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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 73 records · Page 4

Effect of the Lignin Structure on the Physicochemical Properties of Lignin-Grafted-Poly(ε-caprolactone) and Its Application for Water/Oil Separation

Lignin-grafted poly(ε-caprolactone) copolymers (lignin-g-PCLs) have shown wide application potentials in coatings, biocomposites, and biomedical fields. However, the structural heterogeneity of lignin affecting the structures and properties of lignin-g-PCL has been scarcely investigated. In this study, kraft lignin is fractionated into four precursors, namely, F ins , F1, F2, and F3, with declining molecular weights and increased hydroxyl contents. Lignin-g-PCLs are synthesized via ring-opening polymerization of ε-caprolactone with lignin and characterized by GPC, FTIR, 1 H and 31 P NMR, DSC, TGA, and iGC. The mechanical properties, UV barrier, and enzymatic biodegradability of the lignin-g-PCLs are evaluated. Results show that lignin with a higher molecular weight and aliphatic OH favors the copolymerization, leading to lignin-g-PCLs with longer PCL arms. Moreover, lignin incorporation improves the thermal stability, hydrophobicity, and UV-blocking ability but reduces the lipase hydrolyzability of the copolymers. We also demonstrated that the lignin-g-PCL-coated filter paper could successfully separate chloroform–, petroleum ether–, and hexane–water mixtures with an efficiency up to 99.2%. The separation efficiency remains above 90% even after 15 cycles. The structural differences of copolymers derived from the fractionation showed minimal influence on the separation efficiency. This work provides new insights into lignin-based copolymerization and the versatility of lignin valorization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deconstruction of Woody Biomass via Protic and Aprotic Ionic Liquid Pretreatment for Ethanol Production

Ionic liquids (ILs) have emerged as important solvents for conversion of lignocellulosic feedstocks to fuels and chemicals due to their ability to enable efficient biomass deconstruction and fractionation. Woody biomass derived from forest and agricultural residues has the potential to be used for production of biofuels and its removal from forests can help mitigate disastrous wildfires in fire-prone states like California. This study evaluated woody biomass types (pine, almond, walnut, and fir) from California as potential biofuel feedstocks. The feedstocks were pretreated with the ILs cholinium lysinate ([Ch][Lys]) and ethanolamine acetate ([EOA][OAc]), followed by enzymatic hydrolysis and fermentation of lignocellulosic sugars to produce ethanol. Under optimal conditions, [EOA][OAc] pretreatment and enzymatic hydrolysis generated glucose and xylose yields in the range of 24-82 and 14-80%, respectively, while glucose and xylose yields for the [Ch][Lys] ranged between 28-83 and 23-80%, respectively. Maximum fermentable sugar was released from almond wood, and the lowest amount was from pine and fir. Further, blends of feedstocks were also explored, and a blend with a mass ratio of 2/2/1 (almond/walnut/pine) resulted in maximum glucose and xylose (>90%) yields using [Ch][Lys]. Fermentation of this hydrolysate using a C5-utilizing strain of Saccharomyces cerevisiae resulted in a maximum ethanol concentration of 17.9 g/L for mixture biomass hydrolysate, corresponding to 60.8% fermentation efficiency. This study represents the first demonstration of the use of these ILs for pretreatment of woody biomass blends that resulted in a high overall conversion efficiency for ethanol production.

09 BIOMASS FUELS↗

Amplification of primordial perturbations from the rise or fall of the inflaton

The next generation of cosmic microwave background, gravitational wave, and large scale structure, experiments will provide an unprecedented opportunity to probe the primordial power spectrum on small scales. An exciting possibility for what lurks on small scales is a sharp rise in the primordial power spectrum: this can lead to the formation of primordial black holes, providing a dark matter candidate or the black holes observed by the LIGO-Virgo collaboration. In this study we develop a mechanism for the amplification of the small-scale primordial power spectrum, in the context of single-field inflation with a step-like feature in the inflaton potential. Specifically, we consider both the upward and the downward step in the potential. We also discuss the possibility of the strong coupling between perturbations because the rapid changes of the potential derivatives with the time-dependent field value, caused by the step-like feature, could make the coupling stronger. As a result, we find that the perturbations can remain weakly coupled yet sufficiently enhanced if the step realizes the rapid changes of the potential derivatives in some fraction of an e-fold, Script O(P R 1/2) ≲ ΔN < 1, where P R is the power spectrum of the curvature perturbation at that time. We also discuss the PBH formation rate from the inflaton trapping at the local minimum, which can occur in the potential with an upward step.

