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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mechanistic understanding of catalytic conversion of ethanol to 1-butene over 2D-pillared MFI zeolite

Ethanol is an important C2 platform molecule for producing value-added chemicals and distillate hydrocarbon fuels (e.g., jet and diesel). Among these, catalytic upgrading of ethanol to butenes can generate valuable commodity chemicals (e.g., 1-butene) and provide C4 olefin intermediates that can be further upgraded to jet/diesel fuels. 2D zeolites offer hierarchical mesoporous structures, leading to improved mass transport and reduced diffusion length, which can help to address the coking challenges faced by ethanol conversion to hydrocarbons over 3D zeolites. In this study, we investigate the acid-catalyzed conversion of ethanol to 1-butene over the Brønsted acid sites (BAS) in 2D-pillared MFI zeolite (2D-PMFI) using ab initio molecular dynamics (AIMD) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and calorimetric measurements. A detailed thermodynamic analysis, using quasi-harmonic approximation (QHA), on the Gibbs free energy pathway of ethanol conversion shows that the consideration of entropy is critical to accurately capture the detailed thermodynamic profiles. The formation of bulky ethoxy-ethene complex is found to be a potential rate-determining step (RDS), proceeding via stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through a careful control of number of BAS and operating temperatures. The accuracy of computational model is confirmed through the comparison of calculated vibrational density of states (VDOS) against the experimental DRIFTS measurements. Overall, our study provides mechanistic insights into ethanol upgrading over the 2D-PMFI and shows the importance of evaluating entropic effects in such confined system.

Ethanol conversion, 2D-pillared zeolite, MFI, Anha↗
DOE OSTI2021

Characteristics and mechanisms of hydrogen-induced quasi-cleavage fracture of lath martensitic steel

Here this study presents an in-depth characterization of the microstructures, crystallographic orientations, and dislocation characteristics beneath hydrogen-induced quasi-cleavage fracture features of an as-quenched, lath martensitic (α') 22MnB5 steel. The fracture surfaces of gaseous hydrogen-embrittled martensitic specimens were analyzed by a combination of multiple analytical tools: scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), and transmission Kikuchi diffraction (TKD). The dominant fracture mode in the hydrogen-affected zones was quasi-cleavage fracture, which involved significant plasticity, evidenced by plastic zones near tear ridges and a high density of dislocations beneath the quasi-cleavage facets. The martensite constituent sizes, variant orientations, and boundaries influenced the quasi-cleavage surface morphologies. Fractography revealed the occurrence of {100} α' -type cleavage across martensitic laths, developing relatively “flat” quasi-cleavage surfaces, in addition to {110} α' -type cracking likely along lath and block boundaries, and fracture along non-cleavage planes. The likelihood of the formation of the relatively “flat” quasi-cleavage surfaces increased with increasing martensitic constituent sizes. Substantial dislocation bands formed on intersecting {112} α' slip planes within a martensite block below the hydrogen-induced cleavage fractures on {100} α' planes. River markings on the quasi-cleavage surfaces were found to originate from the complex, hierarchical lath martensitic microstructure. Steps and ridges on the quasi-cleavage facets generally linked with the various martensitic boundaries, suggesting that they were produced as a result of crack deviations at those boundaries. The fracture paths and martensite quasi-cleavage mechanisms are discussed in the context of the role of hydrogen and Cottrell cleavage model.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Cosmological density fluctuations and large-scale structure From N-point correlation functions to the probability distribution

Knowledge of N-point correlation functions for all N allows one to invert and obtain the probability distribution of mass fluctuations in a fixed volume. The hierarchical sequence of higher order is applied to correlations with dimensionless amplitudes suggested by the BBGKY equations. The resulting distribution is significantly non-Gaussian, even for quite small mean square fluctuations. The qualitative and to some degree quantitative results are to a large degree independent of the exact sequence of amplitudes. An ensemble of such models compared with N-body simulations fails in detail to account for the low-density frequency distribution.

Fry, J. N.↗
NASA NTRS1991

Human life support during interplanetary travel and domicile. II - Generic Modular Flow Schematic modeling

This paper describes the Generic Modular Flow Schematic (GMFS) architecture capable of encompassing all functional elements of a physical/chemical life support system (LSS). The GMFS can be implemented to synthesize, model, analyze, and quantitatively compare many configurations of LSSs, from a simple, completely open-loop to a very complex closed-loop. The GMFS model is coded in ASPEN, a state-of-the-art chemical process simulation program, to accurately compute the material, heat, and power flow quantities for every stream in each of the subsystem functional elements (SFEs) in the chosen configuration of a life support system. The GMFS approach integrates the various SFEs and subsystems in a hierarchical and modular fashion facilitating rapid substitutions and reconfiguration of a life support system. The comprehensive ASPEN material and energy balance output is transferred to a systems and technology assessment spreadsheet for rigorous system analysis and trade studies.

