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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Abundance Measurements of Titan's Stratospheric HCN, HC3N, C3H4, and CH3CN from ALMA Observations

Previous investigations have employed more than 100 close observations of Titan by the Cassini orbiter to elucidate connections between the production and distribution of Titan's vast, organic-rich chemical inventory and its atmospheric dynamics. However, as Titan transitions into northern summer, the lack of incoming data from the Cassini orbiter presents a potential barrier to the continued study of seasonal changes in Titan's atmosphere. In our previous work, we demonstrated that the Atacama Large Millimeter/submillimeter Array (ALMA) is well suited for measurements of Titan's atmosphere in the stratosphere and lower mesosphere (~100 - 500 km) through the use of spatially resolved (beam sizes <1") flux calibration observations of Titan. Here, we derive vertical abundance profiles of four of Titan's trace atmospheric species from the same 3 independent spatial regions across Titan's disk during the same epoch (2012-2015): HCN, HC3N, C3H4, and CH3CN. We find that Titan's minor constituents exhibit large latitudinal variations, with enhanced abundances at high latitudes compared to equatorial measurements; this includes CH3CN, which eluded previous detection by Cassini in the stratosphere, and thus spatially resolved abundance measurements were unattainable. Even over the short 3-year period, vertical profiles and integrated emission maps of these molecules allow us to observe temporal changes in Titan's atmospheric circulation during northern spring. Our derived abundance profiles are comparable to contemporary measurements from Cassini infrared observations, and we find additional evidence for subsidence of enriched air onto Titan's south pole during this time period. Continued observations of Titan with ALMA beyond the summer solstice will enable further study of how Titan's atmospheric composition and dynamics respond to seasonal changes.

Thelen, Alexander E.↗
NASA NTRSDate not supplied

REACTER 2.0: Quantum-Informed Reaction Constraints and Automated Interaction Typing

REACTER is a heuristic method for modeling chemical reactions in classical molecular dynamics simulations, implemented in LAMMPS as fix bond/react. The authors recently extended LAMMPS to support alphanumeric labels for atom types, bond types etc., which enables the pre- and post-reaction templates required by the REACTER protocol to be portable between different simulations and greatly simplifies the task of creating simulation-ready reaction templates. To further increase the generality of reaction templates, support for wildcard characters within atom types has been added, along with the automatic assignment of interaction types for new bonds, angles, etc. based on the involved atom types. In some cases, this feature can express a class of reactions with one pair of reaction templates, where previously dozens may have been required. Advanced reaction constraints have also been added, including an Arrhenius constraint to enforce an effective activation energy, a root-mean-square-deviation option for complex geometrical constraints, as well as a custom constraint that leverages LAMMPS’ powerful built-in variable framework. Other new features include variable support for various inputs (e.g., to allow reaction rates or cutoffs to be dependent on overall conversion), on-the-fly update of molecule IDs, and the ability to create new atoms positioned with respect to the reaction site. The new features are applied to modeling polymeric, thermosetting and composite materials, and advanced applications of the new reaction constraints are demonstrated. For example, REACTER is shown to accurately reproduce mechanically-induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a constraint on the total potential energy of the involved atoms.

polymer simulations↗
DOE OSTI2024

In-Situ Species Concentration Measurements in Ammonia-Mix Flames Using FTIR Spectroscopy

Hydrogen and ammonia represent two carbon-free fuel sources that could be used in place of current fossil energy sources in combustion systems. To develop optimized ammonia combustion systems, validated modeling tools are needed. In the open literature, it has been shown that the complex chemistry associated with fuel-bound nitrogen contained in ammonia differs greatly from natural gas or hydrogen combustion. As a result, several new chemical kinetic mechanisms have been developed. Many of these mechanisms have been validated experimentally, however this has primarily focused on bulk parameters such as laminar flame speed and ignition delay time. Critically, high quality measurements of species concentrations are needed under controlled conditions which are easily represented by simple models. In this paper, direct, in-situ measurements of species concentrations and gas temperature are performed in a laminar flat-flame burner. This arrangement enables comparison with 1D model predictions, better isolating chemical kinetics from the fluid dynamics. Quantitative species concentrations are determined by absorption spectroscopy using an FTIR spectrometer. Fuel compositions representative of cracked ammonia (NH3/H2) and ammonia-natural gas (NH3/CH4) are considered for rich and lean equivalence ratios. A major focus of the paper is on the selection of spectral features for nitric oxide and ammonia and correcting for large amounts of baseline H2O absorption.

