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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 145 records · Page 8

Considerations for a TeV collider based on dielectric laser accelerators

Particle acceleration in dielectric microstructures powered by infrared lasers, or "dielectric laser acceleration" (DLA), is a promising area of advanced accelerator research with the potential to enable more affordable and higher-gradient accelerators for energy frontier science and a variety of other applications. DLA leverages well-established industrial fabrication capabilities and the commercial availability of tabletop lasers to reduce cost, with axial accelerating fields in the GV/m range. Further, desirable luminosities would be obtained by operating with very low charge per bunch but at extremely high repetition rates. And as a consequence of its unique operating parameter regime, coupling of the laser to the accelerator can potentially be in the 50% range and with low beamstrahlung energy loss due at the interaction point, making DLA a promising approach for a future multi-TeV linear collider.

43 PARTICLE ACCELERATORS↗

Multi-site reaction dynamics through multi-fragment density matrix embedding

The practical description of disordered chemical reactions, where the reactions involve multiple species at multiple sites, is presently a challenge using correlated electronic structure methods due to their high computational cost and steep scaling. Here, we describe the gradient theory of multi-fragment density matrix embedding theory, which potentially provides a minimal computational framework to model such processes at the correlated electron level. We present the derivation and implementation of the gradient theory, its validation on model systems and chemical reactions using density matrix embedding, and its application to a molecular dynamics simulation of proton transport in a small water cluster, a simple example of multi-site reaction dynamics.

Chemistry↗

A generalized effective potential for differentially rotating plasmas

Global stability of differentially rotating plasma is investigated using a generalized effective potential. We first, for a current-free system, obtain a general form of an effective potential in terms of the free energies of global curvature and gradients of rotation for non-axisymmetric disturbances. We then examine the stability of differentially rotating disks for several rotation profiles and present the associated effective potential for the onset of these instabilities in the MHD regime. In particular, results for global axisymmetric magnetorotational instability as well as local and global non-axisymmetric modes are presented. The latter constitute two distinct non-axisymmetric modes, a high frequency local MRI and a global low-frequency non-axisymmetric mode (the magneto-curvature mode, introduced in Ebrahimi and Pharr [Astrophys. J. 936, 145 (2022)]), confined either between two Alfvénic resonances or an Alfvénic resonance and a boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Learning in continuous action space for developing high dimensional potential energy models

Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as in chess, Shogi and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search problems and learning domains that have continuous action spaces. Exploring high-dimensional potential energy models of materials is an example. Traditionally, these searches are time consuming (often several years for a single bulk system) and driven by human intuition and/or expertise and more recently by global/local optimization searches that have issues with convergence and/or do not scale well with the search dimensionality. Here, in a departure from discrete action and other gradient-based approaches, we introduce a RL strategy based on decision trees that incorporates modified rewards for improved exploration, efficient sampling during playouts and a “window scaling scheme" for enhanced exploitation, to enable efficient and scalable search for continuous action space problems. Using high-dimensional artificial landscapes and control RL problems, we successfully benchmark our approach against popular global optimization schemes and state of the art policy gradient methods, respectively. We demonstrate its efficacy to parameterize potential models (physics based and high-dimensional neural networks) for 54 different elemental systems across the periodic table as well as alloys. We analyze error trends across different elements in the latent space and trace their origin to elemental structural diversity and the smoothness of the element energy surface. Broadly, our RL strategy will be applicable to many other physical science problems involving search over continuous action spaces.

36 MATERIALS SCIENCE↗

Segmentation and Classification of Fission as Pores in Reactor Irradiated Annular U–10Zr Metallic Fuel Using Machine Learning Models

Metallic fuels, particularly U—10Zr, are promising candidates for next-generation sodium-cooled fast reactors. Irradiation of nuclear fuels in reactors can lead to the formation of solid and gas fission product which subsequently forms microstructural pores, deteriorating fuel performance. Due to the massive amount of pores and complex phases formed, a quantitative description of fission gas pores is not yet available, preventing the development of microstructure-informed fuel performance modeling for fuel qualification. This paper applied a pre-trained deep learning model to ~10,260 high magnification scanning electron microscopy images. This method increased the accuracy of fission gas pore segmentation and allows statistical features to be extracted which cannot be achieved manually. A pre-trained decision tree model worked on the segemenation results and further classified the pores into different categories to produce a correlation between the pores, movement of lanthanides, and temperature gradient during irradiation. Finally, this paper emphasizes the potentials of machine learning models to accelerate fuel research, development, and qualification for advanced reactors.

