Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Shape function”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47

VRC34-Antibody Lineage Development Reveals How a Required Rare Mutation Shapes the Maturation of a Broad HIV-Neutralizing Lineage

Rare mutations have been proposed to restrict the development of broadly neutralizing antibodies against HIV-1, but this has not been explicitly demonstrated. We hypothesized that such rare mutations might be identified by comparing broadly neutralizing and non-broadly neutralizing branches of an antibody-developmental tree. Because sequences of antibodies isolated from the fusion peptide (FP)-targeting VRC34-antibody lineage suggested it might be suitable for such rare mutation analysis, we carried out next-generation sequencing (NGS) on B cell transcripts from donor N123, the source of the VRC34 lineage, and functionally and structurally characterized inferred intermediates along broadly neutralizing and poorly neutralizing developmental branches. The broadly neutralizing VRC34.01 branch required the rare heavy-chain mutation Y33P to bind FP, whereas the early bifurcated VRC34.05 branch did not require this rare mutation and evolved less breadth. Our results demonstrate how a required rare mutation can restrict development and shape the maturation of a broad HIV-1-neutralizing antibody lineage.

59 BASIC BIOLOGICAL SCIENCES↗

The effect of elastic strains on the adsorption energy of H, O, and OH in transition metals

The influence of elastic strains on the adsorption of H, O, and OH on the (111) surfaces of 8 fcc (Ni, Cu, Pd, Ag, Pt, Au, Rh, Ir) and on the (0001) surfaces of 3 hcp (Co, Zn, Cd) transition metals was analyzed by means of density functional theory calculations. To this end, surface slabs were subjected to different strain states (uniaxial, biaxial, shear, and a combination of them) up to strains dictated by the mechanical stability limits indicated by phonon calculations. It was found that the adsorption energy followed the predictions of the d-band theory but – surprisingly – the variations in the adsorption energy only depended on the area of the adsorption hole and not on the particular elastic strain tensor applied to achieve this area. The analysis of the electronic structure showed that the applied strains did not modify the shape of the Projected Density of States (PDOS) of the d-orbitals of the transition metals but only led to a shift in the energy levels. Moreover, the presence of the adsorbates on the surfaces led to negligible changes in the PDOS. Thus, the adsorption energies were a function of the Fermi energy which in turn was associated with the change of the area of the adsorption through a general linear law that was valid for all metals. Furthermore, the information in this paper allows the immediate and accurate estimation of the effect of any elastic strain on the adsorption energies of H, O, and OH in 11 transition metals with more than half-filled d-orbitals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗

Linking the Dynamic Response of the Carbon Dioxide-Concentrating Mechanism to Carbon Assimilation Behavior in Fremyella diplosiphon

ABSTRACT Cyanobacteria use a carbon dioxide (CO 2 )-concentrating mechanism (CCM) that enhances their carbon fixation efficiency and is regulated by many environmental factors that impact photosynthesis, including carbon availability, light levels, and nutrient access. Efforts to connect the regulation of the CCM by these factors to functional effects on carbon assimilation rates have been complicated by the aqueous nature of cyanobacteria. Here, we describe the use of cyanobacteria in a semiwet state on glass fiber filtration discs—cyanobacterial discs—to establish dynamic carbon assimilation behavior using gas exchange analysis. In combination with quantitative PCR (qPCR) and transmission electron microscopy (TEM) analyses, we linked the regulation of CCM components to corresponding carbon assimilation behavior in the freshwater, filamentous cyanobacterium Fremyella diplosiphon . Inorganic carbon (C i ) levels, light quantity, and light quality have all been shown to influence carbon assimilation behavior in F. diplosiphon . Our results suggest a biphasic model of cyanobacterial carbon fixation. While behavior at low levels of CO 2 is driven mainly by the C i uptake ability of the cyanobacterium, at higher CO 2 levels, carbon assimilation behavior is multifaceted and depends on C i availability, carboxysome morphology, linear electron flow, and cell shape. Carbon response curves (CRCs) generated via gas exchange analysis enable rapid examination of CO 2 assimilation behavior in cyanobacteria and can be used for cells grown under distinct conditions to provide insight into how CO 2 assimilation correlates with the regulation of critical cellular functions, such as the environmental control of the CCM and downstream photosynthetic capacity. IMPORTANCE Environmental regulation of photosynthesis in cyanobacteria enhances organismal fitness, light capture, and associated carbon fixation under dynamic conditions. Concentration of carbon dioxide (CO 2 ) near the carbon-fixing enzyme RubisCO occurs via the CO 2 -concentrating mechanism (CCM). The CCM is also tuned in response to carbon availability, light quality or levels, or nutrient access—cues that also impact photosynthesis. We adapted dynamic gas exchange methods generally used with plants to investigate environmental regulation of the CCM and carbon fixation capacity using glass fiber-filtered cells of the cyanobacterium Fremyella diplosiphon . We describe a breakthrough in measuring real-time carbon uptake and associated assimilation capacity for cells grown in distinct conditions (i.e., light quality, light quantity, or carbon status). These measurements demonstrate that the CCM modulates carbon uptake and assimilation under low-C i conditions and that light-dependent regulation of pigmentation, cell shape, and downstream stages of carbon fixation are critical for tuning carbon uptake and assimilation.

