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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration

Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.

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

Structural basis for antibody binding to adenylate cyclase toxin reveals RTX linkers as neutralization-sensitive epitopes

RTX leukotoxins are a diverse family of prokaryotic virulence factors that are secreted by the type 1 secretion system (T1SS) and target leukocytes to subvert host defenses. T1SS substrates all contain a C-terminal RTX domain that mediates recruitment to the T1SS and drives secretion via a Brownian ratchet mechanism. Neutralizing antibodies against the Bordetella pertussis adenylate cyclase toxin, an RTX leukotoxin essential for B . pertussis colonization, have been shown to target the RTX domain and prevent binding to the α M β 2 integrin receptor. Knowledge of the mechanisms by which antibodies bind and neutralize RTX leukotoxins is required to inform structure-based design of bacterial vaccines, however, no structural data are available for antibody binding to any T1SS substrate. Here, we determine the crystal structure of an engineered RTX domain fragment containing the α M β 2 -binding site bound to two neutralizing antibodies. Notably, the receptor-blocking antibodies bind to the linker regions of RTX blocks I–III, suggesting they are key neutralization-sensitive sites within the RTX domain and are likely involved in binding the α M β 2 receptor. As the engineered RTX fragment contained these key epitopes, we assessed its immunogenicity in mice and showed that it elicits similar neutralizing antibody titers to the full RTX domain. The results from these studies will support the development of bacterial vaccines targeting RTX leukotoxins, as well as next-generation B . pertussis vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bivalent recognition of fatty acyl-CoA by a human integral membrane palmitoyltransferase

S-acylation, also known as palmitoylation, is the most abundant form of protein lipidation in humans. This reversible posttranslational modification, which targets thousands of proteins, is catalyzed by 23 members of the DHHC family of integral membrane enzymes. DHHC enzymes use fatty acyl-CoA as the ubiquitous fatty acyl donor and become autoacylated at a catalytic cysteine; this intermediate subsequently transfers the fatty acyl group to a cysteine in the target protein. Protein S-acylation intersects with almost all areas of human physiology, and several DHHC enzymes are considered as possible therapeutic targets against diseases such as cancer. These efforts would greatly benefit from a detailed understanding of the molecular basis for this crucial enzymatic reaction. Here, in this study, we combine X-ray crystallography with all-atom molecular dynamics simulations to elucidate the structure of the precatalytic complex of human DHHC20 in complex with palmitoyl CoA. The resulting structure reveals that the fatty acyl chain inserts into a hydrophobic pocket within the transmembrane spanning region of the protein, whereas the CoA headgroup is recognized by the cytosolic domain through polar and ionic interactions. Biochemical experiments corroborate the predictions from our structural model. We show, using both computational and experimental analyses, that palmitoyl CoA acts as a bivalent ligand where the interaction of the DHHC enzyme with both the fatty acyl chain and the CoA headgroup is important for catalytic chemistry to proceed. This bivalency explains how, in the presence of high concentrations of free CoA under physiological conditions, DHHC enzymes can efficiently use palmitoyl CoA as a substrate for autoacylation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MAL TIR ) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88 TIR ). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88 TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MAL TIR . We demonstrate via mutagenesis that the MyD88 TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88 TIR . Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Preferential interactions of primary amine-terminated quantum dots with membrane domain boundaries and lipid rafts revealed with nanometer resolution

The initial interactions of engineered nanoparticles (NPs) with living cells are governed by physicochemical properties of the NP and the molecular composition and structure of the cell membrane. Eukaryotic cell membranes contain lipid rafts – liquid-ordered nanodomains involved in membrane trafficking and molecular signaling. However, the impact of these membrane structures on cellular interactions of NPs remains unclear. Here we investigate the role of membrane domains in the interactions of primary amine-terminated quantum dots (Qdots) with liquid-ordered domains or lipid rafts in model membranes and intact cells, respectively. Using correlative atomic force and fluorescence microscopy, we found that the Qdots preferentially localized to boundaries between liquid-ordered and liquid-disordered phases in supported bilayers. The Qdots also induced holes at these phase boundaries. Using super resolution fluorescence microscopy (STORM), we found that the Qdots preferentially co-localized with lipid rafts in the membrane of intact trout gill epithelial cells – a model cell type for environmental exposures. Our observations uncovered preferential interactions of amine-terminated Qdots with liquid-ordered domains and their boundaries, possibly due to membrane curvature at phase boundaries creating energetically favorable sites for NP interactions. The preferential interaction of the Qdots with lipid rafts supports their potential internalization via lipid raft-mediated endocytosis and interactions with raft-resident signaling molecules.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Neutralizing Antibodies to SARS-CoV-2 Selected from a Human Antibody Library Constructed Decades Ago

