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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Processing and characterization of multi-cellular monolithic bioceramics for bone regenerative scaffolds

Multicellular monolithic ceramic body is a ceramic material which has many gas or liquid passages partitioned by thin walls throughout the bulk material. There are many currently known advanced industrial applications of multicellular ceramics structures i.e. as supports for various catalysts, electrode support structure for solid oxide fuel cells, refractories, electric/electronic materials, aerospace vehicle re-entry heat shields and biomaterials for dental as well as orthopaedic implants by naming only a few. Multicellular ceramic bodies are usually made of ceramic phases such as mullite, cordierite, aluminum titanate or pure oxides such as silica, zirconia and alumina. What make alumina ceramics is excellent for the above functions are the intrinsic properties of alumina which are hard, wear resistant, excellent dielectric properties, resists strong acid and alkali attacks at elevated temperatures, good thermal conductivities, high strength and stiffness as well as biocompatible. In this work the processing technology leading to truly multicellular monolithic alumina ceramic bodies and their characterization are reported. Ceramic slip with 66 wt.% solid loading was found to be optimum as impregnant to the polyurethane foam template. Mullitic ceramic composite of alumina-sodium alumino disilicate-Leucite-like phases with bulk and true densities of 0.852 and 1.241 g cm{sup −3} respectively, pore linear density of ±35 cm{sup −1}, linear and bulk volume shrinkages of 7-16% and 32 vol.% were obtained. The compressive strength and elastic modulus of the bioceramics are ≈0.5-1.0 and ≈20 MPa respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Monte Carlo/CFD Coupling for Accurate Modeling of the Delayed Neutron Precursors and Compressibility Effects in Molten Salt Reactors

Multiphysics reactor analysis has become one of the leading activities of most nuclear engineering research groups. Coupled neutronics and thermal/hydraulics (T/H) simulations have traditionally been performed by adopting deterministic transport tools and reactor system T/H codes. The main reason for avoiding higher fidelity numerical methods like continuous-energy Monte Carlo analysis has been the high computational cost of coupled, full-scale simulations. Nowadays, high fidelity multiphysics simulations represent a hot research topic, with several applications involving advanced nuclear systems. Liquid fuel Molten Salt Reactors (MSRs) feature peculiar physical phenomena that are not present in solid fuel reactors. Some of these phenomena are not correctly resolved by legacy reactor physics tools, and require specific treatments. This work focuses in particular on the analysis of the effect of the delayed neutron precursors drift and the impact of liquid fluid thermal expansion and compressibility in postulated criticality excursion transients in fast-spectrum MSRs. A new modeling tool based on a Monte Carlo approach for neutronics (Serpent code) coupled to a Computational Fluid Dynamic (CFD) analysis (OpenFOAM) was developed to obtain accurate modeling and simulation of these phenomena. The development of the Serpent Monte Carlo code [1] at VTT in the past few years has made this code particularly attractive for performing multiphysics studies. The availability of a flexible multiphysics interface, on-the-fly Doppler broadening and density-based collision rejection, and Delta-tracking, proved of paramount importance for the computationally efficient performance of coupled Monte Carlo/CFD calculations [2]. OpenFOAM is a C++ multiphysics toolkit featured by automatic matrix construction and solution capabilities for scalar and vector partial differential equations (PDEs), adopting several possible differencing and interpolation schemes, based on the Finite-Volume method. The ease of implementing the constitutive equations of different physical phenomena makes OpenFOAM particularly suitable for the modeling of complex coupled phenomena. In the past, several research activities proposed the adoption of both Serpent and OpenFOAM for the modeling and simulation of MSRs and the associated fuel cycles. In this work, these tools have been internally coupled for the steady-state and transient analysis of fast-spectrum systems, accounting for the effect of delayed neutron precursors transport and the salt thermal expansion and compressibility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Steam-air blown bubbling fluidized bed biomass gasification (BFBBG): Multi-scale models and experimental validation