36 MATERIALS SCIENCE↗

Multireference Electron Correlation Methods: Journeys along Potential Energy Surfaces

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way and, therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces. This includes the optimization of molecular geometries, such as equilibrium geometries and conical intersections and on-the-fly photodynamics simulations, both of which depend heavily on the ability of the method to properly explore the potential energy surface. Because such applications require nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly enhances the scope of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. A detailed account of the analytical nuclear gradient and derivative coupling theories is presented. Emphasis is given to the software infrastructure that allows one to make use of these methods. Notable applications of multireference electron correlation methods to chemistry, including geometry optimizations and on-the-fly dynamics, are summarized at the end followed by a discussion of future prospects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dosimetric delivery validation of dynamically collimated pencil beam scanning proton therapy

Pencil beam scanning (PBS) proton therapy target dose conformity can be improved with energy layer-specific collimation. One such collimator is the dynamic collimation system (DCS), which consists of four nickel trimmer blades that intercept the scanning beam as it approaches the lateral extent of the target. While the dosimetric benefits of the DCS have been demonstrated through computational treatment planning studies, there has yet to be experimental verification of these benefits for composite multi-energy layer fields. The objective of this work is to dosimetrically characterize and experimentally validate the delivery of dynamically collimated proton therapy with the DCS equipped to a clinical PBS system. Approach. Optimized single field, uniform dose treatment plans for 3 × 3 × 3 cm 3 target volumes were generated using Monte Carlo dose calculations with depths ranging from 5 to 15 cm, trimmer-to-surface distances ranging from 5 to 18.15 cm, with and without a 4 cm thick polyethylene range shifter. Treatment plans were then delivered to a water phantom using a prototype DCS and an IBA dedicated nozzle system and measured with a Zebra multilayer ionization chamber, a MatriXX PT ionization chamber array, and Gafchromic™ EBT3 film. Main results. For measurements made within the SOBPs, average 2D gamma pass rates exceeded 98.5% for the MatriXX PT and 96.5% for film at the 2%/2 mm criterion across all measured uncollimated and collimated plans, respectively. For verification of the penumbra width reduction with collimation, film agreed with Monte Carlo with differences within 0.3 mm on average compared to 0.9 mm for the MatriXX PT. Significance. We have experimentally verified the delivery of DCS-collimated fields using a clinical PBS system and commonly available dosimeters and have also identified potential weaknesses for dosimeters subject to steep dose gradients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Progress towards edge-localized mode suppression via magnetic perturbations in hydrogen plasmas

Abstract The suppression of edge-localized modes (ELMs) by applying resonant magnetic perturbations (RMPs) is well studied in low collisionality deuterium plasmas as a measure to reduce transient divertor heat loads. However, ELM suppression has yet to be demonstrated in non-nuclear fuels such as hydrogen and hydrogen + helium mixtures which are the main ion species to be used in the ITER pre-fusion power operation (PFPO) phase. For the first time, attempts have been made to access ELM suppression with RMPs in ITER-like low collisionality hydrogen plasmas at DIII-D and ASDEX Upgrade. The DIII-D experiments focused on operation with injected power slightly above the L–H power threshold similar to the expected conditions in the ITER PFPO phase with limited external heating power. The RMPs were found to trigger H–L backtransitions, which is shown to be avoided by reducing the L–H power threshold by diluting the plasma with helium. The additional helium combined with a larger measured neutral density of hydrogen inside the separatrix compared to ELM suppressed deuterium plasmas precluded access to a pedestal top density below the known RMP-ELM suppression threshold. At ASDEX Upgrade, RMP-ELM suppression has been achieved when the concentration of 1 H in the hydrogen isotope mix is below 40 % . While all known access criteria for RMP-ELM suppression were met above this threshold, full ELM suppression was replaced by strong mitigation. The most prominent difference between the hydrogen and deuterium plasmas was a change of turbulence characteristics in the pedestal where Doppler reflectometry measurements suggest a significant reduction of turbulence even at small hydrogen concentrations. In conclusion, these experiments not only identify issues that may prevent access to RMP-ELM suppression in the ITER PFPO phase, but also highlight missing physics in our current understanding of RMP-ELM suppression such as potentially the role of turbulence in the pedestal gradient region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Beam dynamics challenges in linear colliders based on laser-plasma accelerators

