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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Vibrational Signatures of Electronic Properties in Renewable-Energy Catalysis

The objective of this research program is to discover and develop new approaches for ab initio computational simulations of molecular motion. Specifically, this program aims to decipher the connection between the underlying electronic structure and the accordant molecular vibrations in reactive ions and radicals for renewable-energy purposes. Recent experimental progress in ion sources and optical spectroscopies has unearthed considerable new inner-sphere detail for these complexes, but the connection between these spectral signatures and mechanistic information often remains elusive, to the continued frustration of experimentalists. For this purpose, new anharmonic vibrational frequency methods, along with a publicly deployed software package, will be developed. Working closely with committed experimental collaborators, this conceptual and computational framework will be used to explain the results of new spectroscopy experiments, focusing specifically on the inner-shell mechanisms of renewable-energy catalysis. The oxidation half of catalytic water-splitting chemistry will be a central focus, along with fundamental studies of the manner in which strong ions and radicals activate solvent as a chemical species. The resulting products of the research program will include openly available software and algorithms for the ab initio simulation of challenging vibrational spectra, as well as critical mechanistic insight into energy-focused catalytic processes that are opaque to other existing analytical techniques.

42 ENGINEERING↗
DOE OSTI2021

Chemical Preparation, Crystal Structure Reinvestigation and Vibrational Study of CoNa 3 P 3 O 10 ·12H 2 O and X-ray Characterization of the New Anhydrous Triphosphate CoNa 3 P 3 O 10

The triphosphate dodecahydrate of cobalt and sodium CoNa 3 P 3 O 10 ·12H 2 O was prepared by the ion exchange resin process. Its structure was studied by X-ray diffraction and determined in the monoclinic space group P12 1 /c1 with the unit-cell parameters a = 14.6650(5) Å, b=9.1916(3) Å, c = 15.0239(5) Å,β =90.2210(10)°, Z = 4 and V = 2025.13(12) Å 3 . The thermal dehydration of this compound was performed, leading to an anhydrous new form, CoNa 3 P 3 O 10 , which was characterized by X-ray diffraction. The obtained CoNa 3 P 3 O 10 crystallized in monoclinic space group P21/n with the unit-cell parameters a=15,3774 Å, b=7,6988 A°, c=14,2832A°, β=92,9115°. The characteristic IR wavenumbers of the P 3 O 10 5- ions observed in the vibrational spectra were calculated using isotopic substitutions, which confirms the existence of these groups in the studied compound. A comparison between the IR and Raman wavenumbers of CoNa 3 P 3 O 10 ·12H 2 O, CoNa 3 P 3 O 10 and Na 5 P 3 O 10 ·12H 2 was performed. A kinetic study was also made for CoNa 3 P 3 O 10 ·12H 2 O.

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

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Three-beam hybrid fs/ps coherent anti-Stokes Raman scattering of rotation–vibration non-equilibrium

In this work, we demonstrate time-resolved rotational and vibrational temperature measurements to probe plasma non-equilibrium through a simple three-beam hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) system. A single pump/Stokes pair is employed to generate both the pure-rotational and ro-vibrational Raman coherence. A novel phase-matching scheme, to our knowledge, is employed to spatially overlap the two CARS signals, simplifying the optical design and allowing signal selection by tuning a single spectrometer grating. Measurements were performed near the electrodes in a N 2 DC glow discharge. Both the rotational temperature and the vibrational populations up to $v$ = 8 were calculated from the separately measured single-shot pure-rotational and ro-vibrational CARS spectra. Strong rotation–vibration non-equilibrium was observed at both electrodes, with the cathode showing higher vibrational and rotational temperatures. In addition, non-Boltzmann behaviors were observed at both electrodes. This simplified approach enables measurements of rotational and vibrational temperatures with high spatial resolution in non-equilibrium flows.

42 ENGINEERING↗
DOE OSTI2025

High-Resolution Photoelectron Spectroscopy of NO3 – Vibrationally Excited Along Its ν3 Mode

The nitrate (NO3) radical has long been the subject of both experimental and theoretical studies due to its complex electronic structure resulting from vibronic interactions between its X̃2A2' and B̃2E' states. In particular, the definite assignment of the fundamental of its degenerate stretching vibration (ν3) is still under debate. Here, we report high-resolution photoelectron spectra of vibrationally pre-excited NO3- using the recently developed IR-cryo-SEVI technique. The anions are excited through infrared (IR) excitation near 1350 cm-1, accessing the ν3 and 2ν3(e') vibrational levels with band centers at 1350.5 and ∼2700 cm-1, respectively. The IR-cryo-SEVI spectrum for 2ν3 pre-excitation shows clear evidence for an intense 321 transition. From the position of this feature (30031 cm-1), the electron affinity of NO3 also determined in this work (31680 cm-1), and the IR excitation energy, we obtain a fundamental frequency of 1051 cm-1 for the ν3 fundamental of the NO3 radical. This assignment and other features in the IR-cryo-SEVI spectra are supported by spectral simulations based on a vibronic Köppel-Domcke-Cederbaum Hamiltonian. The simulations also show that nearly all features in the IR-cryo-SEVI spectra arise because of pseudo-Jahn-Teller coupling between the X̃ and B̃ states of NO3. The results and analysis presented here settle a long-standing controversy regarding the ν3 frequency of NO3.