79 ASTRONOMY AND ASTROPHYSICS↗

On the use of neural networks for energy reconstruction in high-granularity calorimeters

We contrasted the performance of deep neural networks — Convolutional Neural Network (CNN) and Graph Neural Network (GNN) — to current state of the art energy regression methods in a finely 3D-segmented calorimeter simulated by GEANT4. This comparative benchmark gives us some insight to assess the particular latent signals neural network methods exploit to achieve superior resolution. A CNN trained solely on a pure sample of pions achieved substantial improvement in the energy resolution for both single pions and jets over the conventional approaches. It maintained good performance for electron and photon reconstruction. We also used the Graph Neural Network (GNN) with edge convolution to assess the importance of timing information in the shower development for improved energy reconstruction. We implement a simple simulation based correction to the energy sum derived from the fraction of energy deposited in the electromagnetic shower component. This serves as an approximate dual-readout analogue for our benchmark comparison. Although this study does not include the simulation of detector effects, such as electronic noise, the margin of improvement seems robust enough to suggest these benefits will endure in real-world application. We also find reason to infer that the CNN/GNN methods leverage latent features that concur with our current understanding of the physics of calorimeter measurement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Revisiting GeV-scale annihilating dark matter with the AMS-02 positron fraction

Antimatter cosmic-rays are used to probe new phenomena in physics, including dark matter annihilation. Here, we use the cosmic-ray positron fraction spectrum by the Alpha Magnetic Spectrometer, to search for such an annihilation signal in the Galaxy. We focus on dark matter with mass between 5 and 120 GeV, producing high-energy electrons and positrons. In these cosmic-ray energies the interplay of multiple astrophysical sources and phenomena, makes this search highly sensitive to the underlying astrophysical background assumptions. We use a vast public library of astrophysical models for the cosmic-ray positron fraction background, to derive robust upper limits on the dark matter's annihilation cross section for a number of annihilation channels. This library accounts for different types of cosmic-ray sources and uncertainties on their distribution in space and time. Also, it accounts for uncertainties on those sources' output, their injected into the interstellar medium cosmic-ray spectra and for uncertainties on cosmic-ray propagation. For any given dark matter particle mass and annihilation channel, upper limits on the annihilation cross section are given by bands that stretch a full order of magnitude in its value. Our work provides weaker limits compared to earlier results, that are however robust to all the relevant astrophysical uncertainties. Between 5 and 15 GeV, we find indications for a possible excess flux of cosmic-ray electrons and positrons. That excess is found for most, but not all of our astrophysical background parameter space, and its significance can vary appreciably. Further scrutiny is necessary to improve the understanding of these lower energy cosmic rays. Finally, we note that even if an excess signal is found in these energies, the current background uncertainties do not allow us to accurately deduce its underlying particle properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessment of CMIP5 and CMIP6 AMIP Simulated Clouds and Surface Shortwave Radiation Using ARM Observations over Different Climate Regions

The simulations of clouds and surface radiation from 10 CMIP6 models and their CMIP5 predecessors are compared to the ARM ground-based observations over different climate regions. Compared to the ARM radar-lidar derived total cloud fractions (CFT) and cloud fraction vertical distributions over the six selected sites, both CMIP5 and CMIP6 significantly underestimated CFT and low-level CF over the Northern Hemispheric midlatitude sites (SGPC1 and ENAC1), although the biases are generally smaller in CMIP6. Over the tropical oceanic site (TWPC2), 5 out of 10 CMIP6 models better simulated low-level CF than their CMIP5 predecessors. CMIP6 simulations generally agreed well with the ARM observations in CFT and cloud fraction vertical distributions over the tropical continental (MAOM1) and coastal (TWPC3) sites but missed the transitions between dry and wet seasons, similar to CMIP5 simulations. The improvements in downwelling shortwave fluxes (SWdn) at the surface from the majority of CMIP6 compared to CMIP5 primarily resulted from the improved cloud fraction simulations, especially over the SGPC1, ENAC1, and TWPC3 sites. By contrast, both CMIP5 and CMIP6 models exhibited diverse performances of clouds and shortwave radiation over the Arctic site (NSAC1), where CMIP6 models produced more clouds than CMIP5 models, especially for the low-level clouds. The comparisons between observations and CMIP5 and CMIP6 simulations provide valuable quantitative assessments of the accuracy of mean states and variabilities in the model simulations and shed light on general directions to improve climate models in different regions.

