Search NASA⌕ Search

SEARCH · Search NASA

Results for “Heterogeneous media”

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.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fracture Intensity Impacts on Reaction Front Propagation and Mineral Weathering in Three‐Dimensional Fractured Media

Abstract Studying reaction front propagation in heterogeneous natural settings is challenging, but numerical simulations can provide insight into the varying spatial and temporal scales of reaction front propagation. Here, the impact of increasing fracture intensity on mineral dissolution rates, and the extent of reaction front propagation is investigated using reactive transport simulations in upscaled discrete fracture network domains with varied fracture intensity. Domain‐averaged dissolution rates vary less than 0.5 log units regardless of the fracture intensity, but the spatial distribution of reactions is controlled by the location and number of dead‐end fractures and the number of connected flowpaths through the domain. Higher fracture intensities lead to more weathering in the domain because of more available mineral for water‐rock interactions. We find that reaction fronts propagate through the primary flowpaths in the first 10,000 years of the simulation for a 10‐m length domain, then propagate into secondary flowpaths and dead‐end fractures between 10,000 and 100,000 years, and finally into the matrix over timescales of hundreds of thousands of years. The domain‐averaged reaction rates decrease through time corresponding to a transition from dissolution in advection‐dominated, fast‐flowing pathways, to dissolution in transport‐limited zones of disconnected fractures and matrix. Matrix dissolution, or dissolution under transport‐limited conditions, is the dominant process at late times in these simulations. The results of these simulations recreate the observed paradox found in nature where highly fractured hillslopes tend to be more weathered but have slower weathering rates, while hillslopes with fewer fractures, are less weathered but have higher dissolution rates.

58 GEOSCIENCES↗
DOE OSTI2025

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution. In this study, we introduce the method of time-resolved Brownian tomography to investigate the temporal evolution of the 3D atomic structures of individual nanocrystals in solution. The methodology is applied to examine the atomic-level structural transformations of Pt nanocrystals during oxidative etching. The time-resolved 3D atomic maps reveal the structural evolution of dissolving Pt nanocrystals, transitioning from a crystalline to a disordered structure. Our study demonstrates the emergence of a phase at the nanometer length scale that has received less attention in bulk thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Neural network–based pore flow field prediction in porous media using super resolution

Direct pore-scale simulations of fluid flow through porous media are computationally expensive to perform for realistic systems. Previous works have demonstrated using the geometry of the microstructure of porous media to predict the velocity fields therein based on neural networks. However, such trained neural networks do not perform well for unseen porous media with a large degree of heterogeneity. In this study we propose that incorporating a coarse velocity field in the input of neural networks is an effective way to improve the prediction performance. The coarse velocity field can be simulated with a low computational cost and provides global information to regularize the ill-posedness of the learning problem, which is usually caused by the use of local geometries due to the computational resource constraints. We show that incorporating the coarse-mesh velocity field significantly improves the prediction accuracy of the fine-mesh velocity field by comparison to the prediction that relies on geometric information alone, especially for the porous medium with a large interior vuggy pore space. We also show the flexibility of training the network in using coarse velocity fields with various resolutions. The results suggest that even using coarse velocity field with a very low resolution, the predictions are still enhanced and close to the ground truths. The feasibility of the method is further demonstrated by testing the trained network on real rocks. This study highlights the merits of incorporating a coarse-mesh velocity field into the input for neural networks, which provides global, physics-based information for the model, thereby improving the model's generalization capability.

42 ENGINEERING↗
DOE OSTI2022

Machine-Learning of Nonlocal Kernels for Anomalous Subsurface Transport from Breakthrough Curves

Anomalous behavior is ubiquitous in subsurface solute transport due to the presence of high degrees of heterogeneity at different scales in the media. Although fractional models have been extensively used to describe the anomalous transport in various subsurface applications, their application is hindered by computational challenges. Simpler nonlocal models characterized by integrable kernels and finite interaction length represent a computationally feasible alternative to fractional models; yet, the informed choice of their kernel functions still remains an open problem. We propose a general data-driven framework for the discovery of optimal kernels on the basis of very small and sparse data sets in the context of anomalous subsurface transport. Using spatially sparse breakthrough curves recovered from fine-scale particle-density simulations, we learn the best coarse-scale nonlocal model using a nonlocal operator regression technique. Predictions of the breakthrough curves obtained using the optimal nonlocal model show good agreement with fine-scale simulation results even at locations and time intervals different from the ones used to train the kernel, confirming the excellent generalization properties of the proposed algorithm. A comparison with trained classical models and with black-box deep neural networks confirms the superiority of the predictive capability of the proposed model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

In Situ Imaging of Faujasite Surface Growth Reveals Unique Pathways of Zeolite Crystallization

