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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Denoising atomic resolution 4D scanning transmission electron microscopy data with tensor singular value decomposition

Tensor singular value decomposition (SVD) is a method to find a low-dimensional representation of data with meaningful structure in three or more dimensions. Here, tensor SVD has been applied to denoise atomic-resolution 4D scanning transmission electron microscopy (4D STEM) data. On data simulated from a SrTiO 3 [100] perfect crystal and a Si [110] edge dislocation, tensor SVD achieved an average peak signal-to-noise ratio (PSNR) of ~40 dB, which matches or exceeds the performance of other denoising methods, with processing times at least 100 times shorter. On experimental data from SrTiO 3 [100] and LiZnSb [11 2 ¯ 0]/GaSb [110] samples, tensor SVD denoises multiple GB 4D STEM data sets in ten minutes on a typical personal computer. Denoising with tensor SVD improves both convergent beam electron diffraction patterns and virtual-aperture annular dark field images.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Oxygen redox and instability in energy ceramics

Energy ceramics, including solid electrolytes and catalysts for high-temperature fuel/electrolysis cells and oxide cathodes for batteries, often experience harsh chemical and electrochemical conditions. Practical and new applications require that these devices are operated under ever more extreme redox conditions for higher energy density and power density. This challenges the stability of the energy ceramic materials and calls for a better understanding of the degradation mechanisms and innovative strategies for degradation mitigation. Here we present our analysis and perspectives on degradation phenomena in three categories of electrochemical devices of practical interest, including solid oxide fuel/electrolysis cells, protonic ceramic fuel/electrolysis cells, and lithium-ion batteries. We also discuss the stability/degradation of the key ceramic components from the view of oxygen redox and instability arising from anodic bias, transport limitation, and coupled electro-chemo-mechanics at the virtual and physical interfaces. We hope these perspectives provide design principles for electroceramic chemistry, microstructure, and processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Combined plasma–coil optimization algorithms

Combined plasma–coil optimization approaches for designing stellarators are discussed and a new method for calculating free-boundary equilibria for multiregion relaxed magnetohydrodynmics (MRxMHD) is proposed. Four distinct categories of stellarator optimization, two of which are novel approaches, are the fixed-boundary optimization, the generalized fixed-boundary optimization, the quasi-free-boundary optimization, and the free-boundary (coil) optimization. These are described using the MRxMHD energy functional, the Biot–Savart integral, the coil-penalty functional and the virtual casing integral and their derivatives. The proposed free-boundary equilibrium calculation differs from existing methods in how the boundary-value problem is posed, and for the new approach it seems that there is not an associated energy minimization principle because a non-symmetric functional arises. We propose to solve the weak formulation of this problem using a spectral-Galerkin method, and this will reduce the free-boundary equilibrium calculation to something comparable to a fixed-boundary calculation. In our discussion of combined plasma–coil optimization algorithms, we emphasize the importance of the stability matrix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A fast, accurate and easy to implement Kapur–Rokhlin quadrature scheme for singular integrals in axisymmetric geometries

Many applications in magnetic confinement fusion require the efficient calculation of surface integrals with singular integrands. The singularity subtraction approaches typically used to handle such singularities are complicated to implement and low-order accurate. In contrast, we demonstrate that the Kapur–Rokhlin quadrature scheme is well-suited for the logarithmically singular integrals encountered for a toroidally axisymmetric confinement system, is easy to implement and is high-order accurate. As an illustration, we show how to apply this quadrature scheme for the efficient and accurate calculation of the normal component of the magnetic field due to the plasma current on the plasma boundary, via the virtual-casing principle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Congenital toxoplasmosis in humans: an update of worldwide rate of congenital infections

Abstract The morbidity due to congenital toxoplasmosis in humans is very high. Most of these infected children are likely to develop symptoms of clinical toxoplasmosis. Sequelae in fetus resulting from Toxoplasma gondii infections in women who become infected with this parasite during pregnancy can be devastating and enormous efforts are directed in some countries to prevent these consequences. Here, an update on congenital toxoplasmosis in humans, especially the rate of congenital infections in humans worldwide, is provided. Although several countries have surveillance programmes, most information on the rate of congenital transmission is from France and Brazil. Because of compulsory national screening programme in France to detect and treat women with recently acquired T. gondii infection with anti-toxoplasma therapy, the rate of congenital transmission and the severity of disease in children are declining. Infections by this parasite are widely prevalent in Brazil. The severity of clinical toxoplasmosis in Brazilian children is very high and may be associated with the genetic characteristics of T. gondii isolates prevailing in animals and humans in Brazil. Virtually little or no information is available on this topic from China, India and other countries in Asia.

