from type-III to large-amplitude ELMs induced by neon injection has been observed in the EAST tokamak at overlapping q 95 space between large and small ELMs. With neon injection, pedestal density gradient shows a remarkable increase accompanied by some decrease of pedestal electron temperature, and consequently the pressure gradient increases moderately and edge bootstrap current has minimal change. Further experiment demonstrates that the occurrence of large ELMs after neon injection is highly correlated with the change in edge density. Linear peeling-ballooning stability analysis indicates that the large ELM case is more unstable than the type-III ELM case during the ELM transition. A scan of pedestal density gradient in linear stability analysis shows that the direct destabilizing effect of steep pedestal density gradient on peeling-ballooning instabilities via two-fluid effects could also facilitate the transition to large ELMs. In conclusion, these results could provide more insight into the role of pedestal density gradient on pedestal stability and ELM behavior.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Weak collisionless shocks mediated by ion gyroviscosity

Collisionless shocks are ubiquitous in space and astrophysical plasmas, and they are essential dynamical features of these systems. Lacking Coulomb collisions, these shocks are mediated by the anomalous dissipation provided by nonlinear plasma instabilities. By numerically resolving the structure of a steady-state, ion gyroviscous shock, we show that ion gyroviscosity, alone, can produce weak (M≲1.1, where M is the sonic Mach number) shocks in a collisionless, magnetized plasma. We emphasize that this effect does not require an appeal to plasma microturbulence. Moreover, while most collisionless systems may be unsuitable to support purely gyroviscous shocks, we argue that gyro-viscous heating may be an overlooked mechanism, generally; and it may be a key driver within magnetohydrodynamic shocks at large. In conclusion, representative examples include the plasma environments produced on the plasma liner experiment and the magnetized liner inertial fusion platforms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Deciphering the influence of high-flux helium plasma exposure on tungsten nanostructure growth using real-time, in situ spectroscopic ellipsometry

In situ analysis of surfaces during high-flux plasma exposure represents a long-standing challenge in the study of plasma–material interactions. While post-mortem microscopy can provide a detailed picture of structural and compositional changes, in situ techniques can capture the dynamic evolution of the surface. In this study, we demonstrate how spectroscopic ellipsometry can be applied to the real-time characterization of W nanostructure (also known as “fuzz”) growth during exposure to low temperature, high-flux He plasmas. Strikingly, over a wide range of sample temperatures and helium fluences, the measured ellipsometric parameters (Ψ,Δ) collapse onto a single curve that can be directly correlated with surface morphologies characterized by ex situ helium ion microscopy. The initial variation in the (Ψ,Δ) parameters appears to be governed by small changes in surface roughness (<50 nm) produced by helium bubble nucleation and growth, followed by the emergence of 50 nm diameter W tendrils. This basic behavior appears to be reproducible over a wide parameter space, indicating that the spectroscopic ellipsometry may be of general practical use as a diagnostic to study surface morphologies produced by high-flux He implantation in refractory metals. An advantage of the methods outlined here is that they are applicable at low incident ion energies, even below the sputtering threshold. As an example of this application, we apply in situ ellipsometry to examine how W fuzz growth is affected both by varying ion energy and the temperature of the surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Neural Density Estimation and Uncertainty Quantification for ChemCam Spectra [Slides]

The ChemCam instrument of Curiosity uses laser-induced breakdown spectroscopy (LIBS). It fires a laser at target and vaporizes rock surfaces, creating a plasma. Three spectrographs divide the plasma light into wavelengths for chemical analysis: ultraviolet, violet, and visible near-infrared. Regression methods (SVR, PCR, CNN) have been employed for calibration (prediction of the elemental composition of samples); however, labeled ChemCam samples are limited. Here, we focus on unsupervised learning and employ generative models from ChemCam analysis. Further, we use labels (supervised) in combination to the generative model to compute uncertainties related to predictions. We report generative modeling can be successfully applied to model real-world data. Normalizing flow models can be efficiently constructed on latent spaces for fast downstream inference. Unsupervised and supervised learning can be combined to form an uncertainty quantification framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A multifidelity Bayesian optimization method for inertial confinement fusion design

Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical simulations to guide design. As simulation technology progresses, so too can the fidelity of models used to plan for new experiments. However, these high-fidelity models are by themselves insufficient for optimal experimental design, because their computational cost remains too high to efficiently and effectively explore the numerous parameters required to describe a typical experiment. Therefore, traditionally, ICF design has relied on low-fidelity modeling to initially identify potentially interesting design regions, which are then subsequently explored via selected high-fidelity modeling. In this paper, we demonstrate that this two-step approach can be insufficient: even for simple design problems, a two-step optimization strategy can lead high-fidelity searching toward incorrect regions and consequently waste computational resources on parameter regimes far away from the true optimal solution. We reveal that a primary cause of this behavior in ICF design problems is the presence of low-fidelity optima in different regions of the parameter space far away from high-fidelity optima. To address this issue, we propose an iterative multifidelity Bayesian optimization method based on Gaussian Process Regression that leverages both low- and high-fidelity models simultaneously. We demonstrate, using both two- and eight-dimensional ICF test problems, that our algorithm can effectively utilize both low-fidelity and high-fidelity models to refine the designs. This approach proves to be more efficient than relying solely on high-fidelity modeling for optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Filamentation and focusing of electron beams due to interactions with plasma waves

Results of numerical modeling of the interaction of an electron beam propagating across relativistic plasma waves indicate that electron beam filamentation and focusing may occur under certain conditions. The model is based on solving the relativistic equation of motion in three dimensions for the individual electrons in a tenuous Gaussian beam, as they pass through a relativistic plasma wave. Several electron beam and plasma wave parameters were varied, and the results are summarized. One of the results is that the spacing of the electron beam filaments correlates with the wavelength of the plasma wave. The electron beam filaments appear as vertical slabs after the beam exits the plasma waves. The electron beam also compresses to a focus after it exits the plasma, and the focal distance depends on several parameters including the electron beam energy and phase velocity of the relativistic plasma wave. It is suggested that these focusing and filamentation phenomena may be the basis for diagnostics schemes for laser plasma interactions. The parameters used in the model were electron beam energies in the 5–50 keV range and plasma wave properties typical for the beat-wave produced by CO2 lasers, which correspond to the facilities available in our laboratory. The limitations of these results to lower energy density beam and plasma regimes and to higher energy density regimes will be discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Ballooning theory for micro-tearing mode in tokamak

This paper aims to investigate the impact of magnetic drift on the linear micro-tearing mode by using a kinetic approach to derive a reduced two-field eigen system in real space. Here, since the magnetic drift in real space has derivatives, it is more efficient to solve the mode equations in a Fourier-ballooning representation using the two-dimensional (2D) ballooning transform. The lowest-order eigen system in the Fourier-ballooning representation consists of two integral equations, which are numerically solved using the finite difference method for both eigenvalues and wave functions. The main results will be presented through graphical eigenvalue scans for each parameter. Furthermore, we present a graphical comparison between the predictions of the ballooning theory and GENE gyrokinetic code simulation in the pedestal region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE

As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Straight lightning as a signature of macroscopic dark matter

Macroscopic dark matter (macros) is a broad class of alternative candidates to particle dark matter. These candidates would transfer energy to matter primarily through elastic scattering. A sufficiently large macro passing through the atmosphere would produce a straight channel of ionized plasma. If the cross-section of the macro is σx ≳ 6 × 10 –9 cm 2 , then under atmospheric conditions conducive to lightning (eg. a thunderstorm) the plasma channel would be sufficient to seed a lightning strike with a single leader. This is entirely unlike ordinary bolt lightning in which a long sequence of hundreds or thousands of few-meter-long leaders are strung together. This macro-induced lightning would be extremely straight, and thus highly distinctive. Neither wind shear nor magnetohydrodynamic instabilities would markedly spoil its straightness. The only photographically documented case of a straight lightning bolt is probably not straight enough to have been macro-induced. We estimate the region of macro parameter space that could be probed by a search for straight lightning from the number of thunderstorms happening on Earth at any time. In conclusion, we also estimate the parameter space that can be probed by carefully monitoring Jupiter, e.g. using the Hubble Space Telescope.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Trends in relativistic laser–matter interaction: the promises of structured light

Time and space envelope, frequency and wavelength distributions, polarization, and phase are quantities that define the properties of laser light. Controlling them opens up strategies for manipulating the properties of atoms in various media. At relativistic intensity, matter is rapidly transformed into a plasma state, which is modifying the laser’s propagation, its absorption enabling the generation of intense magnetic and electric fields. In this context, structured light presents exciting, promising, and challenging opportunities for research. This review article aims to explain the concepts of structured light, their applications to real experiments at relativistic intensities, practical considerations, and some scientific perspectives.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Reduced diffusion and enhanced retention of multiple radionuclides from pore structure characterization of barrier materials for enhanced repository performance