Bedick, Clinton↗
DOE OSTI2020

LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure

A single-molecule three-dimensional (3D) structure is essential for understanding the thermal vibrations and dynamics as well as the conformational changes during the chemical reaction of macromolecules. Individual-particle electron tomography (IPET) is an approach for obtaining a snap-shot 3D structure of an individual macromolecule particle by aligning the tilt series of electron tomographic (ET) images of a targeted particle through a focused iterative 3D reconstruction method. The method can reduce the influence on the 3D reconstruction from large-scale image distortion and deformation. Due to the mechanical tilt limitation, 3D reconstruction often contains missing-wedge artifacts, presented as elongation and an anisotropic resolution. Here, we report a post-processing method to correct the missing-wedge artifact. This low-tilt tomographic reconstruction (LoTToR) method contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dynamic Surface Restructuring in Cu(Au) Alloys Driven by Oxygen-Mediated Au Mobility

Alloying plays a crucial role in tuning the surface properties of metals, but the atomic-level mechanisms by which alloying elements influence surface structure dynamics under reactive conditions remain elusive. Using Cu(Au) in oxidizing environments as a model system, we reveal a dynamic oxygen-induced transformation of the topmost atomic layer into a periodically hill-and-valley morphology with reversible switching between undulated and flattened surface states. These interconversions are driven by the retreat of surface Au to the subsurface during oxygen adsorption and its resegregation to the surface upon oxygen desorption. This cyclical mobility establishes a feedback loop, allowing the surface to dynamically reconfigure in response to changes in the oxygen pressure. The results offer a broadly applicable framework for understanding atomic-scale surface restructuring in alloy systems, where differences in the chemical reactivity of alloying elements drive dynamic redistribution between surface and subsurface regions. As a result, this dynamic coupling has practical implications for designing corrosion-resistant coatings and metastable nanostructures with tunable catalytic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRSDate not supplied

An Examination of Autumn Southern Polar Ozone Tendencies and the Residual Circulation in MERRA-2 Products

Changes in lower stratospheric ozone caused by dynamical transport can be difficult to characterize and thus are sometimes difficult to distinguish from chemical losses. Correlations between ozone changes and various dynamical proxies (e.g., the eddy heat flux) from year to year can be of interest, but they do little in themselves to explain the ozone transport mechanisms behind such correlations. In this study, we use products from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) to calculate the ozone mass flux, integrating it in space and time over the upper tropospheric/lower stratospheric Southern polar cap during periods when little chemical loss is expected. The ozone mass flux is expressed in terms of components of the residual circulation of the Transformed Eulerian Mean (TEM, i.e., 𝑣𝑣̅ ∗and 𝑤𝑤(∗) as well as eddy mixing terms. We relate these terms to the local ozone mass tendency ("#! "$ ), similarly integrated, and we find that the interannual variability of the ozone changes are strongly related to the residual meridional circulation and the meridional eddy mixing terms. These directly calculated dynamical transport terms provide clearer ozone proxies. Removing these advective terms from a long-term ozone time series can more effectively reveal ozone variations and long-term trends, specifically those caused by photochemical production and losses (e.g., human-produced ozone depletion).