Zeolite crystallization occurs by complex processes involving a variety of possible mechanisms. The sol gel media used to prepare zeolites leads to heterogeneous mixtures of solution and solid states with diverse solute species. At later stages of zeolite synthesis when growth occurs predominantly from solution, classical two-dimensional nucleation and spreading of layers on crystal surfaces via the addition of soluble species is the dominant pathway. At earlier stages, these processes occur in parallel with nonclassical pathways involving crystallization by particle attachment (CPA). The relative roles of solution- and solid-state species in zeolite crystallization have been a subject of debate. Here, in this work, we investigate the growth mechanism of a commercially relevant zeolite, faujasite (FAU). In situ atomic force microscopy (AFM) measurements reveal that supernatant solutions extracted from a conventional FAU synthesis at various times do not result in growth, indicating that FAU growth predominantly occurs from the solid state through a disorder-to-order transition of amorphous precursors. Elemental analysis shows that supernatant solutions are significantly more siliceous than both the original growth mixture and the FAU zeolite product; however, in situ AFM studies using a dilute clear solution with a lower Si/Al ratio revealed three-dimensional growth of surfaces that is distinct from layer-by-layer and CPA pathways. This unique mechanism of growth differs from those observed in studies of other zeolites. Given that relatively few zeolite frameworks have been the subject of mechanistic investigation by in situ techniques, these observations of FAU crystallization raise the question whether its growth pathway is characteristic of other zeolite structures.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Multiphase combustion experimentation in microgravity

This paper examines the need for and implementation of microgravity combustion studies of two phase media. Experimental and analytical aspects of several heterogeneous kinetic systems are discussed. These include: flame propagation and extinction for quiescent clouds of uniformly premixed fuel particulates in an oxidizing atmosphere; autoignition of clouds of uniformly premixed fuel particulates in a quiescent oxidizing atmosphere; and the roles of catalytically significant surfaces in gaseous autoignition processes.

Berlad, A. L.↗
DOE OSTI2024

Support for U.S. Participants at the 18 th International Congress on Catalysis

The 18 th International Congress on Catalysis (ICC) was held Lyon, France on July 14-19, 2024. It provided a premier technical gathering in surface and organometallic catalysis, industrial homogeneous and heterogeneous catalysis, electrocatalysis, photocatalysis, and catalysis in condensed media. This meeting brough together participants from academia, industry, and national laboratories. The organization that overseed this meeting was the Council of the International Congress on Catalysis. This international committee has over 27 signature countries. The United States is represented in the Council of the International Congress on Catalysis through two permanent representatives. These representatives are elected by the Board of Directors of the North American Catalysis Society (NACS), an organization which coordinates and overseas the activities of 12 largely autonomous clubs within the United States, Canada, and Mexico. The critical importance of catalysis is reflected by the fact that 25-30% of all manufactured goods in the United States involve at least one catalytic step. Because advances in a large number of catalytic processes, which are crucial to U.S. interests, were presented at this meeting, it was important to ensure participation from both the U.S. academic and the industrial sectors.

02 PETROLEUM↗
DOE OSTI2024

Progress towards subsurface spectroscopy inside heterogeneous materials using four wave mixing phase conjugation

Herein, we report preliminary results on subsurface spectroscopy inside heterogeneous materials using four wave mixing phase conjugation. For our test material we use an inert plastic bonded explosive simulant that contains fluorescent guidestar particles. Using phase conjugation, we are able to obtain spectral enhancements approximately equal to the phase conjugate reflectivity. Additionally, we discuss future directions to improve this technique to obtain greater signal enhancements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Efficient reconstruction and validation of heterogeneous microstructures for energy applications

The digital reconstruction of microstructures is necessary for simulations in fields ranging from geology to electrochemistry, but the state-of-the-art digital reconstruction techniques often compromise between resolution and field of view. It is challenging to retain detailed microstructure information in large-scale reconstructions. Here, this study investigates different aspects of the Yeong-Torquato algorithm based on correlation functions to make it more efficient. We achieve this goal by reducing the computational complexity of the chord-length distribution function and the two-point correlation function, applying the random sphere-packing method as the initial condition, and restricting potential voxel swaps to interfaces. In addition, a novel superposition parallel scheme is introduced to aid in searching for potential voxel swaps. The algorithm proposed is validated by comparing the pore-size distributions of reconstructed 3D custom battery electrodes from a sample dataset obtained from transmission X-ray microscopy. From a sample image with 200 x 200 pixels, the code can reconstruct a 300 x 300 x 300 structure in under 22 h and reconstruct a 400 x 400 x 400 structure in 43 h with eight cores.

