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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Atomistic origins of biomass recalcitrance in organosolv pretreatment

Separation of lignocellulosic biomass components for use in sustainable energy and biomaterials applications remains challenging, since biopolymers such as cellulose and hemicellulose carbohydrates and polyaromatic lignin are found in close proximity within the plant secondary cell wall. Organic solvents have been used to pretreat recalcitrant biomass and separate the interacting polymers, solubilizing the lignin fraction for lignin-first valorization approaches. However, no single organosolv pretreatment approach has proven superior for heterogeneous biomass samples. Here we present a complementary atomic view of interactions between biomass components using molecular simulations, specific to lignin and cellulose, resolving mechanistic hypotheses for how lignin-cellulose composition influences separation processes. Further, using lignin-cellulose binding free energy calculated using molecular simulations, we find polar protic solvents such as methanol and ethanol separate lignin from cellulose, irrespective of the charge on the lignin monomer. Aprotic organic solvents (DMSO, THF, 1,4-dioxane) separate uncharged lignin (phenols and monolignols) from cellulose, while charged lignin (cinnamates) prefer binding to cellulose.

09 BIOMASS FUELS↗
DOE OSTI2018

Structure–Property of Lithium–Sulfur Nanoparticles via Molecular Dynamics Simulation

Lithium-sulfur (Li-S) batteries offer higher energy densities than most reported lithium-ion batteries. However, our understanding of Li-S battery is still largely unknown at the level of the nanoscale. Here, the structural properties of Li-S materials were investigated via molecular dynamics (MD) simulations using the ReaxFF force field. everal Li-S nanoparticles with different Li:S composition ratios (2:1 and 2:8) and various structures are studied. Our MD simulations show that, among the four structures we constructed for Li 2 S 8 nanoparticles, the core-shell structure is the most thermodynamically stable one during the charging (delithiation) process. In contrast to bulk crystal Li 2 S, we find the presence of mixed lithium sulfide and polysulfide species are common features for these Li-S (Li 2 S, Li 2 S 8 ) nanoparticles. The complex distribution of these sulfide and polysulfide speciation are dictated by both stoichiometry and local atomic structures in the nanoparticle. Finally, these findings will provide insight into further development of functionalized lithium-sulfur cathodes.

25 ENERGY STORAGE↗
DOE OSTI2016

Dosimetric comparison of stopping power calibration with dual-energy CT and single-energy CT in proton therapy treatment planning

Purpose: The accuracy of proton dose calculation is dependent on the ability to correctly characterize patient tissues with medical imaging. The most common method is to correlate computed tomography (CT) numbers obtained via single-energy CT (SECT) with proton stopping power ratio (SPR). CT numbers, however, cannot discriminate between a change in mass density and change in chemical composition of patient tissues. This limitation can have consequences on SPR calibration accuracy. Dual-energy CT (DECT) is receiving increasing interest as an alternative imaging modality for proton therapy treatment planning due to its ability to discriminate between changes in patient density and chemical composition. In the current work we use a phantom of known composition to demonstrate the dosimetric advantages of proton therapy treatment planning with DECT over SECT. Methods: A phantom of known composition was scanned with a clinical SECT radiotherapy CT-simulator. The phantom was rescanned at a lower X-ray tube potential to generate a complimentary DECT image set. A set of reference materials similar in composition to the phantom was used to perform a stoichiometric calibration of SECT CT number to proton SPRs. The same set of reference materials was used to perform a DECT stoichiometric calibration based on effective atomic number. The known composition of the phantom was used to assess the accuracy of SPR calibration with SECT and DECT. Intensity modulated proton therapy (IMPT) treatment plans were generated with the SECT and DECT image sets to assess the dosimetric effect of the imaging modality. Isodose difference maps and root mean square (RMS) error calculations were used to assess dose calculation accuracy. Results: SPR calculation accuracy was found to be superior, on average, with DECT relative to SECT. Maximum errors of 12.8% and 2.2% were found for SECT and DECT, respectively. Qualitative examination of dose difference maps clearly showed the dosimetric advantages of DECT imaging, compared to SECT imaging for IMPT dose calculation for the case investigated. Quantitatively, the maximum dose calculation error in the SECT plan was 7.8%, compared to a value of 1.4% in the DECT plan. When considering the high dose target region, the root mean square (RMS) error in dose calculation was 2.1% and 0.4% for SECT and DECT, respectively. Conclusions: DECT-based proton treatment planning in a commercial treatment planning system was successfully demonstrated for the first time. DECT is an attractive imaging modality for proton therapy treatment planning owing to its ability to characterize density and chemical composition of patient tissues. SECT and DECT scans of a phantom of known composition have been used to demonstrate the dosimetric advantages obtainable in proton therapy treatment planning with DECT over the current approach based on SECT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Synthesis of cuboid BiOCl nanosheets coupled with CdS quantum dots by region-selective deposition process with enhanced photocatalytic activity

