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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Plant Based Poly-functional Hindered Phenol Derivative as an Alternative for Silane in Cis-Polyisoprene and its Functionalized Derivative Systems Containing Nano-sized Particulates

The present work provides extensive insight into the newly developed sustainable bio-resin (terpene) functionalized Natural Rubber (NR). Structural elucidation of the functionalized NR was established by proton nuclear magnetic resonance ({sup 1}H NMR) and Fourier transform infrared spectroscopy (FTIR) respectively. This study demonstrates the effect of Bio-Resin Functionalized NR (BR-NR)/Epoxidized Natural rubber (ENR) blends combined with four different specific surface areas of highly dispersible silica (HDS). The primary aim of these analyses is the description of the interfacial area on the HDS surface involved in physical form (Micro pearl and Granule) and synergistic rubber-filler interaction mechanism for the superior reinforcement. Improved state of HDS dispersion has been achieved in absence of conventional toxic processing oil, silane coupling agent and normal zinc oxide. Remarkable improvement in overall properties corroborated with various meticulous characterization including cure characteristics, bound rubber content, Mullins effect and physico-mechanical properties etc. An augmented rubber-filler interaction is also supported by micro computed tomography morphology study. Dynamic mechanical analysis shows an ultra-low rolling resistance coupled with high traction and advanced elastic response of the greener macromolecules. More decisively, the macromolecule system toned up sparingly in the presence of the bio-resin. Newly developed BR-NR together with ENR 25 and their significant contribution to the improvements of properties are schematically explained.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Tunable noninteracting free-energy density functionals for high-energy-density physics applications

In this work, we introduce the concept of a tunable noninteracting free-energy density functional and present two examples realized: (i) via a simple one-parameter convex combination of two existing functionals and (ii) via the construction of a generalized gradient approximation (GGA) enhancement factor that contains one free parameter and is designed to satisfy a set of incorporated constraints. Functional (i), constructed as a combination of the local Thomas–Fermi and a pseudopotential-adapted GGA for the noninteracting free-energy, has already demonstrated its practical usability for establishing the high temperature end of the equation of state of deuterium [Phys. Rev. B 104, 144104 (2021)] and CHON resin [Phys. Rev. E 106, 045207 (2022)] for inertial confinement fusion applications. Hugoniot calculations for liquid deuterium are given as another example of how the application of computationally efficient orbital-free density functional theory (OF-DFT) can be utilized with the employment of the developed functionals. Once the functionals have been tuned such that the OF-DFT Hugoniot calculation matches the Kohn–Sham solution at some low-temperature point, agreement with the reference Kohn–Sham results for the rest of the high temperature Hugoniot path is very good with relative errors for compression and pressure on the order of 2% or less.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Proton exchange membrane fuel cells

Disclosed embodiments concern a membrane electrode assembly or a proton exchange membrane fuel cell comprising a phosphoric acid-doped polymeric membrane comprising a cationic functional group, such as an assembly or fuel cell having an ion exchange capacity of 0.8 to 3 mmol/gram and an operating temperature range of from 80° C. to 220° C. The cationic functional group can be any suitable functional group, such as ammonium, imidazolium, guanidinium, phosphazenium, sulfonium, oxonium, and phosphonium, with working embodiments typically using quaternary ammonium cationic functional groups tethered to the polymeric core. The polymeric material may be any suitable polymeric material, such as a material selected from polyaryl polymers, polyarylamides, polyimides, polystyrenes, polysulfones, polyethers, polyether sulfones, polyketones, polyetherketones, polyarylethers, polyolefins, and polynitriles. The membrane electrode assembly or a proton exchange membrane fuel cell can be used in any application now known or hereafter developed, such as a vehicle or a stationary power device.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Warming Up Density Functional Theory [Book Chapter]

Density functional theory (DFT) has become the most popular approach to electronic structure across disciplines, especially in material and chemical sciences. In 2016, at least 30,000 papers used DFT to make useful predictions or give insight into an enormous diversity of scientific problems, ranging from battery development to solar cell efficiency and far beyond. The success of this field has been driven by usefully accurate approximations based on known exact conditions and careful testing and validation. In the last decade, applications of DFT in a new area, warm dense matter, have exploded. DFT is revolutionizing simulations of warm dense matter including applications in controlled fusion, planetary interiors, and other areas of high energy density physics. Over the past decade or so, molecular dynamics calculations driven by modern density functional theory have played a crucial role in bringing chemical realism to these applications, often (but not always) in excellent agreement with experiment. This chapter summarizes recent work from our group on density functional theory at nonzero temperatures, which we call thermal DFT. We explain the relevance of this work in the context of warm dense matter, and the importance of quantum chemistry to this regime. We illustrate many basic concepts on a simple model system, the asymmetric Hubbard dimer.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enrichment of root-associated Streptomyces strains in response to drought is driven by diverse functional traits and does not predict beneficial effects on plant growth

