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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantifying particle movement in a spout-fluidized bed with irregular feedstock morphology

Here, the spout-bed fluidization behavior of nonspherical, 140 μm SiC feedstock was quantified via particle image velocimetry for varying gas distributor geometries. A bench-scale, room-temperature fluidization setup was assembled to model a 50 mm fluidized bed chemical vapor deposition (FB-CVD) system, and fluidized bed motion was captured using a high-speed camera. Modular tips with varying inlet geometries were 3D printed and tested on the bench-scale rig using identical feedstock and gas flow rates in the range of 3.0–9.0 L/min. Fluidization behavior was quantified by extracting parameters of the bed velocity, frequency, dead time, and other measurements, which were ranked for each inlet geometry configuration tested. The results from this work demonstrate that changing the path of inlet gas flow can significantly change the hydrodynamics within a spout-fluidized bed under identical feedstock, loading, and flow rate conditions, potentially enabling experimental control of particle fluidization behavior for a given condition. Moreover, composite rankings of fluidization behavior for unique distributor geometries hold potential to guide the design of FB-CVD experiments for various engineering and scientific applications.

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

Effect of hydration on morphology of thin phosphonate block copolymer electrolyte membranes studied by electron tomography

The morphological changes of phosphonate polypeptoid electrolyte membranes, poly-N-(2-ethyl)hexylglycine-block-poly-N-phosphonomethylglycine (pNeh m -b-pNpm n ), in hydrated and dry states were characterized by cryogenic transmission electron microscopy (cryo-TEM) and cryogenic electron tomography (cryo-ET). The analysis of 3D tomograms revealed that the pNeh 9 -b-pNpm 9 thin films absorbed a large amount of water, resulting in the formation of membranes that were nearly flat and giant multicompartment vesicles dispersed in the water phase. A simple lamellar phase appeared when the films were dried. In contrast, pNeh 18 -b-pNpm 18 thin films absorbed little water and formed small highly curved unilamellar and multilamellar vesicles. Water was located mainly outside the closely-packed vesicles. When water was removed by drying, the walls of adjacent vesicles collapsed to form honeycomb-like capsules. Here, the changes in domain size reflected changes in chain conformations. The pNpm9 blocks were saturated by water and fully extended, while pNpm 18 blocks were neither saturated by water nor fully extended. In addition, the thicknesses of hydrophobic blocks in the hydrated films of both pNeh 9 -b-pNpm 9 and pNeh 18 -b-pNpm 18 were smaller than those in the dry films, reflecting an increase of the average distance between the neighboring junctions of polypeptoid molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗
NASA NTRS2002

Surface Processes of Faceted Growth

Atomic force microscopy and high precision optical interferometry allow to analyze the processes that are in the core of our present understanding of faceted crystal growth. Some of these processes will be reviewed. Recent experiments suggest that the Gibbs-Thomson Law (GTL) may not be applicable to the weakly fluctuating strongly polygonized steps, with low kink density. Propagation rate of a straight short step segment changes with the segment length much steeper than predicted by GTL. If the step fluctuations are still well developed, the typical transition length may be determined just by the radius of rounded comers of the polygonized step. If fluctuations do not have enough time to develop, the kinetic effects may be essential. Indeed, 'communications' between comers of a short straight step segment may occur and, thus, the GTL may be implemented only via kink exchange. E.g., dissolutions of this short segment at macroscopic equilibrium occurs as follows: The kinks are split from one comer as a result of fluctuations, and annihilate with kinks of the opposite sign generated by another comer. Similarly, an exchange via chain of kinks on a rough step is the mechanism to implement the GT Law. If there is a supersaturation with respect to a large crystal, the kinks not only diffuse along the step, but move back the generating comers. This 'wind' prevents communication between the comers and places upper limit supersaturation only below which GTL is applicable. Steps replace kinks in the 3D case, though, of course, another dimensionality brings about another physics. Another specific problem to think about is if fluctuations are always fast enough to provide enough kinks for linear dependence of step rate on supersaturation. Increasing azimuthal polygonization of growth hillocks is a sign of insufficient fluctuation rate. Morphological stability of vicinal faces is usually considered on the basis of mutually parallel steps. Azimuthal anisotropy and interlacing of step bunches inducing the well known bunch splitting is another challenge. Among other challenging problems are: existence of surface diffusion on the crystal/so1ution interface, step interaction in solutions, achievement of step flow modes from liquids, impurity effects. New phenomena essential in biomacromolecular crystallization is another interesting area.

