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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deciphering the evolution of flavin-dependent monooxygenase stereoselectivity using ancestral sequence reconstruction

Controlling the selectivity of a reaction is critical for target-oriented synthesis. Accessing complementary selectivity profiles enables divergent synthetic strategies, but is challenging to achieve in biocatalytic reactions given enzymes’ innate preferences of a single selectivity. Thus, it is critical to understand the structural features that control selectivity in biocatalytic reactions to achieve tunable selectivity. Here, we investigate the structural features that control the stereoselectivity in an oxidative dearomatization reaction that is key to making azaphilone natural products. Crystal structures of enantiocomplementary biocatalysts guided the development of multiple hypotheses centered on the structural features that control the stereochemical outcome of the reaction; however, in many cases, direct substitutions of active site residues in natural proteins led to inactive enzymes. Ancestral sequence reconstruction (ASR) and resurrection were employed as an alternative strategy to probe the impact of each residue on the stereochemical outcome of the dearomatization reaction. These studies suggest that two mechanisms are active in controlling the stereochemical outcome of the oxidative dearomatization reaction: one involving multiple active site residues in AzaH and the other dominated by a single Phe to Tyr switch in TropB and AfoD. Moreover, this study suggests that the flavin-dependent monooxygenases (FDMOs) adopt simple and flexible strategies to control stereoselectivity, which has led to stereocomplementary azaphilone natural products produced by fungi. This paradigm of combining ASR and resurrection with mutational and computational studies showcases sets of tools for understanding enzyme mechanisms and provides a solid foundation for future protein engineering efforts.

Science & Technology - Other Topics↗
DOE OSTI2023

Tuning the output of a laser

In a general aspect, a laser system includes a laser and a frequency comb generator system. The laser is configured to generate a laser signal, and the frequency comb generator system is configured to generate a frequency comb based on the laser signal. The frequency comb includes frequency comb signals at respective comb frequencies. The laser system also includes a frequency comb dispersion system configured to spatially separate the frequency comb signals onto respective optical channels of the frequency comb dispersion system. The laser system additionally includes a frequency selector system configured to generate a selected frequency signal from the frequency comb signals after separation. The selected frequency signal includes a target separated frequency comb signal. The laser system also includes a frequency shifter configured to alter the selected frequency signal toward a target output frequency of the laser system.

Liu, Chang↗
DOE OSTI2020

Enhanced tensor polarization in solid-state targets

In this work, we report measurements of enhanced tensor polarization on solid-state targets. The results here represent an increase in tensor polarization over that previously achieved in high energy and nuclear scattering experiments that focused on the measurement of tensor polarized observables. Enhancement techniques are used which require RF produced close to the Larmor frequency of the target spins and use selective semi-saturation resulting from two sources of irradiation, microwave for the DNP process and the additional RF used to manipulate the population of the energy levels in the target material. The spin dynamics of the solid target are used to align the spins enhancing the ensemble average to improve the figure of merit of the scattering experiment. Target rotation at an optimized rate can lead to additional enhancement by applying selective semi-saturation in polycrystalline materials that possess a Pake doublet in their NMR signal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Discovery and molecular basis of subtype-selective cyclophilin inhibitors

Abstract Although cyclophilins are attractive targets for probing biology and therapeutic intervention, no subtype-selective cyclophilin inhibitors have been described. We discovered novel cyclophilin inhibitors from the in vitro selection of a DNA-templated library of 256,000 drug-like macrocycles for cyclophilin D (CypD) affinity. Iterated macrocycle engineering guided by ten X-ray co-crystal structures yielded potent and selective inhibitors (half maximal inhibitory concentration (IC 50 ) = 10 nM) that bind the active site of CypD and also make novel interactions with non-conserved residues in the S2 pocket, an adjacent exo-site. The resulting macrocycles inhibit CypD activity with 21- to >10,000-fold selectivity over other cyclophilins and inhibit mitochondrial permeability transition pore opening in isolated mitochondria. We further exploited S2 pocket interactions to develop the first cyclophilin E (CypE)-selective inhibitor, which forms a reversible covalent bond with a CypE S2 pocket lysine, and exhibits 30- to >4,000-fold selectivity over other cyclophilins. These findings reveal a strategy to generate isoform-selective small-molecule cyclophilin modulators, advancing their suitability as targets for biological investigation and therapeutic development.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Naegleria fowleri: Protein structures to facilitate drug discovery for the deadly, pathogenic free-living amoeba

