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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

Vegetation Type and Decomposition Priming Mediate Brackish Marsh Carbon Accumulation Under Interacting Facets of Global Change

Coastal wetland carbon pools are globally important, but their response to interacting facets of global change remain unclear. Numerical models neglect species-specific vegetation responses to sea level rise (SLR) and elevated CO 2 (eCO 2 ) that are observed in field experiments, while field experiments cannot address the long-term feedbacks between flooding and soil growth that models show are important. Here, we present a novel numerical model of marsh carbon accumulation parameterized with empirical observations from a long-running eCO 2 experiment in an organic rich, brackish marsh. Model results indicate that eCO 2 and SLR interact synergistically to increase soil carbon burial, driven by shifts in plant community composition and soil volume expansion. Furthermore, newly parameterized interactions between plant biomass and decomposition (i.e. soil priming) reduce the impact of eCO 2 on marsh survival, and by inference, the impact of eCO 2 on soil carbon accumulation.

54 ENVIRONMENTAL SCIENCES↗

Entropy and crystal-facet modulation of P2-type layered cathodes for long-lasting sodium-based batteries

Abstract P2-type sodium manganese-rich layered oxides are promising cathode candidates for sodium-based batteries because of their appealing cost-effective and capacity features. However, the structural distortion and cationic rearrangement induced by irreversible phase transition and anionic redox reaction at high cell voltage (i.e., >4.0 V) cause sluggish Na-ion kinetics and severe capacity decay. To circumvent these issues, here, we report a strategy to develop P2-type layered cathodes via configurational entropy and ion-diffusion structural tuning. In situ synchrotron X-ray diffraction combined with electrochemical kinetic tests and microstructural characterizations reveal that the entropy-tuned Na 0.62 Mn 0.67 Ni 0.23 Cu 0.05 Mg 0.07 Ti 0.01 O 2 (CuMgTi-571) cathode possesses more {010} active facet, improved structural and thermal stability and faster anionic redox kinetics compared to Na 0.62 Mn 0.67 Ni 0.37 O 2 . When tested in combination with a Na metal anode and a non-aqueous NaClO 4 -based electrolyte solution in coin cell configuration, the CuMgTi-571-based positive electrode enables an 87% capacity retention after 500 cycles at 120 mA g −1 and about 75% capacity retention after 2000 cycles at 1.2 A g −1 .

25 ENERGY STORAGE↗

Power conversion in SnS photocathodes made by electrochemical growth is limited by recombination at (002) buried facets

Herzenbergite α-SnS is a promising p-type semiconductor for photovoltaic and solar fuel applications, but current devices are plagued by substantial photovoltage losses. Here we use vibrating Kelvin probe surface photovoltage for the first time to study the recombination losses in microcrystalline SnS photoelectrodes. α-SnS films of varied crystal orientation, size, and shape are obtained by electrochemical growth from aqueous tin( II ) chloride and sodium thiosulfate solutions near room temperature. After application of a CdS passivation layer, the films function as photocathodes for the methylviologen reduction reaction. Photoelectrochemical and surface photovoltage measurements reveal that the performance of these devices is sensitively controlled by mainly the SnS crystal orientation and to a lesser extent by the grain size. For example, the highest charge recombination rates of 8.97 × 10 14 s −1 cm −2 and lowest photocurrent (0.73 mA cm −2 ) and lowest photovoltage (0.12 V) occur for SnS films containing 500 nm crystals with irregular shapes and SnS lattices tilted away from the (001) orientation. On the other hand, the best performance (1.62 mA cm −2 , 0.16 V, 3.32 × 10 12 s −1 cm −2 ) is seen for 1100 nm fully (001) oriented SnS nanoplates. Furthermore, these findings agree with improved charge carrier mobility in the 001 direction and they also show that charge recombination in SnS films occurs mainly at dangling Sn–S bonds at buried (002) facets. Such buried interfaces need to be suppressed for optimized solar energy conversion with SnS.