Anions↗
DOE OSTI2020

Nonlinear spectroscopy in the condensed phase: The role of Duschinsky rotations and third order cumulant contributions

First-principles modeling of nonlinear optical spectra in the condensed phase is highly challenging because both environment and vibronic interactions can play a large role in determining spectral shapes and excited state dynamics. In this work, we compute two dimensional electronic spectroscopy (2DES) signals based on a cumulant expansion of the energy gap fluctuation operator, with specific focus on analyzing mode mixing effects introduced by the Duschinsky rotation and the role of the third order term in the cumulant expansion for both model and realistic condensed phase systems. We show that for a harmonic model system, the third order cumulant correction captures effects introduced by a mismatch in curvatures of ground and excited state potential energy surfaces, as well as effects of mode mixing. We also demonstrate that 2DES signals can be accurately reconstructed from purely classical correlation functions using quantum correction factors. We then compute nonlinear optical spectra for the Nile red and methylene blue chromophores in solution, assessing the third order cumulant contribution for realistic systems. We show that the third order cumulant correction is strongly dependent on the treatment of the solvent environment, revealing the interplay between environmental polarization and the electronic-vibrational coupling.

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

Bonding and Acidity of the Formal Hydride in the Prototypical Au 9 (PPh 3 ) 8 H 2+ Nanocluster

The role of hydrogen atoms as surface ligands on metal nanoclusters is of profound importance but remains difficult to directly study. While hydrogen atoms often appear to be incorporated formally as hydrides, evidence suggests that they donate electrons to the cluster's delocalized superatomic orbitals and may consequently behave as acidic protons that play key roles in synthetic or catalytic mechanisms. Here we directly test this assertion for the prototypical Au 9 (PPh 3 ) 8 H 2+ nanocluster, formed by addition of a hydride to the well-characterized Au 9 (PPh 3 ) 8 3+ . Using gas-phase infrared spectroscopy, we were able to unambiguously isolate Au 9 (PPh 3 ) 8 H 2+ and Au 9 (PPh 3 ) 8 D 2+ , revealing an Au–H stretching mode at 1528 cm –1 that shifts to 1038 cm –1 upon deuteration. This shift is greater than the maximum expected for a typical harmonic potential, suggesting a potential governing cluster-H bonding that has some square-well character consistent with the hydrogen nucleus behaving as a metal atom in the cluster core. Complexing this cluster with very weak bases reveals a redshift of 37 cm –1 in the Au–H vibration, consistent with those typically seen for moderately acidic groups in gas phase molecules and providing an estimate of the acidity of Au 9 (PPh 3 ) 8 H 2+ , at least with regard to its surface reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

Chemistry↗
DOE OSTI2023

Unraveling local structures of Salt-in-Water and Water-in-Salt electrolytes via ab initio molecular dynamics

Water-in-salt electrolytes (WiSE) are attractive for electrochemical energy storage applications owing to their wide electrochemical stability windows and inherent safety. The high concentration of salts is widely known to suppress the decomposition of water, which otherwise limits the stability of conventional aqueous salt-in-water electrolytes (SiWE). Nevertheless, the microstructural features of WiSE that lead to this enhanced stability have not yet been fully elucidated. In this work, ab initio molecular dynamics simulations were performed to study the energetic, structural, and spectroscopic properties of LiTFSI SiWE and WiSE solutions. A detailed mapping of water-water and water-anion hydrogen bonding and cation–anion electrostatic interactions is reported for both electrolytes. Structural features are presented in terms of both radial and spatial distribution functions. Analysis of IR and vibrational power spectra reveal key differences in the intermolecular interactions in SiWE and WiSE that arise from modified solvation shell structures. Finally, the results obtained herein reveal the most important structural and spectroscopic differences between the electrolytes in normal and superconcentrated concentrations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Evidence for Photoinduced Polaron Generation in a High Persistence Length Low Bandgap Conjugated Polymer in Solution

Using ultrafast time-resolved infrared (TRIR) spectroscopy, we studied the solution-phase excited-state structural evolution of an indacenodithiophene-co-benzothiadiazole polymer (C8-IDTBT). Following band gap excitation, the TRIR spectra reveal vibrational features that develop within 10 ps and decay over 4 ns. Using pulse radiolysis measurements, charge-modulation spectroscopy, and quantum-chemical calculations, the IR features are assigned to polaron pairs. Interestingly, these features appear on an evolving broad mid-IR electronic absorption background, with kinetics correlating with the formation and decay of the cationradical vibrational bands. A three-state kinetic model successfully reproduces the spectral evolution, revealing that the polaron and exciton populations exist in dynamic equilibrium on picosecond time scales, with time constants for exciton dissociation in the range of 3− 5 ps and polaron-to-exciton reformation between 20 and 100 ps, while both species decay to the ground state on much slower nanosecond time scales (∼1 ns), yielding a remarkably high polaron-generation efficiency, higher than 50%. These findings provide fundamental insights into intramolecular charge photogeneration mechanisms in conjugated polymers, demonstrating efficient bound-polaron formation in isolated polymer chains.