Naegleria fowleri is a pathogenic, thermophilic, free-living amoeba which causes primary amebic meningoencephalitis (PAM). Penetrating the olfactory mucosa, the brain-eating amoeba travels along the olfactory nerves, burrowing through the cribriform plate to its destination: the brain’s frontal lobes. The amoeba thrives in warm, freshwater environments, with peak infection rates in the summer months and has a mortality rate of approximately 97%. A major contributor to the pathogen’s high mortality is the lack of sensitivity of N . fowleri to current drug therapies, even in the face of combination-drug therapy. To enable rational drug discovery and design efforts we have pursued protein production and crystallography-based structure determination efforts for likely drug targets from N . fowleri . The genes were selected if they had homology to drug targets listed in Drug Bank or were nominated by primary investigators engaged in N . fowleri research. In 2017, 178 N . fowleri protein targets were queued to the Seattle Structural Genomics Center of Infectious Disease (SSGCID) pipeline, and to date 89 soluble recombinant proteins and 19 unique target structures have been produced. Many of the new protein structures are potential drug targets and contain structural differences compared to their human homologs, which could allow for the development of pathogen-specific inhibitors. Five of the structures were analyzed in more detail, and four of five show promise that selective inhibitors of the active site could be found. The 19 solved crystal structures build a foundation for future work in combating this devastating disease by encouraging further investigation to stimulate drug discovery for this neglected pathogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structural and biochemical analyses of selectivity determinants in chimeric Streptococcus Class A sortase enzymes

Abstract Sequence variation in related proteins is an important characteristic that modulates activity and selectivity. An example of a protein family with a large degree of sequence variation is that of bacterial sortases, which are cysteine transpeptidases on the surface of gram‐positive bacteria. Class A sortases are responsible for attachment of diverse proteins to the cell wall to facilitate environmental adaption and interaction. These enzymes are also used in protein engineering applications for sortase‐mediated ligations (SML) or sortagging of protein targets. We previously investigated SrtA from Streptococcus pneumoniae , identifying a number of putative β7–β8 loop‐mediated interactions that affected in vitro enzyme function. We identified residues that contributed to the ability of S. pneumoniae SrtA to recognize several amino acids at the P1′ position of the substrate motif, underlined in LPXT G , in contrast to the strict P1′ Gly recognition of SrtA from Staphylococcus aureus . However, motivated by the lack of a structural model for the active, monomeric form of S. pneumoniae SrtA, here, we expanded our studies to other Streptococcus SrtA proteins. We solved the first monomeric structure of S. agalactiae SrtA which includes the C‐terminus, and three others of β7–β8 loop chimeras from S. pyogenes and S. agalactiae SrtA. These structures and accompanying biochemical data support our previously identified β7–β8 loop‐mediated interactions and provide additional insight into their role in Class A sortase substrate selectivity. A greater understanding of individual SrtA sequence and structural determinants of target selectivity may also facilitate the design or discovery of improved sortagging tools.

Gao, Melody↗
DOE OSTI2024

Design, Selection, and Evaluation of Reinforcement Learning Single Agents for Ground Target Tracking

Previous approaches for small fixed-wing unmanned air systems that carry strapdown rather than gimbaled cameras achieved satisfactory ground target tracking performance using both standard and deep reinforcement learning algorithms. However, these approaches have significant restrictions and abstractions to the dynamics of the vehicle, such as constant airspeed and constant altitude, because the number of states and actions was necessarily limited. Thus, extensive tuning was required to obtain good tracking performance. The expansion from 4 state–action degrees of freedom to 15 enabled the agent to exploit previous reward functions that produced novel yet undesirable emergent behavior. This paper investigates the causes of and various potential solutions to undesirable emergent behavior in the ground target tracking problem. A combination of changes to the environment, reward structure, action space simplification, command rate, and controller implementation provides insight into obtaining stable tracking results. Consideration is given to reward structure selection and refinement to mitigate undesirable emergent behavior. Results presented in the paper for a simulated environment of a single unmanned air system tracking a randomly moving single ground target show that a soft actor–critic algorithm can produce feasible tracking trajectories without limiting the state space and action space, provided that the environment is properly posed.