54 ENVIRONMENTAL SCIENCES↗

VITAL-Viral InhibiTors from ALgae: Generating Extracts for Antiviral Activity Assays

Algae from marine and extreme environments may provide novel compounds with antiviral activity for use in therapeutic drug development. We established a first effort combining experience and cultures used in biofuel research and from the Culture Collection of Microbes from Extreme Environments at PNNL. We generated a novel library of fractionated, algae-derived compounds for guiding research on small molecules in the environment and for the treatment of SARS-CoV-2 and other infectious diseases.

09 BIOMASS FUELS↗

Baryon fraction from the BAO amplitude: a consistent approach to parameterizing perturbation growth

Galaxy clustering constrains the baryon fraction Omega_b/Omega_m through the amplitude of baryon acoustic oscillations and the suppression of perturbations entering the horizon before recombination. This produces a different pre-recombination distribution of baryons and dark matter. After recombination, the gravitational potential responds to both components in proportion to their mass, allowing robust measurement of the baryon fraction. This is independent of new-physics scenarios altering the recombination background (e.g. Early Dark Energy). The accuracy of such measurements does, however, depend on how baryons and CDM are modeled in the power spectrum. Previous template-based splitting relied on approximate transfer functions that neglected part of information. We present a new method that embeds an extra parameter controlling the balance between baryons and dark matter in the growth terms of the perturbation equations in the CAMB Boltzmann solver. This approach captures the baryonic suppression of CDM prior to recombination, avoids inconsistencies, and yields a clean parametrization of the baryon fraction in the linear power spectrum, separating out the simple physics of growth due to the combined matter potential. We implement this framework in an analysis pipeline using Effective Field Theory of Large-Scale Structure with HOD-informed priors and validate it against noiseless LCDM and EDE cosmologies with DESI-like errors. The new scheme achieves comparable precision to previous splitting while reducing systematic biases, providing a more robust way to baryon-fraction measurements. In combination with BBN constraints on the baryon density and Alcock-Paczynski estimates of the matter density, these results strengthen the use of baryon fraction measurements to derive a Hubble constant from energy densities, with future DESI and Euclid data expected to deliver competitive constraints.

Crespi, Andrea [U. Waterloo (main); Waterloo U., I↗

Artificial neural network based isotopic analysis of airborne radioactivity measurement for radiological incident detection

Responders need tools to rapidly detect and identify airborne alpha radioactivity during consequence management scenarios. Traditional continuous air monitor systems used for this purpose compute the net counts in various energy windows to determine the presence of specified isotopes, such as 235U, 239Pu, and 241Am. These calculations rely on having a well-calibrated detector, which is challenging in low-background environments. Here an alternative approach of using artificial neural networks to classify alpha spectra is presented. Two network architectures, fully connected and convolutional networks, were trained to classify alpha spectra into four categories: background and background plus the three isotopes above. Sources were injected into measured background at various fractions of the derived response level (DRL) corresponding to early-phase Protective Action Guides. The convolutional network identifies all sources at 1% of the DRL with average probability of detection of 95% and false alarm probability of 1%. Further, the network identifies sources ranging between 0.25% and 1% of the DRL with higher than 80% probability of detection and lower than 7% false alarm probability. Most significantly, the network performance improves in low-count background conditions, increasing its minimum probability of detection to 93% and reducing the false alarm probabilities to lower than 0.25%. These results show that, once trained on datasets representing a range of detection scenarios, artificial neural networks can accurately identify alpha isotopes of interest without the need for detector calibration.

Woldegiorgis, Surafel F.↗

Estimating the Impact of Seep Methane Oxidation on Ocean pH and Dissolved Inorganic Radiocarbon Along the U.S. Mid-Atlantic Bight

Ongoing ocean warming can release methane (CH 4 ) currently stored in ocean sediments asfree gas and gas hydrates. Once dissolved in ocean waters, this CH 4 can be oxidized to carbon dioxide(CO 2 ). While it has been hypothesized that the CO 2 produced from aerobic CH4oxidation could enhanceocean acidification, a previous study conducted in Hudson Canyon shows that CH 4 oxidation has a smallshort-term influence on ocean pH and dissolved inorganic radiocarbon. Here we expand upon thatinvestigation to assess the impact of widespread CH 4 seepage on CO 2 chemistry and possible accumulationof this carbon injection along 234 km of the U.S. Mid-Atlantic Bight. Consistent with the estimates fromHudson Canyon, we demonstrate that a small fraction of ancient CH 4 -derived carbon is being assimilatedinto the dissolved inorganic radiocarbon (mean fraction of 0.5 ± 0.4%). The areas with the highest fractionsof ancient carbon coincide with elevated CH 4 concentration and active gas seepage. This suggests thataerobic CH 4 oxidation has a greater influence on the dissolved inorganic pool in areas where CH 4 concentrations are locally elevated, instead of displaying a cumulative effect downcurrent from widespreadgroupings of CH 4 seeps. Afirst-order approximation of the input rate of ancient-derived dissolved inorganiccarbon (DIC) into the waters overlying the northern U.S. Mid-Atlantic Bight further suggests thatoxidation of ancient CH 4 -derived carbon is not negligible on the global scale and could contribute todeepwater acidification over longer time scales.

