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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Residual tissue repositories as a resource for population-based cancer proteomic studies

Background: Mass spectrometry-based proteomics has become a powerful tool for the identification and quantification of proteins from a wide variety of biological specimens. To date, the majority of studies utilizing tissue samples have been carried out on prospectively collected fresh frozen or optimal cutting temperature (OCT) embedded specimens. However, such specimens are often difficult to obtain, in limited in supply, and clinical information and outcomes on patients are inherently delayed as compared to banked samples. Annotated formalin fixed, paraffin embedded (FFPE) tumor tissue specimens are available for research use from a variety of tissue banks, such as from the surveillance, epidemiology and end results (SEER) registries’ residual tissue repositories. Given the wealth of outcomes information associated with such samples, the reuse of archived FFPE blocks for deep proteomic characterization with mass spectrometry technologies would provide a valuable resource for population-based cancer studies. Further, due to the widespread availability of FFPE specimens, validation of specimen integrity opens the possibility for thousands of studies that can be conducted worldwide. Methods: To examine the suitability of the SEER repository tissues for proteomic and phosphoproteomic analysis, we analyzed 60 SEER patient samples, with time in storage ranging from 7 to 32 years; 60 samples with expression proteomics and 18 with phosphoproteomics, using isobaric labeling. Linear modeling and gene set enrichment analysis was used to evaluate the impacts of collection site and storage time. Results: All samples, regardless of age, yielded suitable protein mass after extraction for expression analysis and 18 samples yielded sufficient mass for phosphopeptide analysis. Although peptide, protein, and phosphopeptide identifications were reduced by 50, 20 and 76% respectively, from comparable OCT specimens, we found no statistically significant differences in protein quantitation correlating with collection site or specimen age. GSEA analysis of GOterm level measurements of protein abundance differences between FFPE and OCT embedded specimens suggest that the formalin fixation process may alter representation of protein categories in the resulting dataset. Conclusions: These studies demonstrate that residual FFPE tissue specimens, of varying age and collection site, are a promising source of protein for proteomic investigations if paired with rigorously verified mass spectrometry workflows.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Analysis of Joist Masonry Moisture Content Monitoring

BSC TO5 Task 7.2 Analysis of Joist Masonry Moisture Content Monitoring House - Lawrence, MA 01840 This work involved the field monitoring of embedded wood joist ends in a solid brick building in zone 5A that was retrofitted with interior insulation. Eleven joists throughout the building (which have a variety of orientations, exposures, and masonry wall types) were monitored for wood MCs at the embedded joist ends and for temperatures and RHs within the joist pocket. Indoor and outdoor conditions were also recorded. Results were collected for 28 months (December 2012-April 2015). One limitation was that the renovation was still ongoing; limited wintertime construction heating and no permanent occupancy were factors. Much of the building experienced cold interior temperatures (e.g., construction heating) during the winters. These were not typical interior heating set points. Because the building was essentially unoccupied, no significant interior moisture was generated. These boundary conditions are not normal service conditions. Overall, the RHs and MCs measured in joist pockets were higher than recommended for longterm durability. Many of the joist pockets had sustained conditions of 100% RH, and many wood MCs were in the 25%-35% range for extended periods. Typical guidance includes: (1) MCs lower than 20% are safe, and (2) decay fungi become active at MCs higher than 28%. ASHRAE xi 160 analysis showed that high RH levels coincided with temperatures that were high enough to support mold growth for most of the monitoring period (60%-70% of the hours) in most joists. However, no damage was seen at the joist ends when the instrumentation was installed or when a joist end sample was removed. This suggests that dense, old-growth framing might be able to survive these MCs without damage. Orientation has a significant effect on RH and MC levels: solar heating and drying kept all southfacing joist MCs well within the safe range. The east and west orientations had mixed results: some were in the safe range, but others exceeded the 20% MC level. The north side joists consistently had the highest MCs. Almost all the joists showed seasonal rises and falls; MC and RH conditions were higher during the summer and lower during the winter. This indicates the temperature gradient caused moisture to be driven inward during the summer. MC plots with driving rain showed no discernable correlations. In the parts of the building that had significant wintertime heating, many joists showed a drop in MC that coincided with the addition of heat, even after insulation and air sealing were installed. The joist ends showed a repeated pattern of MC measurements at their upper and lower ends. The lower joist end was consistently wetter than the upper joist end, which can be attributed to contact with the masonry pocket, gravity drainage of bulk water to the bottom of the pocket, greater drying at the top of the beam or deeper embedment at the bottom of the beam, and a larger air pocket at the top of the beam. The north-facing insulated and uninsulated joist ends were compared; a significant or consistent MC or RH difference was not seen between these cases. All three joist pockets essentially remained at a constant 100% RH.