Combinatorial antibody libraries not only effectively reduce antibody discovery to a numbers game, but enable documentation of the history of antibody responses in an individual. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has prompted a wider application of this technology to meet the public health challenge of pandemic threats in the modern era. Herein, a combinatorial human antibody library constructed 20 years before the coronavirus disease 2019 (COVID-19) pandemic is used to discover three highly potent antibodies that selectively bind SARS-CoV-2 spike protein and neutralize authentic SARS-CoV-2 virus. Compared to neutralizing antibodies from COVID-19 patients with generally low somatic hypermutation (SHM), these three antibodies contain over 13–22 SHMs, many of which are involved in specific interactions in their crystal structures with SARS-CoV-2 spike receptor binding domain. The identification of these somatically mutated antibodies in a pre-pandemic library raises intriguing questions about the origin and evolution of these antibodies with respect to their reactivity with SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Achieving High Thermoelectric Performance and Metallic Transport in Solvent-Sheared PEDOT:PSS

Polymer-based materials hold great potential for use in thermoelectric applications but are limited by their poor electrical properties. Through a combination of solution-shearing deposition and directionally applied solvent treatments, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) thin films with metallic-like conductivities can be obtained with high power factors in excess of 800 µW m -1 K -2 . X-ray scattering and absorption data indicate that structural alignment of PEDOT chains and larger-sized domains are responsible for the enhanced electrical conductivity. Overall, it is expected that further enhancements to the power factor can be obtained through device geometry and postdeposition solvent shearing optimization.

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

Photonic devices fabricated from (111)‐oriented single crystal diamond

Abstract Diamond is a material of choice in the pursuit of integrated quantum photonic technologies. So far, the majority of photonic devices fabricated from diamond are made from (100)‐oriented crystals. In this work, we demonstrate a methodology for the fabrication of optically active membranes from (111)‐oriented diamond. We use a liftoff technique to generate membranes, followed by chemical vapor deposition of diamond in the presence of silicon to generate homogenous silicon vacancy color centers with emission properties that are superior to those in (100)‐oriented diamond. We further use the diamond membranes to fabricate microring resonators with quality factors exceeding ~ 3000. Supported by finite‐difference time‐domain calculations, we discuss the advantages of (111)‐oriented structures as building blocks for quantum nanophotonic devices. image

Regan, Blake↗
DOE OSTI2025

In Situ 4D‐STEM Imaging of the Orientation of Lamellar Clusters in Polymer Crystallization

In semi‐crystalline polymeric materials, the initial stages of nucleation and the growth path of crystalline domains can determine the final performance. Here, in this work, we used four‐dimensional scanning transmission electron microscopy (4D‐STEM) imaging to analyze the changes in lamellar orientation in high‐density polyethylene (HDPE) during heating and cooling. This method allowed us to quantitatively detect the formation of lamellae clusters with different in‐plane orientations, which are not visible with traditional methods. Our analysis provided detailed insights into the orientation and size changes of crystalline domains. Additionally, this technique enabled direct observation of lattice structures in hierarchical lamellae and the growth of crystals, confirming the local variability in lamellar orientation. This innovative approach significantly improves our understanding of polymer crystallization, linking changes in morphology and lattice structures at different length scales.

4D-STEM↗
DOE OSTI2022

Detecting Thermally-Induced Spinodal Decomposition with Picosecond Ultrasonics in Cast Austenitic Stainless Steels

Destructive techniques to monitor nuclear reactor component health may not always be available during service, as they are time-consuming and often require pre-installed inspection coupons. Non-destructive evaluation (NDE) techniques can bridge this gap by rapidly identifying the state of mission-critical reactor components, via inference between NDE-measurable material properties and those of ultimate interest, such as ductility and toughness. Here, we demonstrate one such inference about the health of thermally aged cast austenitic stainless steels. Observations of surface acoustic wave peak (SAW) splitting correlate with spinodal decomposition-induced embrittlement as destructively measured by Charpy impact energy. Elastodynamic calculations and molecular dynamics simulations of the effects of spinodal decomposition on elastic moduli support that the new acoustic modes present are due to stiffening in the δ-ferrite domains. Finally, this discovery enables one to probe structure-property relationships in materials in a greatly accelerated manner, suggesting that similar inference methods can be used to determine material fitness-for-service, or to quickly uncover new structure-property relationships.