54 ENVIRONMENTAL SCIENCES↗

Anticorrosive epoxy coatings from direct epoxidation of bioethanol fractionated lignin

The development of lignin-based anticorrosive epoxy coatings for steel protection is beneficial for both alleviating the fossil resource depletion and value-added utilization of lignin but remains a challenge due to the inherent heterogeneous structure of lignin. Here, in this study, we selectively extract the low molecular weight (MW) fraction of a crop residue-derived enzymatic hydrolysis lignin (EHL) through a bioethanol fractionation process and prepare epoxy resin by direct epoxidation of the bioethanol fractionated lignin (BFL). The coatings are then fabricated using 20–100 wt% of BFL-based epoxy resin (LEp) as the commercial epoxy resin substitute. The low MW and high p-hydroxyphenyl content of the BFL offer high solubility and good workability for BFL and LEp during epoxidation and coating production, respectively. Lignin-based coatings with 20–40 wt% LEp exhibit good adhesion property (5B) and superior corrosion resistance, compared to the commercial epoxy coating. Although coating with high LEp concentrations (i.e., 60–100 wt%) resulted in decreased adhesion strength, the coating with 100 wt% LEp still displayed corrosion protection performance comparable to that of the commercial epoxy coating. Overall, this study provides a simple and effective approach to converting lignin to epoxy resins for a wide variety of surface coating applications.

09 BIOMASS FUELS↗

Root carbon interation with soil minerals is dynamic, leaving a legacy of microbially derived residues

Minerals preserve the oldest most persistent soil carbon, and mineral characteristics appear to play a critical role in the formation of soil organic matter (SOM) associations. To test the hypothesis that carbon source and soil microorganisms also influence mineral-SOM associations, we incubated permeable minerals bags in soil microcosms with and without plants, in a 13CO2 labelling chamber. Mineral bags contained quartz, ferrihydrite, kaolinite, or native soil minerals isolated via density separation. Using 13C-NMR, FTICR-MS, and lipidomics, we traced plant-derived carbon onto minerals harvested from microcosms at three plant growth stages, characterizing total carbon, 13C enrichment, and SOM chemistry. While C accumulation was rapid and mineral-dependent, the accumulated amount was not significantly affected by the presence of plant roots. However, the rhizosphere did shape the chemistry of mineral-associated SOM. Minerals incubated in the rhizosphere were associated with a more diverse array of compounds with different C functional groups (carbonyl, aromatics, carbohydrates, lipids) than minerals incubated in a bulk soil control. These diverse rhizosphere-derived compounds may represent a “transient fraction” of mineral SOM, rapidly exchanging with mineral surfaces. Our results also suggest that many of the lipids which persist on minerals are microbially-derived with a large fraction of fungal lipids.

Rhizosphere, soil organic matter, grassland, 13C-N↗

Rock-Sourced Nitrogen in Semi-Arid, Shale-Derived California Soils

Models suggest that rock-derived nitrogen (N) inputs are of global importance to ecosystem N budgets; however, field studies demonstrating the significance of rock N inputs are rare. We examined rock-derived N fluxes in soils derived from sedimentary rocks along a catena formed under a semi-arid climate. Our measurements demonstrate that there are distinct and traceable pools of N in the soil and bedrock and that the fraction of rock-derived N declines downslope along the catena. We used geochemical mass balance weathering flux measurements to estimate a rock-derived N flux of 0.145 to 0.896 kg ha -1 yr -1 at the ridgecrest. We also developed independent N flux estimates using a 15 N-based isotope mixing model. While geochemical mass-balance-based estimates fell within the 95% confidence range derived from the isotope mixing model (-1.1 to 44.3 kg ha -1 yr -1 ), this range was large due to uncertainty in values for atmospheric 15 N deposition. Along the catena, N isotopes suggest a diminishing effect of rock-derived N downslope. Overall, we found that despite relatively large N pools within the saprolite and bedrock, slow chemical weathering and landscape denudation limit the influence of rock-derived N, letting atmospheric N deposition (7.1 kg ha -1 yr -1 ) and N fixation (0.9-3.1 kg ha -1 yr -1 ) dominate N inputs to this grassland ecosystem.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the Sum-of-Fractions Methodology for Water and Polyethylene Moderated Systems