59 BASIC BIOLOGICAL SCIENCES↗

Stochastic and deterministic processes shape bioenergy crop microbiomes along a vertical soil niche

Abstract Sustainable biofuel cropping systems aim to address climate change while meeting energy needs. Understanding how soil and plant‐associated microbes respond to these different cropping systems is key to promoting agriculture sustainability and evaluating changes in ecosystem functions. Here, we leverage a long‐term biofuel cropping system field experiment to dissect soil and root microbiome changes across a soil‐depth gradient in poplar, restored prairie and switchgrass to understand their effects on the microbial communities. High throughput amplicon sequencing of the fungal internal transcribed spacer (ITS) and prokaryotic 16S DNA regions showed a common trend of root and soil microbial community richness decreasing and evenness increasing with depth. Ecological niche (root vs. soil) had the strongest effect on community structure, followed by depth, then crop. Stochastic processes dominated the structuring of fungal communities in deeper soil layers while operational taxonomic units (OTUs) in surface soil layers were more likely to co‐occur and to be enriched by plant hosts. Prokaryotic communities were dispersal limited at deeper depths. Microbial networks showed a higher density, connectedness, average degree and module size in deeper soils. We observed a decrease in fungal‐fungal links and an increase of bacteria–bacteria links with increasing depth in all crops, particularly in the root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

Probing the state of hydrogen in δ − AlOOH at mantle conditions with machine learning potential

Hydrous and nominally anhydrous minerals are a fundamental class of solids of enormous significance to geophysics. They are the water carriers in the deep geological water cycle and impact structural, elastic, plastic, and thermodynamic properties and phase relations in Earth's forming aggregates (rocks). They play a critical role in the geochemical and geophysical processes that shape the planet. Their complexity has prevented predictive calculations of their properties, but progress in materials simulations ushered by machine-learning potentials is transforming this state of affairs. Here, we adopt a hybrid approach that combines deep learning potentials (DPs) with the strongly constrained and appropriately normed meta-generalized gradient approximation functional to simulate a prototypical hydrous system. We illustrate the success of this approach to simulate δ − AlOOH ( δ ) , a phase capable of transporting water down to near the core-mantle boundary of the Earth ( ∼ 2900 km depth and ∼ 135 GPa ) in subducting slabs. A high-throughput sampling of phase space using molecular dynamics simulations with DPs sheds light on the hydrogen-bond behavior and proton diffusion at geophysical conditions. These simulations provide a pathway for a deeper understanding of these crucial components that shape Earth's internal state. Published by the American Physical Society 2024

Luo, Chenxing (ORCID:0000000341166851)↗

Experimental Fabrication of Porous Additive Manufactured Material

Nuclear industries can benefit from materials that can perform well mechanically and thermally in high temperature and corrosion environments. Functionally graded materials (FGM) are materials manufactured with complex spatial, structural, and chemical compositions, creating components predesigned with tailored microstructural and mechanical properties. Porosity-graded FGMs are designed to introduce pores into a component’s structure as a mechanism to increase bulk or surface material performance, such as stress accommodation and negative thermal conductivity. Additive manufacturing (AM) techniques such as laser energy net shape (LENS) and wire arc additive manufacturing (WAAM), excel in high energy density, point-to-point metal deposition, and present in combination with other combinatorial approaches, exciting methods to manufacture porous FGM components. This project is also examining plasma jet printing as another means for method evaluations for smaller scale graded components. This study explores AM FGM process parameters and combinatorial fabrication methodologies for stainless steel components functionally graded in porosity levels. Preliminary characterization results are provided to attest the feasibility of the combinational fabrication techniques.

