Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complex structure”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2024

Learning a General Model of Single Phase Flow in Complex 3D Porous Media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Mutation of active site glutamate in serine hydroxymethyltransferase allows trapping a reactive intermediate: a combined neutron and X-ray crystallography study

Serine hydroxymethyltransferase (SHMT) is a pyridoxal-5′-phosphate (PLP) dependent enzyme that catalyzes a chemical transformation essential for the one-carbon (1C) metabolism. SHMT reversibly converts L-Ser into Gly and transfers a 1C unit to tetrahydrofolate (THF) to give 5,10-methylene-THF (5,10-MTHF). 5,10-MTHF, a 1C-unit donor, plays a crucial role in the downstream biomolecular syntheses required for the cell homeostasis and proliferation. SHMT is a prominent target for the drug discovery to battle bacterial and parasitic infections, and to treat various types of cancer. SHMT-catalyzed chemistry is governed by the general acid-base catalysis. Knowledge of the catalytic mechanism can aid drug design but can only be achieved when the atomic details of each reaction step are mapped, including accurate determination of hydrogen atom positions. Here we utilized the inactive E53Q mutant of Thermus thermophilus ( Tth ) SHMT to directly determine protonation states with room-temperature neutron crystallography and to capture a reactive intermediate containing the PLP-L-Ser external aldimine and THF in the enzyme active site. We observed protonation of the Schiff base nitrogen (N SB ) in the PLP internal aldimine but no change in the protonation states of other ionizable PLP groups and active site residues compared to wild-type Tth SHMT. X-ray structural analysis of the ternary intermediate complex E53Q-Ser-THF that eluded previous structural characterization shows the strategic positioning of the E53Q side chain in close proximity to the external aldimine and THF and reinforces the proposed role for E53 as the driver of proton transfer events along the reaction pathway.

Drago, Victoria N. [Oak Ridge National Laboratory ↗
DOE OSTI2024

Identifying Topological Defects in Lamellar Phases through Contour Analysis of Complex Wave Fields

Lamellar phases frequently contain structural imperfections that significantly affect their behaviors and properties. Our previous research successfully reconstructed real-space configurations of defective lamellar phases from diffuse scattering patterns, indicating the presence of phase vortices as a potential method for identifying topological defects disrupting the smectic ordering. Here, this report presents a mathematical framework using regularized wave fields to represent defective lamellar structures in real space. Phase singularities, resulting from the interference of random waves and indicating lamellar order disruption, are identified through a contour integral. These wave fields, derived from coherent scattering in reciprocal space, were validated via computational benchmarks analyzing small-angle neutron scattering data from AOT surfactant solutions, facilitating further statistical analysis of the defects. Our study highlights the potential to extract meaningful information about topological defects in lyotropic phases by inversely analyzing experimentally measured two-point static correlations. Our method allows for detailed structural analysis of various lyotropic phases, both particulate and nonparticulate, in their quiescent states and facilitates quantitative investigation of defects’ role in phase transitions. By integrating small-angle scattering, deep learning, and vortex tangle analysis, our comprehensive approach shows promise in addressing complex challenges in the structural analysis of soft matter systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Medium-Range Structural Order as the Driver of Activated Dynamics and Complexity Reduction in Glass-Forming Liquids

Here, we analyze in depth the Elastically Collective Nonlinear Langevin Equation theory of activated dynamics in metastable liquids to establish that the predicted inter-relationships between the alpha relaxation time, local cage and collective elastic barriers, dynamic localization length, and shear modulus are causally related within the theory to the medium range order (MRO) static correlation length. The latter grows exponentially with density for metastable hard sphere fluids and as a nonuniversal inverse power law with temperature for supercooled liquids under isobaric conditions. The physical origin of predicted connections between the alpha time and other metrics of cage order and the thermodynamic inverse dimensionless compressibility is fully established. It is discovered that although kinetic constraints from the real space first coordination shell are important for the alpha time, they are of secondary importance compared to the consequences of the more universal MRO correlations in both the modestly and deeply metastable regimes. This understanding sheds new light on the theoretical basis for, and prior successes of, the predictive mapping of chemically complex thermal liquids to effective hard sphere fluids based on matching their dimensionless compressibilities, a scheme we call “complexity reduction”. In essence, the latter is equivalent to the physical requirement that the thermal liquid MRO correlation equals that of its effective hard sphere analog. The mapping alone is shown to provide a remarkable level of quantitative predictive power for the glass transition temperature T g of 21 molecular and polymer liquids. Predictions for the chemically specific absolute magnitude and growth with cooling of the MRO correlation length are obtained and lie in the window of 2–6 nm at T g . Dynamic heterogeneity, elastic facilitation, and beyond pair structure issues are briefly discussed. Future opportunities to theoretically analyze the equilibrated deep glass regime are outlined.