The genus Streptomyces has consistently been found enriched in drought-stressed plant root microbiomes, yet the ecological basis and functional variation underlying this enrichment at the strain and isolate level remain unclear. Using two 16S rRNA sequencing methods with different levels of taxonomic resolution, we confirmed drought-associated enrichment (DE) of Streptomyces in field-grown sorghum roots and identified five closely related but distinct amplicon sequence variants (ASVs) belonging to the genus with variable drought enrichment patterns. From a culture collection of sorghum root endophytes, we selected 12 Streptomyces isolates representing these ASVs for phenotypic and genomic characterization. Whole-genome sequencing revealed substantial variation in gene content, even among closely related isolates, and exometabolomic profiling showed distinct metabolic responses to media supplemented with drought- versus well-watered root tissue. Traits linked to drought survival, including osmotic stress tolerance, siderophore production, and carbon utilization, varied widely among isolates and were not phylogenetically conserved. Using a broader panel of 48 Streptomyces, we demonstrate that DE scores, determined through mono-association experiments in gnotobiotic sorghum systems, showed high variability and lacked correlation with plant growth promotion. Pangenome-wide association identified orthogroups involved in osmolyte transport (e.g., proP) and membrane biosynthesis (e.g., fabG) as positively associated with DE, though most associations lacked phylogenetic signal. Collectively, these results demonstrate that Streptomyces DE is not a conserved genus-level trait but is instead strain-specific and functionally heterogeneous. Furthermore, DE in the root microbiome was shown not to predict beneficial effects on plant growth. This work underscores the need to resolve functional traits at the strain level and highlights the complexity of microbe-host-environment interactions under abiotic stress.

Fonseca-Garcia, Citlali↗
DOE OSTI2017

Supporting resilience in nuclear power plant operations - conceptual frames for human factors development and validation - 166

This is a summary paper of conceptual developments on nuclear power plant operation by the human factors team at VTT Technical Research Centre of Finland. While drawing together years of studies, the paper also discusses recent progresses in training development. Firstly, there is a long background in work analysis and system validation. The analysis model applied provides a model for assessing and identifying 'core-task functions,' that is, basic functions that should be fulfilled within work activity. Secondly, we have evaluated the existing training practices at a Finnish plant and identified challenges that could be generally prevalent in the nuclear domain - they seem to reflect the hierarchical and safety-critical nature of NPP operation. In terms of potential solutions, we are currently testing and developing some new self-evaluation and self-confrontation methods. First and foremost, however, we discuss the common theory basis for our research approaches. On the broadest level, our development and research work reflects the view of safety as expressed by resilience engineering literature: safety is not seen merely as 'negative' lack of mistakes, but also as 'positive' capability to solve and anticipate problems. For example, it is assumed that operators' capability for situational interpretation should be supported at all times: even if the emergency procedures dictate operator activity specifically, the operators should understand the influence of the operating procedures for the plant process and system state. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Density functional theory based neural network force fields from energy decompositions

In order to develop force fields (FF) for molecular dynamics simulations that retain the accuracy of ab initio density functional theory (DFT), in this work we developed a machine learning protocol based on an energy decomposition scheme that extracts atomic energies from DFT calculations. Our DFT to FF (DFT2FF) approach provides almost hundreds of times more data for the DFT energies, which dramatically improves accuracy with less DFT calculations. In addition, we use piecewise cosine basis functions to systematically construct symmetry invariant features into the neural network model. We illustrate this DFT2FF approach for amorphous silicon where only 800 DFT configurations are sufficient to achieve an accuracy of 1 meV/atom for energy and 0.1 eV/A for forces. We then use the resulting FF model to calculate the thermal conductivity of amorphous Si based on long molecular dynamics simulations. The dramatic speedup in training in our DFT2FF protocol allows the adoption of a simulation paradigm where an accurate and problem specific FF for a given physics phenomenon is trained on-the-spot through a quick DFT precalculation and FF training.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

cxcl12 gene engineered endothelial progenitor cells further improve the functions of oligodendrocyte precursor cells