Fluid flow and chemical transport in porous media are the macroscopic consequences of pore structure, which integrates geometry (e.g., pore size and surface area, pore-size distribution) and topology (e.g., pore connectivity). Low-permeability geological media whose pores are poorly interconnected will exhibit the characteristics of anomalous diffusion and sample size-dependent effective porosity, which will strongly impact long-term net diffusion and retention of radionuclides in geological repository settings involving different host rocks and barrier materials. A suite of innovative and complementary experimental approaches is utilized to study the microscopic pore structure and macroscopic fluid flow & chemical transport for a range of host rocks and barrier materials, in addition to standard clay minerals and reference rocks. With a particular focus on quantifying the presence and magnitude of “isolated” pores for a reduced effective porosity in low-permeability geomedia, the integrated methodologies for basic properties and pore structure characterization of these geomedia include X-ray diffraction, thin section petrography, grain size distribution, water immersion porosimetry after vacuum-pulling for full saturation, mercury intrusion porosimetry, nitrogen physisorption, scanning electron microscopy, X-ray computed tomography, and (ultra-)small angle neutron (X-ray) scattering. In addition, custom-designed gas diffusion, tracer recipe involving a range of anionic and cationic chemicals with subsequent analyses by laser ablation and inductively coupled plasma-mass spectrometry, along with batch sorption, column transport, and imbibition tests were conducted for coupled effects of pore structure and chemical retention/transport. From the perspectives of pore structure in conjunction with multiple and complementary approaches to examining a range of sample sizes under different observational scales, we find that the poor pore connectivity is prevalent in low-permeability media (mudstone and crystalline rock) that is related to geological processes (e.g., compaction, diagenesis and thermal maturation). For example, the deep and organic matter-rich mudstones have a much smaller effective porosity than the total porosity (as a result of poor pore connectivity) and associated diffusion coefficient, and the effective porosity & diffusion coefficients are also dependent upon the sample sizes used in the measurement. Similarly, most of the pore space in the shallow mudstone is also controlled by pore-throat diameters in the 5-50 nm range of intergranular pore types from its fine-grained nature, but with an overall good pore connectivity. However, the nm-sized pore space (physically pore-network architecture) and strong sorption capacities (chemical retention from clay minerals) of both shallow and deep mudstones lead to the synergistic retention of cationic radionuclides and their utilities as effective host rocks and barrier materials. Our unique approaches of studying how the micro-scale pore structure affect macro-scale fluid flow, diffusion & retention, and chemical transport produce improved mechanistic understanding, and realistic quantification, of diffusion and retention of typical radionuclides in a range of generic host rocks and barrier materials (clay/shale, salt, crystalline rock, and tuff), with the overall results leading to scientifically-based understanding of enhanced isolation (from both diffusion and retention) of radionuclides and improved confidence on the long-term performance of geological repository to store high-level radioactive wastes. In addition to the training of 25 undergraduates, graduates, and postdocs of UTA, the scientists (organizations) involved in performing this work (e.g., discussion, sample sharing, and operation of SANS and SAXS instruments) include Ed Matteo, Yifeng Wang, and Kristopher Kuhlman (Sandia National Laboratories), Jens Birkholzer, Liange Zheng, Tim Kneafsey, and Sharon Borglin (Lawrence Berkeley National Laboratory), Mavrik Zavarin (Lawrence Livermore National Laboratory), Yukio Tachi and Yuta Fukatsu (Japan Atomic Energy Agency), Mieke de Craen (Euridice, Belgium), Markus Bleuel (NIST), Wei-Ren Chen, Gergely Nagy, Changwoo Do, William Heller, Larry Anovitz, and Kenneth Littrell (ORNL), as well as Jan Illvsky, Ivan Kuzmenko, Ju-Sang Park and Jon Almers (ANL). Key deliverables include a total of 13 peer-reviewed journal articles (nine published and three under review), 23 presentations at scientific conferences (AAPG, AAPG Southwest Section, AGU, Asian Clay Conference, GSA, GSA South-Central Section, IHLRWM, InterPore, International Conference on Chemistry and Migration Behavior of Actinides and Fission Products in the Geosphere, International Conference on Coupled Processes in Fractured Geological Media: Observation, Modeling and Application), and academic institutions (UTA, New Mexico State University; University of Poitiers, France; University of Helsinki, Finland; Uppsala University, Sweden; Istanbul Technical University, Turkey) and other organizations (Andra, France; Posiva Oy, Finland).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