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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Comparison of Two Coronal Magnetic Field Models to Reconstruct a Sigmoidal Solar Active Region with Coronal Loops

Magnetic field extrapolation is an important tool to study the three-dimensional (3D) solar coronal magnetic field, which is difficult to directly measure. Various analytic models and numerical codes exist, but their results often drastically differ. Thus, a critical comparison of the modeled magnetic field lines with the observed coronal loops is strongly required to establish the credibility of the model. Here we compare two different non-potential extrapolation codes, a nonlinear force-free field code (CESE–MHD–NLFFF) and a non-force-free field (NFFF) code, in modeling a solar active region (AR) that has a sigmoidal configuration just before a major flare erupted from the region. A 2D coronal-loop tracing and fitting method is employed to study the 3D misalignment angles between the extrapolated magnetic field lines and the EUV loops as imaged by SDO /AIA. It is found that the CESE–MHD–NLFFF code with preprocessed magnetogram performs the best, outputting a field that matches the coronal loops in the AR core imaged in AIA 94 Å with a misalignment angle of ∼10°. This suggests that the CESE–MHD–NLFFF code, even without using the information of the coronal loops in constraining the magnetic field, performs as good as some coronal-loop forward-fitting models. For the loops as imaged by AIA 171 Å in the outskirts of the AR, all the codes including the potential field give comparable results of the mean misalignment angle (∼30°). Thus, further improvement of the codes is needed for a better reconstruction of the long loops enveloping the core region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

Abstract. Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. Estimates of future land use and land cover differ significantly across economic models as a result of differences in drivers, model structure, and model parameters; however, these models often rely on heuristics to determine model parameters. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. Specifically, we generate a large set of model parameter perturbations for the selected parameters and run gcamland simulations with these parameter sets over the historical period in the United States to quantify land use and land cover, determine how well the model reproduces observations, and identify parameter combinations that best replicate observations, assuming other model parameters are fixed. We also test alternate methods for forming expectations about uncertain crop yields and prices, including adaptive, perfect, linear, and hybrid approaches. In particular, we estimate parameters for six parameters used in the formation of expectations and three of seven logit exponents for the USA only. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops, landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We examine the change in model parameters as the metric of model error changes, finding that the measure of model fitness affects the choice of parameter sets. Finally, we discuss how the methodology and results used in this study could be used for other regions or economic models to improve projections of future land use and land cover change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A COMPARATIVE ANALYSIS OF THE SUPERNOVA LEGACY SURVEY SAMPLE WITH ΛCDM AND THE R{sub h}=ct UNIVERSE

The use of Type Ia supernovae (SNe Ia) has thus far produced the most reliable measurement of the expansion history of the universe, suggesting that ΛCDM offers the best explanation for the redshift–luminosity distribution observed in these events. However, analysis of other kinds of sources, such as cosmic chronometers, gamma-ray bursts, and high-z quasars, conflicts with this conclusion, indicating instead that the constant expansion rate implied by the R{sub h} = ct universe is a better fit to the data. The central difficulty with the use of SNe Ia as standard candles is that one must optimize three or four nuisance parameters characterizing supernova (SN) luminosities simultaneously with the parameters of an expansion model. Hence, in comparing competing models, one must reduce the data independently for each. We carry out such a comparison of ΛCDM and the R{sub h} = ct universe using the SN Legacy Survey sample of 252 SN events, and show that each model fits its individually reduced data very well. However, since R{sub h} = ct has only one free parameter (the Hubble constant), it follows from a standard model selection technique that it is to be preferred over ΛCDM, the minimalist version of which has three (the Hubble constant, the scaled matter density, and either the spatial curvature constant or the dark energy equation-of-state parameter). We estimate using the Bayes Information Criterion that in a pairwise comparison, the likelihood of R{sub h} = ct is ∼90%, compared with only ∼10% for a minimalist form of ΛCDM, in which dark energy is simply a cosmological constant. Compared to R{sub h} = ct, versions of the standard model with more elaborate parametrizations of dark energy are judged to be even less likely.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

