SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Research activity related to the science of materials is described. The following areas are included: elastic and thermal properties of composite materials, acoustic waves and devices, amorphous materials, crystal structure, synthesis of metal-metal bonds, interactions of solids with solutions, electrochemistry, fatigue damage, superconductivity and molecular physics and phase transition kinetics.
Surface morphologies of SiC deposits obtained via chemical vapor deposition (CVD) were studied as functions of substrate surface temperature and the concentration of the silicon and carbon source material, methyltrichlorosilane. Substrates of graphite and alpha-SiC crystals were used. Explanations of the observed morphologies on graphite substrates and their marked changes with temperature are given in terms of chemical kinetics and mass transport arguments. The results of thermodynamic calculations were used to help explain the observed morphologies of the deposits on alpha-SiC substrates.
A glass of nominal Bi(1.5)Pb(0.5)Sr2Ca2Cu3O(x) composition, prepared by rapid quenching of the melt, showed a glass transition temperature of 383 C, crystallization temperature of 446 C, melting temperature of 855 C, and bulk density of 5.69 g/cu cm in air. The activation energy for crystallization of the glass was estimated to be 292kJ/mol from non-isothermal DSC. On heating in oxygen, the glass showed a slow and continuous weight gain starting at approximately 530 C which reached a plateau at approximately 820 C. The weight gained during heating was retained on cooling to ambient conditions indicating an irreversible oxidation step. The influence of annealing conditions on the formation of various phases in the glass has been investigated. The Bi(2)Sr(2)Ca(0)Cu(1)O(6) phase crystallized out first followed by formation of other phases at higher temperatures. The high-T(sub c) phase, isostructural with Bi(2)Sr(2)Ca(2)Cu(3)O(10) was not detected below 840 C, but its fraction increased with the annealing time at 840 C. A sample annealed at 840 C for 243h in air and furnace cooled showed the highest T(sub c)(R=0) of 107.2K and a narrow transition width, delta T(sub c)(10 to 90 percent), of approximately 2 K. The high T(sub c) phase does not seem to crystallize out directly from the glass but is rather produced at high temperature by reaction between the phases formed at lower temperatures. The kinetics of 110K phase formation was sluggish. It appears that the presence of lead helps in the formation and/or stabilization of the 110 K phase.
•SO2 is reactive with several common elements e.g. calcium [1-4] •Knowledge on chemical reactions has implications for the past and current state of Venus - Venus may have had liquid water on its surface [5], thus hydrous silicates may have formed at that time [6]. - The Venus Emissivity Mapper (on VERITAS and EnVision) will be used to determine bulk composition of the surface by observing transition metal content [8-9] - Calcium diffuses through basalt to react with CO2 and SO2, changing the bulk composition and decreasing the emissivity from orbit [8] - Experiments investigating kinetics will be informative for future emissivity data •Goal: - Constrain reaction rate between several calcium minerals and SO2 - Determine the effect, if any, crystal lattices may have on these rates
A new finite strain thermomechanical model for the high-rate deformation of the β-polymorph of cyclotetramethylene tetranitramine (β-HMX) has been developed and applied to simulations of plate impact experiments. The crystal plasticity model is based on a model developed previously for RDX (Luscher et al. 2017), which is extended to incorporate deformation twinning. Twinning during normal plate impacts is simulated with a phase-field twin model. First, material parameters governing the kinetics of dislocation slip are calibrated on the subset of simulations which had negative Schmid factors for the twin system. Second, a parametric study of the twin material parameters was performed to find suitable values. Overall, the results of the simulations with the phase-field twinning model are reported for impacts on several crystal orientations. We find that the twin growth decreases with increasing distance from the impact surface because of dissipation of the shock front via dislocation-mediated plasticity, and that the simulated interface velocity with and without phase-field twinning do not show appreciable differences. These modeling results suggest that the significance of twinning in β-HMX cannot be determined with traditional loading configurations and diagnostics.
