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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2021

Platinum Deposited Nitrogen-Doped Vertically Aligned Carbon Nanofibers as Methanol Tolerant Catalyst for Oxygen Reduction Reaction with Improved Durability

Nitrogen doping in carbon materials can modify the employed carbon material’s electronic and structural properties, which helps in creating a stronger metal-support interaction. In this study, the role of nitrogen doping in improving the durability of Pt catalysts supported on a three-dimensional vertically aligned carbon nanofiber (VACNF) array towards oxygen reduction reaction (ORR) was explored. The nitrogen moieties present in the N-VACNF enhanced the metal-support interaction and contributed to a reduction in the Pt particle size from 3.1 nm to 2.3 nm. The Pt/N-VACNF catalyst showed better durability when compared to Pt/VACNF and Pt/C catalysts with similar Pt loading. DFT calculations validated the increase in the durability of the Pt NPs with an increase in pyridinic N and corroborated the molecular ORR pathway for Pt/N-VACNF. Moreover, the Pt/N-VACNF catalyst was found to have excellent tolerance towards methanol crossover.

Elangovan, Ayyappan↗
DOE OSTI2021

Granulibacter bethesdensis, a Pathogen from Patients with Chronic Granulomatous Disease, Produces a Penta-Acylated Hypostimulatory Glycero-D-talo-oct-2-ulosonic Acid–Lipid A Glycolipid (Ko-Lipid A)

Granulibacter bethesdensis can infect patients with chronic granulomatous disease, an immunodeficiency caused by reduced phagocyte NADPH oxidase function. Intact G. bethesdensis (Gb) is hypostimulatory compared to Escherichia coli, i.e., cytokine production in human blood requires 10–100 times more G. bethesdensis CFU/mL than E. coli. To better understand the pathogenicity of G. bethesdensis, we isolated its lipopolysaccharide (GbLPS) and characterized its lipid A. Unlike with typical Enterobacteriaceae, the release of presumptive Gb lipid A from its LPS required a strong acid. NMR and mass spectrometry demonstrated that the carbohydrate portion of the isolated glycolipid consists of α-Manp-(1→4)-β-GlcpN3N-(1→6)-α-GlcpN-(1⇿1)-α-GlcpA tetra-saccharide substituted with five acyl chains: the amide-linked N-3′ 14:0(3-OH), N-2′ 16:0(3-O16:0), and N-2 18:0(3-OH) and the ester-linked O-3 14:0(3-OH) and 16:0. The identification of glycero-d-talo-oct-2-ulosonic acid (Ko) as the first constituent of the core region of the LPS that is covalently attached to GlcpN3N of the lipid backbone may account for the acid resistance of GbLPS. In addition, the presence of Ko and only five acyl chains may explain the >10-fold lower proinflammatory potency of GbKo–lipidA compared to E. coli lipid A, as measured by cytokine induction in human blood. These unusual structural properties of the G.bethesdensis Ko–lipid A glycolipid likely contribute to immune evasion during pathogenesis and resistance to antimicrobial peptides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗
DOE OSTI2025

Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning

Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.

Naghshnejad, Pegah [Department of Chemical Enginee↗
DOE OSTI2020

Comparing Zwitterionic and PEG Exteriors of Polyelectrolyte Complex Micelles

A series of model polyelectrolyte complex micelles (PCMs) was prepared to investigate the consequences of neutral and zwitterionic chemistries and distinct charged cores on the size and stability of nanocarriers. Using aqueous reversible addition-fragmentation chain transfer (RAFT) polymerization, we synthesized a well-defined diblock polyelectrolyte system, poly(2-methacryloyloxyethyl phosphorylcholine methacrylate)-block-poly((vinylbenzyl) trimethylammonium) (PMPC-PVBTMA), at various neutral and charged block lengths to compare directly against PCM structure–property relationships centered on poly(ethylene glycol)-block-poly((vinylbenzyl) trimethylammonium) (PEG-PVBTMA) and poly(ethylene glycol)-block-poly(l-lysine) (PEG-PLK). After complexation with a common polyanion, poly(sodium acrylate), the resulting PCMs were characterized by dynamic light scattering (DLS) and small angle X-ray scattering (SAXS). We observed uniform assemblies of spherical micelles with a diameter ~1.5–2× larger when PMPC-PVBTMA was used compared to PEG-PLK and PEG-PVBTMA via SAXS and DLS. In addition, PEG-PLK PCMs proved most resistant to dissolution by both monovalent and divalent salt, followed by PEG-PVBTMA then PMPC-PVBTMA. All micelle systems were serum stable in 100% fetal bovine serum over the course of 8 h by time-resolved DLS, demonstrating minimal interactions with serum proteins and potential as in vivo drug delivery vehicles. This thorough study of the synthesis, assembly, and characterization of zwitterionic polymers in PCMs advances the design space for charge-driven micelle assemblies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring pH Dynamics in Amino Acid Solutions Under Low-Temperature Plasma Exposure