Array↗
DOE OSTI2021

On the Origin of Sinter‐Resistance and Catalyst Accessibility in Raspberry‐Colloid‐Templated Catalyst Design

Abstract Nanoparticle (NP) sintering is a major cause of the deactivation of supported catalysts. Raspberry‐colloid‐templated (RCT) catalysts are an emerging class of materials that show an unprecedented level of sinter‐resistance and exhibit high catalytic activity. Here a comprehensive study of the origin of NP stability and accessibility in RCT catalysts using theoretical modeling, 3D electron microscopy, and epitaxial overgrowth is reported. The approach is showcased for silica‐based RCT catalysts containing dilute Pd‐in‐Au NPs previously used in hydrogenation and oxidation catalysis. Modeling of the contact line of the silica precursor infiltrating into the assembled raspberry colloids suggests that a large part of the particles must be embedded into silica, which is confirmed by quantitative visualization of >200 individual NPs by dual‐axis electron tomography. The RCT catalysts have a unique structure in which all NPs reside at the pore wall but have >50% of their surface embedded in the matrix, giving rise to the strongly enhanced thermal and mechanical stability. Importantly, epitaxial overgrowth of Ag on the supported NPs reveals that not only the NP surface exposed to the pore but the embedded interface as well remained chemically accessible. This mechanistic understanding provides valuable guidance in the design of stable catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Moisture Absorbing and Water Self‐Releasing from Hybrid Hydrogel Desiccants

Abstract Atmospheric moisture is a valuable resource for fresh water and potentially sustainable energy. However, direct harvesting water from moisture (the vapor form) remains the most challenging. Hybrid desiccants made from hydrogels embedded with salt offer promise in absorbing moisture. However, the desorption process often requires additional energy to heat the samples. Here, poly(acrylic acid) (PAA) hydrogels embedded with lithium chloride are prepared, demonstratng simultaneous moisture absorption and self‐release of liquid water at room temperature with 50–90% relative humidity. The water self‐releasing process can be separated into two distinct stages: 1) surface release, where water droplets grow on the hydrogel surface due to differences in nucleation and diffusion rates, and 2) bulk release, triggered by the collapse of polymer chains, subsequently releasing water from the hydrogel network. Factors such as salt concentration, hydrogel crosslinking density, and film thickness are investigated to better understand the moisture absorption and water‐releasing processes. Moreover, hydrophobic domains are introduced onto the salt‐embedded PAA films, creating an edge effect that enhances the droplet growth rates. When the hydrophobic domains are patterned, the movement of released water can be guided, resulting in a threefold increase in water removal rate attributed to gravitational force.

Chemistry↗
DOE OSTI2018

Enhanced Stability of Lithium Metal Anode by using a 3D Porous Nickel Substrate

Lithium (Li) metal is considered the “holy grail” anode for high energy density batteries, but its applications in rechargeable Li metal batteries are still hindered by the formation of Li dendrites and low Coulombic efficiency for Li plating/stripping. An effective strategy to stabilize Li metal is by embedding Li metal anode in a three-dimensional (3D) current collector. Here, a highly porous 3D Ni substrate is reported to effectively stabilize Li metal anode. Using galvanostatic intermittent titration technique combined with scanning electron microscopy, the underlying mechanism on the improved stability of Li metal anode is revealed. It is clearly demonstrated that the use of porous 3D Ni substrate can effectively suppress the formation of “dead” Li and forms a dense surface layer, whereas a porous “dead” Li layer is accumulated on the 2D Li metal which eventually leads to mass transport limitations. X-ray photoelectron spectroscopy results further revealed the compositional differences in the solid-electrolyte interphase layer formed on the Li metal embedded in porous 3D Ni substrate and the 2D copper substrate.

Yu, Lu↗
DOE OSTI2018

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on an embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

OpenGraphGym: A Parallel Reinforcement Learning Framework for Graph Optimization Problems

This paper presents an open-source, parallel AI environment (named OpenGraphGym) to facilitate the application of reinforcement learning (RL) algorithms to address combinatorial graph optimization problems. This environment incorporates a basic deep reinforcement learning method, and several graph embeddings to capture graph features, it also allows users to rapidly plug in and test new RL algorithms and graph embeddings for graph optimization problems. This new open-source RL framework is targeted at achieving both high performance and high quality of the computed graph solutions. This RL framework forms the foundation of several ongoing research directions, including 1) benchmark works on different RL algorithms and embedding methods for classic graph problems; 2) advanced parallel strategies for extreme-scale graph computations, as well as 3) performance evaluation on real-world graph solutions.