Ozone↗
NASA NTRS2013

Improved Understanding of the Modeled QBO Using MLS Observations and MERRA Reanalysis

The Quasi-Biennial Oscillation (QBO) dominates the variability of the tropical stratosphere on interannual time scales. The QBO has been shown to extend its influence into the chemical composition of this region through dynamical mechanisms. We have started our analysis using the realistic QBO internally generated by the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 33 years. We will show targeted comparisons with observations from NASAs Aura satellite Microwave Limb Sounder (MLS) and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis to provide insight into the simulation of the primary and secondary circulations associated with the QBO. Using frequency spectrum analysis and multiple linear regression we can illuminate the resulting circulations and deduce the strengths and weaknesses in their modeled representation. Inclusion of the QBO in our simulation improves the representation of the subtropical barriers and overall tropical variability. The QBO impact on tropical upwelling is important to quantify when calculating trends in sub-decadal scale datasets.

MERRA↗
DOE OSTI2022

Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics

Ab initio molecular dynamics (AIMD) has become one of the most popular and robust approaches for modeling complicated chemical, liquid, and material systems. However, the formidable computational cost often limits its widespread application in simulations of the largest-scale systems. Furthermore, the situation becomes even more severe in cases where the hydrogen nuclei may be better described as quantized particles using a path integral representation. Here, we present a computational approach that combines machine learning with recent advances in path integral contraction schemes, and we achieve a 2 orders of magnitude acceleration over direct path integral AIMD simulation while at the same time maintaining its accuracy.

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

Dynamic Motions of Topological Defects in Nematic Liquid Crystals under Spatial Confinement

Abstract Topological defects (TDs) have become a sensational topic due to their significant influence on the unusual optical and physiochemical characteristics of the material. To facilitate their application across a wide range of disciplines it is desirable to analyze and gain fundamental understanding of TDs in both equilibrium and nonequilibrium systems. Liquid crystals (LCs) are considered an ideal system for study given the direct visualization of TDs and a straightforward analyzation process. In addition to the equilibrium morphology of LC TDs, it is also of great interest to track and control the formation and annihilation of defects during thermodynamic processes. However, controlling the dynamic behavior of formed defects remains a challenge. Here, nematic LCs confined in a cell exhibiting surfaces with periodic anchoring conditions containing surface topography are relied on. The effects of patterned surface characteristics such as width, periodicity, and degree of curvature on defects dynamic motion, stabilization, and annihilation are explored. The computational experiments recapitulate the TDs transition path and provide free energy‐based predictions of critical distances for defect annihilation. Taken together, this simple approach offers a promising opportunity to control the dynamics of TDs in LCs through chemical patterned surfaces with topography.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Detailed Multidimensional Simulations of the Structure and Dynamics of Flames

Numerical simulations in which the various physical and chemical processes can be independently controlled can significantly advance our understanding of the structure, stability, dynamics and extinction of flames. Therefore, our approach has been to use detailed time-dependent, multidimensional, multispecies numerical models to perform carefully designed computational experiments of flames on Earth and in microgravity environments. Some of these computational experiments are complementary to physical experiments performed under the Microgravity Program while others provide a fundamental understanding that cannot be obtained from physical experiments alone. In this report, we provide a brief summary of our recent research highlighting the contributions since the previous microgravity combustion workshop. There are a number of mechanisms that can cause flame instabilities and result in the formation of dynamic multidimensional structures. In the past, we have used numerical simulations to show that it is the thermo-diffusive instability rather than an instability due to preferential diffusion that is the dominant mechanism for the formation of cellular flames in lean hydrogen-air mixtures. Other studies have explored the role of gravity on flame dynamics and extinguishment, multi-step kinetics and radiative losses on flame instabilities in rich hydrogen-air flames, and heat losses on burner-stabilized flames in microgravity. The recent emphasis of our work has been on exploring flame-vortex interactions and further investigating the structure and dynamics of lean hydrogen-air flames in microgravity. These topics are briefly discussed after a brief discussion of our computational approach for solving these problems.