Farral, Joseph F.↗
NASA NTRS2007

Hierarchically Structured Non-Intrusive Sign Language Recognition

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Zieren, Jorg↗
DOE OSTI2021

Structure–Property Correlation of Hierarchically Porous Carbons for Fluorocarbon Adsorption

Although traditional commercially available porous carbon-fluorocarbon working pairs have shown promising applicability for adsorption cooling, advancements in synthetic carbons may further improve performance. Moreover, insights into structure-property relationships that target higher sorption capacities within these synthesized carbons may guide such materials' future design. We utilized hierarchically porous synthetic carbons (HPCs) with colossal microporous and mesoporous characterized by high surface areas (up to 2689 m 2 /g) and pore volumes (up to 10.31 cm 3 /g) towards fluorocarbon R134a adsorption. This unique pore topology leads to exceptional R134a uptake, ~250 wt.%, outperforming the highest uptake carbon material to date, Maxsorb III (~220 wt.%). Additionally, material characterizations reveal that the outstanding R134a capacity may be attributed to textural properties and oxygen-terminated functional groups more than graphitization of the material. Most importantly, HPCs are efficiently utilized in a two-bed model chiller device, where the performance shows excellent working capacity (105 wt%, ~1.5 times the value of reported carbon materials/R134a). Fluorocarbons adsorption on HPCs also displays fast kinetics (equilibrium time: ~2 min) mainly driven by physical adsorption (Qst: ~27 kJ/mol), characteristic of swiftly reversible behavior adsorption-desorption behaviors. This work provides a fundamental understanding of the applicability of HPCs/R134a working pair for adsorption cooling.

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

Modeling Interactions within and between Peptide Amphiphile Supramolecular Filaments

Many peptides are able to self-assemble into one-dimensional (1D) nanostructures, such as cylindrical fibers or ribbons of variable widths, but the relationship between the morphology of 1D objects and their molecular structure is not well understood. Here, we use coarse-grained molecular dynamics (CG-MD) simulations to study the nanostructures formed by self-assembly of different peptide amphiphiles (PAs). The results show that ribbons are hierarchical superstructures formed by laterally assembled cylindrical fibers. Simulations starting from bilayer structures demonstrate the formation of filaments, whereas other simulations starting from filaments indicate varying degrees of interaction among them depending on chemical structure. These interactions are verified by observations using atomic force microscopy of the various systems. The interfilament interactions are predicted to be strongest in supramolecular assemblies that display hydrophilic groups on their surfaces, while those with hydrophobic ones are predicted to interact more weakly as confirmed by viscosity measurements. The simulations also suggest that peptide amphiphiles with hydrophobic termini bend to reduce their interfacial energy with water, which may explain why these systems do not collapse into superstructures of bundled filaments. The simulations suggest that future experiments will need to address mechanistic questions about the self-assembly of these systems into hierarchical structures, namely, the preformation of interactive filaments vs equilibration of large assemblies into superstructures.

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

Advancing Chemical Separations: Unraveling the Structure and Dynamics of Phase Splitting in Liquid–Liquid Extraction

Liquid-liquid extraction (LLE), the go-to process for a variety of chemical separations, is limited by spontaneous organic phase splitting upon sufficient solute loading, called third phase formation. In this study we explore the applicability of critical phenomena theory to gain insight into this deleterious phase behavior with the goal of improving separations efficiency and minimizing waste. Here, a series of samples representative of rare earth purification were constructed to include each of one light and one heavy lanthanide (cerium and lutetium) paired with one of two common malonamide extractants (DMDOHEMA and DMDBTDMA). The resulting postextraction organic phases are chemically complex and often form rich hierarchical structures whose statics and dynamics near the critical point were probed herein with small-angle X-ray scattering and high-speed X-ray photon correlation spectroscopy. Despite their different extraction behaviors, all samples show remarkably similar critical behavior with exponents well described by classical critical point theory consistent with the 3D Ising model, where the critical behavior is characterized by fluctuations with a single diverging length scale. This unexpected result indicates a significant reduction in relevant chemical parameters at the critical point, indicating that the underlying behavior of phase transitions in LLE rely on far fewer variables than are generally assumed. The obtained scalar order parameter is attributed to the extractant fraction of the extractant/diluent mixture, revealing that other solution components and their respective concentrations simply shift the critical temperature but do not affect the nature of the critical fluctuations. These findings point to an opportunity to drastically simplify studies of liquid-liquid phase separation and phase diagram development in general while providing insights into LLE process improvement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Commensuration Effects in Layered Nanoparticle Solids.