In this paper we discuss design considerations and beam dynamics challenges associated with laser-driven plasma-based accelerators as applied to multi-TeV-scale linear colliders. Plasma accelerators provide ultra-high gradients and ultra-short bunches, offering the potential for compact linacs and reduced power requirements. We show that stable, efficient acceleration with beam quality preservation is possible in the nonlinear bubble regime of laser-plasma accelerators using beam shaping. Ion motion, naturally occuring for dense beams (i.e., low emittance and high energy) severely damps transverse beam instabilities. Coulomb scattering by the background ions is considered and it is shown that the strong focusing in the plasma strongly suppresses scattering-induced emittance growth. Finally, Betatron radiation emission from the transverse motion of the beam in the plasma will result in beam power loss and energy spread growth; however for sub-100 nm emittances, the beam power loss and energy spread growth will be sub-percent for multi-TeV-class plasma linacs.

47 OTHER INSTRUMENTATION↗

Experimental Measurements of Ion Diffusion Coefficients and Heating in a Multi-Ion-Species Plasma Shock

Collisional plasma shocks generated from supersonic flows are an important feature in many astrophysical and laboratory high-energy-density plasmas. Compared to single-ion-species plasma shocks, plasma shock fronts with multiple ion species contain additional structure, including interspecies ion separation driven by gradients in species concentration, temperature, pressure, and electric potential. We present time-resolved density and temperature measurements of two ion species in collisional plasma shocks produced by head-on merging of supersonic plasma jets, allowing determination of the ion diffusion coefficients. Here our results provide the first experimental validation of the fundamental inter-ion-species transport theory. The temperature separation, a higher-order effect reported here, is valuable for advancements in modeling HED and ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The weak land carbon sink hypothesis

Over the past three decades, assessments of the contemporary global carbon budget consistently report a strong net land carbon sink. Here, we review evidence supporting this paradigm and quantify the differences in global and Northern Hemisphere estimates of the net land sink derived from atmospheric inversion and satellite-derived vegetation biomass time series. Our analysis, combined with additional synthesis, supports a hypothesis that the net land sink is substantially weaker than commonly reported. At a global scale, our estimate of the net land carbon sink is 0.8 ± 0.7 petagrams of carbon per year from 2000 through 2019, nearly a factor of two lower than the Global Carbon Project estimate. With concurrent adjustments to ocean (+8%) and fossil fuel (−6%) fluxes, we develop a budget that partially reconciles key constraints provided by vegetation carbon, the north-south CO 2 gradient, and O 2 trends. We further outline potential modifications to models to improve agreement with a weaker land sink and describe several approaches for testing the hypothesis.

Randerson, James T. [Univ. of California, Irvine, ↗

Anisotropic Particle Acceleration in Alfvénic Turbulence

Alfvénic turbulence is an effective mechanism for particle acceleration in strongly magnetized, relativistic plasma. In this study, we investigate a scenario where turbulent plasma is influenced by a strong guide magnetic field, resulting in highly anisotropic turbulent fluctuations. In such cases, the magnetic moments of particles are conserved, which means that acceleration can only occur along the direction of the magnetic field. Consistent with previous analytic studies, we find through particle-in-cell simulations of magnetically dominated pair plasma that the momenta of accelerated particles are closely aligned with the magnetic field lines. Notably, the alignment angle decreases as particle energy increases, potentially limited only by the inherent curvature and gradients of the turbulent magnetic fluctuations. This finding has significant implications for interpreting the synchrotron radiation emitted by highly accelerated particles.

79 ASTRONOMY AND ASTROPHYSICS↗

Root exudate composition reflects drought severity gradient in blue grama (Bouteloua gracilis)

Abstract Plant survival during environmental stress greatly affects ecosystem carbon (C) cycling, and plant–microbe interactions are central to plant stress survival. The release of C-rich root exudates is a key mechanism plants use to manage their microbiome, attracting beneficial microbes and/or suppressing harmful microbes to help plants withstand environmental stress. However, a critical knowledge gap is how plants alter root exudate concentration and composition under varying stress levels. In a greenhouse study, we imposed three drought treatments (control, mild, severe) on blue grama ( Bouteloua gracilis Kunth Lag. Ex Griffiths), and measured plant physiology and root exudate concentration and composition using GC–MS, NMR, and FTICR. With increasing drought severity, root exudate total C and organic C increased concurrently with declining predawn leaf water potential and photosynthesis. Root exudate composition mirrored the physiological gradient of drought severity treatments. Specific compounds that are known to alter plant drought responses and the rhizosphere microbiome mirrored the drought severity-induced root exudate compositional gradient. Despite reducing C uptake, these plants actively invested C to root exudates with increasing drought severity. Patterns of plant physiology and root exudate concentration and composition co-varied along a gradient of drought severity.