Highlights: • cxcl12 gene engineering of EPCs promoted VEGF and IGF expression by EPCs. • Conditioned media from CXCL12-EPCs further promoted the functions of OPCs. • CXCL12-EPCs conditioned media affected the expression of trophic factors by OPCs. • CXCR4 knockdown suppressed the proliferation and migration of OPCs and reduced PDGFR-α and bFGF expression. • CXCR7 knockdown inhibited the expression of MBP by OPCs and caused slower differentiation. Oligodendrocyte precursor cells (OPCs) are needed for white matter repair after various brain injury. Means that promote OPC functions could benefit white matter recovery after injury. Chemokine CXCL12 and endothelial progenitor cells (EPCs) both have been shown to promote remyelination. We hypothesize that the beneficial effects of EPCs and CXCL12 can be harnessed by genetically modifying EPCs with cxcl12 to synergistically improve the functions of OPCs. In this work, CXCL12-EPC was generated using virus-mediated gene transfer. OPCs were cultured with CXCL12-EPC conditioned media (CM) to analyze its impact on the proliferation, migration, differentiation and survival properties of OPCs. We blocked or knocked-down the receptors of CXCL12, namely CXCR4 and CXCR7, respectively to investigate their functions in regulating OPCs properties. Results revealed that CXCL12-EPC CM further promoted OPCs behavioral properties and upregulated the expression of PDGFR-α, bFGF, CXCR4 and CXCR7 in OPCs, albeit following different time course. Blocking CXCR4 diminished the beneficial effects of CXCL12 on OPCs proliferation and migration, while knocking down CXCR7 inhibited OPCs differentiation. Our results supported that cxcl12 gene modification of EPCs further promoted EPCs’ ability in augmenting the remyelination properties of OPCs, suggesting that CXCL12-EPC hold great potential in white matter repair.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1975

Vestibular function in the space environment

The present work presents new results about the interdependence of optical illusory sensations and eye movements in man. To establish to what degree certain illusions previously obtained during centrifugation and parabolic flight can be explained by eye movements and by neuronal integration in the brain, real eye movements were measured as they occurred in the dark without optical fixation, during rectilinear accelerations on the ground, and during weightlessness in parabolic flight. Results provide valuable insight into normal vestibular function as well as resolution of within-the-eye and behind-the-eye contributions to the above illusions.

Von Baumgarten, R. J.↗
DOE OSTI2023

Transforming our understanding of chloroplast-associated genes through comprehensive characterization of protein localizations and protein-protein interactions

Bioenergy crops are a renewable source of fuels and are a critical base for building a carbon-neutral economy. Rational engineering of bioenergy crops has the potential to enhance the yields. However, our ability to engineer plants is limited because the functions of most genes remain unknown. Systematic characterization of gene function in plants thus has the potential to greatly accelerate bioenergy research. Here, we focus on the chloroplast, an underexplored energy-producing organelle that is a hallmark of plants. The chloroplast is one of the promising targets of biofuel crop engineering efforts because of its central role in photosynthesis, metabolism, and intracellular signaling. However, the protein composition of the chloroplast and the functions of most of its proteins remain poorly characterized. At the core of this project, we sought to comprehensively determine the localization of chloroplast-associated proteins and generate a spatially defined protein-protein interaction network for chloroplast. For this purpose, we used the leading model alga Chlamydomonas reinhardtii, which greatly increased experimental speed and throughput. We illustrated the value of our findings to land plants by determining the localization of Arabidopsis thaliana land plant homologs of the Chlamydomonas proteins. Altogether, we were successful in determining the localization of 1,034 chloroplast-associated proteins in Chlamydomonas. The localizations provide numerous insights into the spatial organization of chloroplasts and how they function to support photosynthesis. The localization patterns of distinct proteins revealed new chloroplast structures and revealed new spatial organization inside the chloroplast. We also identified new components of known chloroplast structures, such as the chloroplast envelope, nucleoid, plastoglobuli, and pyrenoid. We identified these new components by investigating the interacting partners of known proteins. Many proteins localized in both the chloroplast and other cellular structures, thereby hinting at new functions and communication between cellular structures. We also applied machine learning on the atlas to generate predictions for the location of all of the proteins in Chlamydomonas. This enabled us to assign putative functions to many uncharacterized proteins based on their cellular location. Altogether, this research establishes a rich resource that opens new avenues of investigation and guides future work in deciphering and manipulating chloroplast function. Next, we developed an extensive protein-protein interaction network for the chloroplast by performing affinity purification-mass spectrometry on ~1,150 tagged chloroplast-associated proteins, the first such large-scale study in any photosynthetic organism. This dataset reveals 4,694 high-confidence protein-protein interactions, offering insights into the functions of thousands of conserved poorly-characterized chloroplast proteins. This systematic identification of protein-protein interactions in the chloroplast also provides multiple exciting new research directions and a detailed blueprint of the chloroplast's operation. This research lays the groundwork to decipher the inner workings of the chloroplast, the cell structure at the heart of photosynthesis. The spatial atlas and protein-protein interactions reveal chloroplast organizational features that would not have been accessible with traditional approaches. The localization mapping, insights into the function, and research materials generated further provide a rich resource for the research community to advance the understanding of how the chloroplast is organized to enable engineering of enhanced photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Analysis of tumor-immune functional responses in a mathematical model of neoantigen cancer vaccines

