Search NASA⌕ Search

SEARCH · Search NASA

Results for “structure sensitivity”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

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

Effects of iron carbide crystal phases and dopants on the conversions of CO 2 into ethylene

The density functional theory method was used to investigate the conversions of CO 2 to ethylene formation on two common iron carbide surfaces: Fe 3 C(0 1 0) and Fe 5 C 2 (1 1 1). Based on the structure relaxation of reaction intermediates and the elementary reaction transition states. We deduced the most competitive reaction pathways for ethylene production. The main CO 2 -to-ethylene routes and the competition of side products, CO and CH 4 , are discussed. Our analyses showed that CO 2 conversion is surface structure sensitive, whereas CH 4 and C2+ hydrocarbon formations depend on the reactivity of native C atoms in the carbides. To modify the intrinsic catalyst performance, mixing dopants in Fe catalysts is an effective strategy. Furthermore, we demonstrate that doping Zn and Zr can alter the local electronic structure and enhance CO 2 adsorption on the catalyst surface.

CO2 hydrogenation↗
DOE OSTI2021

Nonlinear X-ray Optics

Novel X-ray free-electron lasers (XFELs) are capable of producing radiation with unprecedented properties. Specifically, their ultrashort coherent X-ray pulses can generate extreme peak intensities where ordinary rules of light-matter interaction may no longer apply, and nonlinear processes start to become important. XFELs have made it possible to observe some of the most important coherent non-sequential nonlinearities, including X-ray-optical sum frequency generation (SFG), X-ray second harmonic generation (XSHG), two-photon absorption (TPA) and nonlinear two-photon Compton scattering (2PCS). In particular, the 2PCS experiment has led to unexpected results, namely the observation of a substantial anomalous red shift in the energy of photons generated by nonlinear two-photon X-ray Compton scattering in beryllium. The energy shift is in addition to the predicted nonlinear Compton shift and was neither expected from extrapolations from linear X-ray interactions nor from nonlinear effects at optical wavelengths. Our results suggest a novel nonlinear scattering mechanism that can only be observed at high fields at X-ray wavelengths, where the photon energy is a significant fraction of the electron rest mass (and thus a significant momentum transfer to the electron occurs during the scattering) and where the interaction is not dominated by the quiver motion of the electron in the field (ponderomotive potential) as is usually the case at longer (optical) wavelengths. The goal of this research project was the investigation of fundamental nonlinear X-ray-matter interactions. As these processes are typically weak, part of this research is the exploration of more efficient nonlinear X-ray processes by studying novel mechanisms including solid-state effects, the assistance of optical radiation and novel phase-matching techniques. These experiments require extremely large X-ray field strengths, such as produced by XFELs. Nonlinear X-ray effects can lead to important applications in many research fields. For example, it could lead to instantaneous plasma diagnostics for materials in extreme conditions, as a method for combining atomic-scale structural sensitivity with chemical specificity, or as a probe of electron dynamics in solids on the attosecond (1 as = 10 -18 s) time- and Ångstrom (10 -10 m) length scales. In addition, a detailed understanding of nonlinear X-ray matter interactions is crucial for understanding and extending the limits of structural determination at high intensity such as in serial femto-crystallography. The results could have a profound impact on advanced XFEL light sources such as the LCLS-II.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Tunable magneto-optical properties in MoS 2 via defect-induced exciton transitions

The presence of chalcogen vacancies in monolayer transition metal dichalcogenides (TMDs) leads to excitons with mixed localized-delocalized character and to reduced valley selectivity. Recent experimental advances in defect design in TMDs allow for a close examination of such mixed exciton states as a function of their degree of circular polarization under external magnetic fields, revealing strongly varying defect-induced magnetic properties. A theoretical understanding of these observations and their physical origins demands a predictive, structure-sensitive theory. In this work, we study the effect of chalcogen vacancies on the exciton magnetic properties in monolayer MoS 2 . Using many-body perturbation theory, we show how the complex excitonic picture associated with the presence of defects—with reduced valley and spin selectivity due to hybridized electron-hole transitions—leads to a structurally controllable exciton magnetic response. We find a variety of $\textit{g}$-factors with changing magnitudes and sign depending on the exciton energy and character. Further, our findings suggest a pathway to tune the nature of the excitons—and by that their magneto-optical properties—through defect architecture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Surface facet dependence of competing alloying mechanisms