MEASURING THE THREE-DIMENSIONAL SHAPE OF X-RAY CLUSTERS

Observations and numerical simulations of galaxy clusters strongly indicate that the hot intracluster X-ray-emitting gas is not spherically symmetric. In many earlier studies, spherical symmetry has been assumed partly because of limited data quality; however, new deep observations and instrumental designs will make it possible to go beyond that assumption. Measuring the temperature and density profiles are of interest when observing the X-ray gas; however, the spatial shape of the gas itself also carries very useful information. For example, it is believed that the X-ray gas shape in the inner parts of galaxy clusters is greatly affected by feedback mechanisms, cooling, and rotation, and measuring this shape can therefore indirectly provide information on these mechanisms. In this paper, we present a novel method to measure the three-dimensional shape of the intracluster X-ray-emitting gas. We can measure the shape from X-ray observations only, i.e., the method does not require combination with independent measurements of, e.g., the cluster mass or density profile. This is possible when one uses the full spectral information contained in the observed spectra. We demonstrate the method by measuring radially dependent shapes along the line of sight for CHANDRA mock data. We find that at least 10{sup 6} photons are required to get a 5{sigma} detection of shape for an X-ray gas having realistic features such as a cool core and a double power law for the density profile. We illustrate how Bayes' theorem is used to find the best-fitting model of the X-ray gas, an analysis that is very important in a real observational scenario where the true spatial shape is unknown. Not including a shape in the fit may propagate to a mass bias if the X-ray is used to estimate the total cluster mass. We discuss this mass bias for a class of spatial shapes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Modified Johnson–Cook Model for Flow Behavior of Alloy 800H at Intermediate Strain Rates and High Temperatures

A modified Johnson–Cook model for the flow behavior of alloy 800H at intermediate strain rates and high temperatures is presented. The modification is based on a study of the relation between strain hardening and both strain rate and softening parameters. The predicted stresses obtained using the modified model are compared to those obtained using the original Johnson–Cook model. The parameters constitute the two models are determined using the inverse method, Kalman filter. The results show that the modified model fits the experimental data very well for different combinations of strain rates and temperatures, with a mean value of R-squared regression of 0.90 for the modified model and 0.74 for the original Johnson–Cook model.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Quantifying (dis)agreement between direct detection experiments in a halo-independent way

We propose an improved method to study recent and near-future dark matter direct detection experiments with small numbers of observed events. Our method determines in a quantitative and halo-independent way whether the experiments point towards a consistent dark matter signal and identifies the best-fit dark matter parameters. To achieve true halo independence, we apply a recently developed method based on finding the velocity distribution that best describes a given set of data. For a quantitative global analysis we construct a likelihood function suitable for small numbers of events, which allows us to determine the best-fit particle physics properties of dark matter considering all experiments simultaneously. Based on this likelihood function we propose a new test statistic that quantifies how well the proposed model fits the data and how large the tension between different direct detection experiments is. We perform Monte Carlo simulations in order to determine the probability distribution function of this test statistic and to calculate the p-value for both the dark matter hypothesis and the background-only hypothesis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Statistical estimates of the binary properties of rotational variables

ABSTRACT We present a model to estimate the average primary masses, companion mass ranges, the inclination limit for recognizing a rotational variable, and the primary mass spreads for populations of binary stars. The model fits a population’s binary mass function distribution and allows for a probability that some mass functions are incorrectly estimated. Using tests with synthetic data, we assess the model’s sensitivity to each parameter, finding that we are most sensitive to the average primary mass and the minimum companion mass, with less sensitivity to the inclination limit and little to no sensitivity to the primary mass spread. We apply the model to five populations of binary spotted rotational variables identified in ASAS-SN, computing their binary mass functions using RV data from APOGEE. Their average primary mass estimates are consistent with our expectations based on their CMD locations ($\sim 0.75 \, {\rm M}_{\odot }$ for lower main sequence primaries and $\sim 0.9$–$1.2 \, {\rm M}_{\odot }$ for RS CVn and sub-subgiants). Their companion mass range estimates allow companion masses down to $M_2/M_1\simeq 0.1$, although the main sequence population may have a higher minimum mass fraction ($\sim 0.4$). We see weak evidence of an inclination limit $\gtrsim 50^{\circ }$ for the main sequence and sub-subgiant groups and no evidence of an inclination limit in the other groups. No groups show strong evidence for a preferred primary mass spread. We conclude by demonstrating that the approach will provide significantly better estimates of the primary mass and the minimum mass ratio and reasonable sensitivity to the inclination limit with 10 times as many systems.

