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At least 631 records · Page 35

Thaw depth, soil moisture, and vegetation height, Teller and Kougarok sites, Seward Peninsula, Alaska, 2022

Thaw depth, soil moisture, and vegetation height sampled from locations on the Teller MM27, Kougarok MM80, and Kougarok MM82 NGEE-Arctic sites, Seward Peninsula, Alaska. These data were collected in support of the ongoing NGEE-Arctic and NASA ABoVE data synthesis work. Samples were collected in July 2022, including 6 transects covering the entire Teller MM27 watershed and 4 transects covering 4 thaw ponds at Kougarok MM80 and MM82. This data package includes sample information and thaw depth, soil moisture, vegetation height data (.csv). Metadata files include data descriptions (_dd.csv) for tabular data and file level metadata (.csv). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗

Synthesis of Hf 0.75 Ta 0.25 B 2 for self-coating TPS

Ultra-high temperature ceramic materials (UHTCs) are important for designing high-performance aerospace vehicles that can withstand repeated exposures to high temperatures. UHTCs mixed with silicides often have well-controlled oxidation due to the formation of protective silicates, which create a regenerative outer protective layer. Borides are known to have high melting points, high hardness and reasonably good oxidation resistance. In this study, Hf 0.75 Ta 0.25 B 2 (HTB) is proposed as a potential alternative to YSZ protective coatings and ZrB 2- SiC composites via the formation of Hf 6 Ta 2 O 17 (HTO) passivation layer. The objective of this paper is to explore the parameter space of HTB synthesis via borocarbothermal (BCTR). Effects on particle size, phase purity, and residual oxygen content were analyzed with parameters of atmosphere composition, reactant grain sizes, and differing reaction pathways. The BCTR of HfO 2 and Ta 2 O 5 were analyzed to predict HTB behavior. It was shown that both one-step and two-step reaction routes can yield HTB, but two-step yields a purer product. Nano B 4 C produced finer HTB and facilitated reaction completion. Using a reducing atmosphere also enhanced reaction completion

36 MATERIALS SCIENCE↗

Synthesis and dynamic characteristics of large structures with rotating substructures

The variational equations of motion of large structures with rotating substructures are derived by the substructure synthesis approach, whereby a discretization procedure akin to the Rayleigh-Ritz method is used to represent the elastic motion of every substructure by a suitable set of admissible functions. Using an inclusion principle for gyroscopic systems, the effects on the predicted system dynamic characteristics of truncating the number of admissible functions used for each substructure can be assessed. Criteria for rational selection of admissible functions are presented.

Meirovitch, L.↗

Dynamics in Layer Models of Solid Flame Propagation

Self-propagating high-temperature synthesis (SHS) is a process in which combustion waves, e.g., "solid flames", which are considered here, are employed to synthesize desired materials. Like many other systems, SHS is a pattern forming system. The problem of describing experimentally observed patterns and of predicting new, as yet unobserved, patterns continues to attract the attention of scientists and mathematicians due to the fundamental significance of the phenomena in combustion in particular, and in nonlinear science in general. Here, we analyze the dynamics of solid flame propagation in a 2D region by considering the region to be composed of parallel, identical layers aligned along the direction of propagation and having thermal contact. Each layer is then described by wave propagation in 1D, with the transverse Laplacian replaced by a term describing heat exchange between neighboring layers. This configuration is the simplest model of a 2D system because it accounts, in a simple way, for the principal feature of the problem, i.e., heat exchange between neighbors in the transverse direction. For simplicity, we describe the situation for two layers. Because the layers are identical, uniformly propagating waves in each layer must be identical, independent of the heat exchange rate alpha. When the Zeldovich number Z exceeds a critical value Z(sub c), which depends on alpha, uniformly propagating waves become unstable. The stability diagram for the two coupled layers reproduces that for the full 2D problem after appropriate identification of parameters in the two problems. Depending on parameter values, we determine three different steady-state dynamical behaviors (though additional behaviors are also expected to occur). The three behaviors are: (i) waves in each layer which pulsate in phase as they propagate, so that together they form a single pulsating propagating wave; (ii) the waves in each layer are no longer identical, and antiphase pulsations occur, with the two waves alternately advancing and receding as they propagate. This wave is the analog of the spinning wave on the surface of a circular cylinder; (iii) finally, there is a region of bistability between the in phase and antiphase waves. with each having its own domain of attraction, so that which of the two behaviors occur depends on the condition of initiation of the wave. The results of our computations indicate a qualitative similarity in the behavior of combustion waves in the layer model and in the full 2D model. Specifically, due to the similarity between the small alpha wave behavior in the layer model and the large diameter behavior in the model of waves on the surface of a cylinder, we are able to predict the behavior of the mean velocity for the waves on the cylinder, where computations of the full problem can be rather difficult. We also compute solutions for three or more layers. The results of our computations prompt us to predict that, while planar uniformly propagating waves are unstable, the wave will be quasiplanar, i.e., the resulting spinning waves have very low amplitude hot spots, and travel with the velocity close to that of the uniformly propagating wave. Such waves may be difficult to distinguish from uniformly propagating waves in experiments. We also find that for both the layer model and full 2D problem, steady-state time-dependent waves, e.g., pulsating and spinning wave, have a conserved quantity H which characterizes the excess energy in the wave, just as in the case of uniformly propagating waves. The quantity H, which is generated by dissipation, does not vary in time and is proportional to the diffusivity and caloricity of the system, and inversely proportional to the mean wave velocity.