36 MATERIALS SCIENCE↗

4D Printing of Stretchable Supercapacitors via Hybrid Composite Materials

Stretchable supercapacitors (SCs) have attracted significant attention in developing power-independent stretchable electronic systems due to their intrinsic energy storage function and unique mechanical properties. Most current SCs are generally limited by their low stretchability, complicated fabrication process, and insufficient performance and robustness. This study presents a facile method to fabricate arbitrary-shaped stretchable electrodes via 4D printing of conductive composite from reduced graphene oxide, carbon nanotube, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate. The electrode patterns of an arbitrary shape can be deposited onto prestretched substrates by aerosol-jet printing, then self-organized origami (ridge) patterns are generated after releasing the substrates from holding stretchers due to the mismatched strains. The stretchable electrodes demonstrate superior mechanical robustness and stretchability without sacrificing its outstanding electrochemical performance. The symmetric SC prototype possesses a gravimetric capacitance of ≈21.7 F g -1 at a current density of 0.5 A g -1 and a capacitance retention of ≈85.8% from 0.5 to 5 A g -1 . A SC array with arbitrary-shaped electrodes is also fabricated and connected in series to power light-emitting diode patterns for large-scale applications. Finally, the proposed method paves avenues for scalable manufacturing of future energy-storage devices with controlled extensibility and high electrochemical performance.

36 MATERIALS SCIENCE↗

Integrating Reservoirs into the Dissolved Organic Matter Versus Primary Production Paradigm: How Does Chlorophyll-$a$ Change Across Dissolved Organic Carbon Concentrations in Reservoirs?

Primary production in freshwater ecosystems is largely a function of light and nutrient availability, both of which have been changing in many lakes and reservoirs in response to anthropogenic pressures. Recent studies focusing on natural lakes have found a hump-shaped response of primary production (sometimes measured as chlorophyll-$a$) to dissolved organic matter (DOM, measured as dissolved organic carbon, DOC), which has both light-absorbing chromophoric properties and DOM-bound nutrients. We used the United States National Lakes Assessment dataset to integrate reservoirs into this paradigm in comparison with natural lakes and assessed the relative differences in the predicted response’s model structure, regression parameter values, and drivers of the chlorophyll-$a$ residuals. We found that chlorophyll-$a$ in reservoirs exhibited a hump-shaped response to DOC, while natural lakes from this dataset were better fit with a linear response, differing from previous studies focused on boreal lakes. Despite this, reservoirs had a greater maximum chlorophyll-a response compared to natural lakes in this study (45.5 versus 33.8 μg L -1 ), which occurred at a lower DOC concentration threshold (18.3 versus 26.4 mg L -1 ) when compared using quadratic models. Reservoirs had lower median light:nutrient values compared to natural lakes, and greater median surface area and total phosphorus (TP), that can all influence the light environment and the peak chlorophyll-a responses. In both reservoirs and natural lakes, chlorophyll-$a$ residuals were most strongly influenced by TP, where TP < 25-30 µg L -1 suppressed chlorophyll-a residuals and higher TP amplified them. Light:nutrient values were somewhat important predictors, and patterns with chlorophyll-$a$ residuals supported previous work showing low light:nutrient values amplified chlorophyll-$a$ responses and higher values suppressed them. In conclusion, quantifying the shape of the response of primary production to DOM quantity and quality as well as the drivers of the residuals, namely TP for lakes and reservoirs in this dataset, will be important for understanding the effects that changes in water quality may have on primary production and freshwater ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗

Symmetry breaking during low-temperature domain formation in micron-sized magnetite crystals

We report the results of synchrotron Bragg Coherent x-ray Diffraction Imaging (BCDI) experiments to investigate domain formation in a micron-sized magnetite crystal undergoing the Verwey transition at low temperature. A strong splitting of the measured 311 Bragg reflection was observed in the low-temperature phase, indicating the formation of domains. BCDI revealed pronounced strain distributions, characterized by a clear layered stripe domain structure in real-space. Stripes were seen only along the [001] crystallographic direction, normal to the substrate surface direction, breaking the symmetry of the cubic high-temperature phase. It is argued that other domain directions were suppressed by the sample mounting orientation. More surprisingly, only a single domain orientation was observed, suggesting an additional symmetry-breaking influence originating from the shape of the crystal. Gaining insight into how thermal effects induce the formation of layered or striped phases offers a valuable framework for understanding the development of mesoscopic domains and strain patterns in functional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Determination of physically based pseudo-Voigt powder diffraction profile terms from the fundamental parameters approach

In this study, a methodology is developed where a fundamental parameters approach (FPA) description of a laboratory powder diffraction instrument (configured in divergent-beam Bragg–Brentano geometry) is used to determine GSAS-II profile parameters for peak asymmetry and instrumental peak widths. This allows the instrumental contribution to peak shapes to be robustly determined directly from a physical description of the instrument, even though GSAS-II does not directly implement FPA for peak shape computation. The FPA-derived parameters can be used as the starting point for instrument characterization, or to characterize sample broadening without the use of a standard to determine the instrument profile function. This new method can facilitate generation of training sets for machine learning. A plot is generated that shows the differences between the two approaches, demonstrating upper bounds for the accuracy of the GSAS-II profile model for a particular instrumental configuration.