42 ENGINEERING↗
DOE OSTI2026

Enhanced Manganese Oxidation at the Biofilm–Fluid Interface Drives Pore-Scale Patterns in Mineral Precipitation

Microbial oxidation of manganese (Mn) from aqueous Mn(II) to solid-phase Mn(III, IV) minerals catalyzes Mn(II) removal in natural and engineered porous systems. However, little is known about the spatiotemporal evolution of Mn biomineralization in confined spaces that experience simultaneous Mn(II) delivery and Mn oxide precipitation. Here, we combine time-lapse microscopy, image analysis, and mass spectrometry to quantify the extent and rate of Mn biomineralization by Pseudomonas putida GB-1 in an optically transparent two-dimensional porous medium. We found that Mn(II) oxidation initially occurred within biofilms but shifted over time toward the edges of biofilms in contact with pore fluid. Minerals precipitated outside of the initial biofilm footprint likely due to surface-mediated oxidation of Mn(II) by nascent biogenic Mn oxides, reinforcing a gradient in mineral accumulation from the Mn(II) source near the reactor inlet to the outlet. The rate of mineral precipitation outside the biofilm footprint surpassed the rate of mineral accumulation inside biofilms within 6 h and accounted for two-thirds of the total Mn oxide mass in the pore space at the end of the experiment. This work advances a mechanistic understanding of coupled biotic and abiotic Mn oxidation in porous environments while providing a novel platform to quantify microbe-mineral-fluid interactions.

Biofilms↗
NASA NTRS2008

Stochastic Transport Theory for Investigating the Three-Dimensional Canopy Structure from Space Measurements

Radiation reflected from vegetation canopies exhibits high spatial variation. Satellite-borne sensors measure the mean intensities emanating from heterogeneous vegetated pixels. The theory of radiative transfer in stochastic media provides the most logical linkage between satellite observations and the three-dimensional canopy structure through a closed system of simple equations which contains the mean intensity and higher statistical moments directly as its unknowns. Although this theory has been a highly active research field in recent years, its potential for satellite remote sensing of vegetated surfaces has not been fully realized because of the lack of models of a canopy pair-correlation function that the stochastic radiative transfer equations require. The pair correlation function is defined as the probability of finding simultaneously phytoelements at two points. This paper presents analytical and Monte Carlo generated pair correlation functions. Theoretical and numerical analyses show that the spatial correlation between phytoelements is primarily responsible for the effects of the three-dimensional canopy structure on canopy reflective and absorptive properties. The pair correlation function, therefore, is the most natural and physically meaningful measure of the canopy structure over a wide range of scales. The stochastic radiative transfer equations naturally admit this measure and thus provide a powerful means to investigate the three-dimensional canopy structure from space. Canopy reflectances predicted by the stochastic equations are assessed by comparisons with the PARABOLA measurements from coniferous and broadleaf forest stands in the BOREAS Southern Study Areas. The pair correlation functions are derived from data on tree structural parameters collected during field campaigns conducted at these sites. The simulated canopy reflectances compare well with the PARABOLA data.

Huang, Dong↗
DOE OSTI2022

Magnetically recyclable nanocomposites via lanthanide-based MOFs grown on natural sea sponge: Screening hydrogenation of nitrophenol to aminophenol

Catalysts have played a significant role in chemical industries and received significant attention as a result. Unfortunately, many common catalytic systems are comprised of a small number of elemental species or use similar synthetic strategies, which potentially limit innovation in areas such as the discovery of new transformations. Metal-organic frameworks (MOFs) have been established as versatile materials employed in various applications that include catalysis; however, the majority of MOFs have been synthesized using transition metal building blocks, possibly hindering advances towards innovative materials with unique properties. Here this work reports the synthesis of MOFs based on lanthanide elements (Ln = Ce, Gd, La, and Sm), which demonstrate great potential yet are often overlooked. The Ln-based MOFs were grown in situ on natural sea sponge supports and Fe ion containing solution, followed by a thermal carbonization treatment to generate FeLn metal nanoparticles (NPs) embedded on carbon support (FeLn@C). These nanostructured products exhibited good crystallinity and well-confined particle sizes. We then demonstrate that these hybrid materials can be used as effective heterogeneous nanocatalysts for the hydrogenation of nitrophenol to aminophenol in aqueous media. Besides, FeLn@C catalysts had a magnetic property due to Fe atoms in the NPs, which can be mechanically separated out from the aqueous solution since the catalysts are magnetically attracted to the external magnets. This magnetic recyclability combined with the usage of the natural materials highlight the importance of sustainability in the design of Ln-based MOFs and their catalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