304-type stainless steel↗
DOE OSTI2021

Surface and interface structures of epitaxial Sb 2 Se 3 on mica

Sb 2 Se 3 thin film is an emerging photon absorber used in solar cells. We report the study of surface and interface structures of Sb2Se3(1 2 0) film grown on mica substrate by a high-rate vapor transport method. The interface epitaxial relationship between Sb 2 Se 3 and mica examined by the cross- sectional TEM images and diffraction patterns along the [0 0 1] and [10] directions of Sb 2 Se 3 reveal a rectangular structure with lengths of 4.03 ± 0.1 Å and 5.29 ± 0.1 Å, consistent with the [1 2 0] out-of-plane direction of Sb 2 Se 3 bulk lattice parameters. In contrast, the two-dimensional reciprocal space map (2D map) constructed from azimuthal reflection high-energy electron diffraction (ARHEED) patterns from the surface exhibits a decorated hexagonal structure. This surface structure emerges from six epitaxial orientation domains/rods and each domain has a rectangular unit mesh of 3.94 ± 0.09 Å and 26.95 ± 1.16 Å along the [0 0 1] and [10] directions. The 26.95 Å is consistent with the unit mesh of the outermost layer of the Sb 2 Se 3 (1 2 0) domains/rods. Overall, our 2D map reveals surface information that are not easily observed by other diffraction techniques.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Understanding, inhibiting, and engineering membrane transporters with high-throughput mutational screens

Promiscuous membrane transporters play vital roles across domains of life, mediating the uptake and efflux of structurally and chemically diverse substrates. Although many transporter structures have been solved, the fundamental rules of polyspecific transport remain inscrutable. In recent years, high-throughput genetic screens have solidified as powerful tools for comprehensive, unbiased measurements of variant function and hypothesis generation, but have had infrequent application and limited impact in the transporter field. In this primer, we describe the principles of high-throughput screening methods available for studying polyspecific transporters and comment on the necessity and potential of high-throughput methods for deciphering these transporters in particular. We present several screening approaches which could provide a fundamental understanding of the molecular basis of function and promiscuity in transporters. Here, we further posit how this knowledge can be leveraged to design inhibitors that combat multidrug resistance and engineer transporters as needed tools for synthetic biology and biotechnology applications.

EPIs↗
DOE OSTI2023

KEBLM: Knowledge-Enhanced Biomedical Language Models

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

High-order dimensionally-split Cartesian embedded boundary method for non-dissipative schemes

Centered finite-difference schemes are commonly used for high-fidelity turbulent flow simulations in canonical configurations because of their non-dissipative property and computational efficiency. However, their use in flow simulations over complex geometries is limited by the requirements of a structured grid and a stable boundary treatment in the absence of artificial (numerical) dissipation. Cartesian embedded boundary (EB) approaches provide an efficient structured-grid framework to apply difference schemes over complex domains. However, they are often restricted to low orders of accuracy because of numerical instabilities at the embedded boundaries and the issues of small-cell problem that are difficult to address with high-order accuracy. The present work discusses a systematic approach to obtain high-order EB methods with non-dissipative centered schemes in the interior. This approach, based on satisfying the primary and secondary conservation conditions, is employed to derive EB schemes that are up to sixth-order accurate in the interior and fourth-order accurate globally for hyperbolic, parabolic as well as incompletely parabolic problems. The proposed finite-difference discretization is, by construction, dimensionally split and addresses the small-cell problem without any cell/geometry transformations, thus, highly simplifying implementation in a flow solver. Various linear and non-linear numerical tests are performed to evaluate the stability and the accuracy of the proposed EB schemes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

System risk quantification and decision making support using functional modeling and dynamic Bayesian network

Risk-informed decision-making requires a probabilistic assessment of the likelihood of success of control action, given the system status. This paper presents a systematic state transition modeling approach integrating dynamic probabilistic risk assessment with a decision-making process using a dynamic Bayesian network (DBN) coupled with functional modeling. A functional model designed with multilevel flow modeling (MFM) technique was used to build a system state structure inferred by energy, mass, and information flow so that one can verify the developed model with respect to system functionality. The MFM model represents the causal relationship among the nodes, which captures the structure of process parameters and control units. Each node may have multiple possible states, and the DBN structured by the MFM model represents the time-domain transitions among the defined states. Furthermore, the MFM-DBN integrated state transition modeling is a white-box approach that allows one to draw the system's risk profile by updating the system states and supports the decisions probabilistically with physical inference. An example of a simple heating system has been used to illustrate this process, including decision-making support based on quantitative risk profile. For demonstrating its applicability to a complex system operational decision making, a case study of station blackout accident scenario leading to the seal loss of coolant accident in a nuclear power plant is presented. The proposed approach effectively provided the risk profile along time for each option so that the operators can make the best decision, which minimizes the plant risk.

