Results for “Macroporosity”

DOE OSTI2025

Root‐Pore Interactions, the Underestimated Driver for Rhizosphere Structure and Rhizosheath Development

Physical characteristics of rhizosphere and rhizosheath, that is, root-adhering soil, are crucial for plant performance. Yet, the drivers of the rhizosphere's structural properties and their relationships with rhizosheath development remain unclear. We used X-ray computed micro-tomography (i) to explore two drivers of rhizosphere porosity: root-induced changes vs. preferential root growth into soil with certain pore characteristics and (ii) to estimate their contributions to rhizosphere macroporosity gradients and rhizosheath formation. Rhizosheath development was assessed in relation to rhizosphere macroporosity and rhizodeposition after ¹⁴C labeling. Our results confirmed that both root-induced changes and growth preferences shape rhizosphere structure, with their relative significance depending on the inherent macropore availability. In intact soils, growth preferences were the dominant factor, while in sieved soils the root-induced changes became equally important. Rhizosheath formation was associated with roots compacting their surrounding and releasing carbon. However, no correlation was found between rhizosheath formation and the actual rhizosphere, that is, the volume of soil adjacent to the roots. The study offers new process-level understanding of rhizosphere porosity gradients, while emphasizing caution in interpreting root growth data from sieved soil studies. Similarly, traditional destructively sampled rhizosheath may not fully capture the true characteristics of the actual rhizosphere, underscoring importance of intact-soil analyses.

macroporosity gradients↗

DOE OSTI2024

Hierarchically porous electrospun carbon nanofiber for high-rate capacitive deionization electrodes

Capacitive deionization (CDI) is a promising technology that has gained interest for the desalination of brackish water. Hierarchically porous carbons are commonly used as electrodes for CDI due to their high surface areas and controlled pore size distributions that maximize ion adsorption capacity and rate. Electrospinning is an effective way of generating carbon nanofibers with high inter-fiber macroporosity that can be further modified to improve surface area, total pore volume, and pore size distribution. This work describes the use of sacrificial mesopore formers in tandem with a micropore etching technique to induce hierarchical porosity in electrospun fibers. Mesopores are formed via the dissolution of silica nanoparticles that are introduced into the fibers during the electrospinning step. After mesopore formation, micropores are etched into the resulting surface through KOH impregnation and thermal activation. This sequential technique creates a hierarchical network of pores from the inherent macroporosity of the fiber network, to the mesopores, and finally micropores to simultaneously maximize surface area and accessibility. Micropore formation is optimized to maximize specific surface area while maintaining physical integrity of the fibers. Further, the combination of mesopores and micropores enables fast ion adsorption rates and capacity. Carbon fiber electrodes fabricated in this method achieve specific surface areas exceeding 1400 m 2 g -1 , with pore volumes exceeding 1.0cc g -1 . The pore size distributions are highly controlled, with 80% of total pore volume coming from pores <20nm in radius. In 500 ppm constant voltage CDI tests, these fiber electrodes obtain a salt adsorption capacity of over 14 mg g -1 at a salt adsorption rate of ~4mg g -1 min -1 , showcasing the high capacity matched with high rate of these easily fabricated, inexpensive materials.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Internal Characteristics of Phobos and Deimos from Spectral Properties and Density: Relationship to Landforms and Comparison with Asteroids

Compositional interpretations of new spectral measurements of Phobos and Deimos from Mars Express/OMEGA and MRO/CRISM and density measurements from encounters by multiple spacecraft support refined estimates of the moons' porosity and internal structure. Phobos' estimated macroporosity of 12-20% is consistent with a fractured but coherent interior; Deimos' estimated macroporosity of 23-44% is more consistent with a loosely consolidated interior. These internal differences are reflected in differences in surface morphology: Phobos exhibits a globally coherent pattern of grooves, whereas Deimos has a surface dominated instead by fragmental debris. Comparison with other asteroids .110 km in diameter shows that this correspondence between landforms and inferred internal structure is part of a pervasive pattern: asteroids interpreted to have coherent interiors exhibit pervasive, organized ridge or groove systems, whereas loosely consolidated asteroids have landforms dominated by fragmental debris and/or retain craters >1.3 body radii in diameter suggesting a porous, compressible interior.