Zheng, Weijian↗
DOE OSTI2024

Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution

A central problem in biology is to understand how organisms evolve and adapt to their environment by acquiring variations in the observable characteristics or traits of species across the tree of life. With the growing availability of large-scale image repositories in biology and recent advances in generative modeling, there is an opportunity to accelerate the discovery of evolutionary traits automatically from images. Toward this goal, we introduce Phylo-Diffusion, a novel framework for conditioning diffusion models with phylogenetic knowledge represented in the form of HIERarchical Embeddings (HIER-Embeds). We also propose two new experiments for perturbing the embedding space of Phylo-Diffusion: trait masking and trait swapping, inspired by counterpart experiments of gene knockout and gene editing/swapping. Our work represents a novel methodological advance in generative modeling to structure the embedding space of diffusion models using tree-based knowledge. Our work also opens a new chapter of research in evolutionary biology by using generative models to visualize evolutionary changes directly from images. We empirically demonstrate the usefulness of Phylo-Diffusion in capturing meaningful trait variations for fishes and birds, revealing novel insights about the biological mechanisms of their evolution. (Model and code can be found at imageomics.github.io/phylo-diffusion)

Khurana, Mridul↗
DOE OSTI2019

Hydrophobic Reduced Graphene Oxide-Based Ni Coating for Improved Tribological Application

Electrodeposited nickel-graphene oxide (GO) composite coating was produced by pulse electrodeposition method followed by a functionalization with octadecyl amine (ODA) molecules to convert the embedded hydrophilic GO to hydrophobic reduced GO-ODA. Morphology, compositional, and tribological properties were investigated for the functionalized Ni-GO-ODA composite coating. FE-SEM and AFM microscopic studies show the homogeneous presence of embedded GO-ODA particles in the Ni matrix. XRD, EDS, and Raman spectra confirmed the successful functionalization of GO to GO-ODA. Post-functionalization, the water contact angle of the coating shows 111.8°, thereby confirming its hydrophobic nature. Tribological experiments were conducted by using a linear reciprocating ball on flat sliding microtribometer with varying load and sliding speed at ambient dry sliding condition. Experimental results showed that the wear and friction resistance properties were significantly enhanced after functionalization of GO with ODA. With increasing load, the counter surface penetrates into the bulk of the coating and exposes the embedded particles, which further under shear built a surface film which reduces friction. The wear and failure mechanisms of these coatings subjected to tribological testing were also investigated. This work provides a novel approach to design durable functionalized nano-coatings for tribological applications in various industries such as automotive, aerospace, locomotive and renewable energy technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Magnetic properties of friction stir processed composite

There are many existing inspection systems each with their own advantages and drawbacks. These usually comprise of semi-remote sensors which frequently causes difficulty in reaching complex areas of a component. This study proposes to overcome that difficulty by developing embedded functional composites. Through this route, embedding can be achieved in virtually any component part and can be periodically interrogated by a reading device. The “reinforcement rich” processed areas can then be utilized to record properties like strain, temperature, stress state etc. depending on the reinforcement material. In this work, friction stir processing (FSP) was utilized to fabricate a magnetostrictive composite by embedding galfenol particles into a nonmagnetic aluminum (Al) matrix. It targets to develop a composite that produces strain in a varying magnetic field. Reinforcements were observed to be distributed uniformly in the matrix. Magnetization curves were studied using a vibrating sample magnetometer (VSM). A simple and cheap setup was developed to measure the magnetostrictive strain of the composites. Important factors affecting the magnetic properties were identified and ways to improve the magnetic properties discussed.

Das, Shamiparna↗
DOE OSTI2018

Geometric and algebraic structures associated with the channel quantization problem

We consider the use of surfaces as topological spaces in order to provide an answer to the quantization problem of a discrete memoryless channel (DMC). The aim is to identify the geometric and algebraic properties of the surface associated with the embedding of such a DMC. The procedure is based on the following steps: knowing the complete bipartite graph associated with a given DMC: (1) to determine the minimum and the maximum genus of the corresponding surfaces in which the given graph is embedded; (2) knowing the genus, to specify the roots as the elements of a Farey sequence of a planar algebraic curve; (3) to determine the solutions of a second-order Fuchsian differential equation as the generators of the corresponding Fuchsian group. We consider the cases of the hypergeometric and Heun equations, with three and four regular singular points, respectively. By means of this procedure, the fundamental region associated with the Fuchsian group is identified and this is the region where the planar algebraic curve is uniformized. A generalization of the quantization problem related to an m-ary input n-ary output symmetric channel viewed as a complete bipartite graph K{sub m,n}, by use of the embedding of this channel in compact surfaces is straightforward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Pool boiling heat transfer characteristics of low-GWP refrigerants in a horizontal tube bundle configuration

