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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Flexible Soft X-Ray Image Sensors based on Metal Halide Perovskites With High Quantum Efficiency

Soft X-ray imaging is a powerful tool to explore the structure of cells, probe material with nanometer resolution, and investigate the energetic phenomena in the universe. Conventional soft X-ray image sensors are by and large Si-based charge coupled devices that suffer from low frame rates, complex fabrication processes, mechanical inflexibility, and required cooling below -60 °C. Here, a soft X-ray photodiode is reported based on low-cost metal halide perovskite with comparable performance to commercial Si-based device. Nanothrough network electrode minimized the optical loss due to the shadowing of insensitive layers, while a multidimensional perovskite heterojunction is generated to reduce the photo-generated carrier loss. Further, this strategy promoted a record quantum efficiency of 8 × 10 3 % without cooling, several orders of magnitude greater than the previously achieved. Flexible and curved soft X-ray imaging arrays are fabricated based on this high-performance device structure, demonstrating stable soft X-ray response and sharp imaging capabilities. This work highlights the low-cost and efficient perovskite photodiode as a strong candidate for the next-generation soft X-ray image sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Domain crossover in the reductase subunit of NADPH-dependent assimilatory sulfite reductase

NADPH-dependent assimilatory sulfite reductase (SiR) from Escherichia coli performs a six-electron reduction of sulfite to the bioavailable sulfide. SiR is composed of a flavoprotein (SiRFP) reductase subunit and a hemoprotein (SiRHP) oxidase subunit. There is no known high-resolution structure of SiR or SiRFP, thus we do not yet fully understand how the subunits interact to perform their chemistry. Here, we used small-angle neutron scattering to understand the impact of conformationally restricting the highly mobile SiRFP octamer into an electron accepting (closed) or electron donating (open) conformation, showing that SiR remains active, flexible, and asymmetric even with these conformational restrictions. From these scattering data, we then model the first solution structure of SiRFP. Further, computational modeling of the N-terminal 52 amino acids that are responsible for SiRFP oligomerization suggests an eight-helical bundle tethers together the SiRFP subunits to form the SiR core. Finally, mass spectrometry analysis of the closed SiRFP variant show that SiRFP is capable of inter-molecular domain crossover, in which the electron donating domain from one polypeptide is able to interact directly with the electron accepting domain of another polypeptide. This structural characterization suggests that SiR performs its high-volume electron transfer through both inter- and intramolecular pathways between SiRFP domains and, thus, cis or trans transfer from reductase to oxidase subunits. Such highly redundant potential for electron transfer makes this system a potential target for designing synthetic enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Violation of the rule of parsimony: Mixed local moment and itinerant Fe magnetism in Fe 3 GeN

Ternary iron nitrides are of considerable interest due to their diverse magnetic properties. We find, based on first principles calculations, that the relatively minor structural distortion from the cubic antiperovskite structure in Fe$_3$GeN, consisting of octahedral rotations, leads to unusual magnetic behavior. In particular, there is a separation into Fe sites with very different magnetic behaviors, specifically a site with Fe atoms having a stable local moment and a site where the Fe shows characteristics of much more itinerant behavior. This shows a remarkable flexibility of the Fe magnetic behavior in these nitrides and points towards the possibility of systems where minor structural and chemical changes can lead to dramatic changes in magnetic properties. The results suggest that, analogously to oxide perovskite materials, modulation of magnetic properties via chemical or strain control of octahedral rotation may be feasible. Furthermore, this may then lead to approaches for tuning magnetism to realize properties of interest, for example tuning magnetic transitions to quantum critical regimes or to proximity to metamagnetic transitions of interest for devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nucleation and Growth of Blue Phase 3D Cubic Structure Under Continuously Changing Curved Boundary Conditions

The blue phase of liquid crystals (BPLCs) with a cubic lattice of disclination lines and 3D nanostructure enables the modulation of photonic bandgap thus casting them in the category of photonic crystals. Its unique nature promises applications in display technologies, electro‐optics, and sensors. To integrate these ordered materials into wearable devices a fundamental understanding of curvature, and spatial confinement is necessary. Although continuous confinement in flat geometries have been studied, confining curvature has shown to induce strong destabilization effects on the cubic structure and formation of topological defects, thereby deteriorating their optical performance. Moreover, limitations in controlling the curvature of droplets further hinder studies of nucleation and growth of BPLCs. Here, to address these challenges, micro‐scale patterned surfaces of concentric cylinders are exploited to systematically control curvatures. The impact of curvature on the confined BPLCs is revealed in terms of phase transition temperature, nucleation and growth, morphology, as well as phase transformation. This research offers valuable insights into the stability, and structural characteristics of BPLCs in adaptive photonic devices, paving the way for future advancements in flexible displays, sensors, and other technologies leveraging liquid crystal (LC) materials.

