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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2017

Rigorous Representation of Transporters as Allosteric Machines Enables a Quantitative Understanding of their Functional Mechanisms

The sodium-coupled transporters are prototypical molecular machines of the cell that maintain communication with the environment by moving substances across the membrane. How they use energy to perform the transfer of substrates against their chemical gradient, i.e., by sodium symport along its gradient, is of special biophysical interest. New structural information, and powerful computational methods applied to the analysis of extensive molecular dynamics trajectories, make it possible to incorporate mechanistic elements of ion and substrate transport in structure-informed allosteric models that can be interrogated for specific and quantitative inferences.

Biophysics↗
DOE OSTI2016

Molecular imaging to guide systemic cancer therapy: Illustrative examples of PET imaging cancer biomarkers

Molecular imaging agents have the ability to non-invasively visualize, characterize, and quantify the molecular biology of disease. Recent advances in nuclear probe development, particularly in PET radiotracers, have generated many new imaging agents with precise molecular targets. With such specificity, PET probes may be utilized as biomarkers to objectively interrogate and evaluate pathology. Whereas the current indications for PET imaging are predominately confined to staging and restaging of malignancy, the utility of PET greatly expands when utilized as a biomarker, the topic of this review. As an imaging biomarker, PET may be used to (1) measure target expression to select subsets of patients who would most benefit from targeted therapy; (2) measure early treatment response to predict therapeutic efficacy; and (3) relate tumor response to survival. This work will discuss the application of radiotracers to targeted cancer therapy. Particular attention is given to new radiotracers evaluated in recently completed clinical trials and those with current or potential clinical utility. The diverse roles of PET in clinical trails for drug development are also examined.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗
DOE OSTI2023

Elucidating the speciation of extracted lanthanides by diglycolamides

Many studies over the past few decades have been devoted to addressing the application of diglycolamides (DGAs) for hydrometallurgical-based, f-element separations. Work to date has shown the molecular structure of a DGA derivative can have a significant impact on intra-lanthanide partitioning patterns. More recent studies have pushed towards probing the structure function relationship of the lanthanide-DGA complex to enable the design of more efficient lanthanide separation systems. Spectroscopic techniques, such as UV–Visible, Fourier Transformed Infrared Spectroscopy (FT-IR), Nuclear Magnetic Resonance (NMR), and Extended X-ray Absorption Fine Structure (EXAFS), provide information regarding the inner-sphere coordination of a given lanthanide-DGA complex. Scattering techniques, such as Dynamic Light Scattering (DLS), Small-Angle X-ray Scattering (SAXS), and Small-Angle Neutron Scattering (SANS), address nanoscale structures including aggregate sizes and morphology. Here, this review assesses the current state-of-knowledge regarding lanthanide-DGA hydrometallurgical (i.e., solvent extraction systems) interrogated using spectroscopic and scattering techniques to characterize the extracted Ln 3+ DGA species. Of particular interest to this review is the impact of varied diluents, inclusion and variation of phase modifiers, and DGA derivatization on system characteristics. While there has been extensive literature on the application of DGAs for f-element separations, the literature lacks a collective assessment of the speciation of Ln 3+ in the organic phase. This review provides new insights into the field of DGA separations, explicitly with an application to intra-lanthanide separations. Specifically, this review illustrates the importance of both the co-extraction anion (Cl - , NO 3 - , or ClO 4 - ) as it pertains to both the aggregate size and Ln 3+ distribution coefficient. It is evident the ability of the anion to disrupt the hydrogen bonding network limits both aggregate size and distribution coefficients according to the Hoffmeister series. This suggests the importance of the large, softer anions with a low charge-to-surface area ratio on encouraging hydrogen bond interactions. In addition, the co-extracted cation (H + vs Na + ) is important for mitigating transfer of Ln 3+ from the aqueous to the organic phase through extensive hydrogen bonding networks. These networks are responsible for forming supramolecular aggregates where a change in morphology is observed with increasing concentrations of H + and/or Ln 3+ in the organic phase.