Phillips, Anya (ORCID:000900051914974X)↗
DOE OSTI2025

Dynamics-based halo model for large scale structure

Accurate modeling of the one-to-two halo transition has long been difficult to achieve. Here, we demonstrate that physically motivated halo definitions that respect the bimodal phase-space distribution of dark matter particles near halos resolves this difficulty. Specifically, the two phase-space components are overlapping and correspond to (1) particles orbiting the halo and (2) particles infalling into the halo for the first time. Motivated by this decomposition, García et al. [Mon. Not. R. Astron. Soc. 521, 2464 (2023)] advocated for defining halos as the collection of particles orbiting their self-generated potential. This definition identifies the traditional one-halo term of the halo-mass correlation function with the distribution of orbiting particles around a halo, while the two-halo term governs the distribution of infalling particles. We use dark matter simulations to demonstrate that the distribution of orbiting particles is finite and can be characterized by a single physical scale 𝑟 h , which we refer to as the halo radius. The two-halo term is described using a simple yet accurate empirical model based on the Zel’dovich correlation function. We further demonstrate that the halo radius imprints itself on the distribution of infalling particles at small scales. Our final model for the halo-mass correlation function is accurate at the ≈ 2% level for 𝑟∈ [0.1, 50] ℎ −1 Mpc. The Fourier transform of our best-fit model describes the halo-mass power spectrum with comparable accuracy for 𝑘 ∈ [0.06, 6.0] ℎ Mpc −1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Sci-Fri AM: Quality, Safety, and Professional Issues 04: Predicting waiting times in Radiation Oncology using machine learning

We describe a method for predicting waiting times in radiation oncology. Machine learning is a powerful predictive modelling tool that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The patient waiting experience remains one of the most vexing challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick and in pain, to worry about when they will receive the care they need. In radiation oncology, patients typically experience three types of waiting: Waiting at home for their treatment plan to be prepared Waiting in the waiting room for daily radiotherapy Waiting in the waiting room to see a physician in consultation or follow-up These waiting periods are difficult for staff to predict and only rough estimates are typically provided, based on personal experience. In the present era of electronic health records, waiting times need not be so uncertain. At our centre, we have incorporated the electronic treatment records of all previously-treated patients into our machine learning model. We found that the Random Forest Regression model provides the best predictions for daily radiotherapy treatment waiting times (type 2). Using this model, we achieved a median residual (actual minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. The main features that generated the best fit model (from most to least significant) are: Allocated time, median past duration, fraction number and the number of treatment fields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Constraining the H i–Halo Mass Relation from Galaxy Clustering

We study the dependence of galaxy clustering on H i mass using ∼16,000 galaxies with redshift in the range of 0.0025 10{sup 8} M{sub ⊙}, drawn from the 70% complete sample of the Arecibo Legacy Fast ALFA survey. We construct subsamples of galaxies with M{sub HI} above different thresholds and make volume-limited clustering measurements in terms of three statistics: the projected two-point correlation function, the projected cross-correlation function with respect to a reference sample, and the redshift-space monopole moment. In contrast to previous studies, which found no/weak H i mass dependence, we find both the clustering amplitudes on scales above a few megaparsecs and the bias factors to increase significantly with increasing H i mass for M{sub HI}>10{sup 9} M{sub ⊙}. For H i mass thresholds below ∼10{sup 9} M{sub ⊙}, the inferred galaxy bias factors are systematically lower than the minimum halo bias from mass-selected halo samples. We extend the simple halo model, in which the galaxy content is only determined by halo mass, by including the halo formation time as an additional parameter. A model that puts H i-rich galaxies into halos that formed late can reproduce the clustering measurements reasonably well. We present the implications of our best-fitting model on the correlation of H i mass with halo mass and formation time, as well as the halo occupation distributions and H i mass functions for central and satellite galaxies. These results are compared with the predictions from semianalytic galaxy formation models and hydrodynamic galaxy formation simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Early Blue Excess from the Type Ia Supernova 2017cbv and Implications for Its Progenitor