3D Cubic Structure↗
DOE OSTI2023

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

Abstract Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Strong Effect of Nonpolar Solvent Molecular Structure on CdSe Nanoplatelet Stacking

We report a drastic difference in stacking behavior of oleic acid-stabilized 4-monolayer (4 ML) CdSe nanoplatelets (NPLs) in toluene and methylcyclohexane (MCH), two nonpolar solvents that differ in the conformational flexibility of their molecules. Using liquid cell transmission electron microscopy (TEM) and small angle scattering (SAXS) techniques, we show that NPLs form microns-long ribbons consisting of 4 ML CdSe NPLs in toluene, the solvent widely used to form stable colloidal solutions of a broad range of quasi-spherical nanoparticles. In contrast, 4 ML CdSe NPLs are well dispersed in MCH. The difference in stacking behavior of NPLs in toluene and MCH suggests that the conformational flexibility of the solvent molecules, such as the ability to adopt multiple chair conformations, modulates nanoplatelet interactions. Molecular dynamics (MD) simulations reveal that solvent molecules subtly alter the structure of the organic ligand shell. These solvent-dependent changes propagate to the inorganic core, modulating the degree of CdSe nanoplatelet (NPL) twisting and, consequently, the properties of the nanoparticles. We show that toluene better solvates oleate ligands while MCH induces a bimodal oleate span distribution, which can lead to increased solubility of CdSe NPLs. In addition, the solvent can also influence the inorganic core, which, in turn, can modify the nanoparticle properties. We demonstrate that destabilization of toluene solution containing ribbons of 4 ML CdSe NPLs without CdS shells results in the formation of NPL assemblies with amplified spontaneous emission (ASE) with a low threshold of 14 µJ cm−2 that is comparable with that of CdSe/CdS core/shell NPLs. Our results emphasize that the solvent plays a major role in mediating interactions between NPLs and hence their processability for fabrication of functional structures.

CdSe↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Crystalline Structure-Dependent Mechanical and Thermoelectric Performance in Ag 2 Se 1–x S x System

Self-powered wearable electronics require thermoelectric materials simultaneously with a high dimensionless figure of merit (zT) and good flexibility to convert the heat discharged by the human body into electricity. Ag 2 (S,Se)-based semiconducting materials can well satisfy these requirements, and thus, they are attracting great attention in thermoelectric society recently. Ag 2 (S,Se) crystalizes in an orthorhombic structure or monoclinic structure, depending on the detailed S/Se atomic ratio, but the relationship between its crystalline structure and mechanical/thermoelectric performance is still unclear to date. In this study, a series of Ag 2 Se 1–x S x (x = 0, 0.1, 0.2, 0.3, 0.4, and 0.45) samples were prepared and their mechanical and thermoelectric performance dependence on the crystalline structure was systematically investigated. x = 0.3 in the Ag 2 Se 1–x S x system was found to be the transition boundary between orthorhombic and monoclinic structures. Mechanical property measurement shows that the orthorhombic Ag 2 Se 1–x S x samples are brittle while the monoclinic Ag 2 Se 1–x S x samples are ductile and flexible. In addition, the orthorhombic Ag 2 Se 1–x S x samples show better electrical transport performance and higher zT than the monoclinic samples under a comparable carrier concentration, most likely due to their weaker electron-phonon interactions. This study sheds light on the further development of flexible inorganic TE materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Study of Cost-Saving Potential of Load Flexibility Measures in Grid-Interactive Multifamily Buildings

With recent advances in smart technologies, more and more smart devices are penetrating the residential and commercial buildings market. The introduction of these smart devices is also helping IoT companies emerge with load aggregator roles in the sector. With more utility companies on the track of supporting OpenADR protocols, the aggregators could play a significant role in providing load flexibilities by automatically responding to demand response (DR) events and coordinating load flexibility measures between customers. This would benefit utility companies by reducing stress on the grid during critical peak demand hours as well as customers by allowing them to utilize utility rate structures advantageous to those able to reduce electric usage during high-demand hours. This study evaluates cost and energy savings from adopting multiple load flexibility measures in multifamily buildings. Combinations of different load flexibility measures, including space temperature floating, light dimming, automatic window shading, and water heater temperature floating, are considered. The simulations are performed using OpenStudio®, an open-source U.S. Department of Energy (DOE) simulation platform. For the case study, we used a midrise apartment building with weather conditions from Denver, Colorado. To compare climate zone differences, simulations were also performed for Los Angeles, California, and Chicago, Illinois. Initial results indicate that the application of automated load flexibility measures without careful consideration of dispatching strategies and DR program enrollments could significantly affect the savings. To get meaningful cost savings, aggregators need to encourage tenant awareness to curtail energy usage through occupant behavior in addition to dispatching automatic load flexibility measures. The outcomes from this study are believed to help load aggregators understand the risks and benefits of load flexibility opportunities.