Chernov, A.↗
DOE OSTI2020

Low-temperature MnBi alloys: Electronic and magnetic properties, constitution, morphology and fabrication (Review article)

The article reviews the rich phenomena of physical properties of MnBi. The diverse phenomena include strong spin-orbit interaction, anomalous temperature dependence of the coercivity and the magneto-crystalline anisotropy field, unique magneto-optical properties. Issues addressed include the nature of the electronic ground states of MnBi, the electronic and magnetic structures, Fermi surface, magneto-crystalline anisotropy, x-ray magnetic dichroism. The discussion includes key experiments, such as optical and magneto-optical spectroscopic measurements, de Haas-van Alphen (dHvA) measurements, x-ray photoemission and x-ray absorption spectroscopy measurements as well as x-ray magnetic circular dichroism. The effect of the spin-orbit (SO) interaction and Coulomb repulsion U were found to be crucial for the Fermi surface, cyclotron masses, magneto-optical properties, and x-ray magnetic circular dichroism. The microscopic origin of unique magneto-crystalline anisotropy and giant Kerr effect in MnBi is analyzed in detail. The huge Kerr effect in MnBi is caused by the combination of a sizable magnetic moment on manganese, the large spin-orbit coupling of bismuth, and a strong hybridization between the manganese 3d and the bismuth 6p states. The magneto-optically active states are mainly the 6p states of Bi. We show that the observed temperature dependence of the magneto-crystalline anisotropy can be explained taking into account the spin-orbit interaction together with strong Coulomb electron-electron interaction. The SO coupling of Bi is equally responsible for the large magneto-crystalline anisotropy energy as is the exchange splitting of Mn. The fabrication, morphology, and constitution of low-temperature MnBi alloys in bulk, thin films, and nanoparticles are discussed. The nanocomposite permanent magnetic materials based on MnBi, (Co, Fe) and Nd 2 Fe 14 B are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Irradiation stability and thermomechanical properties of 3D-printed SiC

Neutron irradiation tests were carried out on 3D-printed SiC derived from binderjet additive manufacturing and chemical vapor infiltration. Irradiation was carried to 2.3 dpa over a temperature range of 400–850 °C. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. No degradation in strength was observed in the material before or after irradiation, at various temperatures, or in different orientations. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Testing of spark plasma sintered porous tungsten under neon glow discharge cleaning conditions in LTX-β

This paper demonstrates that tungsten (W) based powder reconstituted Plasma Facing Components (PFCs) can be treated in situ in a fusion reactor to remove W oxide and carbon (C) contamination. Doing so should ease the challenge of using these materials in a Capillary Porous System (CPS) with lithium (Li) by enabling better wetting and less contamination of the Li by the underlying CPS. Most powder reconstituted materials including 3D printed and sintered PFCs suffer from a high surface contamination from oxides and surface C, which complicates their use with liquid Li, a primary PFC candidate. Spark plasma sintered porous W samples were fabricated to be used as a CPS with liquid Li. The samples were characterized in terms of morphology and surface chemistry. Analysis confirms a high C and oxygen (O) contamination. We present the results of exposing this type of CPS to Glow Discharge Cleaning (GDC) cycles in the Lithium Tokamak Experiment-β (LTX-β). The sample was exposed to neon (Ne) GDC in the midplane of the low-field side of LTX-β and analyzed in vacuo with Temperature Programmed Desorption (TPD) and Secondary Ion Mass Spectrometry (SIMS) to investigate the effects the Ne GDC had on the chemical composition of the sample. The combination of Ne GDC with rapid heating as done in TPD was successful in reducing the W oxides and removing the C contamination.

Capillary porous system↗
DOE OSTI2023

Developing a model for the impact of non-conformal lithium contact on electro-chemo-mechanics and dendrite growth

Lithium dendrite growth hinders the use of lithium metal anodes in commercial batteries. We present a 3D model to study the mechanical and electrochemical mechanisms that drive microscale plating. With this model, we investigate electrochemical response across a lithium protrusion characteristic of rough anode surfaces, representing the separator as a porous polymer in non-conformal contact with a lithium anode. The impact of pressure on separator morphology and electrochemical response is of particular interest, as external pressure can improve cell performance. We explore the relationships between plating propensity, stack pressure, and material properties. External pressure suppresses lithium plating due to interfacial stress and separator pore closure, leading to inhomogeneous plating rates. For moderate pressures, dendrite growth is completely suppressed, as plating will occur in the electrolyte-filled gaps between anode and separator. In fast-charging conditions and systems with low electrolyte diffusivities, the benefits of pressure are overridden by ion transport limitations.

