Search NASA⌕ Search

SEARCH · Search NASA

Results for “Describing 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 181 records · Page 10

Soybean ( Glycine max ) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics

Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.

54 ENVIRONMENTAL SCIENCES↗

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗

Challenges in studying water fluxes within the soil-plant-atmosphere continuum: A tracer-based perspective on pathways to progress

Tracing and quantifying water fluxes in the hydrological cycle is crucial for understanding the current state of ecohydrological systems and their vulnerability to environmental change. Especially the interface between ecosystems and the atmosphere that is strongly mediated by plants is important to meaningfully describe ecohydrological system functioning. Many of the dynamic interactions generated by water fluxes between soil, plant and the atmosphere are not well understood, which is partly due to a lack of interdisciplinary research. This opinion paper reflects the outcome of a discussion among hydrologists, plant ecophysiologists and soil scientists on open questions and new opportunities for collaborative research on the topic "water fluxes in the soil-plant-atmosphere continuum" especially focusing on environmental and artificial tracers. We emphasize the need for a multi-scale experimental approach, where a hypothesis is tested at multiple spatial scales and under diverse environmental conditions to better describe the small-scale processes (i.e., causes) that lead to large-scale patterns of ecosystem functioning (i.e., consequences). Novel in-situ, high-frequency measurement techniques offer the opportunity to sample data at a high spatial and temporal resolution needed to understand the underlying processes. Here we advocate for a combination of long-term natural abundance measurements and event-based approaches. Multiple environmental and artificial tracers, such as stable isotopes, and a suite of experimental and analytical approaches should be combined to complement information gained by different methods. Virtual experiments using process-based models should be used to inform sampling campaigns and field experiments, e.g., to improve experimental designs and to simulate experimental outcomes. On the other hand, experimental data are a pre-requisite to improve our currently incomplete models. Interdisciplinary collaboration will help to overcome research gaps that overlap across different earth system science fields and help to generate a more holistic view of water fluxes between soil, plant and atmosphere in diverse ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Conversion of Syngas and CO2 to Light Olefins using Multi-Functional Catalysts

This report describes our effort in developing a novel zeolite encapsulated metal nanoparticle catalyst for the conversion of syngas to light olefins. We have adopted a ligand assisted synthesis protocol in which first metal-amine was prepared using metal salts and suitable amine ligands. The stable metal-amine complex thus prepared was then used as the seed for the growth of zeolite in alkaline solution. We have optimized the synthesis condition as well as different amine ligand to identify the condition to obtain stable metal-amine complex. Upon synthesis of zeolite, metal particles are encapsulated inside the zeolite in a confined space. We have synthesized both Fe and Co catalyst inside silicalite and chabazite zeolite. Catalytic activity of these catalysts were evaluated for syngas conversion reaction and compared with a baseline catalyst. The activity trend of zeolite encapsulated catalyst show very different activity trend compared to the baseline catalyst. While a distribution of products with different carbon number was obtained with baseline catalyst, zeolite encapsulated catalyst show ethylene as the major product. While ~73% selectivity to C 2 -C 6 products were obtained with cahabazite encapsulated Fe catalyst, only 53% selectivity was obtained for the corresponding products with silica-alumina supported Fe catalyst. Not only higher selectivity, Fe-chabazite also produces only C 2 products (ethylene/ethane) while a distribution of products was obtained with Fe-SiAl catalyst. The significantly different reactivity associated with the chabazite encapsulated Fe catalyst was attributed to the confinement effect. We hypothesized that due to the small size of the pore, only ethylene was obtained as the product.

10 SYNTHETIC FUELS↗

Conversion of Syngas to Light Olefins and Oxygenates using Multi-Functional Catalysts

This report describes our effort in developing catalysts for the conversion of syngas to light olefins and oxygenates. We have developed a series of metal/zeolite catalysts and tested their activity towards the conversion of syngas to light olefins. Light olefins produced in our case mostly comprised of C 2 /C 3 . A series of multimetallic catalyst also synthesized and their performance was evaluated for the conversion of syngas to the production of oxygenates. In case of oxygenates, our specific focus was to maximize the selectivity of C 2+ oxygenates which is a precursor for fuel or can be used as high value chemicals. In this direction, we have identified several Rh based catalysts that are specifically shows superior activity towards oxygenates formation.