Engineering↗
DOE OSTI2023

Site-Selective Atomic Layer Deposition at Thermally Generated Surface Oxygen Vacancies on Rutile TiO 2

Unique atomic arrangements (i.e., defects) on material surfaces may exhibit distinctive reactivity that affords opportunities for selective surface chemistry exclusively at those sites. While theoretically appealing, site-selective atomic layer deposition (ALD) processes remain largely unrealized experimentally. Here we provide evidence for site-selective ALD that exclusively targets oxygen vacancies thermally generated at the surface of TiO 2 single crystals. High-resolution in situ ellipsometry reveals the nucleation behavior of dimethylaluminum isopropoxide (DMAI) and water at process conditions precisely tuned for selective hydroxylation of surface defects. An island growth model for nucleation and atomic force microscopy (AFM) imaging are consistent with a site-selective growth mechanism that depends on the surface oxygen vacancy density. This approach to direct ALD reactions at defective surface sites may provide future opportunities for targeted remediation of electronically imperfect interfaces.

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

Quantifying the environmental benefits of a solvent-based separation process for multilayer plastic films

Food packaging often appears in the form of multilayer (ML) plastic films, which leverage the functional properties of different polymers to achieve specific food protection goals (e.g., oxygen, water, and temperature barriers). These properties are essential to enable long shelf lives, reduce refrigeration usage, mitigate food waste, and increase food accessibility. However, ML film production processes generate large amounts of plastic waste that cannot be mechanically recycled. Recently, we have proposed a process, called solvent-targeted recovery and precipitation (STRAP), that enables the separation and recycling of the constituent polymers of ML films. This technology uses a series of solvent washes that selectively dissolve and precipitate target polymers. Quantifying the environmental benefits of STRAP over virgin resin production is essential for the commercial deployment of this technology. Further, this work uses life cycle assessment (LCA) methods to evaluate these impacts in terms of carbon footprint, energy use, water use, and toxicity. We analyze three STRAP process variants that use antisolvent and temperature-driven precipitation to treat different ML films. Our analysis reveals that the STRAP-A and STRAP-B process variants can provide environmental benefits over virgin film production. Furthermore, it gives valuable insight into the critical components of ML films (specific polymers) and of the STRAP processes (equipment) that are responsible for the highest impacts. Ultimately, we believe that the proposed analysis framework can lead to the design of more environmentally-friendly ML films and recycling processes.

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

Gene regulatory networks controlling carbohydrate selective deconstruction pathways in fungi

The work performed at Clark University (PI, David Hibbett) was a subcomponent of the research lead by Jonathan Schilling at University of Minnesota (award number DE-SC0019427). The overall goal of this project was to address how fungi metabolize lignocellulose. Specifically, we targeted a carbohydrate-selective group of fungi known as 'brown rot' fungi that are well-aligned to be harness for bioconversion to biofuels and other products. These organisms orchestrate a two-step mechanism that initiates decomposition using oxidative radical-based chemistry and follows with enzymatic attack. We have helped characterize that this mechanism occurs in this sequence, but currently lack the fundamental regulatory information needed to harness these fungi for application. Thus, the major goal of this project was to use systems biology to create an integrated model of brown rot wood decay that couples fungal gene regulation with the metabolite feedbacks used to coordinate a two-step oxidative-hydrolytic mechanism. The research at Clark University focused on phylogenomic analyses of data produced by other project partners. Hence, the Clark component of the research was staged to initiate somewhat after that in other partner laboratories. The major Clark-based accomplishment was to advise on selection of fungal species for analyses of brown rot decay chemistry, and to interpret results in a phylogenetic context. The Clark University group also performed complementary analyses of gene families encoding plant cell wall-degrading enzymes in the the basidiomycete genus Lentinula, as well as analyses of substrate-specific gene expression and RNA editing in brown rot fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Host-region parameters for an adjustable model for crustal earthquakes to facilitate the implementation of the backbone approach to building ground-motion logic trees in probabilistic seismic hazard analysis