Metal alloys are ubiquitous in many branches of heterogeneous catalysis, and it is now fairly well established that the local atomic structure of an alloy can have a profound influence on its chemical reactivity. While these effects can be difficult to probe in nanoparticle catalysts, model studies using well defined single crystal surfaces alloyed with dopants enable these structure–function correlations to be drawn. The first step in this approach involves understanding the alloying mechanism and the type of ensembles formed. In this study, we examined the atomic structure of RhCu single-atom alloys formed on Cu(111), Cu(100), and Cu(110) surfaces. Our results show a striking difference between Rh atoms alloying in Cu(111) vs the more open Cu(100) and Cu(110) surface facets. Unlike Cu(111) on which Rh atoms preferentially place-exchange with Cu atoms in the local regions above step edges leaving the majority of the Cu surface free of Rh, highly dispersed, homogeneous alloys are formed on the Cu(100) and (110) surfaces. These dramatically different alloying mechanisms are understood by quantifying the energetic barriers for atomic hopping, exchange, swapping, and vacancy filling events for Rh atoms on different Cu surfaces through theoretical calculations. Density functional theory results indicate that the observed differences in the alloying mechanism can be attributed to a faster hopping rate, relatively high atomic exchange barriers, and stronger binding of Rh atoms in the vicinity of step edges on Cu(111) compared to Cu(110) and Cu(100). Furthermore, these model systems will serve as useful platforms for examining structure sensitive chemistry on single-atom alloys.

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

Effect of Ni particle size on the production of renewable methane from CO 2 over Ni/CeO 2 catalyst

Production of ‘renewable Methane’ has attracted renewed research interest as a fundamental probe reaction and process for CO 2 utilization through potential use in C1 fuel production and even for future space exploration technologies. CO 2 methanation is a structure sensitive reaction on Ni/CeO 2 catalysts. To precisely elucidate the size effect of the Ni metal center on the CO 2 methanation performance, we prepared 2%Ni/CeO 2 catalysts with pre-synthesized uniform Ni particles (2, 4 and 8 nm) on a high surface area CeO 2 support. Transmission electron microscopy (TEM) and ambient pressure X-ray photo spectroscopy (AP-XPS) characterization have confirmed that the catalyst structure and chemical state was uniform and stable under reaction conditions. The 8 nm sized catalyst showed superior methanation selectivity over the 4 and 2 nm counterparts, and the methanation activity in term of TOF is 10 times and 70 times higher than for the 4 and 2 nm counterparts, respectively. Here, the DRIFTS studies revealed that the larger Ni (8 nm particles) over CeO 2 efficiently facilitated the hydrogenation of the surface formate intermediates, which is proposed as the rate determining step accounting for the excellent CO 2 methanation performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Size-Controlled Nanoparticles Embedded in a Mesoporous Architecture Leading to Efficient and Selective Hydrogenolysis of Polyolefins

A catalytic architecture, comprising a mesoporous silica shell surrounding platinum nanoparticles (NPs) supported on a solid silica sphere (mSiO2/Pt-X/SiO2; X is the mean NP diameter), catalyzes hydrogenolysis of melt-phase polyethylene (PE) into a narrow C23-centered distribution of hydrocarbons in high yield using very low Pt loadings (~10 -5 g Pt/g PE). During catalysis, a polymer chain enters a pore and contacts a Pt NP where the C–C bond cleavage occurs and then the smaller fragment exits the pore. mSiO 2 /Pt/SiO 2 resists sintering or leaching of Pt and provides high yields of liquids; however, many structural and chemical effects on catalysis are not yet resolved. Here, we report the effects of Pt NP size on activity and selectivity in PE hydrogenolysis. Time-dependent conversion and yields and a lumped kinetics model based on the competitive adsorption of long vs short chains reveal that the activity of catalytic material is highest with the smallest NPs, consistent with a structure-sensitive reaction. Remarkably, the three mSiO 2 /Pt-X/SiO 2 catalysts give equivalent selectivity. We propose that mesoscale pores in the catalytic architecture template the C 23 -centered distribution, whereas the active Pt sites influence the carbon–carbon bond cleavage rate. This conclusion provides a framework for catalyst design by separating the C–C bond cleavage activity at catalytic sites from selectivity for chain lengths of the products influenced by the structure of the catalytic architecture. The increased activity, selectivity, efficiency, and lifetime obtained using this architecture highlight the benefits of localized and confined environments for isolated catalytic particles under condensed-phase reaction conditions.

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

From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning

The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. AlphaFold2 and related models, including RoseTTAFold and ESMFold, employ specialized neural network architectures driven by attention mechanisms to infer relationships between sequence and structure. At a fundamental level, these AI/ML models operate on the long-standing hypothesis that the structure of a protein is determined by its amino acid sequence. More recently, AlphaFold2 has been adapted for the prediction of multiple protein conformations by subsampling multiple sequence alignments. Herein, we provide an overview of the deterministic relationship between sequence and structure, which was hypothesized over half a century ago with profound implications for the biological sciences ever since. We postulate that protein conformational dynamics are also determined, at least in part, by amino acid sequence and that this relationship may be leveraged for construction of AI/ML models dedicated to predicting protein conformational ensembles. Accordingly, we describe a conceptual model architecture, which may be trained on sequence data in combination with conformationally sensitive structural information, coming primarily from nuclear magnetic resonance (NMR) spectroscopy. Notwithstanding certain limitations in this context, NMR offers abundant structural heterogeneity conducive to conformational ensemble prediction. As NMR and other data continue to accumulate, sequence-informed prediction of protein structural dynamics with AI/ML has the potential to emerge as a transformative capability across the biological sciences.