Cancer neoantigen vaccines have emerged as a promising approach to stimulating the immune system to fight cancer. We propose a simple model including key elements of cancer-immune interactions and conduct a phase plane analysis to understand the immunological mechanisms of cancer neoantigen vaccines. Analytical results are obtained for two widely used functional forms that represent the killing rate of tumor cells by immune cells: the law of mass action (LMA) and the dePillis-Radunskaya Law (LPR). Using the LMA, our results reveal that a slowly growing tumor can escape the immune surveillance and that there is a unique periodic solution. The LPR offers richer dynamics, in which tumor elimination and uncontrolled tumor growth are both present. We show that tumor elimination requires sufficient number of initial activated T cells in relationship to the malignant cells, which lends support to using the neoantigen cancer vaccine as an adjuvant therapy after the primary tumor is surgically removed or treated using radiotherapy. We also derive a sufficient condition for uncontrolled tumor growth under the assumption of the LPR. Here, the juxtaposition of analyses with these two different choices for the killing rate function highlights their importance on model behavior and biological implications, by which we hope to spur further theoretical and experimental work to understand mechanisms underlying different functional forms for the killing rate.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2007

Distributed Operations Planning

Maestro software provides a secure and distributed mission planning system for long-term missions in general, and the Mars Exploration Rover Mission (MER) specifically. Maestro, the successor to the Science Activity Planner, has a heavy emphasis on portability and distributed operations, and requires no data replication or expensive hardware, instead relying on a set of services functioning on JPL institutional servers. Maestro works on most current computers with network connections, including laptops. When browsing down-link data from a spacecraft, Maestro functions similarly to being on a Web browser. After authenticating the user, it connects to a database server to query an index of data products. It then contacts a Web server to download and display the actual data products. The software also includes collaboration support based upon a highly reliable messaging system. Modifications made to targets in one instance are quickly and securely transmitted to other instances of Maestro. The back end that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Fox, Jason↗
DOE OSTI2020

The plant pathogen enzyme AldC is a long-chain aliphatic aldehyde dehydrogenase

Aldehyde dehydrogenases are versatile enzymes that serve a range of biochemical functions. Although traditionally considered metabolic housekeeping enzymes because of their ability to detoxify reactive aldehydes, like those generated from lipid peroxidation damage, the contributions of these enzymes to other biological processes are widespread. For example, the plant pathogen Pseudomonas syringae strain PtoDC3000 uses an indole-3-acetaldehyde dehydrogenase to synthesize the phytohormone indole-3-acetic acid to elude host responses. In this work we investigate the biochemical function of AldC from PtoDC3000. Analysis of the substrate profile of AldC suggests that this enzyme functions as a long-chain aliphatic aldehyde dehydrogenase. The 2.5 Å resolution X-ray crystal of the AldC C291A mutant in a dead-end complex with octanal and NAD + reveals an apolar binding site primed for aliphatic aldehyde substrate recognition. Functional characterization of site-directed mutants targeting the substrate- and NAD(H)-binding sites identifies key residues in the active site for ligand interactions, including those in the “aromatic box” that define the aldehyde-binding site. Overall, this study provides molecular insight for understanding the evolution of the prokaryotic aldehyde dehydrogenase superfamily and their diversity of function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Stochastic Resolution of Identity for Real-Time Second-Order Green’s Function: Ionization Potential and Quasi-Particle Spectrum

Here, we develop a stochastic resolution of identity approach to the real-time second-order Green's function (real-time sRI-GF2) theory, extending our recent work for imaginary-time Matsubara Green's function [ Takeshita et al. J. Chem. Phys. 2019 , 151 , 044114 ]. The approach provides a framework to obtain the quasi-particle spectra across a wide range of frequencies and predicts ionization potentials and electron affinities. To assess the accuracy of the real-time sRI-GF2, we study a series of molecules and compare our results to experiments as well as to a many-body perturbation approach based on the GW approximation, where we find that the real-time sRI-GF2 is as accurate as self-consistent GW. The stochastic formulation reduces the formal computatinal scaling from O(N e 5 ) down to O(N e 3 ) where N e is the number of electrons. Finally, this is illustrated for a chain of hydrogen dimers, where we observe a slightly lower than cubic scaling for systems containing up to N e ≈ 1000 electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fully thermal meta-GGA exchange correlation free-energy density functional

