Modeling the Effective Elasticity of Anisotropic Porous Materials
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Ablative thermal protection system (TPS) materials for spacecraft are composites that are often made out of carbon-based reinforcement and a polymeric matrix. They endure high-temperature oxidation and surface recession when re-entering Earth’s atmosphere. Ablation is the result of many coupled and competing thermal, mechanical, and chemical phenomena, and it is difficult to isolate the role of each on the overall degradation of the TPS. Here we develop an ablation model for material recession coupled explicitly to finite rate carbon oxidation in complex microstructures. In this work, Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al, was adapted to tally surface reactions and other surface data on a per-grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also develop robust algorithms which handle the evolution of the flow cells and solid material regions, including split cells (flow cell divided in two by a solid surface). Finally, we demonstrate our implicit chemistry model for 2D and 3D geometries by producing reaction statistics and detailed visualization of oxidation-induced material recession at the microscale.
While macroscale methods for predicting the acoustic properties of porous structures have been popular in the past, they often require time-consuming manufacturing and testing workflows. Meanwhile, microscale approaches allow the prediction of transport parameters based exclusively on a periodic structure’s unit cell geometry. Here, we compare these methods to predict the characteristic impedance of additively manufactured porous structures. We use the microscale approach to estimate the geometry’s transport parameters, then predict the characteristic properties using the Johnson-Champoux-Allard (JCA) model. We measure the acoustic properties of the printed structures using a normal incidence impedance tube and estimate the transport parameters using an inverse characterization approach. We use the two-thickness method as a macroscale approach to predict the characteristic properties from the measured surface impedances of two sample thicknesses. Finally, we compare these characteristic prediction methods. Our results show that the inverse characterization and two-thickness methods offer the closest match to the measured values at low frequencies.
Bulk proteomics has been demonstrated to differentiate subpopulations within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can reshape biological discovery by providing visualization of components of various biomolecular mechanisms. With high mass resolving power and high spatial resolution analyses being routine, we can confidently enable intact protein imaging directly from samples with minimal preparation. Pairing those analyses with bulk experimental libraries can provide high confidence in annotations of post-translational modifications (PTMs) and truncations. Revealing PTM localization within the samples unlocks a direct window into unknown biology at the microscale. However, top-down proteomics (TDP) is not commonplace for microbial species, largely due to challenges in identifying detected peptides and proteins; considering the theoretical proteome of even the well-studied model bacterium Bacillus subtilis was only partially mapped recently. With little still known about the form and function of many of these proteins – let alone proteoforms, where PTMs and truncations of the same protein may possess unique physiological roles – there is a wealth of work to be done. Here we jointly apply TDP and MSI to describe the microscale spatial proteomic landscape within B. subtilis and further demonstrate the feasibility of detecting differentiated subpopulations through proteoforms across the biofilm landscape.
Mechanical testing with sub-sized specimens plays an important role in the nuclear industry, facilitating tests in confined experimental spaces with lower irradiation levels and accelerating the qualification of new materials. The reduced size of specimens results in different material behavior at the microscale, mesoscale, and macroscale, in comparison to standard-sized specimens, which is referred to as the “specimen size effect.” Although analytical models have been proposed to correlate the properties of sub-sized specimens to standard-sized specimens, these models lack broad applicability across different materials and testing conditions. The objective of this study is to create the first large public dataset of tensile properties for sub-sized specimens used in nuclear structural materials. We performed an extensive literature review of relevant publications and extracted over 1,000 tensile testing records comprising 55 columns including material type and composition, manufacturing information, irradiation conditions, specimen dimensions, and tensile properties. The dataset can serve as a valuable resource to investigate the specimen size effect and develop computational methods to correlate the tensile properties of sub-sized specimens.