We present very early, high-cadence photometric observations of the nearby Type Ia SN 2017cbv. The light curve is unique in that it has a blue bump during the first five days of observations in the U , B , and g bands, which is clearly resolved given our photometric cadence of 5.7 hr during that time span. We model the light curve as the combination of early shocking of the supernova ejecta against a nondegenerate companion star plus a standard SN Ia component. Our best-fit model suggests the presence of a subgiant star 56 R {sub ☉} from the exploding white dwarf, although this number is highly model-dependent. While this model matches the optical light curve well, it overpredicts the observed flux in the ultraviolet bands. This may indicate that the shock is not a blackbody, perhaps because of line blanketing in the UV. Alternatively, it could point to another physical explanation for the optical blue bump, such as interaction with circumstellar material or an unusual nickel distribution. Early optical spectra of SN 2017cbv show strong carbon (C ii λ 6580) absorption up through day −13 with respect to maximum light, suggesting that the progenitor system contains a significant amount of unburned material. These early results on SN 2017cbv illustrate the power of early discovery and intense follow-up of nearby supernovae to resolve standing questions about the progenitor systems and explosion mechanisms of SNe Ia.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Carbon exchange in an Amazon forest: from hours to years

Abstract. In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well ( R 2 = 0.81 and 0.59, respectively). Modeled phenology explained 1 % of hourly and 26 % of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light- or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgC ha −1 of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

XRISM Spectroscopy of the Fe Kα Emission Line in the Seyfert Active Galactic Nucleus NGC 4151 Reveals the Disk, Broad-line Region, and Torus

Abstract We present an analysis of the first two XRISM/Resolve spectra of the well-known Seyfert-1.5 active galactic nucleus (AGN) in NGC 4151, obtained in 2023 December. Our work focuses on the nature of the narrow Fe K α emission line at 6.4 keV, the strongest and most common X-ray line observed in AGN. The total line is found to consist of three components. Even the narrowest component of the line is resolved with evident Fe K α ,1 (6.404 keV) and K α ,2 (6.391 keV) contributions in a 2:1 flux ratio, fully consistent with neutral gas with negligible bulk velocity. Subject to the limitations of our models, the narrowest and intermediate-width components are consistent with emission from optically thin gas, suggesting that they arise in a disk atmosphere and/or wind. Modeling the three line components in terms of Keplerian broadening, they are readily associated with (1) the inner wall of the “torus,” (2) the innermost optical “broad-line region” (or “X-ray BLR”), and (3) a region with a radius of r ≃ 100 GM / c 2 that may signal a warp in the accretion disk. Viable alternative explanations of the broadest component include a fast-wind component and/or scattering; however, we find evidence of variability in the narrow Fe K α line complex on timescales consistent with small radii. The best-fit models are statistically superior to simple Voigt functions, but when fit with Voigt profiles the time-averaged lines are consistent with a projected velocity broadening of FWHM = 1600 − 200 + 400 km s − 1 . Overall, the resolution and sensitivity of XRISM show that the narrow Fe K line in AGN is an effective probe of all key parts of the accretion flow, as it is currently understood. We discuss the implications of these findings for our understanding of AGN accretion, future studies with XRISM, and X-ray-based black hole mass measurements.