59 BASIC BIOLOGICAL SCIENCES↗

2020 State of the Science Report, Chapter 1: Marine Renewable Energy and Ocean Energy System

Research, development, and deployment of marine renewable energy (MRE) conversion technologies that harvest all forms of ocean renewable resources are being advanced around the world. The potential benefits derived from capturing the abundant energy of tides, waves, ocean currents, as well as thermal and salinity gradients, continue to drive the development of the emerging MRE industry. Stakeholder understanding of the potential benefits of MRE as a renewable energy source is informed by increased science-based understanding of the potential effects of MRE installations worldwide. The international Ocean Energy Systems (OES)-Environmental collaboration continues to promote global technology cooperation and information exchange to accelerate environmentally acceptable development of viable ocean energy systems. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-1-MRE-OES

13 HYDRO ENERGY↗

Steep sulfur gradient in CZTSSe solar cells by H 2 S-assisted rapid surface sulfurization

Sulfur/selenium grading is a widely used optimization strategy in kesterite thin-film solar cells to obtain a bandgap-graded absorber material and to optimize optical and electrical properties of the solar-cell device. In this work, we present a novel approach to introduce a [S]/([S] + [Se]) grading for Cu 2 ZnSn(S,Se) 4 solar cells. In contrast to commonly used methods with slow process dynamics, the presented approach aims to create a fast sulfurization reaction on the surface of pure selenide kesterite absorbers by using highly reactive H 2 S gas and high sulfurization temperatures in a rapid flash-type process. With a combination of X-ray photoelectron spectroscopy, X-ray emission spectroscopy, Raman spectroscopy, and Raman-shallow angle cross sections spectroscopy, we gain depth-varied information on the [S]/([S] + [Se]) ratio and discuss the impact of different process parameter variations on the material and device properties. The results demonstrate the potential of the developed process to generate a steep gradient of sulfur that is confined mainly to the surface region of the absorber film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon-sequestration gradient insulation composites

The massive use of carbon-sequestration building materials promises a potential global carbon sink in decarbonizing the building industry. Renewable biogenic materials from abundant agriculture waste for building practice have been around over thousands of years. However, in addition to their flammability and moisture problems, addressing their low thermal and structural performance is also becoming indispensable and urgent when it comes to environmentally sustainable and energy-efficient buildings. Here, we report a nature-inspired biogenic gradient insulation composite with an optimized silica concentration of 30 wt %, a density of 0.246 g/cm 3 , and a porosity of 86%. The gradient hybrid composite exhibits a thermal conductivity of 28.2 mW m -1 K -1 , which is the lowest achieved under optimal preparation conditions. Here, it also shows a flexural modulus of 590 MPa for the aerogel-rich layer without surface modification, and it demonstrates superior fire retardancy and superhydrophobicity after surface treatment.

36 MATERIALS SCIENCE↗

Activity gradient mass transport accelerated corrosion of stainless steel in molten salt

Advanced energy systems based on molten salt technologies have gained increasing interest, and their design and construction are likely going to involve the use of materials of dissimilar chemistries. With dissimilar materials being used, galvanic coupling induced corrosion acceleration is one of the mechanisms believed to be an issue for the deployment of molten salt systems. However, non-galvanic interaction mechanisms such as activity gradient mass transport have also been theorized to represent a potential challenge. Unfortunately, the two effects have often been compounded in the literature, such that it is still unclear which degradation mechanisms are at play in these systems. In the following study, electrochemical measurements are used to predict the effect that galvanic coupling would have on dissimilar materials submerged in the same molten salt medium. Dissimilar material salt exposure tests are then performed to investigate whether galvanic coupling or activity gradient driven processes account for the levels of materials degradation observed. Finally, these separate effect electrochemical and corrosion experiments uniquely elucidate the degradation mechanisms in dissimilar materials systems.

36 MATERIALS SCIENCE↗