Topics covered include: Measurement and Controls Data Acquisition System IMU/GPS System Provides Position and Attitude Data Using Artificial Intelligence to Inform Pilots of Weather Fast Lossless Compression of Multispectral-Image Data Developing Signal-Pattern-Recognition Programs Implementing Access to Data Distributed on Many Processors Compact, Efficient Drive Circuit for a Piezoelectric Pump; Dual Common Planes for Time Multiplexing of Dual-Color QWIPs; MMIC Power Amplifier Puts Out 40 mW From 75 to 110 GHz; 2D/3D Visual Tracker for Rover Mast; Adding Hierarchical Objects to Relational Database General-Purpose XML-Based Information Managements; Vaporizable Scaffolds for Fabricating Thermoelectric Modules; Producing Quantum Dots by Spray Pyrolysis; Mobile Robot for Exploring Cold Liquid/Solid Environments; System Would Acquire Core and Powder Samples of Rocks; Improved Fabrication of Lithium Films Having Micron Features; Manufacture of Regularly Shaped Sol-Gel Pellets; Regulating Glucose and pH, and Monitoring Oxygen in a Bioreactor; Satellite Multiangle Spectropolarimetric Imaging of Aerosols; Interferometric System for Measuring Thickness of Sea Ice; Microscale Regenerative Heat Exchanger Protocols for Handling Messages Between Simulation Computers Statistical Detection of Atypical Aircraft Flights NASA's Aviation Safety and Modeling Project Multimode-Guided-Wave Ultrasonic Scanning of Materials Algorithms for Maneuvering Spacecraft Around Small Bodies Improved Solar-Radiation-Pressure Models for GPS Satellites Measuring Attitude of a Large, Flexible, Orbiting Structure
Composite structures are susceptible to localized flaws, or variability, that drive global failure. To capture this variance, a multiscale model needs to be introduced that not only accurately represents the statistical nature of the composite microstructure but is also efficient. At the microscale, fiber aggregation creates local stress concentrations, where failure is likely to occur sooner than expected. A method of rapid microstructure generation, in conjunction with cluster characterization, is examined to develop accurate reproductions of 2D composite cross-sections. Parameterization of shape and size of fiber clusters is used to characterize representative volume elements. The discrete element method is used to generate pseudo-microstructures. The clustering parameters from the pseudo- and actual microstructure arrangements (obtained from micrographs) can be compared to determine the validity of the representative volume element generated with the discrete element method. Results show a promising approach to evaluating randomness of fiber distributions and how to accurately recreate microstructures for strength analysis.
Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.
Thermally responsive ionic liquids (ILs) exhibit liquid-liquid phase separation into a water-rich (WR) and ionic-liquid-rich (ILR) phase when heated above a lower critical solution temperature (LCST). This phase behavior has been leveraged for applications ranging from forward osmosis (FO) desalination, where the IL acts as a draw solute, to refrigeration and dehumidification cycles, where the IL acts as a liquid desiccant. While significant effort has been devoted to characterizing the thermodynamic and thermophysical properties of LCST ILs, their phase separation kinetics have not been investigated. In this work, we describe the macroscale phase separation kinetics (phase separation time) by gleaning insight into the microscale colloidal behavior of aqueous mixtures of four different materials, P 4444 TFA (tetrabutylphosphonium-2,4-trifluoroacetate), P 4444 DMBS (tetrabutylphosphonium-2,4-dimethyl-benzenesulfonate), N 4444 Sal (tetrabutylammonium salicylate), and P 4444 Sal (tetrabutylphosphonium salicylate) as a function of IL concentration at a separation temperature of 70 °C. We report the discontinuous microscale size distributions for each material and correlate their theoretical settling velocities to experimental phase separation times. The results indicate that a simple Stokes' law model can predict the phase separation time within reasonable accuracy. Overall, this work lays the foundation for understanding the micro- to macroscale phase separation behavior and kinetics of LCST ILs for various water-energy applications.
This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the Large-Eddy simulations. The data will be divided according to the storm intensity level at the simulation time. Category 2: Harvey, Nate Category 3: Michael, Delta Category 4: Michael, Laura
This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the mesoscale simulations, separated by each storm.
Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. For example, the fact that some abundant predators cannot thrive on the mean concentration of their prey in the ocean implies that they are somehow capable of exploiting small-scale patches of prey whose concentrations are much larger than the mean. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. Additional information is contained in the original extended abstract.