25 ENERGY STORAGE↗
DOE OSTI2026

Strain mapping of three-dimensionally structured two-dimensional materials

Strain plays a crucial role in tuning materials’ properties, influencing their optical, electrical, and chemical performances. In two-dimensional (2D) materials, applied stress often induces out-of-plane deformation, resulting in a more intricate three-dimensional (3D) topography, where mapping the strain remains a challenge due to the limitations of conventional characterization techniques. In this work, we introduce BRIGHT (Bragg-Rod Informed, Gradient-based Height-mapping Technique), an integrated method for reconstructing both the topography and planar strain profile of 3D-structured 2D materials using nanobeam four-dimensional scanning transmission electron microscopy (4D-STEM). We apply BRIGHT to a MoS2-MoSe2 transition metal dichalcogenide (TMD) lateral heterojunctions exhibiting built-in strain and out-of-plane ripples and show that varying heterojunction widths lead to distinct surface morphologies and corresponding changes in the planar strain distribution. These results establish a foundation for more effective strain engineering in 2D materials by accounting for out-of-plane structural features, thereby enabling more precise control of strain-dependent properties.

Mireles, Adan [Rice Univ., Houston, TX (United Sta↗
DOE OSTI2022

In Situ X-ray Radiography and Computational Modeling to Predict Grain Morphology in $\beta$-Titanium during Simulated Additive Manufacturing

The continued development of metal additive manufacturing (AM) has expanded the engineering metallic alloys for which these processes may be applied, including beta-titanium alloys with desirable strength-to-density ratios. To understand the response of beta-titanium alloys to AM processing, solidification and microstructure evolution needs to be investigated. In particular, thermal gradients (Gs) and solidification velocities (Vs) experienced during AM are needed to link processing to microstructure development, including the columnar-to-equiaxed transition (CET). In this work, in situ synchrotron X-ray radiography of the beta-titanium alloy Ti-10V-2Fe-3Al (wt.%) (Ti-1023) during simulated laser-powder bed fusion (L-PBF) was performed at the Advanced Photon Source at Argonne National Laboratory, allowing for direct determination of Vs. Two different computational modeling tools, SYSWELD and FLOW-3D, were utilized to investigate the solidification conditions of spot and raster melt scenarios. The predicted Vs obtained from both pieces of computational software exhibited good agreement with those obtained from in situ synchrotron X-ray radiography measurements. The model that accounted for fluid flow also showed the ability to predict trends unobservable in the in situ synchrotron X-ray radiography, but are known to occur during rapid solidification. A CET model for Ti-1023 was also developed using the Kurz–Giovanola–Trivedi model, which allowed modeled Gs and Vs to be compared in the context of predicted grain morphologies. Both pieces of software were in agreement for morphology predictions of spot-melts, but drastically differed for raster predictions. The discrepancy is attributable to the difference in accounting for fluid flow, resulting in magnitude-different values of Gs for similar Vs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗
NASA NTRS1990

Analysis of stratospheric ozone, temperature, and minor constituent data

The objective of this research is to use available satellite measurements of temperature and constituent concentrations to test the conceptual picture of stratospheric chemistry and transport. This was originally broken down into two sub-goals: first, to use the constituent data to search for critical tests of our understanding of stratospheric chemistry and second, to examine constituent transport processes emphasizing interactions with chemistry on various time scales. A third important goal which has evolved is to use the available solar backscattered ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) data from Nimbus 7 to describe the morphology of recent changes in Antarctic and global ozone with emphasis on searching for constraints to theories. The major effort now being pursued relative to the two original goals is our effort as a theoretical team for the Arctic Airborne Stratospheric Expedition (AASE). Our effort for the AASE is based on the 3D transport and chemistry model at Goddard. Our goal is to use this model to place the results from the mission data in a regional and global context. Specifically, we set out to make model runs starting in late December and running through March of 1989, both with and without heterogeneous chemistry. The transport is to be carried out using dynamical fields from a 4D data assimilation model being developed under separate funding from this task. We have successfully carried out a series of single constituent transport experiments. One of the things demonstrated by these runs was the difficulty in obtaining observed low N2O abundances in the vortex without simultaneously obtaining very high ozone values. Because the runs start in late December, this difficulty arises in the attempt to define consistent initial conditions for the 3D model. To accomplish a consistent set of initial conditions, we are using the 2D photochemistry-transport model of Jackman and Douglass and mapping in potential temperature, potential vorticity space as developed by Schoeberl and coworkers.