Highlights: • Region-selective deposition process was adopted to prepare high-dispersed CdS QDs/BiOCl nanocomposites consisting of cuboid BiOCl nanosheets exposing (001) facet and CdS QDs with size of 5–10 nm. • The TGA was used as bridge linked the CdS QDs and BiOCl, which enables CdS QDs spread homogeneously on the (001) facet of BiOCl. • The optical absorption properties and charge transfer efficiency of CdS QDs/BiOCl nanocomposites are much improved owing to the widespread heterojunction between CdS QDs and BiOCl. • The photocatalytic degradation activities of CdS QDs/BiOCl composites are excellent for MO dyes and phenol contaminants under simulated solar and UV light, respectively. - Abstract: A facile region-selective deposition process was adopted to prepare high-dispersed CdS QDs on BiOCl nanosheets with the surface modification of thioglycollic acid (TGA). The samples were systematically characterized by XRD, SEM, TEM, HRTEM, EDS, XPS, UV–vis DRS, EIS and PL. The results indicate that CdS QDs with size of 5–10 nm dispersed uniformly on the surface of cuboid BiOCl nanosheets. The photocatalytic performance tests reveal that the CdS QDs-3%/BiOCl composite exhibits an excellent photocatalytic activity, which is over 4.0 and 4.8 times as high as pure BiOCl for methyl orange (MO) and phenol photodegradation rate under simulated solar light and UV light illumination, respectively. The enhanced photocatalytic performance of the CdS QDs/BiOCl composites should be attributed to the improved visible light absorption and the high migration efficiency of the photogenerated electron-holes due to the matched band gap and the widespread heterostructure between CdS QDs and BiOCl.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

SU-E-J-149: Secondary Emission Detection for Improved Proton Relative Stopping Power Identification

Purpose: This research investigates application of secondary prompt gamma (PG) emission spectra, resulting from nuclear reactions induced by protons, to characterize tissue composition along the particle path. The objective of utilizing the intensity of discrete high-energy peaks of PG is to improve the accuracy of relative stopping power (RSP) values available for proton therapy treatment planning on a patient specific basis and to reduce uncertainty in dose depth calculations. Methods: In this research, MCNP6 was used to simulate PG emission spectra generated from proton induced nuclear reactions in medium of varying composition of carbon, oxygen, calcium and nitrogen, the predominant elements found in human tissue. The relative peak intensities at discrete energies predicted by MCNP6 were compared to the corresponding atomic composition of the medium. Results: The results have shown a good general agreement with experimentally measured values reported by other investigators. Unexpected divergence from experimental spectra was noted in the peak intensities for some cases depending on the source of the cross-section data when using compiled proton table libraries vs. physics models built into MCNP6. While the use of proton cross-section libraries is generally recommended when available, these libraries lack data for several less abundant isotopes. This limits the range of their applicability and forces the simulations to rely on physics models for reactions with natural atomic compositions. Conclusion: Current end-of-range proton imaging provides an average RSP for the total estimated track length. The accurate identification of tissue composition along the incident particle path using PG detection and characterization allows for improved determination of the tissue RSP on the local level. While this would allow for more accurate depth calculations resulting in tighter treatment margins, precise understanding of proton beam behavior in tissue of various compositions is necessary requiring detailed simulations with a high degree of accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

3D Modeling Effect of Spherical Inclusions on the Magnetostriction of Bulk Superconductors

In this paper, the dependence of the effective magnetostriction of bulk superconductors on the elastic parameters including the volume fraction and elastic modulus ratio is studied by a three-dimensional model consisting of a spherical inclusion–superconducting matrix system. The effect of the elastic modulus and volume fraction on the magnetostriction is also obtained through the magnetostriction loop. The results indicate that the elastic modulus and volume fraction have obvious effects on the effective magnetostriction of the superconducting composite, which gives an explanation about the differences between the experimental and the theoretical results. Furthermore, it is worth pointing out that the linear field dependence of magnetostriction is unique to the Bean model by comparing the curve shapes of the magnetostriction loop with and without inclusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗
DOE OSTI2023

