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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 307 records · Page 17

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

Simulations of carbon dioxide (CO 2 ) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO 2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. Here, we show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Atom Clusters on AuCu Nanoparticle Surface During CO Oxidation

Supported alloy nanoparticles are prevailing alternative low-cost catalysts for both heterogeneous and electrochemical catalytic processes. Selective interaction of an alloy component with a specific reactant induces a dynamic structural change of alloy nanoparticles under reaction conditions and largely controls their catalytic properties. However, such a multi-component dynamic-interaction-controlled evolution, both structural and chemical, remains far from clear. Herein, by using state-of-the-art environmental TEM, we directly visualize, in-situ at the atomic scale, the evolution of an AuCu alloy nanoparticle supported on CeO2 during CO oxidation. We find that gas molecules can “free” metal atoms on the {001} surface and form highly mobile atom clusters. Remarkably, we discover that CO exposure induces Au segregation and activation on nanoparticle surface, while O2 exposure leads to the segregation and oxidation of Cu on the particle surface. The as-formed Cu2O/AuCu interface may facilitate CO-O interaction corroborated by DFT calculations. These findings provide insights into the atomistic mechanisms on alloy nanoparticles during catalytic CO oxidation reaction, and to a broad scope of rational design of alloy nanoparticle catalysts.

Luo, Langli↗

Surface chemistry models for GaAs epitaxial growth and hydride cracking using reacting flow simulations

Hydride vapor phase epitaxy (HVPE) is a promising technology that can aid in the cost reduction of III-V materials and devices manufacturing, particularly high-efficiency solar cells for space and terrestrial applications. However, recent demonstrations of ultrafast growth rates (~500 µm/h) via uncracked hydrides are not well described by present models for the growth. Therefore, it is necessary to understand the kinetics of the growth process and its coupling with transport phenomena, so as to enable fast and uniform epitaxial growth. In this work, we derive a kinetic model using experimental data and integrate it into a computational fluid dynamics simulation of an HVPE growth reactor. We also modify an existing hydride cracking model that we validate against numerical simulations and experimental data. Here, we show that the developed growth model and the improved cracking model are able to reproduce experimental growth measurements of GaAs in an existing HVPE system.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Development of toughened epoxy polymers for high performance composite and ablative applications

A survey of current procedures for the assessment of state of cure in epoxy polymers and for the evaluation of polymer toughness as related to nature of the crosslinking agent was made to facilitate a cause-effect study of the chemical modification of epoxy polymers. Various conformations of sample morphology were examined to identify testing variables and to establish optimum conditions for the selected physical test methods. Dynamic viscoelasticity testing was examined in conjunction with chemical analyses to allow observation of the extent of the curing reaction with size of the crosslinking agent the primary variable. Specifically the aims of the project were twofold: (1) to consider the experimental variables associated with development of "extent of cure" analysis, and (2) to assess methodology of fracture energy determination and to prescribe a meaningful and reproducible procedure. The following is separated into two categories for ease of presentation.

Allen, V. R.↗

Laser diagnostics of photochemistry and reaction dynamics

Experiments will be described which illustrate how tunable dye lasers are used to determine the quantum state distributions of the free radicals that are produced in photochemical systems. Other experiments will be described to show how lasers can be used to accurately measure the effects of internal energy upon the rate of chemical reactions.

Jackson, W. M.↗

Experimental and computational investigations of ethane and ethylene kinetics with copper oxide particles for Chemical Looping Combustion