The application of density functional theory to materials in the warm dense matter regime has motivated the development of exchange-correlation functionals which incorporate proper, explicit temperature dependence. Previous work has yielded fully-thermal exchange-correlation free energy functionals at the local density approximation (LDA) and generalized gradient approximation (GGA) levels of refinement. Recently an additive thermal correction scheme was utilized to construct a meta-GGA exchange-correlation (XC) functional in which thermal effects are treated at the GGA level. Here, the f TSCAN free-energy XC functional presented here includes thermal effects through the meta-GGA level in the context of the SCAN (strongly constrained and appropriately normed) ground-state functional. The f TSCAN functional provides generality while achieving similar performance to a thermal GGA functional at high temperatures, e.g. pressures within 1% of path integral Monte Carlo simulations of warm dense hydrogen, and a significant improvement over ground-state functionals. At low temperatures, f TSCAN demonstrates improvements in accuracy relative to lower-level and deorbitalized functionals, indicating that calculations using f TSCAN may be expected to perform well across experimentally relevant densities and pressures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fabrication of Ionic Covalent Triazine Framework-Linked Membranes via a Facile Sol–Gel Approach

Covalent triazine framework (CTF)-based membranes have shown unique properties and wide applications in energy-related fields, but there is still no efficient strategy capable of affording CTF membranes functionalized with ionic moieties, which will bring extra merits and application possibilities. In this work, a robust CTF membrane with ionic functionalities was fabricated via a sol–gel approach promoted by a superacid (FSO 3 H). The CTF skeleton was constructed via the trimerization of cyano groups in the monomer, and piperazine moieties were introduced as reactive sites for the formation of ammonium cations coupled with FSO 3 – anions within the backbone. The obtained transparent and red protonated polymeric CTF-based membrane (PP-CTF) exhibited significant absorption at 646 nm in the solid-state ultraviolet–visible diffuse reflectance spectrum. Comparatively, the neutralized deprotonated counterparts turned to yellow color with a significant blueshift absorption to 492 nm. The theoretical calculation demonstrated that PP-CTF and deprotonated polymeric CTF membrane (DP-CTF) were stable with AB-stacking mode, and PP-CTF had a smaller band gap (0.90 eV) than that of DP-CTF (2.17 eV). The significant optical absorption and emission behavior change of PP-CTF and its robust chemical stability endowed it with the capability to act as pH indicators. The synthetic pathway developed in this work and the performance of the resultant ionic membrane opens new opportunities in the aspects of membrane design, fabrication, and application.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of alloying elements on the $γ$’ antiphase boundary energy in Ni-base superalloys

Mechanical and fatigue performance of γ-γ' Ni-base superalloys are strongly affected by the antiphase boundary energy (APBE) of the γ' precipitates which, in turn, is dictated by the alloy's composition. Due to the multicomponent character of these alloys, establishing composition-APBE relationships are challenging, even though the qualitative effect of individual solutes on the APBE may be known. This work attempts to utilize density functional theory-based cluster expansion calculations to systematically assess the effect of composition on the APBE of the γ' phases in Ni-base superalloys. We aim to elucidate the influence of not only one single element but also multiple coexisting alloying elements on the γ' APBE. By explicit consideration of configurational disorder via Monte Carlo sampling, the effect of temperature on the APBE has also been analyzed. Overall, this work reveals that (1) effects of individual solute element M on the APBE energy obtained in an isolated, ternary condition (i.e. in Ni 3-x Al 1-y M x+y ) does not directly translate to a multi-solute case and that (2) the mutual synergistic interactions among different solute elements are not negligible. Based on the present results, an empirical master equation that predicts the APBE based on the composition of the γ' phases has been obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Asymptotic Normalization Coefficients (Nuclear Vertex Constants), Three-Body Asymptotic Normalization Functions (On-Shell Vertex Functions) and Nuclear Astrophysics

In the present review work, the main methods of the determination of asymptotic normalization coefficients (or respective nuclear vertex constants) for the A + x → B channel and of threebody asymptotic normalization functions (or respective on-shell vertex functions) for the A + b + c → B channel are briefly discussed. The main attention is paid both to the use of the specific asymptotic normalization coefficients and three-body asymptotic normalization functions as a source of getting the valuable information about the pair (nucleon–nucleon, nucleon–cluster and cluster–cluster) nuclear interactions and to their application for the specific direct nuclear-astrophysical radiative capture and peripheral transfer reactions at low energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