During fluidized bed biomass gasification, complex gas-solid mixing patterns and numerous chemical and physical phenomena make identification of optimal operating conditions challenging. In this work, a parametric experimental campaign was carried out alongside the development of a coupled reactor network model which successfully integrates the individually validated sub-models to predict steady-state reactor performance metrics and outputs. The experiments utilized an integrated gasification system consisting of an externally-heated, bench-scale, 4-in., 5 kWth, fluidized bed steam/air blown gasifier fed with woody biomass equipped with a molecular beam mass spectrometer to directly measure tar species. The operating temperature (750-850°C) and air/fuel equivalence ratio (ER = 0-0.157) were independently varied to isolate their effects. Elevating temperature is shown to improve the char gasification rate and reduce tar concentrations. In conclusion, air strongly impacts the composition of tar, accelerating the conversion of lighter polycyclic-aromatic hydrocarbons into soot precursors, while also improving the overall carbon conversion.

09 BIOMASS FUELS↗
DOE OSTI2018

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

This study focused on assessing the effect of mesoscale solid stress in the coarse grid two‐fluid model (TFM) simulation of gas–solid fluidized beds of Geldart Group A particles over a broad range of flow regimes, including bubbling, turbulent, fast, and pneumatic transport fluidization regimes. Particularly, the impact of mesoscale solid pressure, mesoscale solid viscosity, and mesoscale solid stress anisotropy were investigated by comparing six different coarse‐grid TFM settings. Compared with the available experimental data, it is found that both the kinetic theory‐based TFM with only drag correction and the filtered TFM can predict the flow behavior in all fluidization regimes. Mesoscale solid pressure and viscosity have the opposite impact on flow hydrodynamics; they compete and offset each other, which confirms the assumption employed in many previous studies that the mesoscale solid stress could be neglected in coarse‐grid TFM simulation. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. AIChE J , 64: 3565–3581, 2018

Gao, Xi↗
DOE OSTI2025

Microstructure-sensitive mechanical behavior of an additively manufactured psuedoelastic shape memory alloy

The additive manufacturing of shape memory alloys into complex geometries enables fabrication of advanced functional systems across a variety of fields and domains. This work presents results focused on the mechanical behavior of additively manufactured shape memory pseudoelastic NiTi. The deformation induced solid state phase transformation from austenite to martensite allows this system to accommodate large recoverable strains. This deformation behavior is fundamentally driven by crystal-scale transformation physics. Laser powder bed fusion processing reveals that the resulting microstructure, both grain morphology and crystallographic texture, is strongly dependent on the manufacturing processing history. Exhaustive mechanical testing demonstrates that these microstructural factors strongly impact both tensile and cyclic stress–strain behavior. Cyclic dissipative behavior, however, is similar across all tested microstructures following an initial transient period. Remarkably, analysis of spatial strain fields during tensile loading reveals two distinctly different localization “modes”. The first is initiation of localized deformation bands which continuously propagate through the tensile bar during loading. In the second mode localization is observed but lacks propagation; instead additional localization cites nucleate during subsequent loading. The latter phenomena is suspected to be driven by grain-scale deformation physics as the localized band morphologies coincide with grain morphologies. These phenomena strongly impact the resulting aggregate stress–strain behavior. Hence, manufacturers and designers of psuedoelastic functional components must at the very least consider the potential variability in properties when considering additive manufacturing processing. More ideally the process–structure–property relations can be used to further tailor and optimize final functional performance.

Additive manufacturing↗
DOE OSTI2018

Development of silica-enriched cement-based materials with improved aging resistance for application in high-temperature environments