42 ENGINEERING↗
DOE OSTI2024

Stochastic modal velocity field in rough-wall turbulence

Stochastically generated instantaneous velocity profiles are used to reproduce the outer region of rough-wall turbulent boundary layers in a range of Reynolds numbers extending from the wind tunnel to field conditions. Each profile consists in a sequence of steps, defined by the modal velocities and representing uniform momentum zones (UMZs), separated by velocity jumps representing the internal shear layers. Height-dependent UMZ is described by a minimal set of attributes: thickness, mid-height elevation, and streamwise (modal) and vertical velocities. These are informed by experimental observations and reproducing the statistical behaviour of rough-wall turbulence and attached eddy scaling, consistent with the corresponding experimental datasets. Sets of independently generated profiles are reorganized in the streamwise direction to form a spatially consistent modal velocity field, starting from any randomly selected profile. The operation allows one to stretch or compress the velocity field in space, increases the size of the domain and adjusts the size of the largest emerging structures to the Reynolds number of the simulated flow. By imposing the autocorrelation function of the modal velocity field to be anchored on the experimental measurements, we obtain a physically based spatial resolution, which is employed in the computation of the velocity spectrum, and second-order structure functions. The results reproduce the Kolmogorov inertial range extending from the UMZ and their attached-eddy vertical organization to the very-large-scale motions (VLSMs) introduced with the reordering process. The dynamic role of VLSM is confirmed in the –u'w' co-spectra and in their vertical derivative, representing a scale-dependent pressure gradient contribution.

42 ENGINEERING↗
DOE OSTI2021

Co-Design of Free-Space Metasurface Optical Neuromorphic Classifiers for High Performance

Classification of features in a scene typically requires conversion of the incoming photonic field into the electronic domain. Recently, an alternative approach has emerged whereby passive structured materials can perform classification tasks by directly using free-space propagation and diffraction of light. In this manuscript, we present a theoretical and computational study of such systems and establish the basic features that govern their performance. We show that system architecture, material structure, and input light field are intertwined and need to be co-designed to maximize classification accuracy. Our simulations show that a single layer metasurface can achieve classification accuracy better than conventional linear classifiers, with an order of magnitude fewer diffractive features than previously reported. For a wavelength λ, single layer metasurfaces of size 100λ × 100λ with an aperture density λ –2 achieve ~96% testing accuracy on the MNIST data set, for an optimized distance ~100λ to the output plane. This is enabled by an intrinsic nonlinearity in photodetection, despite the use of linear optical metamaterials. Furthermore, we find that once the system is optimized, the number of diffractive features is the main determinant of classification performance. The slow asymptotic scaling with the number of apertures suggests a reason why such systems may benefit from multiple layer designs. Finally, we show a trade-off between the number of apertures and fabrication noise.

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

Homo- and hetero-dimeric subunit interactions set affinity and efficacy in metabotropic glutamate receptors

Metabotropic glutamate receptors (mGluRs) are dimeric class C G-protein–coupled receptors that operate in glia and neurons. Glutamate affinity and efficacy vary greatly between the eight mGluRs. The molecular basis of this diversity is not understood. We used single-molecule fluorescence energy transfer to monitor the structural rearrangements of activation in the mGluR ligand binding domain (LBD). In saturating glutamate, group II homodimers fully occupy the activated LBD conformation (full efficacy) but homodimers of group III mGluRs do not. Strikingly, the reduced efficacy of Group III homodimers does not arise from differences in the glutamate binding pocket but, instead, from interactions within the extracellular dimerization interface that impede active state occupancy. By contrast, the functionally boosted mGluR II/III heterodimers lack these interface ‘brakes’ to activation and heterodimer asymmetry in the flexibility of a disulfide loop connecting LBDs greatly favors occupancy of the activated conformation. Our results suggest that dimerization interface interactions generate substantial functional diversity by differentially stabilizing the activated conformation. This diversity may optimize mGluR responsiveness for the distinct spatio-temporal profiles of synaptic versus extrasynaptic glutamate.

59 BASIC BIOLOGICAL SCIENCES↗