building energy modeling↗
DOE OSTI2021

Structures of the ApoL1 and ApoL2 N-terminal domains reveal a non-classical four-helix bundle motif

Apolipoprotein L1 (ApoL1) is a circulating innate immunity protein protecting against trypanosome infection. However, two ApoL1 coding variants are associated with a highly increased risk of chronic kidney disease. Here we present X-ray and NMR structures of the N-terminal domain (NTD) of ApoL1 and of its closest relative ApoL2. In both proteins, four of the five NTD helices form a four-helix core structure which is different from the classical four-helix bundle and from the pore-forming domain of colicin A. The reactivity with a conformation-specific antibody and structural models predict that this four-helix motif is also present in the NTDs of ApoL3 and ApoL4, suggesting related functions within the small ApoL family. The long helix 5 of ApoL1 is conformationally flexible and contains the BH3-like region. This BH3-like α-helix resembles true BH3 domains only in sequence and structure but not in function, since it does not bind to the pro-survival members of the Bcl-2 family, suggesting a Bcl-2-independent role in cytotoxicity. These findings should expedite a more comprehensive structural and functional understanding of the ApoL immune protein family.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Porogen‐Integrated Rapid Oxidation Enables Structured Mesoporous Metal Oxide Films

Structured metal oxide films have promise in optoelectronics, sensing, energy storage, and catalysis but their uptake is predominately limited due to their long and high‐temperature syntheses. Here, in this study, a self‐assembling polymer is used which can act as a chelating fuel source in a solution combustion reaction to generate highly structured mesoporous aluminum oxide films at <250 °C in a matter of minutes through a process termed porogen‐integrated rapid oxidation (PiRO). The resulting films with thicknesses up to 500 nm show an open‐cell, face‐centered cubic structure of spheroidal pores. Further, an additional ligand can be included to control the self‐assembly step to yield both through‐film ordering or tunable disordering for increased pore volume as confirmed by both grazing incidence small angle X‐ray scattering and ellipsometry. Finally, roll‐to‐roll manufacturing with PiRO is demonstrated on flexible polymeric substrates. The method offers a tunable, scalable, low‐temperature, and lower‐cost method to generate large‐area structured mesoporous metal oxide films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidate the molecular basis of ampholytic chitosan as a high-performance cryoprotectant to myosin denaturation: The importance of saccharide charges

The uses of charged poly/oligo-saccharides enable the retarding of protein denaturation against various environmental stresses during food storage and manufacturing. However, at subzero temperatures, the molecular basis of such stabilization behaviors, i.e., cryoprotections, remain less explored. Here, in this study, we introduced an ampholytic saccharide, carboxymethyl chitooligosaccharide (CMCO) that effectively inhibited the freezing-induced myosin denaturation. The in-depth cryoprotective mechanism was systematically investigated by using molecular dynamic simulation and multispectral characterizations. Results showed that CMCO may interact with myosin through hydrogen bonding and electrostatic interactions, which caused the expelling of water at protein surfaces and the reduced conformational flexibility of myosin molecules. Due to this water replacement event, both secondary and ternary structures of myosin became freezing-resistant, leading to the inhibited protein aggregations and retained functionalities, such as solubility, Ca 2+ -ATPase activity, and gelling properties. Moreover, cryoprotective behaviors of CMCO were charge-dependent. CMCO with a higher degree of carboxymethyl substitution (DS: 1.2) was inclined to bind and stabilize myosin molecules better than the low-DS (DS: 0.8) one, even though both outperformed other cryoprotective saccharides. Therefore, this investigation not only introducing a high-performance myosin cryoprotectant, but also elaborated the cryoprotective mechanism of ampholytic saccharides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

NEML2: An efficient and modular multiphysics constitutive modeling library for hybrid computing environments

This paper presents NEML2, an open-source, high-performance library developed for constitutive material modeling, designed to support the flexible and modular development of models for complex material behavior. Building on the foundational structure of its predecessor, NEML, the NEML2 library introduces significant improvements, including enhanced vectorization, automatic differentiation, and seamless integration with PyTorch, facilitating the application of machine learning techniques in material simulations. NEML2 provides a C++ backend with Python bindings, enabling users to create custom material models that can be executed efficiently on both CPU and GPU platforms. The library also supports coupling with Multiphysics simulation frameworks like MOOSE, making it suitable for realistic simulations involving coupled physical processes. Rigorous quality assurance through unit and regression testing ensures the reliability of results, while the extensible, user-friendly design encourages collaboration and reproducibility across the scientific community. This paper provides an overview of NEML2’s architecture, core features, and applications, highlighting its impact on accelerating material qualification and advancing computational methods in materials science.

