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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one-carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. Here, by ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Quantified uncertainty in thermodynamic modeling for materials design

Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach. Here, the accuracy of CALPHAD predictions vary widely in X-T-P space due to experimental error, model inadequacy and unequal data coverage. In response, researchers have developed frameworks to quantify the uncertainty of thermodynamic property model parameters and propagate it to phase diagram predictions. In most previous studies, uncertainty was represented as intervals on phase boundaries (with respect to composition or temperature) and was unable to represent the uncertainty in invariant reactions or in the stability of phase regions. In this work, we propose a suite of tools that leverages samples from the multivariate model parameter distribution to represent uncertainty in forms that surpass previous limitations and are well suited to materials design. These representations include the distribution of phase diagrams and their features, as well as the dependence of phase stability and the distributions of phase fraction, composition, activity and Gibbs energy on X-T-P location - irrespective of the total number of components. Most critically, the new methodology allows the material designer to interrogate a certain composition and temperature domain and get in return the probability of different phases to be stable, which can positively impact materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel

Silica fiber optic sensors are resistant to corrosive environments and high temperatures, making them attractive candidates for harsh conditions found in nuclear and aerospace industries. Moreover, fibers can be deployed remotely for continuous measuring of spatially distributed temperatures and strains. Here, this study investigated embedding a Ni/Cu bi-metallic coated fiber in a stainless-steel 316 (SS316) matrix using laser powder bed fusion towards functionalizing metal components for site-specific health monitoring. The embedded fiber was continuously interrogated during controlled heating to 1000°C. The measured fiber strains were similar to the expected differential thermal strains between the fiber and the SS316 matrix, until divergent behavior was observed at temperatures >500°C. No debonding at the matrix–coating–fiber interfaces was observed during microscopy, but significant interactions between the coatings and matrix resulted in diffusion-driven chemistry variations and Kirkendall void formation. Applying the strain-lag theory revealed plastic behavior in the Ni coating at temperatures >500°C, limiting the strain transfer to the fiber at higher temperatures. It was estimated that the elastic modulus in the Ni coating had decreased from ~200 GPa at room temperature to below 40 GPa, starting at 600°C. The low elastic modulus above 600°C is within the margin of what the tangent modulus would be in the case of bilinear isotropic hardening. Regardless of the divergent strain transfer at higher temperatures, the fiber was exposed to the equivalent of 1.9 % engineering strain at 1000°C, but measured only a 0.7 % engineering strain due to the poor strain transfer. Although compensating for the plastic behavior of Ni proved challenging, the bonding of a brittle silica fiber to a metal matrix surviving to 1000°C invites potential iterations on coating material for future application. For example, the embedded fiber is sufficient for acoustic energy transfer, realizing high temperature distributed acoustic sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Monitoring of corrosion effects in pipes with multi-mode acoustic signals

Current commercial long-range guided wave inspection and monitoring technologies for pipes usually require establishment of certain specific acoustic modes for wave propagation and use a large number of sensors in a certain geometric arrangement (for example, uniformly-spaced arrays of sensors on a collar, placed around a pipe). This paper, in contrast, presents a long-range corrosion detection method in pipes based on multi-mode guided acoustic waves, generated and received using simple, single-element sensors. In this technique, available guided wave modes in any interrogated zone of the structure are automatically down-selected by the medium, and changes in energy distribution over the selected modes are analyzed through signal processing to monitor material loss or addition. Here, to investigate the feasibility of the proposed method, we have performed both experimental and numerical simulation studies on 50.8-mm (2-in)-diameter schedule-40 carbon steel pipes. In these studies, a linear chirp signal is injected in compression mode, perpendicular to the surface of the pipe, generating multi-mode, multi-directional guided waves that travel within the pipe wall. Corrosion effects in the pipes are simulated numerically and experimentally. To reduce errors in the measurement technique due to changes in the local or global temperature of the measured media, a universal temperature compensation algorithm is introduced. The experimental results show good agreement with simulation results, indicating that the proposed multi-mode wave generation and detection in a pipe could be used for long-range detection and monitoring of corrosion effects, such as pipe wall losses or solid material deposits.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Monitoring of mechanical changes in a pipe assembly with complex geometry using multi-mode acoustic signals