Heat transfer enhancement techniques have been adapted on the shell side to improve the overall performance of the flooded evaporators, such as finned tubes. In recent years, it has been demonstrated that the metal foam structure can offer enhanced heat transfer performance under pool boiling conditions. However, there are not much research in the open literature that examine the feasibility of metal foam embedded tubes in horizontal tube bundle configurations. Therefore, this paper proposed a novel metal foam embedded tube (i.e., foam embedded outside the tube) to improve the heat transfer behavior of flooded evaporators. Further, the experiments were performed on a horizontal tube bundle with a staggered arrangement. Moreover, the performance of low global warming potential (GWP) refrigerants (R-1234yf and R-1234ze(E)) is compared against R-134a for both plain tubes and metal foam tubes with porosities of 81%, 75%, and 62%. The results showed that a metal foam tube with a porosity of 62% showed a maximum heat transfer coefficient (HTC) enhancement of 291% compared to the plain tube. As compared with R-134a, the HTCs of R-1234yf and R-1234ze(E) are nearly 10% higher and 5% lower, respectively.

42 ENGINEERING↗
DOE OSTI2017

Detailed, sterically-resolved modeling of soot oxidation: Role of O atoms, interplay with particle nanostructure, and emergence of inner particle burning

A newly-developed detailed mechanism of soot oxidation was tested against experimental observations. The computations were performed at an atomistic level and with a detailed consideration of soot particle surface sites. Several additional reactions were investigated theoretically and one of them, oxidation of embedded five-member rings by O atoms, was included in the model. Here, the primary focus of the study was on the high-temperature shock-tube experiments of Roth et al. (1991). The reaction model was able to reproduce the experimental results, but required coupling to particle nanostructure: partial oxidation of PAH molecules and the decrease in PAH initial sizes along the oxidation path. The principle reaction mechanism was identified to be the formation of oxyradicals, their decomposition, formation of hard-to-oxidize embedded five-member rings, and oxidation of the latter predominantly by O atoms. The analysis identified O as the most effective oxidizer of the embedded five-member rings, which thus controls the rate of the overall oxidation. The model thus predicts fast oxidation during a brief initial period followed by a slow-oxidation one. The model of partial oxidation of an aromatic molecule and switching to the next intact molecule suggests pore formation and subsequent inner particle burning. We also investigated the ability of the present model to reproduce recent measurements of soot oxidation rates performed by Camacho et al. (2015) at about 1000 K. The initial reaction model failed to predict these results, and no adjustment could reconcile the differences. The only way to bring the model to experimental values was by assuming a catalytic decomposition of water on the reactor wall supplying additional radicals, H and OH, to the reacting gas mixture. Additional chemistry, oxidation through complex formation at neighboring surface sites, was required to fully reproduce the experimental observations. These additional reactions were found to play no role in the high-temperature simulations, nor were they sufficient to reproduce the low-temperature experiment on their own, without the assumed catalytic decomposition of water.

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

In-situ effect in cross-ply laminates under various loading conditions analyzed with hybrid macro/micro-scale computational models

In this article, multi-scale finite element analyses based on three-dimensional (3D) hybrid macro/micro-scale computational models subjected to various loading conditions are carried out to examine the in-situ effect imposed by the neighboring plies on the failure initiation and propagation of cross-ply laminates. A detailed comparative study on crack suppression mechanisms due to the effect of embedded laminar thickness and adjacent ply orientation is presented. Furthermore, we compare the results of in-situ transverse failure strain and strength between the computational models and analytical predictions. Good agreements are generally observed, indicating the constructed computational models are highly accurate to quantify the in-situ effect. Subsequently, empirical formulas for calculating the in-situ strengths as a function of embedded ply thickness and different ply angle between embedded and adjacent plies are developed, during which several material parameters are obtained using a reverse fitting method. Finally, a new set of failure criteria for σ 22 -τ 12 , σ 22 -τ 23 , and σ 11 -τ 12 accounting for the in-situ strengths are proposed to predict laminated composites failure under multi-axial stress states. This study demonstrates an effective and efficient computational technique towards the accurate prediction of the failure behaviors and strengths of cross-ply laminates by including the in-situ effects.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Accurate classical short-range forces for the study of collision cascades in Fe–Ni–Cr