Audard, Marc (ORCID:000000034721034X)↗
DOE OSTI2013

Molecular Biomarker-Based Biokinetic Modeling of a PCE-Dechlorinating and Methanogenic Mixed Culture

Bioremediation of chlorinated ethenes via anaerobic reductive dechlorination relies upon the activity of specific microbial population-most notably Dehalococcoides (DHC) strains. In the lab and field Dehalococcoides grow most robustly in mixed communities which usually contain both fermenters and methanogens. Recently, researchers have been developing quantitative molecular biomarkers to aid in field site diagnostics and it is hoped that these biomarkers could aid in the modeling of anaerobic reductive dechlorination. A comprehensive biokinetic model of a community containing Dehalococcoides mccartyi (formerly D. ethenogenes) was updated to describe continuously fed reactors with specific biomass levels based on quantitative PCR (qPCR)-based population data (DNA and RNA). The model was calibrated and validated with subsets of chemical and molecular biological data from various continuous feed experiments (n = 24) with different loading rates of the electron acceptor (1.5 to 482 μeeq/L-h), types of electron acceptor (PCE, TCE, cis-DCE) and electron donor to electron acceptor ratios. The resulting model predicted the sum of dechlorination products vinyl chloride (VC) and ethene (ETH) well. However, VC alone was under-predicted and ETH was over predicted. Consequently, competitive inhibition among chlorinated ethenes was examined and then added to the model. Additionally, as 16S rRNA gene copy numbers did not provide accurate model fits in all cases, we examined whether an improved fit could be obtained if mRNA levels for key functional enzymes could be used to infer respiration rates. The resulting empirically derived mRNA “adjustment factors” were added to the model for both DHC and the main methanogen in the culture (a Methanosaeta species) to provide a more nuanced prediction of activity. Results of this study suggest that at higher feeding rates competitive inhibition is important and mRNA provides a more accurate indicator of a population’s instantaneous activity than 16S rRNA gene copies alone as biomass estimates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Low energy neutron light output characterization of EJ301D and deuterated stilbene with a comparison of light output characterization methods

The neutron-induced light yield of a 2.54 cm diameter by 2.54 cm long right circular cylinder of EJ301D and a (5.08 cm)3 custom made cube of deuterated trans-stilbene-d12 (d-stilbene) were measured over incident neutron energies from 300 keV to 2.2 MeV and 200 keV to 2.4 MeV, respectively. The measurements were performed using a time-of-flight experiment with a Cf-252 source and an approximately 1.5 m flight path. We compare three light output spectrum full energy deposition edge estimation methods: (1) simulating the neutron energy spectrum edge and fitting it to the light output spectrum, (2) using the inflection point of the light output spectrum edge (derivative method, a.k.a. Kornilov’s method), and (3) using an empirical model fit to the edge of the light output spectrum. Both the derivative and equation fit methods do not account for physical processes such as multiple neutron scattering in the detectors. They instead rely on assumptions about the linear shape continuum shape of the light output spectrum and the direct correlation between the location of the spectrum’s inflection point and maximum energy deposition. These assumptions were found to introduce bias into those methods when tested against simulated spectra with known edge locations. When tested against measured spectra the derivative method was found to differ from the simulation fit by greater than 30% at low energies with large discontinuities for adjacent data points above 800 keV incident neutron energy. The empirical equation fitting method was found to also exhibit bias of a similar magnitude, but with significantly more continuous behavior, especially with the lower count data of the smaller volumed EJ301D scintillator. Experimental light output yield for this neutron energy range is reported using the simulated spectrum fitting method because it includes physics neglected by the other methods, and did not exhibit the bias observed in the other methods

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Multiple emission components in the Cygnus cocoon detected from Fermi -LAT observations