10 SYNTHETIC FUELS↗

A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations

The accuracy and effectiveness of Hermite spectral methods for the numerical discretization of partial differential equations on unbounded domains are strongly affected by the amplitude of the Gaussian weight function employed to describe the approximation space. This is particularly true if the problem is under-resolved, i.e., there are no enough degrees of freedom. The issue becomes even more crucial when the equation under study is time-dependent, forcing in this way the choice of Hermite functions where the corresponding weight depends on time. In order to adapt dynamically the approximation space, it is here proposed an automatic decision-making process that relies on machine learning techniques, such as deep neural networks and support vector machines. The algorithm is numerically tested with success on a simple 1D problem, but the main goal is its exportability in the context of more serious applications. Here we also show at the end an application in the framework of plasma physics.

97 MATHEMATICS AND COMPUTING↗

Stability and Fidelity of Power-Hardware-in-the-Loop Using NREL's CGI

The presentation focuses on dynamic analysis of power hardware-in-the-loop (PHIL) experiments using National Renewable Energy Laboratory Flatirons Campus' grid simulator - 7MVA Controllable Grid Interface (CGI). A control diagram of typical PHIL experiment is described, and transfer functions of critical components are explained. An impedance-based definition of PHIL experiment bandwidth is defined using open loop transfer functions of the system. Further an example resistive divider circuit is introduced that is used to explain implication of PHIL on accuracy of simulation by comparing measured results against ideal expected signals. At the end the real-life PHIL simulation using Maui power system model is described showing various oscillation modes observed and discussing the meaning of these in context of dynamic bandwidth of simulation.

grid simulator↗

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗

Hardware-in-the-Loop Test Bed and Test Methodology for Microgrid Controller Evaluation

Increasing penetration levels of distributed energy resources are making the deployment of microgrids more feasible. Controllers that operate such microgrids are key to realizing the objectives of the microgrid owner or operator and there is a need to evaluate microgrid controller performance prior to field deployment. This paper describes a controller hardware-in-the-loop and power hardware-in-the-loop microgrid controller test bed that was designed and constructed to evaluate the capabilities of a microgrid controller for a proposed campus microgrid. This paper also presents a test methodology to evaluate microgrid controller functionality, and it describes how the controller was assessed through the application of different test scenarios. Results from the testing are presented to provide insight into the capabilities of the test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distribution Function Instead of Steady-State Assumption in Time-Series Simulation

The quasi-steady-state assumption in time-series simulation is inadequate to model phenomena of interest to energy system integration such as inverter clipping, sell-back of excess electricity to a utility and utility hosting capacity, and battery throughput. Researchers are working on stochastic modeling, higher-resolution time series data, and machine learning approaches to address this need. This poster describes a distribution function that allows a maximum value, minimum value, and shape to the curve that can vary within each time-step based only on data inputs at the resolution of that time step (eg. Hourly). The distribution function is not used to synthesize high-resolution data, rather scalar integrals are used to calculate the quantities of interest within each time step. The form of the distribution function shows significant reduction in error when compared to 1 minute data and commercial software employing the distribution function (HOMER Pro version 14.3 and higher) shows a much improved estimate of inverter clipping in an example.

battery↗

Cumulant methods for electron-phonon problems. I. Perturbative expansions

Here in this work, we investigate the ability of the cumulant expansion (CE) to capture one-particle spectral information in electron-phonon coupled systems at both zero and finite temperatures. In particular, we present a comprehensive study of the second- and fourth-order CEs for the one-dimensional Holstein model as compared with numerically exact methods. We investigate both finite sized systems as well as the approach to the thermodynamic limit, drawing distinctions, and connections between the behavior of systems in and away from the thermodynamic limit that enable a greater understanding of the ability of the CE to capture real-frequency information across the full range of wave vectors. We find that for zero electronic momentum, the spectral function is well described by the second-order CE at low and high temperatures. However, for nonzero electronic momenta, the CE is only accurate at high temperature. We analyze the fourth-order cumulant and find that while it improves the description of the short-time dynamics encoded in the one-particle Green's function, it can introduce divergences in the time domain as well as unphysical negative spectral weight in the spectral function. When well-behaved, the fourth-order CE does provide notable accurate corrections to the second-order CE. Finally, we use our results to comment on the use of the CE as a tool for calculating transport behavior in the realistic ab initio modeling of materials.