Guided wave ultrasonic testing has been widely used for nondestructive and long-range evaluation of diverse mechanical structures, such as pipes and plates. In general, a large number of guided wave modes exist even in the simplest geometries, and they exhibit highly dispersive characteristics. Thus, sophisticated excitation methods and elaborate modal analyses need to be implemented to excite, acquire, and process well-defined pure modes as part of such a measurement method. If the interrogated structure has complex geometry, for example, with cross-sectional variations or multiple joints, the utilization of pure modes becomes significantly more difficult. To overcome this difficulty, this paper proposes the use of multi-mode, multi-frequency guided waves for long-range inspection of structures with arbitrarily complex geometries. Furthermore, using broadband chirp signals and multi-mode time–frequency analysis in a prototypical complex pipe assembly that includes multiple pipe diameters, elbows, and flange connections, we experimentally show sensitive detection of mechanical changes (both material addition and loss). In addition, we demonstrate that the complexity of the structure can be modeled in the digital domain with sufficient detail to allow accurate numerical simulation of the acoustic response using this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

In situ growth, structure, and real-time chemical reactivity of well-defined CeO x -Ru(0001) model surfaces

Ceria is an important material for chemical conversion processes in catalysis. Its intrinsic properties as a reducible oxide can be exploited to achieve catalytic selectivity and activity. However, numerous phenomenological characteristics of ceria remain unknown and its active nature is ever slowly being unraveled. Well defined models of ceria (111) are an important way to systematically study these properties and take advantage of new in situ methods that require pristine materials that allow for the interrogation of the most fundamental traits of this material. The ceria-Ru(0001) model is now the most well studied model surface with numerous aspects of its preparation, atomic structure and reactivity studied by several groups. The preparation of CeO x structures oriented with a (111) surface termination can be achieved through molecular beam deposition, facilitating the growth of well-defined nanostructures, microparticles, and films on the Ru(0001) surface. The growth mechanism exploits the epitaxial relationship between CeOx and Ru to form a carpet mode of well oriented layers of Osingle bondCesingle bondO. These models can be studied to unravel the atomic structure and the oxidation state (Ce 4+ and Ce 3+ ), as prepared and under redox conditions (reduction/oxidation) or with reaction using reactants (e.g., H 2 , methanol). Here, we present a discussion of these most recent observations pertaining to the growth mode, arrangement of atoms on the surface, characteristic chemical state, and redox chemistry of the CeO x -Ru surface. As a result, with insights from these studies we propose new strategies to further unravel the chemistry of ceria.

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

DeepMerge: Classifying high-redshift merging galaxies with deep neural networks

In this work, we investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational and experimental noise that mimics that from the Hubble Space Telescope; the data without noise form a "pristine" data set and that with noise form a "noisy" data set. The test set classification accuracy of the CNN is $79\%$ for pristine and $76\%$ for noisy. The CNN outperforms a Random Forest classifier, which was shown to be superior to conventional one- or two-dimensional statistical methods (Concentration, Asymmetry, the Gini, $M_{20}$ statistics etc.), which are commonly used when classifying merging galaxies. We also investigate the selection effects of the classifier with respect to merger state and star formation rate, finding no bias. Finally, we extract Grad-CAMs (Gradient-weighted Class Activation Mapping) from the results to further assess and interrogate the fidelity of the classification model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Small angle neutron scattering and lipidomic analysis of a native, trimeric PSI-SMALP from a thermophilic cyanobacteria