Artificial intelligence↗
NASA NTRS1995

A Method Based on Radiative Cooling for Detecting Structural Changes in Undercooled Metallic Liquids

We introduce a structure-sensitive parameter for undercooled melts which can be measured in containerless processing experiments. We have established that the ratio, R(T), of hemispherical total emissivity epsilon(sub T)(T) to constant-pressure specific heat c(sub p)(T) can serve as an indicator which is sensitive to any changes in short range atomic order in undercooled metallic melts. R(T) (triple bonds) epsilon(sub T)(T)/c(sub p)(T) values for nickel, zirconium, and silicon have been obtained using the high temperature electrostatic levitator while the levitated melts were undergoing purely radiative cooling into the deeply undercooled region. R(T) plots for undercooled liquid nickel and zirconium indicate no significant change in short-range structure from their melting temperatures to 15% undercooling. In contrast, liquid silicon shows marked short-range structural changes beginning above its melting temperature and extending throughout the undercooled region. The short-range structure of liquid silicon is related to the highly-directional covalent bonding which characterizes its solid form. The nickel and zirconium data show that epsilon(sub T) varies linearly with T, in support of metal emissivity theories.

Rulison, Aaron J.↗
DOE OSTI2026

New perspectives on materials and device dynamics using time-resolved full-field diffraction X-ray imaging

Understanding how materials evolve during synthesis, processing, or device operation requires experimental access to structural dynamics across wide ranges of length and time scales, often in bulk samples or even within packaged devices. Time-resolved full-field diffraction X-ray microscopy has recently emerged as a powerful way to meet this need by combining the penetration and structural sensitivity of X-ray diffraction with objective-lens-based magnification, sensitive high-resolution X-ray imaging detectors, and pump-probe and real-time imaging strategies. Advances in full-field X-ray diffraction microscopy, often termed dark-field X-ray microscopy (DFXM), enable simultaneous imaging of extended fields of view while retaining crystallographic selectivity. Time-resolved DFXM promises to enable advances in materials processing and dynamics, electrochemical and photochemical processes, and the design of electronic devices. This Perspective summarizes the key instrumental concepts that define the performance of these methods, including the choice of imaging optics, detector considerations, and the impact of source time structure at synchrotron light sources and X-ray free-electron lasers (XFELs). We discuss the simultaneous use of complementary imaging modes that are increasingly used in practice. The early demonstrations of the potential of time-resolved DFXM include real-time defect and grain-boundary dynamics during metal annealing, stroboscopic imaging of functional devices with high strain sensitivity, and ultrafast pump-probe implementations at XFELs that directly visualize acoustic-wave propagation and energy dissipation in bulk crystals.

Dark-field X-ray microscopy↗
NASA NTRS2004

Advanced Control Surface Seal Development for Future Space Vehicles

High temperature control surface seals have been identified as a critical technology in the development of future space vehicles. These seals must withstand temperatures of up to 2600 F and protect underlying temperature-sensitive structures (such as actuators and sealing capability by remaining resilient during flight conditions. The current baseline seal, used on the Shuttle orbiters and the X-38 vehicle, consists of a Nextel 312 sheath, an internal Inconel X-750 knitted spring tube, and hand-stuffed Saffil batting. Unfortunately at high temperatures (> 1500 F), the seal resiliency significantly degrades due to yielding and creep of the spring tube element. The permanent set in the seals can result in flow passing over the seals and subsequent damage to temperature sensitive components downstream of the seals. Another shortcoming of the baseline seal is that instances have been reported on Shuttle flights where some of the hand-stuffed Saffil batting insulation has been extracted, thus potentially compromising the seal. In vehicles where the thermal protection systems are delicate (such as with Shuttle tiles), the control surface seals must also limit the amount of force applied to the opposing surfaces. Additionally, in many applications the seals are subjected to scrubbing as control surfaces are actuated. The seals must be able to withstand any damage resulting from this high temperature scrubbing and retain their heat/flow blocking abilities.