We have developed a hierarchical nanoparticle transport simulator (HINTS) and adapted it to study commensuration effects in two classes of nanoparticle (NP) solids: (1) a bilayer NP solid (BNS) with an energy offset and (2) a BNS as part of a field effect transistor (FET). HINTS integrates the ab initio characterization of single NPs with the phonon-assisted tunneling transition model of the NP-NP transitions into a kinetic Monte Carlo based simulation of the charge transport in NP solids. First, we studied a BNS with an interlayer energy offset Delta, possibly caused by a fixed electric field. Our results include the following. First, in the independent energy-offset model, we observed the emergence of commensuration effects when scanning the electron filling factor (FF) across integer values. These commensuration effects were profound as they reduced the mobility by several orders of magnitude. We analyzed these commensuration effects in a five-dimensional parameter space, as a function of the on-site charging energy E-C, energy offset Delta, disorder D, the electron FF, and temperature k(B)T. We demonstrated the complexity of our model by showing that at integer FFs commensuration effects are present in some regions of the parameter space, while they vanish in other regions, thus defining distinct dynamical phases of the model. We determined the phase boundaries between these dynamical phases. Second, using these results as a foundation, we shifted our focus to the experimentally much-studied NP-FETs. NP-FETs are also characterized by an interlayer energy offset Delta, which, in contrast to our first model, is set by the gate voltage V-G and thereby related to the electron FF. We repeated many of our simulations and again demonstrated the emergence of commensuration effects and distinct dynamical phases in these NP-FETs. Notably, the commensuration effects in the NP-FETs showed many similarities to those in the independent energy-offset BNS.

Qu, Luman↗
NASA NTRS1987

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

Peuquet, Donna J.↗
DOE OSTI2023

Chemical structure and complex growth modes of magnesium silicate hydrate: Nanoparticle orientation, aggregation, and fusion

The extent of utilization of magnesium silicate hydrate (MSH) in construction is limited partly because of insufficient data ascertaining the kinetics of its precipitation. In this report MSH grown homogeneously or heterogeneously in the range of magnesium to silicon solution molar concentration ratios, [Mg]/[Si] = 0.5-1.5, and temperature = 25-80 °C was analyzed for its chemical structure and morphology. Infrared spectroscopy and geochemical modeling show that increasing the [Mg]/[Si] ratio results in less silicate polymerization in MSH. Atomic force microscopy reveals the presence of nanoparticles that aggregate and fuse to form films. Oriented attachment of nanoparticles and features indicative of enhanced crystallinity were observed at higher temperatures and longer reaction times. These data provide direct evidence for the persistence of hierarchical structures (i.e., nanoparticles forming 3D microparticles and 2D film layers) at the nanoscale to mesoscale. These findings offer insights into the precise chemical synthesis of MSH and its widespread use as a binder for construction purposes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Probing Condensed-Phase Structure and Dynamics in Hierarchical Zeolites and Nanosheets for Catalytic Upgradation of Biomass (Final Report)

Understanding complex reaction pathways in systems governed by multi-scale collective interactions across time and length scales remains a central scientific challenge. This project was guided by the hypothesis that the interplay among oligomers, solvents, and active sites can be tuned by a suitable choice of solvation environment and pore architecture in solid-acid catalysts to direct chemical transformations relevant to biomass conversion. Zeolites and zeolite nanosheets were used as model platforms, allowing for the interaction of macromolecules with the surface of the zeolite nanosheets and with smaller pores that host catalytically active sites. To investigate these coupled phenomena, we employ a multi-scale computational framework that integrates molecular-level descriptions with advanced sampling approaches to capture key physical and chemical interactions. Our work through this project improved fundamental understanding of how reactants and solid-acid catalysts interact in solvent-rich environments, thereby enabling the rational design of catalytic systems that upgrade biomass with enhanced selectivity and energy efficiency. In addition, the project developed advanced sampling methodologies critical for disentangling complex, reactive processes in multi-component catalytic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

CommBench: Micro-Benchmarking Hierarchical Networks with Multi-GPU, Multi-NIC Nodes

Modern high-performance computing systems have multiple GPUs and network interface cards (NICs) per node. The resulting network architectures have multilevel hierarchies of subnetworks with different interconnect and software technologies. These systems offer multiple vendor-provided communication capabilities and library implementations (IPC, MPI, NCCL, RCCL, OneCCL) with APIs providing varying levels of performance across the different levels. Understanding this performance is currently difficult because of the wide range of architectures and programming models (CUDA, HIP, OneAPI). We present CommBench, a library with cross-system portability and a high-level API that enables developers to easily build microbenchmarks relevant to their use cases and gain insight into the performance (bandwidth & latency) of multiple implementation libraries on different networks. We demonstrate CommBench with three sets of microbenchmarks that profile the performance of six systems. Our experimental results reveal the effect of multiple NICs on optimizing the bandwidth across nodes and also present the performance characteristics of four available communication libraries within and across nodes of NVIDIA, AMD, and Intel GPU networks.