cancer↗
DOE OSTI2025

Structure of the D1-Val185Asn mutated photosystem II complex with slow O–O bond formation reveals changes in the Cl1 water channel

During photosynthesis, the photosystem II (PSII) enzyme catalyzes the light-driven oxidation of water, fueling life on Earth by storing light energy and releasing O 2 as a byproduct. Determining the molecular mechanism for this water oxidation reaction has been of significant interest for the development of synthetic catalysts, but many details remain elusive. One of the open questions is how protons are strategically removed from the active site, a Mn 4 CaO 5 cluster called the oxygen-evolving complex (OEC), during the reaction cycle via conserved water channels, and how proton transfer contributes to O–O bond formation energetics. Site-directed mutagenesis studies have investigated the role of conserved amino acid side chains in facilitating proton transfer. One of the most influential mutations is the Val185Asn substitution on the D1 subunit, which substantially slows O 2 release kinetics without abolishing catalytic activity. Forming a molecular understanding of how this mutation affects the active site will provide insight into the water oxidation reaction mechanism. Here, we investigated the structural basis of the Val185Asn substitution by determining a 1.99 Å-resolution cryo-EM structure. We observed that Asn185 orients away from the OEC and donates a H-bond to Cl1, a conserved chloride ion. We furthermore observed an alternative D2-Glu312-facing conformation of the D2-Lys317 side chain in the Cl1 water channel, a conformation that is consistent with recent models for proton transfer. These changes also produce perturbations to the hydrogen-bonding network. Overall, these finding provide insight into proton transfer in the Cl1 channel and its effect on the water oxidation reaction mechanism.

cryo-EM↗
DOE OSTI2025

Processing of DNA single-strand breaks with oxidatively damaged ends by LIG1

Abstract DNA ligase 1 (LIG1) seals broken strand breaks by joining two adjacent ends during DNA replication and repair transactions. We previously reported atomic-level insight into the strategies that LIG1 uses to discriminate mismatches or ribonucleotides. However, how LIG1 processes strand breaks with oxidatively damaged ends in the absence and presence of a “wrong” sugar remains unknown. Here, we determined the crystal structures of LIG1/nick DNA complexes with 3′-8-oxodG and 3′-8-oxorG templating A or C during the pre- and post-catalytic steps of the ligation reaction. Our structures demonstrated differences in the distances at the +1 and +2 nucleotides relative to the 3′-end of the nick and a shift in the template base position to accommodate the oxidative lesion depending on the dual coding potential of 8-oxoG, which forms Hoogsteen or Watson–Crick base pairing in -syn or -anti conformation. Furthermore, these structural adjustments lead to mutagenic ligation or non-mutagenic end joining of the nick substrates. Overall, our findings provide mechanistic insight into how LIG1 processes nicks harboring oxidative damage and ribonucleotides to ensure fidelity at the final ligation step of DNA repair and replication to maintain genome integrity.

Balu, Kanal E [Department of Biochemistry and Mole↗
DOE OSTI2025

A nut-and-bolt assembly of the bimodular large progenitor botulinum neurotoxin complex

Botulinum neurotoxin serotype A (BoNT/A) is naturally produced by bacteria along with four nontoxic neurotoxin-associated proteins (NTNH, HA70, HA33, and HA17), forming a bimodular large progenitor toxin complex (L-PTC). The BoNT/A–NTNH complex protects the toxin from adverse environment, while the complex consisting of HA proteins facilitates toxin absorption during oral intoxication. How these two independent modules assemble into the L-PTC remains unclear. Here, we report the crystal structure of the BoNT/A–NTNH–HA70 complex at ~2.9-Å resolution. The structure reveals that the BoNT/A–NTNH complex is anchored into a concentric double β-barrel channel of trimeric HA70 through a short β-hairpin of NTNH (termed nLoop), resembling a nut-and-bolt attachment. We find that the nLoop of NTNH is strictly conserved across HA-containing BoNT complexes and that NTNH–HA70 binding is interchangeable among them. Furthermore, we demonstrate that the nLoop functions as a minimal motif enabling attachment of a protein-of-interest to the HA complex, with potential applications in oral biologics delivery.