The backbone approach to constructing a ground-motion logic tree for probabilistic seismic hazard analysis (PSHA) can address shortcomings in the traditional approach of populating the branches with multiple existing, or potentially modified, ground-motion models (GMMs) by rendering more transparent the relationship between branch weights and the resulting distribution of predicted accelerations. To capture epistemic uncertainty in a tractable manner, there are benefits in building the logic tree through the application of successive adjustments for differences in source, path, and site characteristics between the host region of the selected backbone GMM and the target region for which the PSHA is being conducted. The implementation of this approach is facilitated by selecting a backbone GMM that is amenable to such host-to-target adjustments for individual source, path, and site characteristics. The NGA-West2 GMM of Chiou and Youngs (CY14) has been identified as a highly adaptable model for crustal seismicity that is well suited to such adjustments. Rather than using generic source, path, and site characteristics assumed appropriate for the host region, the final suite of adjusted GMMs for the target region will be better constrained if the host-region parameters are defined specifically on the basis of their compatibility with the CY14 backbone GMM. To this end, making use of a recently developed crustal shear-wave velocity profile consistent with CY14, we present an inversion of the model to estimate the key source and path parameters, namely the stress parameter and the anelastic attenuation. With these outputs, the effort in constructing a ground-motion logic tree for any PSHA dealing with crustal seismicity can be focused primarily on the estimation of the target-region characteristics and their associated uncertainties. The inversion procedure can also be adapted for any application in which different constraints might be relevant.

Stafford, Peter J.↗
DOE OSTI2021

A Third Generation Potentially Bifunctional Trithiol Chelate, Its nat,1XX Sb(III) Complex, and Selective Chelation of Radioantimony ( 119 Sb) from Its Sn Target

The therapeutic potential of the Meitner-Auger- and conversion-electron emitting radionuclide 119 Sb remains unexplored because of the difficulty of incorporating it into biologically targeted compounds. To address this challenge, we report the development of 119 Sb production from electroplated tin cyclotron targets and its complexation by a novel trithiol chelate. Here, the chelation reaction occurs in harsh solvent conditions even in the presence of large quantities of tin, which are necessary for production on small, low energy (16 MeV) cyclotrons. The 119 Sb-trithiol complex has high stability and can be purified by HPLC. The third generation trithiol chelate and the analogous stable nat Sb-trithiol compound were synthesized and characterized, including by single crystal X-ray diffraction analyses.

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

Selective high-affinity polydentate ligands and methods of making such

This invention provides novel polydentate selective high affinity ligands (SHALs) that can be used in a variety of applications in a manner analogous to the use of antibodies. SHALs typically comprise a multiplicity of ligands that each bind different region son the target molecule. The ligands are joined directly or through a linker thereby forming a polydentate moiety that typically binds the target molecule with high selectivity and avidity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Selective high-affinity polydentate ligands and methods of making such

This invention provides novel polydentate selective high affinity ligands (SHALs) that can be used in a variety of applications in a manner analogous to the use of antibodies. SHALs typically comprise a multiplicity of ligands that each bind different region son the target molecule. The ligands are joined directly or through a linker thereby forming a polydentate moiety that typically binds the target molecule with high selectivity and avidity.

DeNardo, Sally J.↗
DOE OSTI2022

Selective high-affinity polydentate ligands and methods of making such

This invention provides novel polydentate selective high affinity ligands (SHALs) that can be used in a variety of applications in a manner analogous to the use of antibodies. SHALs typically comprise a multiplicity of ligands that each bind different region son the target molecule. The ligands are joined directly or through a linker thereby forming a polydentate moiety that typically binds the target molecule with high selectivity and avidity.

60 APPLIED LIFE SCIENCES↗