47 OTHER INSTRUMENTATION↗

Sensitivity calibration of a Carestream HPX-1 image plate scanner

There is a need to measure the sensitivity of the image plate scanners used to scan Z shot data. The Carestream HPX-1 image plate scanner was tested, and its performance was characterized to determine the system sensitivity in terms of signal per incident photon as a function of x-ray energy. A Manson source was used to simultaneously expose an Amptek x-ray multi-channel analyzer and image plates, allowing for a comparison of the counts as a function of energy to the signal recorded on the image plates. NIST-certified radioactive sources were used to assign an absolute sensitivity. Results indicate that the HPX-1 scanner response matches the shape of the modeled response, allowing for absolute scaling using NIST-certified radioisotope sources. The HPX-1 scanner shows a stable response with measurements taken over one week. In contrast, the sensitivity of the DITABIS scanner was characterized using the same approach, but it exhibits changes in its response that varied by more than 50% over the span of 4 days.

42 ENGINEERING↗

Open library of g-functions for 34,321 configurations

Thermal response functions, known as g-functions, are commonly used in ground heat exchanger design tools and whole building energy simulation programs to simulate the ground heat exchanger performance. Calculation of g-functions can be quite computationally time-consuming, particularly as the number of boreholes gets large. However, once the g-function is computed, the actual simulation time can be quite short, particularly if a hybrid time-step (Cullin and Spitler 2011) approach is used. Because of this, pre-computed g-function libraries are commonly used in design tools and building simulation tools. This paper describes development of a new, publicly available library containing g-functions for 34,321 borehole field configurations; for each configuration, gfunctions are provided for 5 depths to allow interpolation between different borehole-to-height ratios. The available configurations include configurations in standard shapes: lines, rectangles, open rectangles, L-shapes, and U-shapes. It also includes new configurations: C-shapes, lopsided-U-shapes, and zoned rectangles, which are rectangular configurations with different interior and perimeter spacing of the boreholes.

Spitler, Jeffery↗

Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural characterization of strawberry pomace

Strawberries are a nutrient dense food rich in vitamins, minerals, non-nutrient antioxidant phenolics, and fibers. Strawberry fiber bioactive structures are not well characterized and limited information is available about the interaction between strawberry fiber and phenolics. Therefore, we analyzed commercial strawberry pomace in order to provide a detailed carbohydrate structural characterization, and to associate structures with functions. The pomace fraction, which remained after strawberry commercial juice extraction, contained mostly insoluble (49.1 % vs. 5.6 % soluble dietary fiber) dietary fiber, with pectin, xyloglucan, xylan, β-glucan and glucomannan polysaccharides; glucose, fructose, xylose, arabinose, galactose, fucose and galacturonic acid free carbohydrates; protein (15.6 %), fat (8.34 %), and pelargonidin 3-glucoside (562 μg/g). Oligosaccharides from fucogalacto-xyloglucan, methyl-esterified rhamnogalacturonan I with branched arabinogalacto-side chains, rhamnogalacturonan II, homogalacturonan and β-glucan were detected by MALDI-TOF MS, NMR and glycosyl-linkage analysis. Previous reports suggest that these oligosaccharide and polysaccharide structures have prebiotic, bacterial pathogen anti-adhesion, and cholesterol-lowering activity, while anthocyanins are well-known antioxidants. A strawberry pomace microwave acid-extracted (10 min, 80 °C) fraction had high molar mass (2376 kDa) and viscosity (3.75 dL/g), with an extended rod shape. A random coil shape, that was reported previously to bind to phenolic compounds, was observed for other strawberry microwave-extracted fractions. These strawberry fiber structural details suggest that they can thicken foods, while the polysaccharide and polyphenol interaction indicates great potential as a multiple-function bioactive food ingredient important for gut and metabolic health.

59 BASIC BIOLOGICAL SCIENCES↗

A comparison of strategies for state-selective coherent Raman excitation

Here we report on the theoretical and experimental evaluation of state-selective bond activation for coherent Raman spectroscopy and control of chemical reactivity. We compare six different strategies for state-selective activation using shaped broadband femtosecond laser pulses. Results for a pair of long pulses with different wavelengths are also considered. For each of these approaches, we report on their theoretical and experimental ability to excite a desired vibrational mode while minimizing excitation of other modes including harmonics. We find that the double parabola spectral phase function gives the most intense Raman excitation with 10 cm -1 selectivity with the lowest background. The sinusoidal phase function produces intense Raman excitation with high selectivity but gives a series of harmonic excitations which could hinder selectivity. Implications of this study on several fields ranging from sensing, to controlling chemical reactions, and selective excited state excitation by X-ray pulses are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