Understanding the effects of high temperature (HT) and high pressure (HP) conditions on the microstructure of cement-based materials is critical to the construction and safe operation of deep oil and gas wells. Under such conditions, the persistence of calcium-silicate-hydrate (C-S-H) gel is compromised by ongoing crystallization that, if not controlled, may adversely affect the durability of the cement sheath. This work investigates the effect of silica content >35% by-weight-of-cement (BWOC), silica particle size, and solid volume fraction (SVF) on the microstructure and phase composition of cement-silica blends cured hydrothermally at 200 °C and 20.7 MPa. The results of X-ray diffraction and electron microprobe analysis revealed significant impact of these three mix design parameters on the final phase assembly, and on the conversion rate of semi-crystalline C-S-H to gyrolite and 11 Åtobermorite. Incorporation of more fine siliceous material suppressed dissolution of coarse silica particles, resulting in a matrix with improved homogeneity and dominated by fine gel pores. Mixes with lower SVF showed greater formation of 11 Å tobermorite, a higher degree of crystallinity and/or greater crystallite size. Prolonged HTHP curing of all systems (up to three months in this study), irrespective of the initial SVF, increased the fraction of capillary pores, indicating void coalesce caused by crystal growth. However, we find that this coarsening is less pronounced in systems with less pore space available for crystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Use of an ion mobility spectrometer for detecting uranium compounds

The safeguards community currently lacks a method to rapidly determine the chemical form of radioactive and non-radioactive compounds in real time during inspection activities. Chemical speciation identification can provide important information on both the types of materials that are collected during environmental sampling and can inform inspectors as to where to focus efforts during inspections or complementary access visits. Ion Mobility Spectrometry (IMS) is an established field technique for the detection of explosives, narcotics, and other organic compounds. More recently, electrospray ionization (ESI) has been used to introduce inorganic compounds to IMS instruments for analysis. These techniques have shown the ability to supply chemical information about the compounds being analyzed. Although these laboratory based instruments use a liquid-based injection system, there is evidence in the literature of unaltered and intact pharmaceutical tablets being volatilized and ionized in open atmosphere using heat and a Ni-63 source. Lastly, this work determined that a commercial-off-the-shelf (COTS) IMS could be used for the identification of solid uranium compounds directly after sampling using a COTS sample swipe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Pyrolysis reaction models of waste tires: Application of Master-Plots method for energy conversion via devolatilization

Highlights: • Pyrolysis kinetics of waste tire was studied. • Activation energy was obtained using model free methods. • Master Plots were used to predict pyrolysis reaction model. • Reaction model was in a good agreement with experimental data. - Abstract: Land applied disposal of waste tires has far-reaching environmental, economic, and human health consequences. Pyrolysis represents a potential waste management solution, whereby the solid carbonaceous residue is heated in the absence of oxygen to produce liquid and gaseous fuels, and a solid char. The design of an efficient conversion unit requires information on the reaction kinetics of pyrolysis. This work is the first to probe the appropriate reaction model of waste tire pyrolysis. The average activation energy of pyrolysis was determined via iso-conversional methods over a mass fraction conversion range between 0.20 and 0.80 to be 162.8 ± 23.2 kJ mol{sup −1}. Using the Master Plots method, a reaction order of three was found to be the most suitable model to describe the pyrolytic decomposition. This suggests that the chemical reactions themselves (cracking, depolymerization, etc.), not diffusion or boundary layer interactions common with carbonaceous biomasses, are the rate-limiting steps in the pyrolytic decomposition of waste tires.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Wetting of a Hydrophobic Surface: Far-IR Action Spectroscopy and Dynamics of Microhydrated Naphthalene

The interaction of water and polycyclic aromatic hydrocarbons is of fundamental importance in areas as diverse as materials science and atmospheric and interstellar chemistry. The interplay between hydrogen bonding and dipole–π interactions results in subtle dynamics that are challenging to describe from first principles. Here, we employ far-IR action vibrational spectroscopy with the infrared free-electron laser FELIX to investigate naphthalene with one to three water molecules. We observe diffuse bands associated with intermolecular vibrational modes that serve as direct probes of the loose binding of water to the naphthalene surface. These signatures are poorly reproduced by static DFT or Møller–Plesset computations. Instead, a rationalization is achieved through Born–Oppenheimer Molecular Dynamics simulations, revealing the active mobility of water over the surface, even at low temperatures. Therefore, our work provides direct insights into the wetting interactions associated with shallow potential energy surfaces while simultaneously demonstrating a solid experimental–computational framework for their investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Three Regimes of Polymer Surface Dynamics under Crowded Conditions