Hidayetoglu, Mert↗
NASA NTRS2006

Adding Hierarchical Objects to Relational Database General-Purpose XML-Based Information Managements

NETMARK is a flexible, high-throughput software system for managing, storing, and rapid searching of unstructured and semi-structured documents. NETMARK transforms such documents from their original highly complex, constantly changing, heterogeneous data formats into well-structured, common data formats in using Hypertext Markup Language (HTML) and/or Extensible Markup Language (XML). The software implements an object-relational database system that combines the best practices of the relational model utilizing Structured Query Language (SQL) with those of the object-oriented, semantic database model for creating complex data. In particular, NETMARK takes advantage of the Oracle 8i object-relational database model using physical-address data types for very efficient keyword searches of records across both context and content. NETMARK also supports multiple international standards such as WEBDAV for drag-and-drop file management and SOAP for integrated information management using Web services. The document-organization and -searching capabilities afforded by NETMARK are likely to make this software attractive for use in disciplines as diverse as science, auditing, and law enforcement.

Lin, Shu-Chun↗
DOE OSTI2022

Additive friction stir deposition of SS316: Effect of process parameters on microstructure evolution

Solid state nature of additive friction stir deposition (AFSD) additive manufacturing process is very advantageous in terms of defect formation and microstructural refinement in the material. Current study presents the process optimization, microstructural evolution and kinetics of recrystallization for AFSD deposited low stacking fault energy material - SS316. As deposited microstructure shows equiaxed ultra fine grains with an average grain size of ~5.0 ± 0.5 μm. Shear deformation at high temperature during processing leads to the operation of restoration mechanisms. Observation of necklace type microstructure in the as deposited SS316 is attributed to discontinuous dynamic recrystallization during processing. Recrystallization kinetics of the AFSD SS316 is characterized using Johnson-Mehl-Avarami-Kolmogorov (JMAK) model. Deformation – thermal cycling during AFSD process resulted in inconsistent recrystallization kinetics. Variation in strain, strain rate and temperature during processing with processing parameters result in varying microstructure and tool wear. Further, high strength-ductility combination and sustained work hardening in as deposited SS316 appear to arise from transformation and twinning during deformation, leading to the formation of hierarchical twins and martensitic phase after deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Feedback regulation of crystal growth by buffering monomer concentration

Abstract Crystallization is a ubiquitous means of self-assembly that can organize matter over length scales orders of magnitude larger than those of the monomer units. Yet crystallization is notoriously difficult to control because it is exquisitely sensitive to monomer concentration, which changes as monomers are depleted during growth. Living cells control crystallization using chemical reaction networks that offset depletion by synthesizing or activating monomers to regulate monomer concentration, stabilizing growth conditions even as depletion rates change, and thus reliably yielding desired products. Using DNA nanotubes as a model system, here we show that coupling a generic reversible bimolecular monomer buffering reaction to a crystallization process leads to reliable growth of large, uniformly sized crystals even when crystal growth rates change over time. Buffering could be applied broadly as a simple means to regulate and sustain batch crystallization and could facilitate the self-assembly of complex, hierarchical synthetic structures.

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

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗
DOE OSTI2023

Structure-informed clustering for population stratification in association studies

Background: Identifying variants associated with complex traits is a challenging task in genetic association studies due to linkage disequilibrium (LD) between genetic variants and population stratification, unrelated to the disease risk. Existing methods of population structure correction use principal component analysis or linear mixed models with a random effect when modeling associations between a trait of interest and genetic markers. However, due to stringent significance thresholds and latent interactions between the markers, these methods often fail to detect genuinely associated variants. Results: To overcome this, we propose CluStrat, which corrects for complex arbitrarily structured populations while leveraging the linkage disequilibrium induced distances between genetic markers. It performs an agglomerative hierarchical clustering using the Mahalanobis distance covariance matrix of the markers. In simulation studies, we show that our method outperforms existing methods in detecting true causal variants. Applying CluStrat on WTCCC2 and UK Biobank cohorts, we found biologically relevant associations in Schizophrenia and Myocardial Infarction. CluStrat was also able to correct for population structure in polygenic adaptation of height in Europeans. Conclusions: CluStrat highlights the advantages of biologically relevant distance metrics, such as the Mahalanobis distance, which captures the cryptic interactions within populations in the presence of LD better than the Euclidean distance.

59 BASIC BIOLOGICAL SCIENCES↗