Low-temperature plasma (LTP) offers a promising alternative for cancer therapy, as it targets malignant cells selectively while minimizing damage to healthy tissues. Upon interaction with an aqueous solution, LTP generates reactive oxygen and nitrogen species and thereby influences the solution’s pH, which is a crucial factor in cancer proliferation and response to treatment. This study investigated the effects of LTP on the pH of aqueous solutions, with a focus on the effect of LTP parameters such as voltage, frequency, and irradiation time. In addition, it explored the influence of solution composition, specifically the presence of the amino acids, glycine and serine, on pH changes; these amino acids are known to play significant roles in cancer proliferation. Our results indicated that LTP induces acidification in deionized water, in which the extent of acidification increased proportionally with plasma parameters. In glycine-containing solutions, pH changes were concentration-dependent, whereas serine-containing solutions maintained a constant pH across all tested concentrations. To investigate potential changes to the structural properties of glycine and serine exposed to LTP that could be responsible for different pH responses, we analyzed the samples using FTIR spectroscopy. A significant decrease in absorbance was observed for solutions with low concentrations of amino acids, suggesting their degradation.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Light-Driven Charge Transport and Optical Sensing in Molecular Junctions

Probing charge and energy transport in molecular junctions (MJs) has not only enabled a fundamental understanding of quantum transport at the atomic and molecular scale, but it also holds significant promise for the development of molecular-scale electronic devices. Recent years have witnessed a rapidly growing interest in understanding light-matter interactions in illuminated MJs. These studies have profoundly deepened our knowledge of the structure–property relations of various molecular materials and paved critical pathways towards utilizing single molecules in future optoelectronics applications. In this article, we survey recent progress in investigating light-driven charge transport in MJs, including junctions composed of a single molecule and self-assembled monolayers (SAMs) of molecules, and new opportunities in optical sensing at the single-molecule level. We focus our attention on describing the experimental design, key phenomena, and the underlying mechanisms. Specifically, topics presented include light-assisted charge transport, photoswitch, and photoemission in MJs. Emerging Raman sensing in MJs is also discussed. Finally, outstanding challenges are explored, and future perspectives in the field are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MXene-Based Porous Monoliths

In the past decade, a thriving family of 2D nanomaterials, transition-metal carbides/nitrides (MXenes), have garnered tremendous interest due to its intriguing physical/chemical properties, structural features, and versatile functionality. Integrating these 2D nanosheets into 3D monoliths offers an exciting and powerful platform for translating their fundamental advantages into practical applications. Introducing internal pores, such as isotropic pores and aligned channels, within the monoliths can not only address the restacking of MXenes, but also afford a series of novel and, in some cases, unique structural merits to advance the utility of the MXene-based materials. Here, a brief overview of the development of MXene-based porous monoliths, in terms of the types of microstructures, is provided, focusing on the pore design and how the porous microstructure affects the application performance.