Aldushin, A. P.↗

Mapping Galactic 60Fe Synthesis in Cen CIR Region

This included a 1 year no cost time extension. The grant was for research into the origin of radioactive 60Fe, whose detection was a mission goal for INTEGRAL and RHESSI. During the grant period, both missions ultimately discovered gamma-line emission from this long lived radioactivity at precisely the value that had been predicted years before by Timmes and Woosley (ApJ, 449,204 (1995)). Unfortunately, using "revised" stellar models and cross sections Rauscher et a1 (ApJ, 576, 323 (2002)), had meanwhile predicted a much larger value. During the grant period, Dieter Hartmann (PI on the complementary grant at Clemson) and Woosley corresponded on this discrepancy and Hartmann visited Santa Cruz (November 20 - 28,2004). All of the grant funds in NAG513659 paid for the expenses of that visit. Subsequently, partly motivated by conversations with Hartmann and Diehl, Woosley re-investigated the production of 60Fe and 26A1 in massive stars from 12 - 120 solar masses, with an eye towards determining the relevant, uncertain physics. The chief changes in Rauscher et a1 were "new" Hauser Feshbach cross sections for 59,60Fe(ng) and 26Al(np)26Mg. The latter has an experimental evaluation which was actually better represented in the study of Timmes and Woosley. The iron (ng) cross sections are from theory and the Timmes and Woosley values were just as reliable as those from Rauscher. Experiments need to be done to resolve who is right. In addition uncertainties in stellar winds, opacities and the IMF were explored. The bottom line is that the value predicted by Timmes and Woosley could well be the correct one, but the experimental error bar is larger than was realized. At least half of the uncertainty is nuclear cross sections that can, and should be measured in the laboratory.

Woosley, Stanford↗

Synthesis of Honeycomb-Structured Beryllium Oxide via Graphene Liquid Cells

Using high-resolution transmission electron microscopy and electron energy-loss spectroscopy, we demonstrate that beryllium oxide crystallizes in the planar hexagonal structure in a graphene liquid cell by a wet-chemistry approach. These liquid cells can feature van-der-Waals pressures up to 1 GPa, producing a miniaturized high-pressure container for the crystallization in solution. The thickness of as-received crystals is beyond the thermodynamic ultra-thin limit above which the wurtzite phase is energetically more favorable according to the theoretical prediction. The crystallization of the planar phase is ascribed to the near-free-standing condition afforded by the graphene surface. Our calculations show that the energy barrier of the phase transition is responsible for the observed thickness beyond the previously predicted limit. These findings open a new door for exploring aqueous-solution approaches of more metal-oxide semiconductors with exotic phase structures and properties in graphene-encapsulated confined cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

Mechanistic modeling of in vitro transcription incorporating effects of magnesium pyrophosphate crystallization

The in vitro transcription (IVT) reaction used in the production of messenger RNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale-up, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. To help generalize this model to different constructs, a novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 RNA polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.