In this work, single-molecule tracking was used to characterize the mobility of poly(ethylene glycol) chains at a solid–liquid interface over a wide range of surface coverage. Trajectories exhibited intermittent motion consistent with a generalized continuous time random walk (CTRW) model, where strongly confined “waiting times” alternated with rapid flights. The presence of three characteristic regimes emerged as a function of surface coverage, based on an analysis of effective short-time diffusion coefficients, mean-squared displacement, and CTRW distributions. The dilute “site-blocking” regime exhibited increasing short-time diffusion, less confined behavior, and shorter waiting times with higher surface coverage, as anomalously strong adsorption sites were increasingly passivated. At intermediate values of surface coverage, the “crowding” regime was distinguished by the exact opposite trends (slower, more confined mobility), presumably due to increasing intermolecular interactions. The trends reversed yet again in the “brush” regime, where adsorbing molecules interacted weakly with a layer of extended overlapping chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Pseudoelasticity of SrNi2P2 Micropillar via Double Lattice Collapse and Expansion

The maximum recoverable strain of most crystalline solids is less than 1% because plastic deformation or fracture usually occurs at a small strain. In this work, we show that a SrNi 2 P 2 micropillar exhibits pseudoelasticity with a large maximum recoverable strain of ~14% under uniaxial compression via unique reversible structural transformation, double lattice collapse–expansion that is repeatable under cyclic loading. Its high yield strength (~3.8 ± 0.5 GPa) and large maximum recoverable strain bring out the ultrahigh modulus of resilience (~146 ± 19 MJ/m 3 ), a few orders of magnitude higher than that of most engineering materials. The double lattice collapse–expansion mechanism shows stress–strain behaviors similar to that of conventional shape-memory alloys, such as hysteresis and thermo-mechanical actuation, even though the structural changes involved are completely different. Our work suggests that the discovery of a new class of high-performance ThCr 2 Si 2 -structured materials will open new research opportunities in the field of pseudoelasticity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Interfacial Reactivity of Silicon Electrodes: Impact of Electrolyte Solvent and Presence of Conductive Carbon

Silicon (Si) is a promising high-capacity material for lithium-ion batteries; however, its limited reversibility hinders commercial adoption. Approaches such as particle and crystallite size reduction, introduction of conductive carbon, and use of different electrolyte solvents have been explored to overcome these electrochemical limitations. Herein, operando isothermal microcalorimetry (IMC) is used to probe the influence of silicon particle size, electrode composition, and electrolyte additives fluoroethylene carbonate and vinylene carbonate on the heat flow during silicon lithiation. In this work, the IMC data are complemented by X-ray photoelectron and Raman spectroscopies to elucidate differences in solid electrolyte interphase (SEI) composition. Nanosized (~50 nm, n-Si) and micrometer-sized (~4 μm, μ-Si) silicon electrodes are formulated with and without amorphous carbon and electrochemically lithiated in ethylene carbonate (EC), fluoroethylene carbonate (FEC), or vinylene carbonate (VC) based electrolytes. Notably, n-Si electrodes generate 53–61% more normalized heat relative to their μ-Si counterparts, consistent with increased surface area and electrode/electrolyte reactivity. Introduction of amorphous carbon significantly alters the heat flow profile where multiple exothermic peaks and increased normalized heat dissipation are observed for all electrolyte types. Notably, the VC-containing electrolyte demonstrates the greatest normalized heat dissipation of the electrode compositions tested showing as much as a 50% increase compared to the EC or FEC counterparts. The results are relevant to the understanding of silicon negative electrode function in the presence of electrolyte additives and provide insight relative to silicon containing cell reactivity and safety.