2D nanomaterials↗
DOE OSTI2024

Progress and Application of Halide Perovskite Materials for Solar Cells and Light Emitting Devices

Halide perovskite materials have attracted worldwide attention in the photovoltaic area due to the rapid improvement in efficiency, from less than 4% in 2009 to 26.1% in 2023 with only a nanometer lever photo-active layer. Meanwhile, this nova star found applications in many other areas, such as light emitting, sensor, etc. This review started with the fundamentals of physics and chemistry behind the excellent performance of halide perovskite materials for photovoltaic/light emitting and the methods for preparing them. Then, it described the basic principles for solar cells and light emitting devices. It summarized the strategies including nanotechnology to improve the performance and the application of halide perovskite materials in these two areas: from structure–property relation to how each component in the devices affects the overall performance. Moreover, this review listed the challenges for the future applications of halide perovskite materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Theoretical Calculation Study of Nanomaterials

In recent years, theoretical simulations using computational physics and chemistry models have been used widely to predict the physical, chemical, and structural properties of nanomaterials. To reflect such rapid progress, two Special Issues on the theoretical study of nanomaterials were published. The 36 articles collected cover broad re-search fields and applications. In this Editorial, we provide an overview of these pub-lications and summarize the main findings. Based on these research outcomes, we lay out some future research directions.

First-principles calculations↗
DOE OSTI2024

Plant Cell Wall Polysaccharide O-Acetyltransferases

Plant cell walls are largely composed of polysaccharide polymers, including cellulose, hemicelluloses (xyloglucan, xylan, mannan, and mixed-linkage β-1,3/1,4-glucan), and pectins. Among these cell wall polysaccharides, xyloglucan, xylan, mannan, and pectins are often O-acetylated, and polysaccharide O-acetylation plays important roles in cell wall assembly and disease resistance. Genetic and biochemical analyses have implicated the involvement of three groups of proteins in plant cell wall polysaccharide O-acetylation: trichome birefringence-like (TBL)/domain of unknown function 231 (DUF231), reduced wall acetylation (RWA), and altered xyloglucan 9 (AXY9). Although the exact roles of RWAs and AXY9 are yet to be identified, members of the TBL/DUF231 family have been found to be O-acetyltransferases responsible for the O-acetylation of xyloglucan, xylan, mannan, and pectins. Here, we provide a comprehensive overview of the occurrence of O-acetylated cell wall polysaccharides, the biochemical properties, structural features, and evolution of cell wall polysaccharide O-acetyltransferases, and the potential biotechnological applications of manipulations of cell wall polysaccharide acetylation. Further in-depth studies of the biochemical mechanisms of cell wall polysaccharide O-acetylation will not only enrich our understanding of cell wall biology, but also have important implications in engineering plants with increased disease resistance and reduced recalcitrance for biofuel production.

Plant Sciences↗
DOE OSTI2022

Predicting the Mechanical Response of Polyhydroxyalkanoate Biopolymers Using Molecular Dynamics Simulations

Polyhydroxyalkanoates (PHAs) have emerged as a promising class of biosynthesizable, biocompatible, and biodegradable polymers to replace petroleum-based plastics for addressing the global plastic pollution problem. Although PHAs offer a wide range of chemical diversity, the structure–property relationships in this class of polymers remain poorly established. In particular, the available experimental data on the mechanical properties is scarce. In this contribution, we have used molecular dynamics simulations employing a recently developed forcefield to predict chemical trends in mechanical properties of PHAs. Specifically, we make predictions for Young’s modulus, and yield stress for a wide range of PHAs that exhibit varying lengths of backbone and side chains as well as different side chain functional groups. Deformation simulations were performed at six different strain rates and six different temperatures to elucidate their influence on the mechanical properties. Our results indicate that Young’s modulus and yield stress decrease systematically with increase in the number of carbon atoms in the side chain as well as in the polymer backbone. In addition, we find that the mechanical properties were strongly correlated with the chemical nature of the functional group. The functional groups that enhance the interchain interactions lead to an enhancement in both the Young’s modulus and yield stress. Finally, we applied the developed methodology to study composition-dependence of the mechanical properties for a selected set of binary and ternary copolymers. Overall, our work not only provides insights into rational design rules for tailoring mechanical properties in PHAs, but also opens up avenues for future high throughput atomistic simulation studies geared towards identifying functional PHA polymer candidates for targeted applications.