59 BASIC BIOLOGICAL SCIENCES↗

Crystallization of binary nanocrystal superlattices and the relevance of short-range attraction

The synthesis of binary nanocrystal superlattices (BNSLs) enables the targeted integration of orthogonal physical properties, such as photoluminescence and magnetism, into a single superstructure, unlocking a vast design space for multifunctional materials. However, the formation mechanism of BNSLs remains poorly understood, restricting the prediction of the structure and properties of superlattices. Here we use a combination of in situ scattering and molecular simulation to elucidate the self-assembly of two common BNSLs (AlB 2 and NaZn 13 ) through emulsion templating. Our self-assembly experiments reveal that no intermediate structures precede the formation of the final binary phases, indicating that their formation proceeds through classical nucleation. Using simulations, we find that, despite the formation of AlB 2 and NaZn 13 typically being attributed to entropy, their self-assembly is most consistent with the nanocrystals possessing short-range interparticle attraction, which we find can accelerate nucleation kinetics in BNSLs. Here, we also find homogeneous, classical nucleation in simulations, corroborating our experiments. These results establish a robust correspondence between experiment and theory, paving the way towards prediction of BNSLs.

36 MATERIALS SCIENCE↗

Epitaxial growth, magnetoresistance, and electronic band structure of GdSb magnetic semimetal films

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surfaces. The Gd 3 + ion in GdSb has a high spin S=7/2 and no orbital angular momentum, serving as a model system for studying the effects of antiferromagnetic order and strong exchange coupling on the resulting Fermi surface and magnetotransport properties of RE-Vs. Here, we present a surface and structural characterization study mapping the optimal synthesis window of thin epitaxial GdSb films grown on III-V lattice-matched buffer layers via molecular-beam epitaxy. To determine the factors limiting XMR in RE-V thin films and provide a benchmark for band-structure predictions of topological phases of RE-Vs, the electronic band structure of GdSb thin films is studied, comparing carrier densities extracted from magnetotransport, angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT) calculations. ARPES shows a hole-carrier rich, topologically trivial, semimetallic band structure close to complete electron-hole compensation, with quantum confinement effects in the thin films observed through the presence of quantum-well states. DFT-predicted Fermi wave vectors are in excellent agreement with values obtained from quantum oscillations observed in magnetic field-dependent resistivity measurements. An electron-rich Hall coefficient is measured despite the higher hole-carrier density, attributed to the higher electron Hall mobility. The carrier mobilities are limited by surface and interface scattering, resulting in lower magnetoresistance than that measured for bulk crystals.

36 MATERIALS SCIENCE↗

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data

Error-bounded lossy compression is critical to the success of extreme-scale scientific research because of ever-increasing volumes of data produced by today's high-performance computing (HPC) applications. Not only can error-controlled lossy compressors significantly reduce the I/O and storage burden but they can retain high data fidelity for post analysis. Existing state-of-the-art lossy compressors, however, generally suffer from relatively low compression and decompression throughput (up to hundreds of megabytes per second on a single CPU core), which considerably restrict the adoption of lossy compression by many HPC applications especially those with a fairly high data production rate. In this paper, we propose a highly efficient lossy compression approach based on field programmable gate arrays (FPGAs) under the state-of-the-art lossy compression model SZ. Our contributions are fourfold. (1) We adopt a wavefront memory layout to alleviate the data dependency during the prediction for higher-dimensional predictors, such as the Lorenzo predictor. (2) We propose a co-design framework named WAVESZ based on the wavefront memory layout and the characteristics of SZ algorithm and carefully implement it by using high-level synthesis. (3) We propose a hardware-algorithm co-optimization method to improve the performance. (4) We evaluate our proposed WAVESZ on three real-world HPC simulation datasets from the Scientific Data Reduction Benchmarks and compare it with other state-of-the-art methods on both CPUs and FPGAs. Experiments show that our WAVESZ can improve SZ's compression throughput by 6.9x similar to 8.7x over the production version running on a state-of-the-art CPU and improve the compression ratio and throughput by 2.1x and 5.8x on average, respectively, respectively, compared with the state-of-the-art FPGA design.

Compression Ratio↗

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗

Stratification of chemical elements in the atmosphere of the Ap star 53 Camelopardalis

A detailed abundance analysis of Cr, Fe, Mn, Ca, and Ti in the Ap star 53 Cam from IUE high-resolution spectra has been performed. It is found that UV lines give significantly lower abundance than visible lines for Cr and Fe. Theoretical spectra of Cr II line calculated with the stratified chromium abundance distributions predicted a priori by the diffusion-mass loss model match well both visible and UV lines. The spectral shape of the Ca II K line and its variation are well accounted for by the diffusion model with mass loss. A spectrum synthesis with a stratified abundance well reproduces the observations. These findings provide convincing evidence for stratification in the photosphere of 53 Cam.