Transient Creep of a Composite Lower Crust: Constitutive Theory - 1

A composite model is proposed to describe the time-dependent response of the Earth's lower crust. The motivation for such it model is twofold: First, new observations of widespread postseismic deformation indicate that the deep continental crust responds viscoelastically, having both long-and short-term decay times. Second, by any number of observationally based rationales, the lower crust is compositionally and structurally heterogeneous over many length scales. For heterogeneities that have much smaller characteristic lengths than the minimum deformation wavelength of interest, the aggregate rheology can be described by composite media theory. For wavelengths of the order of the thickness of the lower crust (approx. = 25-40 km) and larger, composite theory may be applied to heterogeneities that are smaller than about several hundred meters, or equivalent to the vertical extent of a thick lower crustal mylonitic shear zone. The composite media theory developed here is constructed using both Eshelhy-Mori-Tanaka theory for aligned generalized spheroidal inclusions and a generalized self-consistent method. The inclusions and matrix are considered to be Maxwellian viscoelastic: a rheology that is consistent with past homogeneous models of postseismic stress relaxation. The composite theory presented here introduces a transient response to a suddenly imposed stress field which does not appear in homogeneous Maxwell models. Analytic expressions for the amplitude and duration of the transient and for the effective long-and short-term viscosities of the composite are given which describe the sensitivity to inclusion concentration (phi), to shape, and to ratio of inclusion-to-matrix viscosity (R).

Ivins, Erik R.↗
DOE OSTI2026

Knowledge Graph of RB-Tnseq Data from Fitness Browser (KP-DP1)

Motivation: Predicting microbial gene fitness across environmental conditions remains a central challenge for predictive phenomics and autonomous experimentation. Fitness assays generate large volumes of genotype–phenotype measurements difficult to integrate with experimental metadata and biological function in a form that supports mechanistic reasoning. Knowledge graphs offer a semantic framework for unifying modalities and enabling context-aware inference. Results: We build GIMME (Graph Inference for Microbial Metabolism Exploration), a semantically grounded knowledge graph that unifies gene fitness measurements spanning 10 Pseudomonas species with experimental metadata and biological context. Media are decomposed into chemical components and experiments carry structured links to natural-language descriptions. The resulting graph supports two inference modes: (1) symbolic graph traversal to surface candidate gene–environment and gene–chemical associations, and (2) learned inference using heterogeneous graph neural networks that propagate information across neighborhoods. We formulate link regression over (gene, media, experiment) triplets, combining learned gene embeddings with pretrained LLM sourced text embeddings of node descriptions to predict gene fitness. We then augment a baseline MLP with an auxiliary message-passing encoder (GraphSAGE/GAT) that propagates information over gene–protein–function and media–chemical subgraphs, and fuse the two pathways with a gated residual connection. This approach produces strong agreement with held-out fitness measurements (GraphSAGE Pearson r 0.74) while also highlighting inference challenges in extreme-fitness regimes. We aggregate GAT edge-attention weights by relation type and layer to estimate which biological and environmental relations most influence fitness predictions. Conclusion: This work explores using knowledge graphs as “context graphs” for microbial phenotype prediction. They provide a rich substrate which enables explainable retrieval of supporting evidence, and provides a natural bridge to autonomous workflows that prioritize the next experiment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Experiments Developed to Study Microgravity Smoldering Combustion

The overall objective of the Microgravity Smoldering Combustion (MSC) research program is to understand and predict smoldering combustion under normal and microgravity (near-zero-gravity) conditions to help prevent and control smolder-originated fires, in both environments. Smoldering is defined as a nonflaming, self-sustaining, propagating, exothermic surface reaction. If a material is sufficiently permeable, smoldering is not confined to its outer surface, but can propagate as a reaction wave through the interior of the material. The MSC program will accomplish its goals by conducting smolder experiments on the ground and in a space-based laboratory, and developing theoretical models of the process. Space-based experiments are necessary because smoldering is a very slow process and, consequently, its study in a microgravity environment requires extended periods of time that can only be achieved in space. Smoldering can occur in a variety of processes ranging from the smolder of porous insulating materials to underground coal combustion. Many materials can sustain smoldering, including wood, cloth, foams, tobacco, other dry organic materials, and charcoal. The ignition, propagation, transition to flaming, and extinction of the smolder reaction are controlled by complex, thermochemical mechanisms that are not well understood. As with many forms of combustion, gravity affects the availability of the oxidizer and the transport of heat, and therefore, the rate of combustion. The smoldering combustion of porous materials has been studied both experimentally and theoretically, usually in the context of fire safety. Smoldering encompasses a number of fundamental processes, including heat and mass transfer in a porous media; endothermic pyrolysis of combustible material; ignition, propagation, and extinction of heterogeneous exothermic reactions at the solid-gas pore interface; and the onset of gas phase reactions (flaming) from existing surface reactions. Smoldering presents a serious fire risk because the combustion can propagate slowly in a material's interior and go undetected for long periods of time. It typically yields a substantially higher conversion of fuel to toxic compounds than does flaming (though more slowly), and may undergo a sudden transition to flaming.

Vergilii, Franklin↗