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

Spatial Decorrelation of Young Stars and Dense Gas as a Probe of the Star Formation–Feedback Cycle in Galaxies

The spatial decorrelation of dense molecular gas and young stars observed on ≲1 kpc scales in nearby galaxies indicates rapid dispersal of star-forming regions by stellar feedback. In this work, we explore the sensitivity of this decorrelation to different processes controlling the structure of the interstellar medium, the abundance of molecular gas, star formation, and feedback in a suite of simulations of an isolated dwarf galaxy with structural properties similar to NGC 300 that self-consistently model radiative transfer and molecular chemistry. Our fiducial simulation reproduces the magnitude of decorrelation and its scale dependence measured in NGC 300, and we show that this agreement is due to different aspects of feedback, including H 2 dissociation, gas heating by the locally variable UV field, early mechanical feedback, and supernovae. In particular, early radiative and mechanical feedback affects the correlation on ≲100 pc scales, while supernovae play a significant role on ≳ 100 pc scales. The correlation is also sensitive to the choice of the local star formation efficiency per free fall time, ϵ ff , which provides a strong observational constraint on ϵ ff when the global star formation rate is independent of its value. Finally, we explicitly show that the degree of correlation between the peaks of molecular gas and star formation density is directly related to the distribution of the lifetimes of star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Compact Structures of Massive z ~ 0.7 Post-starburst Galaxies in the ${\bf{SQuIGG}}\vec{{\boldsymbol{L}}}{\bf{E}}$ Sample

We present structural measurements of 145 spectroscopically selected intermediate-redshift (z ~ 0.7), massive (M $\star$ ~ 10 11 M ⊙ ) post-starburst galaxies from the ${\bf{SQuIGG}}\vec{{\boldsymbol{L}}}{\bf{E}}$ sample measured using wide-depth Hyper Suprime-Cam i-band imaging. This deep imaging allows us to probe the sizes and structures of these galaxies, which we compare to a control sample of star-forming and quiescent galaxies drawn from the LEGA-C Survey. We find that post-starburst galaxies systematically lie ~0.1 dex below the quiescent mass–size (half-light radius) relation, with a scatter of ~0.2 dex. This finding is bolstered by nonparametric measures, such as the Gini coefficient and the concentration, which also reveal these galaxies to have more compact light profiles than both quiescent and star-forming populations at similar mass and redshift. The sizes of post-starburst galaxies show either negative or no correlation with the time since quenching, such that more recently quenched galaxies are larger or similarly sized. This empirical finding disfavors the formation of post-starburst galaxies via a purely central burst of star formation that simultaneously shrinks the galaxy and shuts off star formation. We show that the central densities of post-starburst and quiescent galaxies at this epoch are very similar, in contrast with their effective radii. The structural properties of z ~ 0.7 post-starburst galaxies match those of quiescent galaxies that formed in the early universe, suggesting that rapid quenching in the present epoch is driven by a similar mechanism to the one at high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Hubble Space Telescope Imaging of Three Isolated Faint Dwarf Galaxies beyond the Local Group: Pavo, Corvus A, and Kamino

We present new Hubble Space Telescope (HST) imaging of three recently discovered star-forming dwarf galaxies beyond the Local Group: Pavo, Corvus A, and Kamino. The discovery of Kamino is reported here for the first time. They rank among the most isolated faint dwarf galaxies known; hence they provide unique opportunities to study galaxy evolution at the smallest scales, free from the environmental effects of more massive galaxies. Our HST data reach ∼2–4 magnitudes below the tip of the red giant branch (TRGB) for each dwarf, allowing us to measure their distances, structural properties, and recent star formation histories (SFHs). All three galaxies contain a complex stellar population of young and old stars, and are typical of field galaxies in this mass regime (M V = −10.62 ± 0.08 and $D = 2.16_{-0.07}^{+0.08}$ Mpc for Pavo, M V = −10.91 ± 0.10 and D = 3.34 ± 0.11 Mpc for Corvus A, and M V = −12.02 ± 0.12 and $D = 6.50_{-0.11}^{+0.15}$ Mpc for Kamino). Our HST-derived SFHs reveal differences among the three dwarfs: Pavo and Kamino show relatively steady, continuous star formation, while Corvus A formed ∼60% of its stellar mass by 10 Gyr ago. These results align with theoretical predictions of diverse evolutionary pathways for isolated low-mass galaxies.

Mutlu-Pakdil, Burçin [Dartmouth College, Hanover, ↗
DOE OSTI2023

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