Najaf, Zainab [University of California, Davis, CA↗

Surface facet dependence of competing alloying mechanisms

Metal alloys are ubiquitous in many branches of heterogeneous catalysis, and it is now fairly well established that the local atomic structure of an alloy can have a profound influence on its chemical reactivity. While these effects can be difficult to probe in nanoparticle catalysts, model studies using well defined single crystal surfaces alloyed with dopants enable these structure–function correlations to be drawn. The first step in this approach involves understanding the alloying mechanism and the type of ensembles formed. In this study, we examined the atomic structure of RhCu single-atom alloys formed on Cu(111), Cu(100), and Cu(110) surfaces. Our results show a striking difference between Rh atoms alloying in Cu(111) vs the more open Cu(100) and Cu(110) surface facets. Unlike Cu(111) on which Rh atoms preferentially place-exchange with Cu atoms in the local regions above step edges leaving the majority of the Cu surface free of Rh, highly dispersed, homogeneous alloys are formed on the Cu(100) and (110) surfaces. These dramatically different alloying mechanisms are understood by quantifying the energetic barriers for atomic hopping, exchange, swapping, and vacancy filling events for Rh atoms on different Cu surfaces through theoretical calculations. Density functional theory results indicate that the observed differences in the alloying mechanism can be attributed to a faster hopping rate, relatively high atomic exchange barriers, and stronger binding of Rh atoms in the vicinity of step edges on Cu(111) compared to Cu(110) and Cu(100). Furthermore, these model systems will serve as useful platforms for examining structure sensitive chemistry on single-atom alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion coefficients predicting facet-dependent crystallization in amorphous silicon nitride

Amorphous silicon nitride is a common material in microelectronics devices, which acts as an insulating barrier. Extended annealing times at elevated temperature can initiate crystallization of α-Si 3 ⁢ N 4 , which does not possess the same barrier properties. Molecular dynamics can resolve the fundamental mechanism for α-Si 3 ⁢N 4 crystallization and the influence of local environments. Here, we compare two interatomic potentials and conclude that these models predict structural features (e.g., angular distributions and densities) which span the range of experimental measurements. We confirmed these models reproduce experimental estimates of activation energy and leveraged these models to identify crystallization drivers. We conclude that near-T g , facet-dependent silicon nitride crystal growth rates can be predicted directly by either bulk or interfacial diffusion properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sonic Lift-off of GaAs-based Solar Cells with Reduced Surface Facets

Spalling has been proposed as a promising kerfless technique for slicing thin wafers and devices, enhancing the wafer yield from an ingot by reducing kerf-losses and enabling substrate reuse for the case of costly devices. The main challenge of spalling is to control the roughness and thickness variation of the spalled wafers that can be as high as 100% of the wafer thickness. Here, we have shown previously that the thickness variations are largely influenced by the interaction of the crack front with its own reflected waves. Herein we show that through Sonic Lift-off we can offer a modification to standard spalling technologies that minimizes the interaction of reflected waves with the crack front during lift-off of GaAs(100)-based solar cells. We show that the average surface facets amplitude can be reduced by 96% while obtaining a high quality bulk with no discernible residual strain as measured by PL. The resulting spalling depth can easily be tuned from 100 µm to less than 15µm. The electrical characterization of the Sonic lift-off cell shows no degradation of the VOC and a power conversion within 99% relative of a non-spalled baseline.

42 ENGINEERING↗

FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

Sakaguchi, Koichi↗

Non-reactive facet specific adsorption as a route to remediation of chlorinated organic contaminants

The present work quantifies metal-contaminant interactions between palladium substrates and three salient chlorinated organic contaminants, namely trichloroethylene 1,3,5-trichlorobenzene (TCB), and 3,3′,4,4′-tetrachlorobiphenyl (PCB77). Given that Pd is one of the conventional catalytically active materials known for contaminant removal, maximizing catalytic efficiency through optimal adsorption dynamics reduces the cost of remediation of contaminants that are persistent water pollutants chronically affecting public health. Adsorption efficiency analyses from all-atom molecular dynamics (MD) simulations advance the understanding of reaction mechanisms available from density functional theory (DFT) calculations to an extractable feature scale that can fit the parametric design of supported metal catalytic systems and feed into high throughput catalyst selection. Data on residence time, site-specific adsorption, binding energies, packing geometries, orientation profiles, and the effect of adsorbate size show the anomalous behaviour of organic contaminant adsorption on the undercoordinated {110} surface as compared to the {111} and {100} surfaces. The intermolecular interaction within contaminants from molecular dynamics simulation exhibits refreshing results than ordinary single molecule density functional theory calculation. Since complete adsorption and dechlorination is an essential step for chlorinated organic contaminant remediation pathways, the presented profiles provide essential information for designing efficient remediation systems through facet-controlled palladium nanoparticles.

Guo, Hao↗

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

We discuss the implementation of a suite of virtual diagnostics at the FACET-II facility currently under commissioning at SLAC National Accelerator Laboratory. The diagnostics will be used for the prediction of the longitudinal phase space along the linac, spectral reconstruction of the bunch profile, and non-destructive inference of transverse beam quality (emittance) while using edge radiation at the injector dogleg and bunch compressor locations. These measurements will be folded into adaptive feedbacks and Machine Learning (ML)-based reinforcement learning controls to improve the stability and optimize the performance of the machine for different experimental configurations. In this paper we describe each of these diagnostics with expected measurement results that are based on simulation data and discuss progress towards implementation in regular operations.

Emma, Claudio (ORCID:0000000247191831)↗