Parasitology↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Experimental and Computational Evaluation of Lipidomic In-Source Fragmentation as a Result of Postionization with Matrix-Assisted Laser Desorption/Ionization

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide spatially resolved molecular information about a sample. Recently, a postionization approach (MALDI-2) has been commercially integrated with MALDI-MSI, allowing for bettered sensitivity and consequent improved spatial resolution. While advantages of MALDI-2 have previously been established, we demonstrate here statistically increased in-source fragmentation (ISF) results from postionization with a commercial instrument. Via lipid standard analyses, known MALDI ISF pathways (e.g., loss of trimethylamine) were statistically increased in MALDI-2 compared to MALDI-1 (65–172% increase in fragmentation). Gas phase molecular modeling with density functional theory estimated that the most-weighted virtual orbitals to excite within lipids involve ester and phosphate bonds. Protonated lipid excitation energies are furthermore red-shifted compared to those of other adduct types [e.g., 254 nm for protonated PC(16:0/18:1)] and approach the MALDI-2 laser energy (266 nm). Analysis of rat brain homogenate detected statistically more positive-ion mode peaks with MALDI-2 (1090) than that with MALDI-1 (719), where Kernel density estimations showed that the majority of this enhancement occurs with low m/z ions (i.e., m/z 75–500). Taken together with the lipid standard data, these observations may indicate ISF due to postionization. Finally, while artifact contributions from matrix blanks were also noted, both experimental and computational data sets suggest that the overall extent of ISF is statistically increased in MALDI-2 compared to MALDI-1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reduced Dislocation Introduction in III–V/Si Heterostructures with Glide-Enhancing Compressively Strained Superlattices

The novel use of a GaAs y P 1-y /GaP compressively-strained superlattice (CSS) to provide enhanced control over misfit dislocation (MD) evolution and threading dislocation density (TDD) during GaP/Si metamorphic heteroepitaxy is demonstrated. Here, the insertion of the CSS just after critical thickness, and thus prior to substantial dislocation introduction, is found to yield significantly reduced TDD in relaxed, 500 nm thick, n-type GaP/Si versus comparable control samples. The impact of CSS period count on average TDD and the overall dislocation network morphology was examined, supported by quantitative microstructural characterization, revealing a nearly 20× relative TDD reduction (to 2.4 ± 0.4×10 6 cm -2 ) with a 3-period CSS structure. A similarly low TDD (3.0 ± 0.6×10 6 cm -2 ) is maintained when the resultant n-GaP/Si virtual substrate is used for the growth of a subsequent n-type GaAs 0.75 P 0.25 -terminal GaAs y P 1-y step-graded metamorphic buffer. Although the physical mechanism for TDD reduction provided by these structures is not yet entirely understood, this initial work suggests that enhanced glide dynamics of MDs at or within the CSS placed early in the growth leads to a reduction in the total number of dislocations introduced overall, as opposed to annihilation-based reduction that occurs in conventional strained-layer superlattice dislocation filter approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Production of C 2 /C 3 Oxygenates from Planar Copper Nitride-Derived Mesoporous Copper via Electrochemical Reduction of CO 2