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

Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics

Co-injection of conservative tracers with carbon dioxide (CO 2 ) is a viable tool for monitoring subsurface processes during geological CO 2 storage (GCS). This research investigates the simulation and history-matching of a gas tracer (sulfur hexafluoride, SF 6 ) during CO 2 flooding, employing a core flooding result in Berea sandstone. Four extensively used saturation functions are assessed for their efficacy in history matching of CO 2 /SF 6 injection at the core scale. The history-matching process incorporates particle swarm optimization (PSO) to fine-tune constitutive relationships parameters. Next, employing transport models at the aquifer scale, we interrogate the impact on tracer transport and mixing of saturation function uncertainties, arising from the non-uniqueness of constitutive relationships parameters and saturation function types. To assess the effects of geological heterogeneity on behavior of tracer breakthrough curves (BTCs), we employ two normalized parameters assessing the degree of mixing and SF 6 breakthrough time. The aquifer-scale investigation encompasses both homogeneous and heterogeneous systems with and without capillary heterogeneity effects. Our findings underscore the critical importance of addressing saturation function uncertainties, emphasizing the significance of auxiliary experiments and innovative methodologies to enhance predictive accuracy. The findings highlight significant disparities in arrival times, BTC peaks, tails, and mixing levels, even under optimal conditions. Heterogeneity, with or without capillary heterogeneity, plays a crucial role in shaping BTC variations, resulting in accelerated SF 6 breakthrough times and reduced BTC peaks. Evaluation of monitoring points distant from the injector reveals a dampening effect on the SF6 BTC peak, particularly in heterogeneous systems with capillary heterogeneity, where the peak is halved. These insights underscore the challenges associated with tracer monitoring and the necessity for enhanced methodologies to improve predictive accuracy in subsurface processes during GCS.

58 GEOSCIENCES↗
DOE OSTI2014

Evolution of DNA Specificity in a Transcription Factor Family Produced a New Gene Regulatory Module

Complex gene regulatory networks require transcription factors (TFs) to bind distinct DNA sequences. To understand how novel TF specificity evolves, we combined phylogenetic, biochemical, and biophysical approaches to interrogate how DNA recognition diversified in the steroid hormone receptor (SR) family. After duplication of the ancestral SR, three mutations in one copy radically weakened binding to the ancestral estrogen response element (ERE) and improved binding to a new set of DNA sequences (steroid response elements, SREs). They did so by establishing unfavorable interactions with ERE and abolishing unfavorable interactions with SRE; also required were numerous permissive substitutions, which nonspecifically improved cooperativity and affinity of DNA binding. Furthermore, our findings indicate that negative determinants of binding play key roles in TFs’ DNA selectivity and—with our prior work on the evolution of SR ligand specificity during the same interval—show how a specific new gene regulatory module evolved without interfering with the integrity of the ancestral module.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

CRISPR-Cas9 Circular Permutants as Programmable Scaffolds for Genome Modification

The ability to engineer natural proteins is pivotal to a future, pragmatic biology. CRISPR proteins have revolutionized genome modification, yet the CRISPR-Cas9 scaffold is not ideal for fusions or activation by cellular triggers. Here in this paper, we show that a topological rearrangement of Cas9 using circular permutation provides an advanced platform for RNA-guided genome modification and protection. Through systematic interrogation, we find that protein termini can be positioned adjacent to bound DNA, offering a straightforward mechanism for strategically fusing functional domains. Additionally, circular permutation enabled protease-sensing Cas9s (ProCas9s), a unique class of single-molecule effectors possessing programmable inputs and outputs. ProCas9s can sense a wide range of proteases, and we demonstrate that ProCas9 can orchestrate a cellular response to pathogen-associated protease activity. Together, these results provide a toolkit of safer and more efficient genome-modifying enzymes and molecular recorders for the advancement of precision genome engineering in research, agriculture, and biomedicine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Evolution of planar fractures in limestone: The role of flow rate, mineral heterogeneity and local transport processes