Stolarski, Richard S.↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
DOE OSTI2022

X-ray Computed Tomography of Irradiated and Unirradiated AGR-3/4 Compacts

X-ray Computed Tomography (XCT) has been utilized to image and characterize compacts from the combined third and fourth irradiation of the Advanced Gas Reactor (AGR) Program, AGR-3/4, fuel. The experiment contained tristructural isotropic (TRISO)-coated fuel particles as well as designed-to-fail (DTF) fuel particles. Two irradiated compacts, representing the lower and higher range of AGR-3/4 burnup (4.85% and 14.92% fissions per initial heavy metal atom FIMA) were examined. These represent the first known highly irradiated TRISO fuel compacts to be examined via X-ray CT. Additionally, two unirradiated compacts from the same production batch as the examined irradiation compacts were also imaged for a baseline comparison. As XCT of irradiated TRISO compacts is not a commonly implemented characterization technique, a significant portion of the report focuses on developed methodology and imaging conditions. A specialized sample shielding device was developed and fabricated specifically to limit received dose to staff during sample preparation for XCT and to minimize excess gamma radiation dose to sensitive electronic components with the utilized X-ray system. Significant penetration through the uranium oxycarbide fuel kernels by significantly hardening the X-ray beam with specialized proprietary filters acquired from Carl Zeiss NTS Ltd. The filter utilized resulted in an average X ray photon energy of ~110 keV which approaches uranium’s K-edge (~115 keV), maximizing penetration for a microfocus X-ray source. The gamma-radiation emitted from the irradiated AGR-3/4 TRISO compacts, has the same properties and mechanisms for interaction with matter as X-rays, thus the detection of gamma-radiation by the utilized X-ray detectors was initially a concern. However, although ?-rays did produce an observable signal on the X-ray detector, its contribution to the overall imaging results appeared negligible upon 3D reconstruction. The neglibile impact on the resulting 3D reconstructed volumes were likely the result of: (1) a significantly lower detection efficiency for ?-rays relative to X-rays; (2) An X-ray flux at the detector several orders of magnitude higher than that of the impinging ?-rays from the irradiated compacts. These results suggest that irradiated compacts with significantly higher radiation fields can be examined in the future if an acceptable route for sample handling and preparation can be determined. Additionally, the 3D imaging results of XCT can provide a valuable means of assessing compacts. While in many ways complimentary to traditional post irradiation examination techniques such as optical ceramography, XCT can provide additional insight into compact features traditionally difficult to discern directly from cross-sectional imaging alone. Preliminary analyses on kernel size, morphology (aspect ratio and sphericity), and kernel orientation were presented. Sphericity, a simple morphological shape descriptor, was utilized to screen for kernel extrusions within the high burnup compact. The number of kernel extrusions identified via XCT represented an approximate two-fold increase from the quantity of extruded particles observed (via optical ceramography) in adjacent compacts from the same irradiation capsule. While numerical analysis of the compact datasets was highly preliminary, initial results show promise for providing complimentary metrics to current AGR-3/4 PIE and potentially additional insight into the processes driving TRISO fuel degradation during reactor operation. Additional analyses to be performed at a later date include a more detailed examination of kernel size, kernel sphericity (and observed kernel extrusions), and sphericity. Given all particles can be observed in a single data volume possible correlation of spatial position with observed kernel features will also be made at a later date.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Control of monodomain polymer-stabilized cuboidal nanocrystals of chiral nematics by confinement.