36 MATERIALS SCIENCE↗

Resin Assisted Capture Coupled with Isobaric Tandem Mass Tag Labeling for Multiplexed Quantification of Protein Thiol Oxidation

Reversible oxidative modifications on protein thiols have recently emerged as important mediators of cellular function. Herein we describe the detailed procedure of a quantitative redox proteomics method that utilizes resin-assisted capture (RAC) in combination with tandem mass tag (TMT) isobaric labeling and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to allow multiplexed stochiometric quantification of oxidized protein thiols at the proteome level. The site-specific quantitative information on oxidized cysteine residues provides additional insight into the functional impacts of such modifications. The workflow is adaptable across many sample types including cultured cells (e.g. mammalian, prokaryotic) and whole tissues (e.g. heart, lung, muscle) which are initially lysed/homogenized with free thiols being alkylated to prevent artificial oxidation. The oxidized protein thiols are then reduced and captured by a thiol affinity resin which streamlines and simplifies the workflow steps by allowing the proceeding digestion, labeling, and washing procedures to be performed without additional transfer of proteins/peptides. Finally, labeled peptides are eluted and analyzed by LC-MS/MS to reveal comprehensive stoichiometric changes related to thiol oxidation across the entire proteome. This method greatly improves our understanding of the role of redox dependent regulation under physiological and pathophysiological states related to protein thiol oxidation.

RAC, TMT, thiol redox proteomics, cysteine, PTM st↗

Solving reaction dynamics with quantum computing algorithms

The description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. However, the time evolution of quantum states is a natural application for quantum computers that are designed to efficiently perform unitary transformations. Here, in this paper, we study quantum algorithms for response functions, relevant for describing different reactions governed by linear response. We focus on nuclear-physics applications and consider a qubit-efficient mapping on the lattice, which can efficiently represent the large volumes required for realistic scattering simulations. For the case of a contact interaction, we develop an algorithm for time evolution based on the Trotter approximation that scales logarithmically with the lattice size and is combined with quantum phase estimation. We eventually focus on the nuclear two-body system and a typical response function relevant for electron scattering as an example. We also investigate ground-state preparation and examine the total circuit depth required for a realistic calculation and the hardware noise level required to interpret the signal.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Tianlai Cylinder Pathfinder Array: System Functions and Basic Performance Analysis

The Tianlai Cylinder Pathfinder is a radio interferometer array designed to test techniques for 21 cm intensity mapping in the post-reionization Universe, with the ultimate aim of mapping the large scale structure of the Universe and measuring cosmological parameters such as the dark energy equation of state. Each of its three parallel cylinder reflectors are oriented in the north-south direction, and the array has a large field of view. As the Earth rotates, the northern sky is observed by drift scanning. The array is located in Hongliuxia, a radio quiet site in Xinjiang, and saw its first light in September 2016. In this first paper on the data analysis of the Tianlai cylinder array, we describe the system functions of the array, the commissioning observations during 2016- 2018, and present its basic performance characteristics. We show examples of the interferometric visibility data, then using the observational data, we derive the actual beam profile in the east-west direction, the bandpass response, and calibrate the complex gains for the array elements either with a strong astronomical point source, or with an artificial calibrator source. Based on the preliminary analysis of the data, we derive the system temperature and sensitivity of the array.