In this study, the processes that affect the evolution of fracture geometry and reactive transport in limestone fractures were evaluated using an integrated experimental and modeling approach. Flow-through experiments were performed to investigate the alteration of three artificially made planar limestone fractures, which were exposed to HCl-acidified water flow (pH 3.8 ± 0.1) at three different rates. Reactive infiltration instability developed in the fractures because of small fracture aperture variations and naturally occurring heterogeneity in the rock, i.e., the presence of clay spots of higher porosity. The dissolution regime changed from conical to dominant and ramified wormhole with increasing flow rate, i.e., Péclet number. Maps of fracture aperture obtained from X-ray micro-tomography imaging, together with measurements of permeability and analyses of fluid chemistry, provided experimental constraints for modeling. Numerical simulations were performed using a 2.5D continuum reactive transport model to examine the development of flow patterns and the reactivity and permeability evolution over time, and to interrogate the impacts of fluid reactivity, mineral heterogeneity and diffusive boundary layer. The modeling results showed that fracture alteration is very sensitive to initial fluid reactivity and mineralogical heterogeneity, in addition to flow rate. Finally, the changes of local transport processes during fracture opening also affected the reactivity of the fractured samples.

58 GEOSCIENCES↗
DOE OSTI2013

Using Small-Angle Neutron Scattering to Detect Nanoscopic Lipid Domains

The cell plasma membrane is a complex system, which is thought to be capable of exhibiting non-random lateral organization. Studies of live cells and model membranes have yielded mechanisms responsible for the formation, growth, and maintenance of nanoscopic heterogeneities, although the existence and mechanisms that give rise to these heterogeneities remain controversial. Small-angle neutron scattering (SANS) is a tool ideally suited to interrogate lateral heterogeneity in model membranes, primarily due to its unique spatial resolution (i.e., "5 100 nm) and its ability to resolve structure with minimal perturbation to the membrane. In this review we examine several methods used to analyze the SANS signal arising from freely suspended unilamellar vesicles containing lateral heterogeneity. Specifically, we discuss an analytical model for a single, round domain on a spherical vesicle. We then discuss a numerical method that uses Monte Carlo simulation to describe systems with multiple domains and/or more complicated morphologies. Also discussed are several model-independent approaches that are sensitive to membrane heterogeneity. The review concludes with several recent applications of SANS to the study of membrane raft mixtures.

Pan, Jianjun↗
DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

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

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗
DOE OSTI2014

Extracting data from the muck: deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing

It is becoming increasingly clear that microbes within microbial communities, for which cultured isolates have not yet been obtained, have an immense, untapped reservoir of enzymes that could help address grand challenges in human health, energy, and sustainability. Despite the obstacles associated with culturing these microbes, recent advances in next-generation sequencing (NGS) have made it possible to explore complex microbial communities in their native context for the first time. Key to extracting meaning from rapidly growing NGS datasets are bioinformatics tools that assemble the sequence data, annotate homologous sequences and interrogate it to reveal regulatory patterns. Complementing this are advances in proteomics that can link NGS data to biological function. Finally, this combination of next generation sequencing, proteomics and bioinformatic analysis forms a powerful tool to study non-model microbes, which will transform what we know about these dynamic systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Rapidly moving new bacteria to model-organism status

The paradigm of large research communities collectively working on a small number of model bacteria such as Escherichia coli and Bacillus subtilis is changing. While these classic model bacteria will continue to be important for advanced systems biology and new technology development, we envision that increasingly small research teams will be deeply investigating their own favorite strains, for example as new hosts for metabolic engineering or as key members of a complex microbiome. Given the lack of a research community and the sheer number of possible bacteria to interrogate, the development and application of technologies to rapidly and inexpensively advance these unstudied strains to ‘model-organism’ status is imperative. Here, we discuss the minimal information and tools necessary to develop a new model bacterium and how existing approaches can bring this power into the hands of a single investigator.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adapting isotopic tracer and metabolic flux analysis approaches to study C1 metabolism