Electrochemical reduction of CO 2 provides an opportunity to produce fuels and chemicals in a carbon-neutral manner, assuming that CO 2 can be captured from the atmosphere. To do so requires efficient, selective, and stable catalysts. In this study, we report a highly mesoporous metallic Cu catalyst prepared by electrochemical reduction of thermally nitrided Cu foil. Under aqueous saturated CO 2 reduction conditions, the Cu 3 N-derived Cu electrocatalyst produces virtually no CH 4 , very little CO, and exhibits a faradaic efficiency of 68% in C 2+ products (C 2 H 4 , C 2 H 5 OH, and C 3 H 7 OH) at a current density of ~18.5 mA cm –2 and a cathode potential of -1.0 V versus the reversible hydrogen electrode. Under these conditions, the catalyst produces more oxygenated products than hydrocarbons. We show that surface roughness is a good descriptor of catalytic performance. The roughest surface reached 98% CO utilization efficiency for C 2+ product formation from CO 2 reduction and the ratio of oxygenated to hydrocarbon products correlates with the degree of surface roughness. These effects of surface roughness are attributed to the high population of undercoordinated sites as well as a high pH environment within the mesopores and adjacent to the surface of the catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Long-Term Cyclability of NCM-811 at High Voltages in Lithium-Ion Batteries: an In-Depth Diagnostic Study

High-nickel layered oxides, such as LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM-811), offer higher energy density than their low-nickel counterparts at a given voltage and are gaining major traction in automotive lithium-ion batteries for electric vehicles. Besides high-Ni content, higher charging voltages above 4.3 V vs Li + /Li boost the energy and represent another focus in battery development. Here, we investigate the long-term cyclability of NCM-811 in graphite pouch cells over 1000 deep cycles between 2.5–4.2, 2.5–4.4, and 2.5–4.5 V through a suite of sensitive characterization techniques. The NCM-811 full cells show severely deteriorated cyclability with higher charging voltages, from 78% at 4.2 V to 52 and 32% at 4.4 and 4.5 V, respectively. At 4.2 V, minor parasitic electrolyte oxidation as well as cathode Li/Ni mixing and cracking are revealed after cycling, while transition-metal dissolution and surface reconstruction into rock-salt NiO are virtually undetectable. At 4.4 and 4.5 V, transition-metal dissolution and crossover to the anode become much more pronounced and a primary contributor to the capacity fade, while significant surface NiO formation causes substantial voltage polarization, which is less noticeable at 4.2 V. Meanwhile, more severe electrolyte oxidation, Li/Ni mixing, and particle pulverization exacerbate the voltage and capacity fade. Finally, these results outline distinct challenges for stable high-Ni layered oxide cathodes in high-voltage Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na 3 V 2 (PO 4 ) 2 F 3

While powder diffraction methods are routinely utilized to optimize structural models for compounds whose crystal structures are known, the determination of unknown structures is far more challenging. When the unknown structure is large, structure solution can become a virtually intractable problem using standard structure solution methodologies, especially when the space group cannot be unambiguously resolved. One such system is the promising Na-ion battery cathode material Na 3 V 2 (PO 4 ) 2 F 3 whose high temperature and room temperature structures were previously solved, but whose more complex low-temperature structure could not be determined. Here, a novel materials genomic approach is demonstrated for the solution of the unknown 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 in which enumeration methods are first used to generate a large number (~3,000) of trial structures based on plausible orderings of Na ions and then automated Rietveld refinements are carried out to optimize each of these trial structures. Based on both the analysis of the ensemble of optimized trial structures and the density functional theory energy minimization of selected trial structures, the 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 is best described as belonging to the space group A2 1 am with unit cell dimensions of a = 9.01928(4), b = 27.1379(1), c = 10.73307(5). The 100 K unit cell has a large volume of 2627.07(2) Å 3 with Z = 12 and 33 independent crystallographic sites (9 Na, 3 V, 3 P, 12 O, and 6 F) that is 3x and 6x larger than the room- and high-temperature polymorphs of this phase, respectively. Finally, the novel methods described here will be generally applicable for the solution of the complex cation-ordered structures that commonly occur for battery materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders

We report the design/discovery of new materials is highly nontrivial owing to the near-infinite possibilities of material candidates and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to virtually screen material candidates with desired properties by learning a theoretical mapping from material-to-property space, referred to as the forward problem. However, this approach is inefficient and severely constrained by the candidates that the human imagination can conceive. Thus, in this work on polymers, we tackle the materials discovery challenge by solving the inverse problem: directly generating candidates that satisfy desired property/performance objectives. We utilize syntax-directed variational autoencoders (VAE) in tandem with Gaussian process regression (GPR) models to discover polymers expected to be robust under three extreme conditions: (1) high temperatures, (2) high electric field, and (3) high temperature and high electric field, useful for critical structural, electrical, and energy storage applications. This approach to learn from and augment) human ingenuity is general and can be extended to discover polymers with other targeted properties and performance measures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Solid Electrolytes in the Spotlight

This virtual issue is targeted to students and researchers, and highlights 32 research articles published over the past 5 years (from July 2016 to July 2021) in Chemistry of Materials (CM). Here, the compilation of papers summarizes the latest advances in the field of solid-state electrolytes for lithium (Li)-, sodium (Na)-, and multivalent-ion (not among the 32 articles discussed) all-solid-state batteries (ASSBs), with a focus on inorganic materials and excluding hybrid systems, e.g., polymer/ceramic composites or systems including liquid media. A total of 125 articles reporting exciting experimental and/or theoretical findings on solid electrolytes were considered for this issue. During 2017–2019, there were about 25–30 papers published per year on this topic, but 2020 and 2021 saw a significant increase, with 26 publications in the first half of 2021 alone. Submissions came from many countries around the world, as shown in Figure 1. While most papers were led by research groups located in the United States, Germany and Japan follow closely, and Austria, the United Kingdom, Canada, and China are also well represented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

In Situ X-Ray Absorption Spectroscopy Disentangles the Roles of Copper and Silver in a Bimetallic Catalyst for the Oxygen Reduction Reaction

Silver-based bimetallic catalysts for the oxygen reduction reaction (ORR) are promising for a wide variety of renewable energy technologies, including alkaline fuel cells and metal-air batteries. The activity of bimetallic catalysts can sometimes surpass that of either constituent element, but the origin of the enhanced performance is still debated. At a given active site, two complementary mechanisms are proposed to explain the performance improvements: the binding energy of intermediate adsorbates can be tuned by direct electronic contributions from the alloying element or by changes in the bond lengths from lattice distortion. To distinguish between these effects and elucidate the respective roles of each element in the bimetallic, it is critical to study catalysts at the molecular scale under reaction conditions. In this work, we use in situ X-ray absorption spectroscopy (XAS) alongside density functional theory (DFT) to show that direct electronic rather than geometric effects are the primary cause of improved ORR activity in a bimetallic CuAg catalyst. Our results indicate that the local bonding as well as the electronic structure of Ag are virtually unchanged by the presence of Cu, whereas the electronic states of Cu in CuAg are significantly altered. DFT calculations support these experimental findings. We show strong evidence that the activity of the bimetallic CuAg catalyst exceeds the sum of the activities of Cu and Ag, not by incremental improvement of the active Ag sites, but by creating highly active Cu-centered catalytic sites. The insight that the main role of Ag in bimetallic catalysts may be to promote its fellow element through local electronic interactions provides a new design principle for engineering the next generation of bimetallic catalysts for the ORR and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Compositions and Formation Mechanisms of Solid-Electrolyte Interphase on Microporous Carbon/Sulfur Cathodes

We report the formation mechanism and compositions of a solid-electrolyte interphase (SEI) on a microporous carbon/sulfur (MC/S) cathode in Li–S batteries using a carbonate-based electrolyte (1 M LiPF 6 in ethylene carbonate (EC)/dimethyl carbonate, v:v = 1:1). Through characterizations using 1D and 2D solution-phase nuclear magnetic resonance spectroscopy, coupled with model chemical reactions and DFT calculations, we have identified two critical roles of Li + in steering the SEI formation. First, the preferential solvation of Li + by EC in the mixed carbonate electrolyte renders EC as the dominant participant in the SEI formation, and second, Li + coordination to the EC carbonyl alters activation barriers and changes the reaction pathways relative to Na + . The main organic components in the SEI are identified as lithium ethylene monocarbonate and lithium methyl carbonate, which are virtually identical to those formed on Li and graphite anodes of lithium-ion batteries but via a different pathway.

25 ENERGY STORAGE↗