Degradation in interfacial shear strength of carbon fiber/ vinyl ester composites due to long-term exposure to seawater using push-out tests

Here, in this study, single fiber (~7-μm diameter) push-out tests are conducted to evaluate hygrothermal effects on the interfacial shear strength (IFSS) of carbon fiber/vinyl ester (CF/VE) composites. Hygrothermal conditioning is achieved by saturating samples in simulated seawater at 40 °C for two years. An investigation has been conducted on the preparation, validity, and interpretation of the push-out test results. First, the authors present a polishing methodology that results in thin films of CF/VE composites in the thickness range of 15–120 μm and produces an average 41.2% drop in IFSS due to long-term hygrothermal exposure. Using scanning electron microscopy (SEM), we show that during the push-out tests, the failure initiates locally at the zone of minimum bond strength at the bottom (away from the indenter), then propagates along the length of the interface. The influence of radial tensile stresses originating due to bending is found to be negligible. Using the SEM imaging of the pushed-out fibers, we validate the failure of the interface to be the primary source of failure. The associated results are found to depend on the thickness of the interface. We then reevaluate the results using the Weibull distribution, knowing that the failure mechanism is analogous to the weakest link theory. The results show a 25.5% drop in the IFSS of the CFVE composite, measured at an infinitesimal scale due to long-term to hygrothermal conditioning at 40 °C. A significant drop in IFSS was observed after reheating above glass transition temperature (T g ) and cooling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sensitivity and history match analysis of a carbon dioxide “huff-and-puff” injection test in a horizontal shale gas well in Tennessee

Due to improvements in well development, shale gas production has gained importance recently, especially in the United States. To improve gas production and develop a better understanding of shale reservoirs, researchers are conducting field tests to monitor CO 2 storage and enhanced gas recovery. Reservoir simulations can then utilize these field results for sensitivity studies, uncertainty analysis, history matching, gas production forecasts, and CO 2 storage capacity estimations. One such field test was performed for the Chattanooga Shale formation in Morgan County, Tennessee. Approximately 463 tonnes (510 tons) of CO 2 was successfully injected into a hydraulically fractured horizontal well over a thirteen-day period in March 2014. The injection test was achieved in four steps: pre-injection, injection, soaking, and flowback. In this paper, those steps were modeled with a reservoir simulator to match the historic production and injection rates with gas component compositions and forecast the production for five years. The reservoir fluid was modeled as a multi-component gas, including CH 4 , C 2 H 6 , C 3 H 8 , N 2 , and CO 2 . Langmuir constants, reservoir pressure, and fracture network volume were adjusted to match simulation results with observed production rates and gas composition. Results showed that, under the same reservoir conditions, each gas component behaves differently by way of compositional changes in production. CH4 behaves like N2, while CO 2 behaves like heavier hydrocarbons such as C 2 H 6 and C 3 H 8 . CO 2 plume results showed that, after injection, the produced CO 2 is mostly derived from fractured limestone (i.e., Fort Payne Formation) because the injected CO 2 is not adsorbed in limestone but rather by shale formations.

03 NATURAL GAS↗
DOE OSTI2020

Increasing Compressed Gas Energy Storage Density Using CO2–N2 Gas Mixture

This paper demonstrates a new method by which the energy storage density of compressed air systems is increased by 56.8% by changing the composition of the compressed gas to include a condensable component. A higher storage density of 7.33 MJ/m3 is possible using a mixture of 88% CO2 and 12% N2 compared to 4.67 MJ/m3 using pure N2. This ratio of gases representing an optimum mixture was determined through computer simulations that considered a variety of different proportions from pure CO2 to pure N2. The computer simulations are based on a thermodynamic equilibrium model that predicts the mixture composition as a function of volume and pressure under progressive compression to ultimately identify the optimal mixture composition (88% CO2 + 12% N2). The model and simulations predict that the optimal gas mixture attains a higher energy storage density than using either of the pure gases.