79 ASTRONOMY AND ASTROPHYSICS↗

Fermi-liquid theory and divergences of the two-particle irreducible vertex in the periodic Anderson lattice

Here we analyze the divergences of the irreducible vertex function in dynamical mean field theory, which may indicate either a nonphysical breakdown of the perturbation theory or a response to some physical phenomenon. To investigate this question, we construct a quasiparticle vertex from the diverging irreducible vertex functions. This vertex describes the scattering between quasiparticles and quasiholes in a Fermi liquid. We show that the quasparticle vertex does not diverge in the charge channel, wherein the irreducible vertex does diverge; and we show that the quasiparticle vertex does diverge in the spin channel, wherein the irreducible vertex does not diverge. This divergence occurs at the Mott transition, wherein the Fermi-liquid theory breaks down. Both the half filled Hubbard and Anderson lattices are investigated. In general, our results support that the divergences of the irreducible vertex function do not indicate a nonphysical failure of the perturbation theory. Instead, the divergences are the mathematical consequence of inverting a matrix (the local charge susceptibility) which accumulates increasingly negative diagonal elements as the Hubbard interaction suppresses charge fluctuations. Indeed, we find that the first divergences of the irreducible vertex in both Hubbard and Anderson lattices occurs near the maximum magnitude of the (negative) vertex-connected part of the charge susceptibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Measurements of Beam Spin Asymmetries in p+p0 and p´p0 Dihadron Production at CLAS12

Semi-Inclusive Deep Inelastic Scattering (SIDIS) is a powerful experimental tool for studying the internal structure and dynamics of the proton, revealing how quarks and gluons are distributed and interact within it. SIDIS describes a process where an elec tron scatters off one of the constituent quarks within the proton, causing it to undergo hadronization, creating multiple hadrons in the final state. Through factorization, the full process can be split into probabilistic components: one which describes the internal structure of the proton using Parton Distribution Functions (PDFs), and another which describes the hadronization process using Fragmentation Functions (FFs). These functions are non-perturbative quantities of Quantum Chromodynamics (QCD), meaning they cannot be calculated directly from first principles and must instead be extracted from experimental measurements. Acommon approach for accessing PDFs and FFs using SIDIS is to measure asymmetries. In this context, asymmetries correspond to subtle differences in the angular distribution of outgoing particles that arise when the spin orientation of the incoming beam or target is reversed. Because many of these effects only appear when spin is involved, they isolate specific, nuanced properties of the proton’s spin-structure that are otherwise hidden in spin averaged measurements. In practice, they show up as specific azimuthal modulations (e.g., sin ¿R, sin(¿h ´ ¿R)), whose amplitudes isolate convolutions of PDFs and FFs at leading and subleading twist. Non-zero asymmetries of these angular distributions can be traced back to unique combinations of PDFs and FFs, offering a way to probe them directly. In this work, we measure SIDIS by analyzing high energy electron-proton scattering events using the CLAS12 detector at Jefferson Lab. This study focuses on subset of SIDIS referred to as dihadron SIDIS, where pairs of hadrons — here p+p0 and p´p0 — are observed. We analyzed these dihadrons using detector data collected during Fall 2018 and Spring 2019, where longitudinally polarized electrons from the CEBAF accelerator were incident on a liquid hydrogen target. A photon classifier using a Gradient Boosted Trees (GBTs) architecture was trained using Monte Carlo simulations to reduce the amount of iv false combinatorial background p0’s. When deployed on experimental data, the model in creases our dihadron statistics by up to five-fold compared to previous CLAS12 p0 analyses. This work reports the first measurements of beam spin asymmetries for p+p0 and p´p0 dihadron production in SIDIS. The measured asymmetries offer new insights to the spin-dependent structure and dynamics within the proton, as well as the spin-dependent properties of quark fragmentation. Non-zero twist-3 sin¿R amplitudes are observed, pro viding sensitivity to the subleading twist PDF e(x). The PDF e(x) encodes quark-gluon correlations within the proton — a property that is otherwise inaccessible at leading twist. Additionally, this work measured significant twist-2 modulations carried by sin(¿h ´ ¿R) and sin(2¿h ´2¿R), providing experimental access to the helicity dihadron fragmentation function (DiFF) GK 1 . Because there is no equivalent quark helicity-dependent FF in single pion SIDIS, the DiFF GK 1 offers a unique lens into novel spin-dependent fragmentation. For instance, the twist-2 modulations observed in this study are enhanced by vector mesons created during fragmentation — a behavior predicted by phenomenological models. This study broadens our understanding of dihadron fragmentation, revealing new details about the flavor and charge dependence of hadronization.

Matousek, Gregory [Duke Univ., Durham, NC (United ↗