25 ENERGY STORAGE↗
DOE OSTI2023

Chemical Feedback in the Self-Assembly and Function of Air–Liquid Interfaces: Insight into the Bottlenecks of CO 2 Direct Air Capture

As fossil fuels remain a major source of energy throughout the world, developing efficient negative emission technologies, such as direct air capture (DAC), which remove carbon dioxide (CO 2 ) from the air, becomes critical for mitigating climate change. Although all DAC processes involve CO 2 transport from air into a sorbent/solvent, through an air–solid or air–liquid interface, the fundamental roles the interfaces play in DAC remain poorly understood. In this work, we study the interfacial behavior of amino acid (AA) solvents used in DAC through a combination of vibrational sum frequency generation spectroscopy and molecular dynamics simulations. This study revealed that the absorption of atmospheric CO 2 has antagonistic effects on subsequent capture events that are driven by changes in bulk pH and specific ion effects that feedback on surface organization and interactions. Among the three AAs (leucine, valine, and phenylalanine) studied, we identify and separate behaviors from CO 2 loading, chemical changes, variations in pH, and specific ion effects that tune structural and chemical degrees of freedom at the air–aqueous interface. The fundamental mechanistic findings described here are anticipated to enable new approaches to DAC based on exploiting interfaces as a tool to address climate change.

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

Reactivity of Carbonate Solvent Electrolytes on Lithium Silicon Anodes

Silicon (Si) is promising for lithium-ion battery (LIB) anodes due to their high theoretical capacity and low electrochemical potential. However, significant challenges remain, including severe volumetric expansion during cycling and the electrochemical instability of electrolytes, which leads to the formation of a nonuniform solid electrolyte interphase (SEI). To investigate SEI formation mechanisms, computational molecular dynamics simulations offer valuable insights. In this work, we examine the trajectories and charge transfer behavior of lithium hexafluorophosphate (LiPF 6 ) salt with various solvent compositions using density functional theory (DFT) and ab initio molecular dynamics (AIMD). Among the tested electrolyte systems, LiPF 6 with vinylene carbonate (VC) added to ethyl methyl carbonate (EMC) exhibits the lowest reactivity with the Si anode. In contrast, the effects of fluoroethylene carbonate (FEC) and VC depend on whether the primary solvent is EMC alone or a mixture of ethylene carbonate (EC) and EMC. Moreover, we show that electrolyte reactivity varies with the degree of lithiation of the Si anode (LiSi vs Li 15 Si 4 ) and under different charge states. To decouple electrolyte reactivity from surface effects, we analyze the dissociation and formation energies of individual species from solvated configurations. Overall, these first-principles-based findings provide a strategic foundation for electrolyte design to improve cycling stability and extend calendar life in LIBs using Si anodes.

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

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2013

The Influence of Functionals on Density Functional Theory Calculations of the Properties of Reducible Transition Metal Oxide Catalysts

Reducible transition metal oxides (RTMOs) comprise an important class of catalytic materials that are used for the selective oxidation and electro- and photochemical splitting of water, and as supports for metal nanoparticles. It is highly desirable to model the properties of these materials accurately using density functional theory (DFT) in order to understand how oxide structure and performance are related and to guide the search for materials exhibiting superior performance. Unfortunately, accurate description of the structural and electronic properties of RTMOs using DFT has proven particularly challenging. The M06-L density functional, which has been shown to be broadly accurate for calculations of gas phase clusters, has recently become available to researchers carrying out calculations in the solid state, but its performance in determining the properties RTMOs has been little investigated. The aim of this work was to assess the performance of the M06-L functional for describing the structural and electronic properties of a family of RTMOs: MoO 2 , MoO 3 , and Bi 2 Mo 3 O 12 . Lattice constants, band gaps, and densities of states calculated using the M06-L functional are compared to those obtained from DFT+U. We have also used the M06-L functional to determine the reaction barrier for propene activation over Bi 2 Mo 3 O 12 , the rate-limiting step in the oxidation of propene to acrolein. We find that while DFT calculations carried out with the M06-L functional are roughly five times more expensive computationally than those performed with DFT+U, the results obtained using the M06-L functional provide sensible results for all properties investigated, while avoiding the necessary trade-off between accurate electronic structure and accurate thermochemistry that occurs in DFT+U.

Getsoian, Andrew “Bean”↗