25 ENERGY STORAGE↗
DOE OSTI2015

Cosmogenic neutrinos and ultra-high energy cosmic ray models

We use an updated version of SimProp, a Monte Carlo simulation scheme for the propagation of ultra-high energy cosmic rays, to compute cosmogenic neutrino fluxes expected on Earth in various scenarios. These fluxes are compared with the newly detected IceCube events at PeV energies and with recent experimental limits at EeV energies of the Pierre Auger Observatory. This comparison allows us to draw some interesting conclusions about the source models for ultra-high energy cosmic rays. We will show how the available experimental observations are almost at the level of constraining such models, mainly in terms of the injected chemical composition and cosmological evolution of sources. The results presented here will also be important in the evaluation of the discovery capabilities of the future planned ultra-high energy cosmic ray and neutrino observatories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Numerical simulation of systems of shear bands in ductile metal with inclusions

We develop a method for numerical simulations of high strain-rate loading of mesoscale samples of ductile metal with inclusions. Because of its small-scale inhomogeneity, the composite material is prone to localized shear deformation (adiabatic shear bands). This method employs the Generalized Method of Cells of Paley and Aboudi [Mech. Materials, vol. 14, pp. 127–139, 1992] to ensure that the micro mechanical behavior of the metal and inclusions is reflected properly in the behavior of the composite at the mesoscale. To find the effective plastic strain rate when shear bands are present, we extend and apply the analytic and numerical analysis of shear bands of Glimm, Plohr, and Sharp [Mech. Materials, vol. 24, pp. 31–41, 1996]. Our tests of the method focus on the stress/strain response in uniaxial-strain flow, both compressive and tensile, of depleted uranium metal containing silicon carbide inclusions. We use the Preston-Tonks-Wallace viscoplasticity model [J. Appl. Phys., vol. 93, pp. 211–220, 2003], which applies to the high strain-rate regime of an isotropic viscoplastic solid. In results, we verify the elevated temperature and thermal softening at shear bands in our simulations of pure DU and DU/SiC composites. We also note that in composites, due the asymmetry caused by the inclusions, shear band form at different times in different subcells. In particular, in the subcells near inclusions, shear band form much earlier than they do in pure DU.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Numerical approach of the injection molding process of fiber-reinforced composite with considering fiber orientation

One of the most important challenges in the injection molding process of the short-glass fiber/thermoplastic composite parts is being able to predict the fiber orientation, since it controls the mechanical and the physical properties of the final parts. Folgar and Tucker included into the Jeffery equation a diffusive type of term, which introduces a phenomenological coefficient for modeling the randomizing effect of the mechanical interactions between the fibers, to predict the fiber orientation in concentrated suspensions. Their experiments indicated that this coefficient depends on the fiber volume fraction and aspect ratio. However, a definition of the fiber interaction coefficient, which is very necessary in the fiber orientation simulations, hasn't still been proven yet. Consequently, this study proposed a developed fiber interaction model that has been introduced a fiber dynamics simulation in order to obtain a global fiber interaction coefficient. This supposed that the coefficient is a sum function of the fiber concentration, aspect ratio, and angular velocity. The proposed model was incorporated into a computer aided engineering simulation package C-Mold. Short-glass fiber/polyamide-6 composites were produced in the injection molding with the fiber weight concentration of 30 wt.%, 50 wt.%, and 70 wt.%. The physical properties of these composites were examined, and their fiber orientation distributions were measured by micro-computed-tomography equipment μ-CT. The simulation results showed a good agreement with experiment results.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Height control of self-assembled quantum dots by strain engineering during capping

Strain engineering during the capping of III-V quantum dots has been explored as a means to control the height of strained self-assembled quantum dots. Results of Kinetic Monte Carlo simulations are confronted with cross-sectional Scanning Tunnel Microscopy (STM) measurements performed on InAs quantum dots grown by molecular beam epitaxy. We studied InAs quantum dots that are capped by In{sub x}Ga{sub (1−x)}As layers of different indium compositions. Both from our realistic 3D kinetic Monte Carlo simulations and the X-STM measurements on real samples, a trend in the height of the capped quantum dot is found as a function of the lattice mismatch between the quantum dot material and the capping layer. Results obtained on additional material combinations show a generic role of the elastic energy in the control of the quantum dot morphology by strain engineering during capping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Phylogenetic conservation of soil bacterial responses to simulated global changes.