The use of styrene-maleic acid copolymers (SMAs) to produce membrane protein-containing nanodiscs without the initial detergent isolation has gained significant interest over the last decade. We have previously shown that a Photosystem I SMALP from the thermophilic cyanobacterium, Thermosynechococcus elongatus (PSI-SMALP), has much more rapid energy transfer and charge separation in vitro than detergent isolated PSI complexes. In this study, we have utilized small-angle neutron scattering (SANS) to better understand the geometry of these SMALPs. These techniques allow us to investigate the size and shape of these particles in their fully solvated state. Further, the particle's proteolipid core and detergent shell or copolymer belt can be interrogated separately using contrast variation, a capability unique to SANS. Here we report the dimensions of the Thermosynechococcus elongatus PSI-SMALP containing a PSI trimer. At ~1.5 MDa, PSI-SMALP is the largest SMALP to be isolated; our lipidomic analysis indicates it contains ~1300 lipids/per trimeric particle, >40-fold more than the PSI-DDM particle and > 100 fold more than identified in the 1JB0 crystal structure. Interestingly, the lipid composition to the PSI trimer in the PSI-SMALP differs significantly from bulk thylakoid composition, being enriched ~50 % in the anionic sulfolipid, SQDG. Finally, utilizing the contrast match point for the SMA 1440 copolymer, we also can observe the ~1 nm SMA copolymer belt surrounding this SMALP for the first time, consistent with most models of SMA organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Biochemistry & Molecular Biology↗
DOE OSTI2014

VMP1 related autophagy and apoptosis in colorectal cancer cells: VMP1 regulates cell death

Highlights: •This research confirmed VMP1 as a regulator of autophagy in colorectal cancer cell lines. •We proved the pro-survival role of VMP1-mediated autophagy in colorectal cancer cell lines. •We found the interaction between VMP1 and BECLIN1 also existing in colorectal cancer cell lines. -- Abstract: Vacuole membrane protein 1 (VMP1) is an autophagy-related protein and identified as a key regulator of autophagy in recent years. In pancreatic cell lines, VMP1-dependent autophagy has been linked to positive regulation of apoptosis. However, there are no published reports on the role of VMP1 in autophagy and apoptosis in colorectal cancers. Therefore, to address this gap of knowledge, we decided to interrogate regulation of autophagy and apoptosis by VMP1. We have studied the induction of autophagy by starvation and rapamycin treatment in colorectal cell lines using electron microscopy, immunofluorescence, and immunoblotting. We found that starvation-induced autophagy correlated with an increase in VMP1 expression, that VMP1 interacted with BECLIN1, and that siRNA mediated down-regulation of VMP1-reduced autophagy. Next, we examined the relationship between VMP1-dependent autophagy and apoptosis and found that VMP1 down-regulation sensitizes cells to apoptosis and that agents that induce apoptosis down-regulate VMP1. In conclusion, similar to its reported role in other cell types, VMP1 is an important regulator of autophagy in colorectal cell lines. However, in contrast to its role in pancreatic cell lines, in colorectal cancer cells, VMP1-dependent autophagy appears to be pro-survival rather than pro-cell death.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

In vivo cardiac glucose metabolism in the high-fat fed mouse: Comparison of euglycemic–hyperinsulinemic clamp derived measures of glucose uptake with a dynamic metabolomic flux profiling approach