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

Multichannel dynamics in the OH+ n -butane reaction revealed by crossed-beam slice imaging and quasiclassical trajectory calculations

Multidimensional reactions present various channels that can exhibit very different dynamics and give products of varying subsequent reactivity. Here, we present a combination of experiment and theory to reveal the dynamics of hydrogen abstraction by OH radical at primary and secondary sites in n-butane at a collision energy of 8 kcal/mol. Crossed molecular beam slice imaging experiments unequivocally probe the secondary abstraction channel showing backward angular distributions with mild energy release to product translation, which are accurately captured by trajectory calculations using a specific-reaction-parameter Hamiltonian. Additionally, experiments containing both reaction channels indicate a less marked backward character in the angular distribution, whose origin is shown by trajectory calculations to appear as an evolution toward more sideways scattering from the secondary to primary channel. While the two channels have markedly different angular distributions, their energy release is largely comparable, showing ample energy release into the water product. The synergistic combination of crossed-beam imaging and trajectories opens the door to detailed reaction-dynamics studies of chemical reactions with ever-increasing complexity.

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

Hydration structure of flat and stepped MgO surfaces

We investigate the solvation structure of flat and stepped MgO(001) in neutral liquid water using ab initio molecular dynamics based on a hybrid density functional with dispersion corrections. Our simulations show that the MgO surface is covered by a densely packed layer of mixed intact and dissociated adsorbed water molecules in a planar arrangement with strong intermolecular H-bonds. The water dissociation fractions in this layer are >20% and >30% on the flat and stepped surfaces, respectively. Slightly above the first water layer, we observe metastable OH groups perpendicular to the interface, similar to those reported in low temperature studies of water monolayers on MgO. Here, these species receive hydrogen bonds from four nearby water molecules in the first layer and have their hydrophobic H end directed toward bulk water, while their associated protons are bound to surface oxygens. The formation of these OH species is attributed to the strong basicity of the MgO surface and can be relevant for understanding various phenomena from morphology evolution and growth of (nano)crystalline MgO particles to heterogeneous catalysis.

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

Liquid state properties of SEI components in dimethoxyethane

The solid-electrolyte interphase (SEI) layer is a critical constituent of battery technology, which incorporates the use of lithium metals. Since the formation of the SEI is difficult to avoid, the engineering and harnessing of the SEI are absolutely critical to advancing energy storage. One problem is that much fundamental information about SEI properties is lacking due to the difficulty in probing a chemically complex interfacial system. One such property that is currently unknown is the dissolution of the SEI. This process can have significant effects on the stability of the SEI, which is critical to battery performance but is difficult to probe experimentally. Here, we report the use of ab initio computational chemistry simulations to probe the solution state properties of SEI components LiF, Li 2 O, LiOH, and Li 2 CO 3 in order to study their dissolution and other solution-based characteristics. Ab initio molecular dynamics was used to study the solvation structures of the SEI with a combination of radial distribution functions, discrete solvation structure maps, and vibrational density of states, which allows for the determination of free energies. From the change in free energy of dissolution, we determined that LiOH is the most likely component to dissolve in the electrolyte followed by LiF, Li 2 CO 3 , and Li 2 O although none were favored thermodynamically. Furthermore, this indicates that dissolution is not probable, but Li 2 O would make the most stable SEI with regard to dissolution in the electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

General framework for quantifying dissipation pathways in open quantum systems. III. Off-diagonal subsystem–bath couplings

This paper extends the previously reported theory of dissipation pathways [C. W. Kim and I. Franco, J. Chem. Phys. 160, 214111 (2024)] to incorporate off-diagonal subsystem–bath coupling, which is often required to model molecular systems where the environment directly influences transitions and couplings between subsystem states. We systematically derive master equations for both population transfer and dissipation into individual bath components, for which we also rigorously prove energy conservation and detailed balance. The approach is based on second-order perturbation theory with respect to the subsystem–bath couplings, whose form is not limited to any specific model. The accuracy of the developed method is tested by applying it to diverse model Hamiltonians involving linearly coupled harmonic oscillator baths and comparing the outcomes against the hierarchical equations of motion (HEOM) method. Overall, our method accurately quantifies the contributions of specific bath components to the overall dissipation while significantly reducing the computational cost compared to numerically exact methods such as HEOM, thus offering a path to examine how vibronic interactions steer non-adiabatic processes in realistic chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