Soil bacterial communities are altered by anthropogenic drivers such as climate change-related warming and fertilization. However, we lack a predictive understanding of how bacterial communities respond to such global changes. Here, we tested whether phylogenetic information might be more predictive of the response of bacterial taxa to some forms of global change than others. We analysed the composition of soil bacterial communities from perturbation experiments that simulated warming, drought, elevated CO2 concentration and phosphorus (P) addition. Bacterial responses were phylogenetically conserved to all perturbations. The phylogenetic depth of these responses varied minimally among the types of perturbations and was similar when merging data across locations, implying that the context of particular locations did not affect the phylogenetic pattern of response. We further identified taxonomic groups that responded consistently to each type of perturbation. These patterns revealed that, at the level of family and above, most groups responded consistently to only one or two types of perturbations, suggesting that traits with different patterns of phylogenetic conservation underlie the responses to different perturbations. We conclude that a phylogenetic approach may be useful in predicting how soil bacterial communities respond to a variety of global changes. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modelling dislocation-graphene interactions in a BCC Fe matrix by molecular dynamics simulations and gradient plasticity theory

We report graphene nanosheets (GNS) can enhance the strength and ductility of metal-based composites as they can obstruct the propagation of dislocations. The present article employs Molecular Dynamics (MD) simulations to investigate dislocation-GNS interaction mechanisms and possible influencing factors, including the number of GNS layers, the thickness of the metallic amorphous layer and the C - C bond strength. The results indicated that the shear strength of the metal/GNS interface and the bending stiffness of GNS determined the ability of GNS to block dislocation transmission. A physically based phenomenological parameter that can capture such dislocation-GNS interactions is the mechanical interface energy that has been put forth within gradient plasticity. By fitting the theoretical expressions to the simulation data, it was possible to obtain estimates for the mechanical interface energy for the GNS. It was found that increasing the GNS layers and adding an amorphous layer resulted in a strengthening in the stress–strain response and increased the value of this interfacial parameter. This indicates that the mechanical interfacial energy can be a unified measure for capturing and tuning the strength of various interfaces such as grain boundaries, GNS, amorphous-crystalline interface and bimetal interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sulfonated polybenzimidazole membrane with graphene oxide additive for 2,3-butanediol/water separation: A molecular simulation

Membrane separation for 2,3-butanediol (2,3-BDO) recovery from fermentation broth is highly valued for sustainable and renewable processes, but it requires efficient membrane materials. Here, this work evaluates the sulfonated polybenzimidazole (sPBI) and its graphene oxide (GO) doped composite membrane for separating 2,3-BDO and water via atomistic simulations. Density functional theory calculations are applied to identify various forms of sPBI structures and quantify their binding interactions with 2,3-BDO and water. Classical molecular dynamic simulations are used to evaluate the structural changes, diffusivity, and selectivity of 2,3-BDO and water in different sPBI models, GO surfaces, and GO-doped sPBI composite models. Our results suggest that sPBI slightly increases the crystallinity of the membrane structures, enhances the adsorption strength for both 2,3-BDO and water, and improves the water/2,3-BDO selectivity by 2–3 times. The GO surfaces display a maximum selectivity at a surface coverage of 0.1–0.15 for both hydroxyl and epoxy surface groups. The addition of GO flakes to sPBI creates new interaction sites for 2,3-BDO and water at the interface of sPBI and GO, and the water/2,3-BDO selectivity of GO-doped sPBI models is further increased up to 3 times. This work illustrates how the integrated addition of sPBI and GO flakes offers a promising approach to selective separation of 2,3-BDO and water, providing theoretical guidance for polybenzimidazole-based membranes in the potential application of 2,3-BDO recovery.

2,3-butanediol↗
DOE OSTI2020

Optimization of the JUNO liquid scintillator composition using a Daya Bay antineutrino detector

To maximize the light yield of the liquid scintillator (LS) for the Jiangmen Underground Neutrino Observatory (JUNO), a 20 t LS sample was produced in a pilot plant at Daya Bay. The optical properties of the new LS in various compositions were studied by replacing the gadolinium-loaded LS in one antineutrino detector. The concentrations of the fluor, PPO, and the wavelength shifter, bis-MSB, were increased in 12 steps from 0.5 g/L and 0.01 mg/L to 4 g/L and 13 mg/L, respectively. The numbers of total detected photoelectrons suggest that, with the optically purified solvent, the bis-MSB concentration does not need to be more than 4 mg/L. In order to bridge the one order of magnitude in the detector size difference between Daya Bay and JUNO, the Daya Bay data were used to tune the parameters of a newly developed optical model. Then, the model and tuned parameters were used in the JUNO simulation. Overall, this enabled to determine the optimal composition for the JUNO LS: purified solvent LAB with 2.5 g/L PPO, and 1 to 4 mg/L bis-MSB.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