A mechanism of Ni redeposition during dealloying corrosion of Ni-Cr is investigated. A model Ni20Cr (wt%) metal alloy was exposed to molten LiF-NaF-KF eutectic (FLiNaK) at 600 °C and at an applied potential of +2.1 VK+/K, above the critical potential for onset of dealloying. Upon extended exposure times (up to 12 h), prominent salt-filled corrosion channels emerge along grain boundaries. A unique grain boundary corrosion mechanism, with respect to the exposed faces of the grains, a central focus of this investigation, is intrinsically connected to the formation of high purity Ni-rich de-alloyed regions within the salt-filled channel. We implement microscale techniques such as energy dispersive spectroscopy (EDS) and electron backscatter diffraction (EBSD) to uncover morphological and compositional variations in relevance to the formation of bicontinuous porosity from corrosion dealloying. To rationalize our findings, a phase-field model is developed and discovers a mechanism in which dissolved Ni from one grain can be redeposited on an adjacent grain at a given difference in interfacial energies. The interaction of chemical and structural factors at the grain boundaries plays a central role in elucidating the dynamics of this phenomenon and its implications towards corrosion.
Mineral–organic matter (OM) studies have predominantly focused on acidic soils that are abundant in iron (Fe) oxides and aluminum (Al) oxides. We have probed mineral–OM interactions in an alkaline or calcareous soil of the Aridisols class. Unlike the role of Fe and Al, the role of Ca-minerals (particularly calcite), which are ubiquitous in alkaline soils, in OM sequestration is not well understood. Multiple recent model studies with aqueous Ca2+ or synthetic calcite and a suite of OM compounds have shown Ca-OM assemblages to be spatially correlated with calcite at the microscale. To study the chemical state of both Ca and Fe and their competing role in soil organic matter (SOM) stabilization, we performed laboratory characterization using x-ray diffraction, Mössbauer spectroscopy, x-ray photoelectron spectroscopy, scanning electron microscopy, and scanning transmission electron microscopy, alongside synchrotron-based microscale chemical imaging using scanning transmission x-ray microscopy combined with near-edge x-ray absorption fine structure. Ca mineral–organic associations were found to be ubiquitous in this system and are likely critical for understanding SOM stabilization/degradation in alkaline soils. From our findings on mineralogy, speciation, and the nature of Ca-OM bridging, we identified differences in C and Ca chemistry based on the relative location of OM to Ca minerals. The OM near the calcite crystal was enriched in lipid and protein moieties, Ca-OM next to Fe minerals displayed a strong contribution from aromatic compounds, while on the surface of microbes, the carbonate was believed to be of microbial in origin, as also suggested by preliminary works reporting on the formation of amorphous calcite or nano-calcite. In Ca-OM admixed with carbonate, it was difficult to distinguish Ca-associated OM from amorphous calcite or nano-calcite.
Ablative thermal protection system (TPS) materials for spacecraft are composites that often consist of a carbon-based reinforcement and a polymeric matrix. During Earth re-entry, they endure high-temperature oxidation and surface recession. Oxidation is an important mechanism for ablation, sometimes leading to the weakening, spallation, or failure of the oxidized fibers at the surface and in the char layer. However, more details are required including accurate material properties of the fiber microstructure, whether the fibers recede homogenously or localized at pits, and the role of pyrolysis outgassing in order to evaluate the role oxidation plays in the degradation and failure mechanisms of these materials. In this work, we demonstrate a parallelizable oxidation-driven ablation model developed for detailed, large-scale simulations in the DSMC code SPARTA. We also develop robust algorithms which handle the conservation of the surface state after an ablation step. Finally, we verify our model for both simple and more complex chemistry as well as microstructures with reaction statistics, oxidation depth calculations, and detailed visualization of oxidation-induced material recession at the microscale.