GPU↗
DOE OSTI2022

Expanding and quantifying the crystal chemistry of the flexible ligand 15aneN5

Tetraazamacrocycles have been very extensively exploited as transition metal ligands for a variety of purposes, including catalysis, medical imaging, pharmaceuticals, etc. However, the pentaazamacrocycles are much less commonly used for similar purposes because of poor availability, difficulties in their synthesis, and less well-known metal coordination properties. 1,4,7,10,13-pentaazacyclopentadane (15aneN5) was initially synthesized by a published synthetic route, which we simplified and shortened with minimal drop in yield. Eight different transition metal complexes were made using typical complexation methods. X-ray crystallography of multiple novel complexes yielded insight into the flexibility in coordination geometry of this interesting macrocycle as well as the first crystal structures of 15aneN5 with Cr 3+ , Mn 3+ , Fe 3+ , Co 3+ , Cu 2+ , and Ru 2+ . A parameter to quantify the coordination geometry adopted by the ligand was devised and applied to all known crystal structures of its metal complexes. Lastly, oxidation of 15aneN5 to a novel diimine macrocycle was observed during complexation with ruthenium.

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

Enhancing the accuracy of XPS calculations: Exploring hybrid basis set schemes for CVS-EOMIP-CCSD calculations

Reliable computational methodologies and basis sets for modeling x-ray spectra are essential for extracting and interpreting electronic and structural information from experimental x-ray spectra. In particular, the trade-off between numerical accuracy and computational cost due to the size of the basis set is a major challenge, since molecular orbitals undergo extreme relaxation in the core-hole state. To gain clarity on the changes in electronic structure induced by the formation of a core-hole, the use of sufficiently flexible basis for expanding the orbitals, particularly for the core region, has been shown to be essential. This work focuses on the refinement of core-hole ionized state calculations using the equation-of-motion coupled cluster family of methods through an extensive analysis on the effectiveness of “hybrid” and mixed basis sets. In this investigation, we utilize the CVS-EOMIP-CCSD method in combination and construct hybrid basis sets piecewise from readily available Dunning’s correlation consistent basis sets in order to calculate x-ray ionization energies (IEs) for a set of small gas phase molecules. Our results provide insights into the impact of basis sets on the CVS-EOMIP-CCSD calculations of K-edge IEs of first-row p-block elements. Furthermore, these insights enable us to understand more about the basis set dependence of the core IEs computed and allow us to establish a protocol for deriving reliable and cost-effective theoretical estimates for computing IEs of small molecules containing such elements.

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

Structural analysis of molten materials by a remote fiber optic Raman sensor

This study presents a novel in situ high-temperature fiber optic Raman probe that enables the study of the physical properties and structure of molten samples at temperatures up to 1400 °C. To demonstrate the functionality of the high-temperature fiber optic Raman probe, different composition mold fluxes were evaluated in this report. The Raman spectra at flux molten temperature were successfully collected and analyzed. A deconvolution algorithm was employed to identify peaks in the spectra associated with the molecular structure of the components in each sample. Here, the experimental results demonstrate that the composition-dependent Raman signal shift can be detected at high temperatures, indicating that molten materials analysis using a high-temperature Raman system shows significant promise. This flexible and reliable high-temperature Raman measurement method has great potential for various applications, such as materials development, composition and structure monitoring during high-temperature processing, chemical identification, and process monitoring in industrial production.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Planar 2D wireframe DNA origami

Two-dimensional (2D) DNA origami is widely used for applications ranging from excitonics to single-molecule biophysics. Conventional, single-layer 2D DNA origami exhibits flexibility and curvature in solution; however, that may limit its suitability as a 2D structural template. In contrast, 2D wireframe DNA origami rendered with six-helix bundle edges offers local control over duplex orientations with enhanced in-plane rigidity. Here, we investigate the 3D structure of these assemblies using cryo–electron microscopy (cryo-EM). 3D reconstructions reveal a high degree of planarity and homogeneity in solution for polygonal objects with and without internal mesh, enabling 10-Å resolution for a triangle. Coarse-grained simulations were in agreement with cryo-EM data, offering molecular structural insight into this class of 2D DNA origami. Our results suggest that these assemblies may be valuable for 2D material applications and geometries that require high structural fidelity together with local control over duplex orientations, rather than parallel duplex assembly.

59 BASIC BIOLOGICAL SCIENCES↗