The predictive power of a classical molecular dynamics simulation is largely determined by the physical validity of its underlying empirical potential. In the case of high-energy collision cascades, it was recently shown that correctly modeling interactions at short distances is necessary to accurately predict primary damage production. An ab initio based framework is introduced for modifying an existing embedded-atom method FeNiCr potential to handle these short-range interactions. Density functional theory is used to calculate the energetics of two atoms approaching each other, embedded in the alloy, and to calculate the equation of state of the alloy as it is compressed. The pairwise terms and the embedding terms of the potential are modi ed in accordance with the ab initio results. Using this reparametrized potential, collision cascades are performed in Ni 50 Fe 50 , Ni 80 Cr 20 and Ni 33 Fe 33 Cr 33 . The simulations reveal that alloying Ni and NiCr to Fe reduces primary damage production, in agreement with some previous calculations. Alloying Ni and NiFe to Cr does not reduce primary damage production, in contradiction with previous calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The U.S. Department of Veterans' Affairs depleted uranium exposed cohort at 25 Years: Longitudinal surveillance results

Background: A small group of Gulf War I veterans wounded in depleted uranium (DU) friendly-fire incidents have been monitored for health changes in a clinical surveillance program at the Veterans Affairs Medical Center, Baltimore since 1994. Methods: During the spring of 2015, an in-patient clinical surveillance protocol was performed on 36 members of the cohort, including exposure monitoring for total and isotopic uranium concentrations in urine and a comprehensive assessment of health outcomes. Results: On-going mobilization of U from embedded fragments is evidenced by elevated urine U concentrations. The DU isotopic signature is observed principally in participants possessing embedded fragments. Those with only an inhalation exposure have lower urine U concentration and a natural isotopic signature. Conclusions: At 25 years since first exposure to DU, an aging cohort of military veterans continues to show no U-related health effects in known target organs of U toxicity. As U body burden continues to accrue from in-situ mobilization from metal fragment depots, and increases with exposure duration, critical tissue-specific U concentration thresholds may be reached, thus recommending on-going surveillance of this veteran cohort. - Highlights: • Gulf War I veterans wounded with depleted uranium are monitored for health changes. • In 2015 in-patient clinical surveillance was performed on 36 members of the cohort. • Mobilization of U from embedded fragments is evidenced by elevated U in urine. • This cohort of continues to show no U-related health effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power flow equations can be successfully modeled using neural networks. These neural networks can be exactly transformed into mixed integer linear programs and embedded inside challenging optimization problems, thus replacing nonlinearities that are intractable for many applications with tractable piecewise linear approximations. Such approaches, though, suffer from an explosion of the number of binary variables needed to represent the neural network. Accordingly, this paper develops a technique for training an "optimally compact'' neural network, i.e., one that can represent the power flow equations with a sufficiently high degree of accuracy while still maintaining a tractable number of binary variables. We demonstrate the use of this neural network as an approximator of the nonlinear power flow equations by embedding it in the AC unit commitment problem, transforming the problem from a mixed integer nonlinear program into a more manageable mixed integer linear program. We use the 14-, 57-, and 89-bus networks as test cases and compare the AC-feasibility of commitment decisions resulting from the neural network, DC, and linearized power flow approximations. Our results show that the neural network model outperforms both the DC and linearized power flow approximations when embedded in the unit commitment problem. The neural network formulation most often selects a feasible unit commitment schedule, and furthermore, it only s

AC power flow↗
DOE OSTI2016

Mitigating cutting-induced plasticity in the contour method, Part 2: Numerical analysis

Cutting-induced plasticity can have a significant effect on the measurement accuracy of the contour method. The present study examines the benefit of a double-embedded cutting configuration that relies on self-restraint of the specimen, relative to conventional edge-crack cutting configurations. A series of finite element analyses are used to simulate the planar sectioning performed during double-embedded and conventional edge-crack contour cutting configurations. The results of numerical analyses are first compared to measured results to validate the cutting simulations. The simulations are then used to compare the efficacy of different cutting configurations by predicting the deviation of the residual stress profile from an original (pre-cutting) reference stress field, and the extent of cutting-induced plasticity. Comparisons reveal that while the double-embedded cutting configuration produces the most accurate residual stress measurements, the highest levels of plastic flow are generated in this process. As a result, this cutting-induced plastic deformation is, however, largely confined to small ligaments formed as a consequence of the sample sectioning process, and as such it does not significantly affect the back-calculated residual stress field.

36 MATERIALS SCIENCE↗