Rationale: Cardiac metabolism is thought to be altered in insulin resistance and type 2 diabetes (T2D). Our understanding of the regulation of cardiac substrate metabolism and insulin sensitivity has largely been derived from ex vivo preparations which are not subject to the same metabolic regulation as in the intact heart in vivo. Studies are therefore required to examine in vivo cardiac glucose metabolism under physiologically relevant conditions. Objective: To determine the temporal pattern of the development of cardiac insulin resistance and to compare with dynamic approaches to interrogate cardiac glucose and intermediary metabolism in vivo. Methods and results: Studies were conducted to determine the evolution of cardiac insulin resistance in C57Bl/6 mice fed a high-fat diet (HFD) for between 1 and 16 weeks. Dynamic in vivo cardiac glucose metabolism was determined following oral administration of [U-{sup 13}C] glucose. Hearts were collected after 15 and 60 min and flux profiling was determined by measuring {sup 13}C mass isotopomers in glycolytic and tricarboxylic acid (TCA) cycle intermediates. Cardiac insulin resistance, determined by euglycemic–hyperinsulinemic clamp, was evident after 3 weeks of HFD. Despite the presence of insulin resistance, in vivo cardiac glucose metabolism following oral glucose administration was not compromised in HFD mice. This contrasts our recent findings in skeletal muscle, where TCA cycle activity was reduced in mice fed a HFD. Similar to our report in muscle, glucose derived pyruvate entry into the TCA cycle in the heart was almost exclusively via pyruvate dehydrogenase, with pyruvate carboxylase mediated anaplerosis being negligible after oral glucose administration. Conclusions: Under experimental conditions which closely mimic the postprandial state, the insulin resistant mouse heart retains the ability to stimulate glucose metabolism. - Highlights: • Insulin clamp was used to determine the evolution of cardiac insulin resistance. • Clamp measures were compared to a dynamic metabolomics approach. • The clamp revealed the presence of cardiac insulin resistance after 3 weeks of HFD. • Cardiac glucose metabolism was not affected by HFD during an oral glucose challenge.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Metabololipidomic profiling of functional immunoresolvent clusters and eicosanoids in mammalian tissues

Highlights: • New methods for metabololipidomics of specialized proresolving mediators (SPM) and classic eicosanoids. • Illustration from human blood coagulation. • Illustration from solid tumor. • Regulation of SPM biosynthesis by adenosine and adenosine deaminase. Metabolomics enables a systems approach to interrogate the bioactive mediators, their pathways and further metabolites involved in the physiology and pathophysiology of human and animal tissues. New metabololipidomic approaches with mass spectrometry presented in this brief review can now be utilized for the identification and profiling of lipid mediator networks that control inflammation-resolution in human blood and healthy and diseased solid tissues. Coagulation of blood is a protective response that prevents excessive bleeding on injury of blood vessels. Here, we review novel approaches to understand the relationship(s) between coagulation and resolution of inflammation and infection. To determine whether coagulation is involved in host-protective actions by lipid mediators, we used a metabololipidomic-based profiling approach with human whole blood (WB) during coagulation. We identified recently temporal clusters of endogenously produced pro-thrombotic and proinflammatory lipid mediators (eicosanoids), as well as specialized proresolving mediators (SPMs) in this vital process. In addition to the classic eicosanoids (prostaglandins, thromboxanes and leukotrienes), a specific SPM cluster was identified that consists of resolvin E1 (RvE1), RvD1, RvD5, lipoxin B{sub 4}, and maresin 1, each of which present at bioactive concentrations (0.1–1 nM). The removal of adenosine from coagulating blood samples significantly enhances SPM amounts and unleashes the biosynthesis of RvD3, RvD4, and RvD6 evident following rapid snap freezing with centrifugation before extraction and LC-MS-MS. The classic cyclooxygenase inhibitors, celecoxib and indomethacin, that block thromboxanes and prostanoids do not block production of the clot-driven SPM cluster. Unbiased mass cytometry analysis demonstrated that the SPM cluster produced in human blood targets leukocytes at the single-cell level, directly activating extracellular signaling in human neutrophils and monocytes. Human whole blood treated with the components of this SPM cluster enhanced both phagocytosis and killing of Escherichia coli by leukocytes. Thus, we identified a pro-resolving lipid mediator circuit and specific SPM cluster that promotes host defense. This new lipid mediator (LM)-SPM metabololipidomic approach now provides accessible metabolomic profiles in healthy and diseased human tissues, including cancer, for precision and personalized medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Bioenergetic consequences of compromised mitochondrial DNA repair in the mouse heart