Science & Technology - Other Topics↗
DOE OSTI2025

Tailoring multi-dimensional hierarchical self-assembly of metallacages through balancing non-covalent interactions

Despite advances in non-covalent interactions and complex self-assembly, precise control of multi-dimensional hierarchical self-assembly (HSA) from the molecular level to larger scales remains challenging. Herein, we designed and synthesized two rigid tetratopic ligands with multiple preset driving forces, and assembled them with Zn(II) ions to obtain metallacages SC6 and SC12 . Through balancing multiple non-covalent interactions, including metal–organic coordination, hydrophobic, and π–π interactions, SC6 can hierarchically self-assemble driven by a poor solvent, from one-dimensional nanowires to super-helical nanostructures via non-equilibrium self-assembly, progressing continuously with time and the increasing proportion of the poor solvent. However, for SC12 with enhanced hydrophobic interactions, two-dimensional monolayer nanogrids were formed by hierarchical self-assembly. Notably, these structures can be recycled back to primary metallacages through simple dissolution, highlighting their potential for efficient recycling and reuse. These results demonstrate that multi-dimensional hierarchical structures enable precise construction by balancing non-covalent interactions through a bottom-up self-assembly approach. This study provides deeper insight into the mechanisms of HSA and a promising strategy for the tailored creation of complex structures and sustainable porous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology.

IHMCIF↗
DOE OSTI2024

Metabolic complexity drives divergence in microbial communities

Microbial communities are shaped by environmental metabolites, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. Here, in this work, we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but they diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively simpler ones that then participate in cross-feeding between community members, is necessary and sufficient to recapitulate our experimental observations. In addition to helping understand the role of the environment in community assembly, the divergence-complexity effect can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions towards microbiome engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Peptide programming of supramolecular vinylidene fluoride ferroelectric phases

Ferroelectric structures have spontaneous macroscopic polarization that can be inverted using external electric fields and have potential applications including information storage, energy transduction, ultralow-power nanoelectronics and biomedical devices. These functions would benefit from nanoscale control of ferroelectric structure, the ability to switch polarization with lower applied fields (low coercive field) and biocompatibility. Soft ferroelectrics based on poly(vinylidene fluoride) (PVDF) have a thermodynamically unstable ferroelectric phase in the homopolymer, complex semi-crystalline structures, and high coercive fields. Here, in this work, we report on ferroelectric materials formed by water-soluble molecules containing only six VDF repeating units covalently conjugated to a tetrapeptide, with the propensity to assemble into the β-sheet structures that are ubiquitous in proteins. This led to the discovery of ribbon-shaped ferroelectric supramolecular assemblies that are thermodynamically stable with their long axes parallel to both the preferred hydrogen-bonding direction of β-sheets and the bistable polar axes of VDF hexamers. Relative to a commonly used ferroelectric copolymer, the biomolecular assemblies exhibit a coercive field that is two orders of magnitude lower, as the result of supramolecular dynamics, and a similar level of remnant polarization, despite having a peptide content of 49 wt%. Furthermore, the Curie temperature of the assemblies is about 40 °C higher than that of a copolymer containing a similar amount of VDF. This supramolecular system was created using a biologically inspired strategy that is attractive in terms of sustainability and that could lead to new functions for soft ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar ( Control ) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation ( Recovery ) and (2) expansion of selective logging and deforestation ( Degradation ). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted gross primary productivity (GPP) and evapotranspiration (ET). Moreover, both GPP and ET respond negatively to extremes in vapor pressure deficit and downwelling shortwave irradiance in degraded forests in Eastern and Southern Amazon, indicating high sensitivity to droughts. Locally high-biomass forest patches showed little or no negative response of GPP and ET to extreme drought conditions whereas low-biomass forest patches in the same locations—typically degraded forest canopies—responded negatively to higher moisture stress. The results from the Recovery scenario showed similar results to simulations with observed structure; however, under the Degradation scenario, low-biomass forest patches became more abundant, resulting in more regions where GPP and ET are negatively impacted by hot drought conditions according to the ED2 model. Our results suggest that local forest structure is a critical determinant of an ecosystem’s response to climate variability, and that the loss of canopy trees in the Amazon through forest degradation could increase and expand forest vulnerability to droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Trafficking of a nitrogenase FeMo-cofactor assembly intermediate