This data is from the paper calcium is associated with specific soil organic carbon decomposition products, published in SOIL. DOI: https://doi.org/10.5194/soil-11-381-2025, 2025.This file contains CSVs with spectral data and bulk soil data and there is no specific program required to open this data. The data includes Scanning transmission X-ray microscopy carbon near-edge X-ray absorption fine structure spectroscopy. data from the measurement of samples from the Whole-soil Warming project, run by the Belowground Biogeochemistry team at Blodgett Forest Research Center, Georgetown, California run by the University of California, Berkeley. It also includes bulk soil chemical properties. The University of California's Blodgett Forest Research Station (Forest) is situated in the Sierra Nevada foothills (1370 m a.s.l.) near Georgetown, California. The samples were collected from here: 38.912013, -120.661469, https://maps.app.goo.gl/291bCJ1zVqUhgktz6. The Forest soils were characterised as Alfisols, which are equivalent to Dystric Cambisols (IUSS Working Group WRB, 2015), and formed in granitic parent materials, in a temperate climate, under thinned, mixed-coniferous forest (Fig. S3; Gaudinski et al., 2009). With these analyses we aimed to answer the question, is calcium associated with a specific type of organic matter enriched in aromatic and phenolic carbon at the microscale in samples from Blodgett Forest Research Center? and how does this specific type of carbon respond to experiments targetted at removing and adding calcium to the soils, specifically cation exchange and incubation after calcium addition? Abstract from the paper can be found below: Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil-types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca-SOC is removed through cation-exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, highlighting a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca, and in turn, this association inhibits dissolved organic carbon export or further decomposition. We propose that this mechanism could be driven by Ca hotspots on the microscale shifting local decomposition processes and thereby explaining the colocation of Ca with SOC of a specific composition across different acidic soil environments. Incorporating this biogeochemical process into Earth System Models could improve our understanding, predictions, and management of carbon dynamics in soils, and account for their response to Ca-rich amendments.
The near-wall behavior of turbulence is re-examined in a way different from that proposed by Hanjalic and Launder and followers. It is shown that at a certain distance from the wall, all energetic large eddies will reduce to Kolmogorov eddies (the smallest eddies in turbulence). All the important wall parameters, such as friction velocity, viscous length scale, and mean strain rate at the wall, are characterized by Kolmogorov microscales. According to this Kolmogorov behavior of near-wall turbulence, the turbulence quantities, such as turbulent kinetic energy, dissipation rate, etc. at the location where the large eddies become Kolmogorov eddies, can be estimated by using both direct numerical simulation (DNS) data and asymptotic analysis of near-wall turbulence. This information will provide useful boundary conditions for the turbulent transport equations. As an example, the concept is incorporated in the standard k-epsilon model which is then applied to channel and boundary flows. Using appropriate boundary conditions (based on Kolmogorov behavior of near-wall turbulence), there is no need for any wall-modification to the k-epsilon equations (including model constants). Results compare very well with the DNS and experimental data.
Two-photon polymerization (TPP) enables the fabrication of intricate 3D microstructures with submicron precision, offering significant potential in biomedical applications like tissue engineering. In such applications, to print materials and structures with defined mechanics, it is crucial to understand how TPP printing parameters impact the material properties in a physiologically relevant liquid environment. Herein, an experimental approach utilizing microscale tensile testing (μTT) for the systematic measurement of TPP-fabricated microfibers submerged in liquid as a function of printing parameters is introduced. Using a diurethane dimethacrylate-based resin, the influence of printing parameters on microfiber geometry is first explored, demonstrating cross-sectional areas ranging from 1 to 36 μm 2 . Tensile testing reveals Young's moduli between 0.5 and 1.5 GPa and yield strengths from 10 to 60 MPa. The experimental data show an excellent fit with the Ogden hyperelastic polymer model, which enables a detailed analysis of how variations in writing speed, laser power, and printing path influence the mechanical properties of TPP microfibers. The μTT method is also showcased for evaluating multiple commercial resins and for performing cyclic loading experiments. Collectively, this study builds a foundation toward a standardized microscale tensile testing framework to characterize the mechanical properties of TPP printed structures.