Star-forming regions may play an important role in the life cycle of Galactic cosmic rays (CRs), notably as home to specific acceleration mechanisms and transport conditions. Gamma-ray observations of Cygnus X have revealed the presence of an excess of hard-spectrum gamma-ray emission, possibly related to a cocoon of freshly accelerated particles. We seek an improved description of the gamma-ray emission from the cocoon using ~13 yr of observations with the Fermi-Large Area Telescope (LAT) and use it to further constrain the processes and objects responsible for the young CR population. We developed an emission model for a large region of interest, including a description of interstellar emission from the background population of CRs and recent models for other gamma-ray sources in the field. Thus, we performed an improved spectro-morphological characterisation of the residual emission including the cocoon. The best-fit model for the cocoon includes two main emission components: an extended component FCES G78.74+1.56, described by a 2D Gaussian of extension r 68 = 4.4° ± 0.1° -0.1° +0.1° and a smooth broken power law spectrum with spectral indices 1.67 ± 0.05 -0.01 +0.02 and 2.12 ± 0.02 -0.01 +0.00 below and above 3.0 ± 0.6 -0.2 +0.0 GeV, respectively; and a central component FCES G80.00+0.50, traced by the distribution of ionised gas within the borders of the photo-dissociation regions and with a power law spectrum of index 2.19 ± 0.03 -0.01 +0.00 that is significantly different from the spectrum of FCES G78.74+1.56. An additional extended emission component FCES G78.83+3.57, located on the edge of the central cavities in Cygnus X and with a spectrum compatible with that of FCES G80.00+0.50, is likely related to the cocoon. For the two brightest components FCES G80.00+0.50 and FCES G78.74+1.56, spectra and radial-azimuthal profiles of the emission can be accounted for in a diffusion-loss framework involving one single population of non-thermal particles with a flat injection spectrum. Particles span the full extent of FCES G78.74+1.56 as a result of diffusion from a central source, and give rise to source FCES G80.00+0.50 by interacting with ionised gas in the innermost region. For this simple diffusion-loss model, viable setups can be very different in terms of energetics, transport conditions, and timescales involved, and both hadronic and leptonic scenarios are possible. The solutions range from long-lasting particle acceleration, possibly in prominent star clusters such as Cyg OB2 and NGC 6910, to a more recent and short-lived release of particles within the last 10–100 kyr, likely from a supernova remnant. The observables extracted from our analysis can be used to perform detailed comparisons with advanced models of particle acceleration and transport in star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Electrons Emitted From Small Dust Grains: Comparison Of Sphere And Cube

Dust grains are exposed to high-energy electrons in different plasma environments. We have developed the numerical model that provides a description of the electron-solid (represented by grain surface) interaction. The model fits the experimental data from spherical samples of different materials rather well, however, dust grains in space are often edgy and coarse. Thus we extended grain geometry in the model to cubes as a first approximation of irregular surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Functionalization of Single-walled Carbon Nanotubes with Thermo-reversible Block Copolymers and Characterization by Small-angle Neutron Scattering

We demonstrate a protocol for single-walled carbon nanotube functionalization using thermo-sensitive PEO-PPO-PEO triblock copolymers in an aqueous solution In a carbon nanotube/PEO105-PPO70-PEO105 (poloxamer 407) aqueous solution, the amphiphilic poloxamer 407 adsorbs onto the carbon nanotube surfaces and self-assembles into continuous layers, driven by intermolecular interactions between constituent molecules. The addition of 5-methylsalicylic acid changes the self-assembled structure from spherical-micellar to a cylindrical morphology. The fabricated poloxamer 407/carbon nanotube hybrid particles exhibit thermo-responsive structural features so that the density and thickness of poloxamer 407 layers are also reversibly controllable by varying temperature. The detailed structural properties of the poloxamer 407/carbon nanotube particles in suspension can be characterized by small-angle neutron scattering experiments and model fit analyses. The distinct curve shapes of the scattering intensities depending on temperature control or addition of aromatic additives are well described by a modified core-shell cylinder model consisting of a carbon nanotube core cylinder, a hydrophobic shell, and a hydrated polymer layer. In conclusion, this method can provide a simple but efficient way for the fabrication and in-situ characterization of carbon nanotube-based nano particles with a structure-tunable encapsulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