The maturation of the unique FeMo-cofactor of molybdenum nitrogenase is a multistep process requiring the sequential action of a series of maturase complexes. As a final step, the NifEN complex forms FeMo-cofactor from the precursor NifB-co, also called L-cluster, through replacement of an apical iron ion by molybdenum and the attachment of an organic homocitrate ligand. NifB-co is delivered by a small cofactor chaperone, NifX, and initially bound near the surface of the maturase NifEN. Here, we report high-resolution cryo-electron microscopy structures of NifEN in complex with NifX, showing NifB-co binding to NifEN in full detail, capturing both interacting partners in the act of cluster transfer. In a dynamic transfer complex, the large metal cluster is coordinated by single residues from both NifEN and NifX. In silico studies concur with these structures but suggest a third, internal conversion site where cluster maturation likely takes place.

metalloproteins↗
DOE OSTI2024

Structural insights into binding of polyglutamylated tetrahydrofolate by serine hydroxymethyltransferase 8 from soybean

Tetrahydrofolate and its derivatives participate in one-carbon transfer reactions in all organisms. The cellular form of tetrahydrofolate (THF) is modified by multiple glutamate residues and polyglutamylation plays a key role in organellar and cellular folate homeostasis. In addition, polyglutamylation of THF is known to increase the binding affinity to enzymes in the folate cycle, many of which can utilize polyglutamylated THF as a substrate. Here, we use X-ray crystallography to provide a high-resolution view of interactions between the enzyme serine hydroxymethyltransferase (SHMT), which provides one carbon precursors for the folate cycle, and a polyglutamylated form of THF. Our 1.7 Å crystal structure of soybean SHMT8 in complex with diglutamylated 5-formyl-THF reveals, for the first time, a structural rearrangement of a loop at the entrance to the folate binding site accompanied by the formation of novel specific interactions between the enzyme and the diglutamyl tail of the ligand. Biochemical assays show that additional glutamate moieties on the folate ligand increase both enzyme stability and binding affinity. Together these studies provide new information on SHMT structure and function and inform the design of anti-folate agents.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cryo-EM captures the coordination of asymmetric electron transfer through a di-copper site in DPOR

Enzymes that catalyze long-range electron transfer (ET) reactions often function as higher order complexes that possess two structurally symmetrical halves. The functional advantages for such an architecture remain a mystery. Using cryoelectron microscopy we capture snapshots of the nitrogenase-like dark-operative protochlorophyllide oxidoreductase (DPOR) during substrate binding and turnover. DPOR catalyzes reduction of the C17 = C18 double bond in protochlorophyllide during the dark chlorophyll biosynthetic pathway. DPOR is composed of electron donor (L-protein) and acceptor (NB-protein) component proteins that transiently form a complex in the presence of ATP to facilitate ET. NB-protein is an α 2 β 2 heterotetramer with two structurally identical halves. However, our structures reveal that NB-protein becomes functionally asymmetric upon substrate binding. Asymmetry results in allosteric inhibition of L-protein engagement and ET in one half. Residues that form a conduit for ET are aligned in one half while misaligned in the other. An ATP hydrolysis-coupled conformational switch is triggered once ET is accomplished in one half. These structural changes are then relayed to the other half through a di-nuclear copper center at the tetrameric interface of the NB-protein and leads to activation of ET and substrate reduction. These findings provide a mechanistic blueprint for regulation of long-range electron transfer reactions.

Computational biophysics↗
DOE OSTI2025

Advances in relaxation and memory effects of magnetic nanoparticles for biomedical applications

Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.

36 MATERIALS SCIENCE↗