Highlights: • Loss of mitochondrial DNA repair compromises bioenergetic efficiency. • Impairments in bioenergetic efficiency result from ETS stoichiometry shifts. • Bioenergetic flux in Polg{sup m/m} mitochondria favors accelerated electron leak. The progeroid phenotype of mitochondrial DNA (mtDNA) mutator mice has been nebulously attributed to general mitochondrial ‘dysfunction’, though few studies have rigorously defined the bioenergetic consequences of accumulating mtDNA mutations. Comprehensive mitochondrial diagnostics was employed to interrogate the bioenergetic properties of isolated cardiac mitochondria from mtDNA mutator mice and wild type littermates. Assessment of respiratory flux in conjunction with parallel measurements of mitochondrial free energy all point to the cause of respiratory flux limitations observed in mtDNA mutator mouse mitochondria being due to impairments within the energy transduction step catalyzed by the electron transport system in which NADH/NAD{sup +} free energy is transduced to the proton motive force (ΔP). The primary bioenergetic consequence of this limitation appears to be hyper-reduction of NAD(P)H/NAD(P){sup +} redox poise across multiple substrate conditions, particularly evident at moderate to high respiration rates. This hyper-reduced phenotype appears to result from specific reductions in both complex I and complex IV expression, presumably due to compromised mtDNA integrity. Translation of these findings to the working heart would suggest that the primary biological consequence of accumulated mtDNA damage is accelerated electron leak driven by an increase in electron redox pressure for a given rate of oxygen consumption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Macromolecular gelatin properties affect fibrin microarchitecture and tumor spheroid behavior in fibrin-gelatin gels

The biophysical properties of extracellular matrices (ECM) are known to regulate cell behavior, however decoupling cell behavior changes due to the relative contributions of material microstructure versus biomechanics or nutrient permeability remains challenging, especially within complex, multi-material matrices. We developed four gelatin-fibrin interpenetrating network (IPN) formulations which are identical in composition but possess variable gelatin molecular weight distributions, and display differences in microstructure, biomechanics, and diffusivity. In this work we interrogate the response of multicellular tumor spheroids to these IPN formulations and found that a high stiffness, gelatin-network dominated IPNs impeded remodeling and invasion of multicellular tumor spheroids; whereas relatively lower stiffness, fibrin-network dominated IPNs permitted protease-dependent remodeling and spheroid invasion. Cell proliferation correlated to nutrient diffusivity across tested IPN formulations. These findings demonstrate the complexity of ECM IPNs, relative to single polymer matrices, and highlight that cell response does not derive from a single aspect of the ECM, but rather from the interplay of multiple biomechanical properties. The methodology developed in this study represents a framework for future studies which aim to characterize cellular phenotypic responses to biophysical cues present within complex, multi-material matrices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design and evaluation of novel analogs of 2-amino-4-boronobutanoic acid (ABBA) as inhibitors of human gamma-glutamyl transpeptidase

Inhibitors of gamma-glutamyl transpeptidase (GGT1, aka gamma-glutamyl transferase) are needed for the treatment of cancer, cardiovascular illness and other diseases. Compounds that inhibit GGT1 have been evaluated in the clinic, but no inhibitor has successfully demonstrated specific and systemic GGT1 inhibition. All have severe side effects. L-2-amino-4-boronobutanoic acid (l-ABBA), a glutamate analog, is the most potent GGT1 inhibitor in vitro. In this study, we have solved the crystal structure of human GGT1 (hGGT1) with ABBA bound in the active site. The structure was interrogated to identify interactions between the enzyme and the inhibitor. Based on these data, a series of novel ABBA analogs were designed and synthesized. Their inhibitory activity against the hydrolysis and transpeptidation activities of hGGT1 were determined. The lead compounds were crystalized with hGGT1 and the structures solved. The kinetic data and structures of the complexes provide new insights into the critical role of protein structure dynamics in developing compounds for inhibition of hGGT1.

60 APPLIED LIFE SCIENCES↗