DeMange, Jeffrey J.↗
DOE OSTI2024

Overview of NETL’s Low Temperature CO2 Electrolysis Research

This keynote lecture will briefly overview diverse research areas of National Energy Technology Laboratory (NETL) to advance energy and environmental sustainability along with carbon management. Our electrochemistry efforts on carbon conversion directly support the US goal of achieving carbon-free power sector by 2035 and net zero emissions by 2050. Since CO2 electroreduction is highly structure-sensitive, NETL ongoing research has been focused on the rational design and engineering of electrocatalysts to facilitate the CO2 conversion to desirable products with good selectivity, activity, and durability. Different classes and types of electrocatalytic materials will be covered in this talk, from well-defined atomic-scale model catalysts to heterogenous, scalable powder systems at nano- and micro-scale for “real world” performance evaluation. Several spectroscopic, microscopic, and electrochemical characterization techniques along with computational findings will be additionally discussed to gain more insights into the structure-activity relation. The last part of this seminar will provide more detail on how NETL has transitioned from the most common aqueous H-type reactor for lab-scale validation to more realistic full electrolyzer cell in bench-scale prototype. The knowledge, electrocatalytic materials, and device validation achieved from NETL in-house research will be translated to industrial sector for large scale deployment and the anticipated outcome will help advance the development of low temperature CO2 electrolysis technologies.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Evaluating Radiation Impact on Transmon Qubits in Above and Underground Facilities

Superconducting qubits can be sensitive to abrupt energy deposits caused by cosmic rays and ambient radioactivity. Previous studies have focused on understanding possible correlated effects over time and distance due to cosmic rays. In this study, for the first time, we directly compare the response of a transmon qubit measured initially at the Fermilab SQMS above-ground facilities and then at the deep underground Gran Sasso Laboratory (INFN-LNGS, Italy). We observe same average qubit lifetime T$_1$ of roughly 80 microseconds at above and underground facilities. We then apply a fast decay detection protocol and investigate the time structure, sensitivity and relative rates of triggered events due to radiation versus intrinsic noise, comparing above and underground performance of several high-coherence qubits. Using gamma sources of variable activity we calibrate the response of the qubit to different levels of radiation in an environment with minimal background radiation. Results indicate that qubits respond to a strong gamma source and it is possible to detect particle impacts. However, when comparing above and underground results, we do not observe a difference in radiation induced-like events for these sapphire and niobium-based transmon qubits. We conclude that the majority of these events are not radiation related and to be attributed to other noise sources which by far dominate single qubit errors in modern transmon qubits.

Roy, Tanay↗
DOE OSTI2024

Evaluating Radiation Impact on Superconducting Transmon Qubits in Above and Underground Facilities

Superconducting qubits can be sensitive to sudden energy deposits into the substrate from cosmic rays and ambient radioactivity. While previous studies have primarily focused on exploring correlated effects over time and distance due to cosmic rays, this study uniquely offers a direct comparison of a transmon qubit's response at Fermilab SQMS above-ground facilities and the deep-underground Gran Sasso Laboratory (INFN-LNGS, Italy). Despite the vastly different radiation environments, we observe a similar average qubit lifetime (T1) of approximately 80 microseconds at both sites. We then employ a fast decay detection protocol and investigate the time structure, sensitivity, and relative rates of triggered events due to radiation versus intrinsic noise. We compare the above and underground performance of several high-coherence qubits with similar designs. Our findings reveal no significant difference in events with radiation-like signatures between above-ground and underground conditions for these sapphire and niobium-based transmon qubits. This suggests that most such events are likely due to other noise sources, which predominantly contribute to single-qubit errors in contemporary transmon qubits. By exposing the qubits to gamma sources with varying activity levels, we further evaluate their response to radiation in a low-background environment. The results show that qubits can indeed detect particle impacts; however, this capability is only realized by substantially reducing other noise sources, which in turn affects detection efficiency [1].

Roy, Tanay↗
DOE OSTI2024

Size and Structure Effects of Carbon-Supported Ruthenium Nanoparticles on Waste Polypropylene Hydrogenolysis Activity, Selectivity, and Product Microstructure

Hydrogenolysis of plastic waste using Ru-based catalysts is promising for deconstructing polyolefins into lower molecular weight products. Yet, the effect of catalyst atomic structure and size on activity and product selectivity is poorly understood. Herein, we expose the effect of metal particle size and atomic structure on isotactic-polypropylene (i-PP) hydrogenolysis over Ru supported on carbon. Despite similar molecular weight distributions of solid and liquid products, their physical properties are distinct due to different chain regio-irregular CH3 sequences of steric pentads containing racemo configurations. We propose that i-PP hydrogenolysis entails an interplay of C–C bond scission and stereoisomerization. The active site’s local electronic environment and structure dictate the former, whereas polymer–catalyst surface interactions creating suitable polymer conformations control the latter. C–C scission and stereoisomerization are structure-sensitive. Small, disordered nanoclusters are effective in C–C bond scission, whereas larger metal nanoparticles promote stereoisomerization. Finally, we hypothesize that a heterogeneous distribution of metal active sites is essential for deconstruction and product (lubricant base oil) quality control.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗
NASA NTRS1991

Multidisciplinary optimization of controlled space structures with global sensitivity equations

A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.

Padula, Sharon L.↗