Liquid crystals are important components of optical technologies. Cuboidal crystals consisting of chiral liquid crystals-the so-called blue phases (BPs), are of particular interest due to their crystalline structures and fast response times, but it is critical that control be gained over their phase behavior as well as the underlying dislocations and grain boundaries that arise in such systems. Blue phases exhibit cubic crystalline symmetries with lattice parameters in the 100 nm range and a network of disclination lines that can be polymerized to widen the range of temperatures over which they occur. Here, we introduce the concept of strain-controlled polymerization of BPs under confinement, which enables formation of strain-correlated stabilized morphologies that, under some circumstances, can adopt perfect single-crystal monodomain structures and undergo reversible crystal-to-crystal transformations, even if their disclination lines are polymerized. We have used super-resolution laser confocal microscopy to reveal the periodic structure and the lattice planes of the strain and polymerization stabilized BPs in 3D real space. Our experimental observations are supported and interpreted by relying on theory and computational simulations in terms of a free energy functional for a tensorial order parameter. Simulations are used to determine the orientation of the lattice planes unambiguously. The findings presented here offer opportunities for engineering optical devices based on single-crystal, polymer-stabilized BPs whose inherent liquid nature, fast dynamics, and long-range crystalline order can be fully exploited.

confinement↗
DOE OSTI2023

A Novel Experimental Approach to Understand the Transport of Nanodrugs

Nanoparticle-based drugs offer attractive advantages like targeted delivery to the diseased site and size and shape-controlled properties. Therefore, understanding the particulate flow of the nanodrugs is important for effective delivery, accurate prediction of required dosage, and developing efficient drug delivery platforms for nanodrugs. In this study, the transport of nanodrugs including flow velocity and deposition is investigated using three model metal oxide nanodrugs of different sizes including iron oxide, zinc oxide, and combined Cu-Zn-Fe oxide synthesized via a modified polyol approach. The hydrodynamic size, size, morphology, chemical composition, crystal phase, and surface functional groups of the water-soluble nanodrugs were characterized via dynamic light scattering, transmission electron microscopy, scanning electron microscopy-energy dispersive X-ray, X-ray diffraction, and fourier transform infrared spectroscopy, respectively. Two different biomimetic flow channels with customized surfaces are developed via 3D printing to experimentally monitor the velocity and deposition of the different nanodrugs. A diffusion dominated mechanism of flow is seen in size ranges 92 nm to 110 nm of the nanodrugs, from the experimental velocity and mass loss profiles. The flow velocity analysis also shows that the transport of nanodrugs is controlled by sedimentation processes in the larger size ranges of 110–302 nm. However, the combined overview from experimental mass loss and velocity trends indicates presence of both diffusive and sedimentation forces in the 110–302 nm size ranges. It is also discovered that the nanodrugs with higher positive surface charges are transported faster through the two test channels, which also leads to lower deposition of these nanodrugs on the walls of the flow channels. The results from this study will be valuable in realizing reliable and cost-effective in vitro experimental approaches that can support in vivo methods to predict the flow of new nanodrugs.

36 MATERIALS SCIENCE↗
NASA NTRS2011

VESGEN Mapping of Bioactive Protection against Intestinal Inflammation: Application to Human Spaceflight and ISS Experiments

Challenges to successful space exploration and colonization include adverse physiological reactions to micro gravity and space radiation factors. Constant remodeling of the microvasculature is critical for tissue preservation, wound healing, and recovery after ischemia. Regulation of the vascular system in the intestine is particularly important to enable nutrient absorption while maintaining barrier function and mucosal defense against micro biota. Although tremendous progress has been made in understanding the molecular circuits regulating neovascularization, our knowledge of the adaptations of the vascular system to environmental challenges in the intestine remains incomplete. This is in part because of the lack of methods to observe and quantify the complex processes associated with vascular responses in vivo. Developed by GRC as a mature beta version, pre-release research software, VESsel GENeration Analysis (VESGEN) maps and quantifies the fractal-based complexity of vascular branching for novel insights into the cytokine, transgenic and therapeutic regulation of angiogenesis, lymphangiogenesis and microvascular remodeling. Here we demonstrate that VESGEN can be used to characterize the dynamic vascular responses to acute intestinal inflammation and mucosal recovery from in vivo confocal microscopic 3D image series. We induced transient intestinal inflammation in mice by DSS treatment and investigated whether the ability of the pro biotic yeast Saccharomyces boulardii (Sb) to protect against intestinal inflammation was due to regulation of vascular remodeling. A primary characteristic of inflammation is excessive neovascularization (angiogenesis) resulting in fragile vessels prone to bleeding. Morphological parameters for triplicate specimens revealed that Sb treatment greatly reduced the inflammatory response of vascular networks by an average of 78%. This resulted from Sb inhibition of vascular endothelial growth factor receptor signaling, a major angiogenesis signaling pathway. It needs to be determined whether pro biotic yeast represents a promising approach to GI protection in space. GRC performed only the VESGEN post-testing analysis.

Parsons-Wingerter, P. A.↗