Patnaik, G.↗
DOE OSTI2020

Large Exciton Diffusion Coefficients in Two Dimensional Covalent Organic Frameworks with Different Domain Sizes Revealed by Ultrafast Exciton Dynamics

Large singlet exciton diffusion lengths are a hallmark of high performance in organic-based devices such as photovoltaics, chemical sensors, and photodetectors. In this study, exciton dynamics of a two-dimensional covalent organic framework, 2D COF-S, is investigated using ultrafast spectroscopic techniques. After photoexcitation, the COF-S exciton decays via three pathways: (1) excimer formation (4 +/- 2 ps), (2) excimer relaxation (160 +/- 40 ps), and (3) excimer decay (>3 ns). Excitation fluence-dependent transient absorption studies suggest that COF-5 has a relatively large diffusion coefficient (0.08 cm(2)/s). Furthermore, exciton-exciton annihilation processes are characterized as a function of COF-S crystallite domain size in four different samples, which reveal domain-size-dependent exciton diffusion kinetics. These results reveal that exciton diffusion in COF-S is constrained by its crystalline domain size. These insights indicate the outstanding promise of delocalized excitonic processes available in 2D COFs, which motivate their continued design and implementation into optoelectronic devices.

Flanders, Nathan C.↗
NASA NTRS1991

The Upper Atmosphere Research Satellite (UARS) - An overview

UARS is designed to provide the most extensive data base ever obtained on the coupled energy input, chemistry, and dynamics of the earth's upper atmosphere to increase enormously the current understanding of the upper atmosphere and to improve assessments of the depletion of stratospheric ozone caused by human activities. The UARS mission, observatory, and investigations are described. The UARS experimental investigations consist of energy input experiments, chemical species and temperature experiments, and dynamics experiments. Two instruments measure solar UV energy input while another measures energetic particle energy input and associated X-radiation emission from the atmosphere. Four instruments address chemical concentrations, and two make direct measurements of upper atmosphere winds.

Mcneal, Robert J.↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
DOE OSTI2023

Time-resolving state-specific molecular dissociation with XUV broadband absorption spectroscopy

The electronic and nuclear dynamics inside molecules are essential for chemical reactions, where different pathways typically unfold on ultrafast timescales. Extreme ultraviolet (XUV) light pulses generated by free-electron lasers (FELs) allow atomic-site and electronic-state selectivity, triggering specific molecular dynamics while providing femtosecond resolution. Yet, time-resolved experiments are either blind to neutral fragments or limited by the spectral bandwidth of FEL pulses. Here, we combine a broadband XUV probe pulse from high-order harmonic generation with an FEL pump pulse to observe dissociation pathways leading to fragments in different quantum states. We temporally resolve the dissociation of a specific O 2 + state into two competing channels by measuring the resonances of ionic and neutral fragments. This scheme can be applied to investigate convoluted dynamics in larger molecules relevant to diverse science fields.

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

Determination of the chemical shift tensor anisotropy and asymmetry of strongly dipolar coupled protons under fast MAS

Orientationally-dependent interactions such as dipolar coupling, quadrupolar coupling, and chemical shift anisotropy (CSA) contain a wealth of spatial information that can be used to elucidate molecular conformations and dynamics. To determine the sign of the chemical shift tensor anisotropy parameter (δ aniso ), both the |m| = 1 and |m| = 2 components of the CSA need to be symmetry allowed, while the recoupling of the |m| = 1 term is accompanied with the reintroduction of homonuclear dipolar coupling components. Therefore, previously suggested sequences which solely recouple the |m| = 2 term cannot determine the sign a 1 H's δ aniso in a densely-coupled network. Here, we demonstrate the CSA recoupling of strongly dipolar coupled 1 H spins using the $Cn^1_n (90_{0}360_{180}540_{0}360_{180}90_{0})$ sequence. This pulse scheme recouples both the |m| = 1 and |m| = 2 CSA terms but the scaling factors for the homonuclear dipolar coupling terms are zeroed. Consequently, the sequence is sensitive to the sign of δ aniso but is not influenced by homonuclear dipolar interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