Single-carbon (C1, or one-carbon) substrates are promising feedstocks for sustainable biofuel and biochemical production. Crucial to the goal of engineering C1-utilizing strains for improved production is a quantitative understanding of the organization, regulation and rates of the reactions that underpin C1 metabolism. 13 C Metabolic flux analysis (MFA) is a well-established platform for interrogating these questions with multi-carbon substrates, and uses the differential labeling of metabolites that results from feeding a substrate with position-specific incorporation of 13 C in order to infer quantitative fluxes and pathway topology. Furthermore, adapting isotopic tracer approaches to C1 metabolism, where position-specific substrate labeling is impossible, requires additional experimental considerations. Here we review recent studies that have developed isotopic tracer approaches to overcome the challenge of uniform metabolite labeling and provide quantitative insight into C1 metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Measurements of sound propagation in Mars' lower atmosphere

Acoustics has become extraterrestrial and Mars provides a new natural laboratory for testing sound propagation models compared to those ones on Earth. Owing to the unique combination of a microphone and two sound sources, the Ingenuity helicopter and the SuperCam laser-induced sparks, the Mars 2020 Perseverance rover payload enables the in situ characterization of unique sound propagation properties of the low-pressure CO 2 -dominated Mars atmosphere. In this study, we show that atmospheric turbulence is responsible for a large variability in the sound amplitudes from laser-induced sparks. This variability follows the diurnal pattern of turbulence. In addition, acoustic measurements acquired over one Martian year reveal a variation of the sound intensity by a factor of 1.8 from a constant source due to the seasonal cycle of pressure and temperature that significantly modifies the acoustic impedance and shock-wave formation. Finally, we show that the evolution of the Ingenuity tones and laser spark amplitudes with distance is consistent with one of the existing sound absorption models, which is a key parameter for numerical simulations applied to geophysical experiments on CO 2 -rich atmospheres. Overall, these results demonstrate the potential of sound propagation to interrogate the Mars environment and will therefore help in the design of future acoustic-based experiments for Mars or other planetary atmospheres such as Venus and Titan.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Native mass spectrometry of photosynthetic pigment–protein complexes

Native mass spectrometry (MS), or as is sometimes called “native electrospray ionization” allows proteins in their native or near‐native states in solution to be introduced into the gas phase and interrogated by mass spectrometry. This approach is now a powerful tool to investigate protein complexes. This article reviews the background of native MS of protein complexes and describes its strengths, taking photosynthetic pigment–protein complexes as examples. Native MS can be utilized in combination with other MS‐based approaches to obtain complementary information to that provided by tools such as X‐ray crystallography and NMR spectroscopy to understand the structure–function relationships of protein complexes. When additional information beyond that provided by native MS is required, other MS‐based strategies can be successfully applied to augment the results of native MS.

14 SOLAR ENERGY↗
DOE OSTI2017

Determination of origin and intended use of plutonium metal using nuclear forensic techniques

Nuclear forensics techniques, including micro-XRF, gamma spectrometry, trace elemental analysis and isotopic/chronometric characterization were used to interrogate two, potentially related plutonium metal foils. These samples were submitted for analysis with only limited production information, and a comprehensive suite of forensic analyses were performed. Resulting analytical data was paired with available reactor model and historical information to provide insight into the materials’ properties, origins, and likely intended uses. Both were super-grade plutonium, containing less than 3% 240 Pu, and age-dating suggested that most recent chemical purification occurred in 1948 and 1955 for the respective metals. Additional consideration of reactor modelling feedback and trace elemental observables indicate plausible U.S. reactor origin associated with the Hanford site production efforts. In conclusion, based on this investigation, the most likely intended use for these plutonium foils was 239 Pu fission foil targets for physics experiments, such as cross-section measurements, etc.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