Murchie, S. L.↗

DOE OSTI2024

Sol-gel derived silicate-phosphate glass SiO 2 –P 2 O 5 –CaO–TiO 2 : The effect of titanium isopropoxide on porosity and thermomechanical stability

Despite of several decades lasting extensive research of bioactive and bioresorbable glasses the systematic parametrization and determination of the key factors affecting porosity and thermomechanical characteristics still remains challenging. Here, we present silica-phosphate glasses, with the composition 70SiO 2 - 20P 2 O 5 - (10-x)CaO-xTiO 2 (mol%; x = 0, 2.5, 5, and 7.5), prepared by sol -gel method and reinforced by titanium dioxide via titanium isopropoxide (TTIP) incorporation which demonstrated tunable variation of porosity from micro-to macro -region and superb mechanical integrity during the calcination process. The presence of 7.5 mol% TiO 2 promotes dimensional stability up to 1000°C as investigated by thermomechanical analysis. The XRD showed the dominant presence of silicon phosphate [Si(P 2 O 7 )], titanium phosphate [Ti(P 2 O 7 )] and calcium phosphates [β-Ca(P 2 O 6 ) and γ- Ca 2 (P 2 O 7 )]. The effect of TiO 2 doping on the multiscale morphology and porosity was investigated by means of SEM, MIP, μCT, N 2 adsorption and USAXS/SAXS. Increasing TiO 2 content leads to the formation of open porosity up to 70vol% and drives the formation of a refined interconnected macroporosity of 2-30 μm. In contrast, mesoporosity with a dominance of 3-6nm pores decreases in all samples with increasing TiO 2 content. USAXS/SAXS revealed an increase in primary particle size with increasing TiO 2 content which is in good agreement with the nitrogen physisorption analysis showing that microporosity decreases with increasing TiO2 content.

36 MATERIALS SCIENCE↗

NASA NTRS1976

The surface structure and composition of 60017,43

A surface fragment of 60017, itself an exposed section of Shadow Rock, has been characterized structurally and chemically using gas adsorption, helium pycnometry, scanning electron microscopy, and Auger and ESCA spectroscopy. The fragment is seen as a partially melted devitrified-glass impact breccia possessing a relatively low surface area, macroporosity, and low absolute density. The fragment appears to be plagioclase-enriched with respect to 60017 and to possess significant surface heterogeneity. Confirmation of the surface reduction of iron was obtained; however, the extent of this reduction varied from point to point. Significant amounts of surface volatiles were also found, and it is hypothesized that these were released during the North Ray cratering event. If this is proved correct, similar volatile concentrations should be found on other North Ray ejecta.

Cadenhead, D. A.↗

NASA NTRS1979

Variations in pore structure of reaction-bonded silicon nitride /RBSN/

A discussion is presented relating the observed pore structures (sizes) to the reaction mechanisms in reaction-bonded silicon nitride (alpha- and beta-Si3N4) on the basis of information available from the literature. While the techniques for reducing the residual macroporosity are quite well-developed for reaction-bonded Si3N4 (RBSN), it is important to be aware of three other orders of magnitude for porosity present in RBSN as a result of the nitriding process itself, and how these types of nitridation-induced porosity can be controlled. For ease of description, these types of nitridation-induced porosity are called micropores, nanopores, and picopores in order of their decreasing size. A scanning electron micrograph is presented, showing nanopores isolated in the unreacted Si and picopores in the alpha-matte Si3N4. The assumption that an alpha-matte growth mechanism is active explains the occurrence of nanopores and their partial filling with alpha-Si3N4, leaving behind very fine-grained alpha-matte and picopores.

Danforth, S. C.↗

NASA NTRS2001

The Porosity of 433 Eros

Data from the NEAR mission show the bulk density of 433 Eros is 2.67 g/cm 3 . Given an L or LL composition, the bulk porosity of Eros is in the range of 25-29% and the macroporosity is 14-18%. This is consistent with a fractured, but coherent asteroid. Additional information is contained in the original extended abstract.

Britt, D. T.↗

NASA NTRSDate not supplied

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

NASA NTRSDate not supplied

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

DOE OSTI2023

Exploring density and strength variations in asteroid 16 Psyche’s composition with 3D hydrocode modeling of its deepest impact structure

Asteroid 16 Psyche is the largest metallic Main Belt Asteroid and is the subject of a forthcoming NASA mission. The composition of Psyche is still unknown and subject of recent debate. In particular, how much porosity is within Psyche, along with how much of Psyche consists of non-metallic versus metallic materials, are central questions to the issue of Psyche’s composition. If Psyche is indeed predominantly composed of metallic materials, it would need to have considerable porosity (~ 30%–50%) for a composition consistent with its expected bulk density (~ 3.7–4.1 g/cm). In this work, we vary the density and strength of Psyche by including uniform and layered fields of pseudo-microporosity, in addition to investigating the presence of macroscopic voids, i.e., spaces larger than the size of the simulation’s mesh cells, in rubble-pile configurations. Further, all configurations result in bulk densities within the uncertainties of measured values, however the strength of Psyche and the distribution of pseudo-pores are varied. Through 3D computational models of Psyche’s deepest impact structure, we show that Psyche’s composition is unlikely to contain only pseudo-microporosity. Rather, rubble pile structures, which include macroscopic voids, are shown to match the crater’s measured aspect ratio better than simulations of structures that included only pseudo-microporosity.

3D↗