Sum-of-Fractions is a method intended to assure a subcritical margin for aqueous solutions and slurries of fissionable isotopes. The method indicates that a system is subcritical if the sum of the ratios of the mass of each isotope in a mixture to its individual minimum subcritical mass limit is less than or equal to one. The basis of the Sum-of Fractions has historically been derived from allowances given in ANSI/ANS-8.15-1981. However, the allowance was removed in ANSI/ANS-8.15-2014 due to a lack of technical basis. A methodology was developed to assess the validity of using the Sum-of-Fractions for water or polyethylene moderated systems for the following nuclides: 232 U, 233 U, 234 U, 235 U, 237 Np, 236 Pu, 238 Pu, 239 Pu, 240 Pu, 241 Pu, 242 Pu, 241 Am, 242 mAm, 243 Am, 242 Cm, 243 Cm, 244 Cm, 245 Cm, 246 Cm, 247 Cm, 249 Cf, and 251 Cf. The methodology uses available benchmark data for mixtures of 233 U, 235 U, and 239 Pu to establish the calculational margin, and a mass limit reduction to establish the margin of subcriticality. Water or polyethylene moderated and reflected mixtures containing the nuclides are evaluated with SCALE 6.2.4. Including the calculational margin, subcritical mass limits for each nuclide were computed for optimally water or polyethylene moderated and fully reflected systems. These masses were used to create nuclide mixtures in which the sum of the mass to subcritical mass limit ratios is one. The various nuclide mixtures were modeled over a range of moderation and demonstrate the k eff does not exceed the calculational margin. For additional assurance of subcriticality, a significant mass reduction is applied to each computed minimum critical mass of the nuclides without adequate benchmark data consistent with the method in ANSI/ANS-8.15-2014.

07 ISOTOPE AND RADIATION SOURCES↗

Learning Spectral Templates for Photometric Redshift Estimation from Broadband Photometry

Estimating redshifts from broadband photometry is often limited by how accurately we can map the colors of galaxies to an underlying spectral template. Current techniques utilize spectrophotometric samples of galaxies or spectra derived from spectral synthesis models. Both of these approaches have their limitations: either the sample sizes are small and often not representative of the diversity of galaxy colors, or the model colors can be biased (often as a function of wavelength), which introduces systematics in the derived redshifts. In this paper, we learn the underlying spectral energy distributions from an ensemble of ∼100 K galaxies with measured redshifts and colors. We show that we are able to reconstruct emission and absorption lines at a significantly higher resolution than the broadband filters used to measure the photometry for a sample of 20 spectral templates. We find that our training algorithm reduces the fraction of outliers in the derived photometric redshifts by up to 28%, bias up to 91%, and scatter up to 25%, when compared to estimates using a standard set of spectral templates. We discuss the current limitations of this approach and its applicability for recovering the underlying properties of galaxies. Our derived templates and the code used to produce these results are publicly available in a dedicated Github repository: https://github.com/dirac-institute/photoz-template-learning.

79 ASTRONOMY AND ASTROPHYSICS↗

Photometry and astrometry with JWST – III. A NIRCam-Gaia DR3 analysis of the open cluster NGC 2506

ABSTRACT In the third paper of this series aimed at developing the tools for analysing resolved stellar populations using the cameras on board of the James Webb Space Telescope (JWST), we present a detailed multiband study of the 2 Gyr Galactic open cluster NGC 2506. We employ public calibration data sets collected in multiple filters to: (i) derive improved effective Point Spread Functions (ePSFs) for 10 NIRCam filters; (ii) extract high-precision photometry and astrometry for stars in the cluster, approaching the main sequence (MS) lower mass of ∼0.1 M⊙; and (iii) take advantage of the synergy between JWST and Gaia DR3 to perform a comprehensive analysis of the cluster’s global and local properties. We derived a MS binary fraction of ∼57.5 per cent, extending the Gaia limit (∼0.8 M⊙) to lower masses (∼0.4 M⊙) with JWST. We conducted a study on the mass functions (MFs) of NGC 2506, mapping the mass segregation with Gaia data, and extending MFs to lower masses with the JWST field. We also combined information on the derived MFs to infer an estimate of the cluster present-day total mass. Lastly, we investigated the presence of white dwarfs (WDs) and identified a strong candidate. However, to firmly establish its cluster membership, as well as that of four other WD candidates and of the majority of faint low-mass MS stars, further JWST equally deep observations will be required. We make publicly available catalogues, atlases, and the improved ePSFs.

Nardiello, D. (ORCID:0000000311493659)↗