The dynamic diamond anvil cell (dDAC) technique has attracted great interest because it possibly provides a bridge between static and dynamic compression studies with fast, repeatable, and controllable compression rates. The dDAC can be a particularly useful tool to study the pathways and kinetics of phase transitions under dynamic pressurization if simultaneous measurements of physical quantities are possible as a function of time. We report the development of a real-time event monitoring (RTEM) system with dDAC, which can simultaneously record the volume, pressure, optical image, and structure of materials during dynamic compression runs. In particular, the volume measurement using both Fabry–Pérot interferogram and optical images facilitates the construction of an equation of state (EoS) using the dDAC in a home-laboratory. We also developed an in-line ruby pressure measurement (IRPM) system to be deployed at a synchrotron x-ray facility. This system provides simultaneous measurements of pressure and x-ray diffraction in low and narrow pressure ranges. The EoSs of ice VI obtained from the RTEM and the x-ray diffraction data with the IRPM are consistent with each other. The complementarity of both RTEM and IRPM systems will provide a great opportunity to scrutinize the detailed kinetic pathways of phase transitions using dDAC.
While bio-inspired synthesis offers great potential for controlling nucleation and growth of inorganic particles, precisely tuning biomolecule-particle interactions is a long-standing challenge. Herein, we used variations in peptoid sequence to manipulate peptoid-Au interaction, leading to synthesis of concave five-fold twinned, five-pointed Au nanostars via a process of repeated particle attachment and facet stabilization. Ex situ and liquid-phase TEM observations show that a balance between particle attachment biased to occur near the star points, preferential growth along the [100] direction, and stabilization of (111) facets is critical to forming star-shaped particles. Molecular simulations predict that interaction strengths between peptoids and distinct Au facets differ significantly and thus can alter attachment kinetics and surface energies to form the stars. This work provides new insights into how sequence-defined ligands affect particle growth to regulate crystal morphology.
Not provided.
A fundamental understanding of mineral precipitation kinetics relies largely on microscopic observations of the dynamics of mineral surfaces exposed to supersaturated solutions. Deconvolution of tightly bound transport, surface reaction, and crystal nucleation phenomena still remains one of the main challenges. Particularly, the influence of these processes on texture and morphology of mineral precipitate remains unclear. This study presents a coupling of pore-scale reactive transport modeling with the Arbitrary Lagrangian-Eulerian approach for tracking evolution of explicit solid interface during mineral precipitation. It incorporates a heterogeneous nucleation mechanism according to Classical Nucleation Theory which can be turned “on” or “off.” This approach allows us to demonstrate the role of nucleation on precipitate texture with a focus at micrometer scale. In this work precipitate formation is modeled on a 10 micrometer radius particle in reactive flow. The evolution of explicit interface accounts for the surface curvature which is crucial at this scale in the regime of emerging instabilities. The results illustrate how the surface reaction and reactive fluid flow affect the shape of precipitate on a solid particle. It is shown that nucleation promotes the formation of irregularly shaped precipitate and diminishes the effect of the flow on the asymmetry of precipitation around the particle. The observed differences in precipitate structure are expected to be an important benchmark for reaction-driven precipitation in natural environments.
Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.
Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.
CRM 197 is a genetically detoxified mutant of diphtheria toxin (DT) that is widely used as a carrier protein in conjugate vaccines. Protective immune responses to several bacterial diseases are obtained by coupling CRM 197 to glycans from these pathogens. Wild-type DT has been described in two oligomeric forms: a monomer and a domain-swapped dimer. Their proportions depend on the chemical conditions and especially the pH, with a large kinetic barrier to interconversion. A similar situation occurs in CRM 197 , where the monomer is preferred for vaccine synthesis. Despite 30 years of research and the increasing application of CRM 197 in conjugate vaccines, until now all of its available crystal structures have been dimeric. Here, CRM 197 was expressed as a soluble, intracellular protein in an Escherichia coli strain engineered to have an oxidative cytoplasm. The purified product, called EcoCRM, remained monomeric throughout crystallization. The structure of monomeric EcoCRM is reported at 2.0 Å resolution with the domain-swapping hinge loop (residues 379–387) in an extended, exposed conformation, similar to monomeric wild-type DT. The structure enables comparisons across expression systems and across oligomeric states, with implications for monomer–dimer interconversion and for the optimization of conjugation.