Babel, J.↗

2.3.4.501 - Synthesis and Analysis of Performance-Advantaged Bioproducts

This project focuses on the synthesis and analysis of performance-advantaged bioproducts (PABPs). We have established collaborations with other BETO-funded projects and academic and industrial collaborators to source new molecules that have promising manufacturing pathways and that could be serve as performance-advantaged biochemicals or biopolymers. We conduct synthesis and characterization of biochemicals and biopolymers alongside techno-economic analysis and life cycle assessment to estimate their cost and environmental impacts relative to incumbent materials. As part of the project, Profs. Linda Broadbelt and Brent Shanks are developing computational pathway prediction tools to identify optimal production pathways for bio-based compounds via biological and chemo-catalytic transformations. When coupled to the polyID tool from the Inverse Design project, these tools will ultimately enable a narrowing of design space for PABPs. From FY21-FY23, we described a framework for benchmarking PAPBs, estimated the energy and GHG emissions for commodity organic chemicals, developed performance-advantaged nylons and polyesters from beta-ketoadipic acid, and produced lignin-based plasticizers. We have shown that aromatic amines can be used in performance thermosets and that polyhydroxyalkanoates with crosslinked side chains can exhibit rubber-like properties, along with repair and degradability. We are working actively with industry partners on scale-up and validation of multiple PABPs.

BIOMASS FUELS↗

Comparing approaches for introducing polycyclic aromatic hydrocarbons to Ge(001) to seed graphene nanoribbon synthesis by CH 4 chemical vapor deposition

Here, we evaluate two approaches for introducing polycyclic aromatic hydrocarbons (PAHs) to a graphene catalyst substrate as part of a two-step chemical vapor deposition (CVD) process for growing graphene nanoribbons (GNRs). In this process, PAHs first form graphene-like seeds on Ge, and then GNRs are subsequently evolved from these PAH-derived seeds via substrate-mediated anisotropic growth kinetics during the CVD of CH4. The first seeding approach sublimes controlled doses of PAH thin films into the CVD chamber, while the second delivers PAHs directly from the vapor phase at set concentrations. Using these two approaches, we measure the dependence of GNR density on PAH dose and compare the experimental results with predictions from a rate model of PAH diffusion, desorption, and clustering. We find that PAHs that more strongly adsorb to the catalyst surface (generally larger PAHs) desirably remain more individualized prior to GNR evolution whereas smaller, more weakly bound PAHs aggregate into larger clusters with various sizes on Ge that are undesirable for synthesizing more monodisperse GNRs. As a result, this work is important because it offers a framework that enables the rational selection and design of seed molecules, advancing anisotropic GNR CVD synthesis.

CVD↗

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi↗

Contrasting responses to climate change at Himalayan treelines revealed by population demographics of two dominant species

Abstract Alpine treelines are expected to shift upward due to recent climate change. However, interpretation of changes in montane systems has been problematic because effects of climate change are frequently confounded with those of land use changes. The eastern Himalaya, particularly Langtang National Park, Central Nepal, has been relatively undisturbed for centuries and thus presents an opportunity for studying climate change impacts on alpine treeline uncontaminated by potential confounding factors. We studied two dominant species, Abies spectabilis (AS) and Rhododendron campanulatum (RC) , above and below the treeline on two mountains. We constructed 13 transects, each spanning up to 400 m in elevation, in which we recorded height and state (dead or alive) of all trees, as well as slope, aspect, canopy density, and measures of anthropogenic and animal disturbance. All size classes of RC plants had lower mortality above treeline than below it, and young RC plants (<2 m tall) were at higher density above treeline than below. AS shows little evidence of a position change from the historic treeline, with a sudden extreme drop in density above treeline compared to below. Recruitment, as measured by size–class distribution, was greater above treeline than below for both species but AS is confined to ~25 m above treeline whereas RC is luxuriantly growing up to 200 m above treeline. Synthesis . Evidence suggests that the elevational limits of RC have shifted upward both because (a) young plants above treeline benefited from facilitation of recruitment by surrounding vegetation, allowing upward expansion of recruitment, and (b) temperature amelioration to mature plants increased adult survival. We predict that the current pure stand of RC growing above treeline will be colonized by AS that will, in turn, outshade and eventually relegate RC to be a minor component of the community, as is the current situation below the treeline.

54 ENVIRONMENTAL SCIENCES↗