In this work, reaction pathways for the oxidation of methane, ethane, and ethylene with CuO was obtained by ReaxFF Molecular Dynamics (MD) simulations between temperatures of 1000 K and 2000 K. Experiments in a fixed-bed flow reactor were preformed with methane, ethane, and ethylene at temperatures ranging from 500 K to 1000 K with time-dependent species measurements from an Electron-Ionization Molecular Beam Mass Spectrometer (MBMS), and species validation with Gas Chromatography (GC) for detection of complete and intermediate combustion products. The MBMS and GC allow for the detection of oxygenated species and larger species produced from radical reformation. The simulation and experiment agree on the production of such species as CH 3 CHO, CH 2 O, CO, and H 2 O, which allow for the creation of simple C1 and C2 reaction pathways, which can be used in kinetic models of C2 species and larger fuels such as biofuels, which inherently depend on C1 and C2 kinetics and reaction pathway. The simulation and experiment disagree on the formation of C 2 H 2 , CH 3 OH, and CO 2 with large amounts of C 2 H 2 being measured in the ethylene oxidation simulations and CH 3 OH being formed in methane oxidation simulations, while neither species were experimentally found. In the case of CO 2 large amounts of CO 2 are rapidly produced in experiments with C2 fuels at 800 K, while little-to-no CO 2 was observed in simulations. This is believed to be resulting from the extremely short timescale of the simulations, preventing total oxidation of the fuel. Here, the differences in products produced between simulation and experiment allow for the potential to modify the ReaxFF potential functions to more accurately model the experimental products of Cu–H–O–C reaction kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nuclear–Electronic Orbital Quantum Mechanical/Molecular Mechanical Real-Time Dynamics

Simulating the nuclear–electronic quantum dynamics of large-scale molecular systems in the condensed phase is key for studying biologically and chemically important processes such as proton transfer and proton-coupled electron transfer reactions. Herein, the real-time nuclear–electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) approach is combined with a hybrid quantum mechanical/molecular mechanical (QM/MM) strategy to enable the accurate description of coupled nuclear–electronic quantum dynamics in the presence of heterogeneous environments such as solvent or proteins. The densities of the electrons and quantum protons are propagated in real time, while the other nuclei are propagated classically on the instantaneous electron–proton vibronic surface. This approach is applied to phenol bound to lysozyme, intramolecular proton transfer in malonaldehyde, and nonequilibrium excited-state intramolecular proton transfer in o-hydroxybenzaldehyde. Furthermore, these examples illustrate that the RT-NEO-TDDFT framework, coupled with an atomistic representation of the environment, allows the simulation of condensed-phase systems that exhibit significant nuclear quantum effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

Tracking the ultraviolet-induced photochemistry of thiophenone during and after ultrafast ring opening

Photoinduced isomerization reactions lie at the heart of many chemical processes in nature. The mechanisms of such reactions are determined by a delicate interplay of coupled electronic and nuclear dynamics occurring on the femtosecond scale, followed by the slower redistribution of energy into different vibrational degrees of freedom. In this study, we apply time-resolved photoelectron spectroscopy with a seeded extreme ultraviolet free-electron laser to trace the ultrafast ring opening of gas-phase thiophenone molecules following ultraviolet photoexcitation. When combined with ab initio electronic structure and molecular dynamics calculations of the excited- and ground-state molecules, the results provide insights into both the electronic and nuclear dynamics of this fundamental class of reactions. The initial ring opening and non-adiabatic coupling to the electronic ground state are shown to be driven by ballistic S–C bond extension and to be complete within 350 fs. Theory and experiment also enable visualization of the rich ground-state dynamics that involve the formation of, and interconversion between, ring-opened isomers and the cyclic structure, as well as fragmentation over much longer timescales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards a generalized computational fluid dynamics technique for all Mach numbers

Currently there exists no single unified approach for efficiently and accurately solving computational fluid dynamics (CFD) problems across the Mach number regime, from truly low speed incompressible flows to hypersonic speeds. There are several CFD codes that have evolved into sophisticated prediction tools with a wide variety of features including multiblock capabilities, generalized chemistry and thermodynamics models among other features. However, as these codes evolve, the demand placed on the end user also increases simply because of the myriad of features that are incorporated into these codes. In order for a user to be able to solve a wide range of problems, several codes may be needed requiring the user to be familiar with the intricacies of each code and their rather complicated input files. Moreover, the cost of training users and maintaining several codes becomes prohibitive. The objective of the current work is to extend the compressible, characteristic-based, thermochemical nonequilibrium Navier-Stokes code GASP to very low speed flows and simultaneously improve convergence at all speeds. Before this work began, the practical speed range of GASP was Mach numbers on the order of 0.1 and higher. In addition, a number of new techniques have been developed for more accurate physical and numerical modeling. The primary focus has been on the development of optimal preconditioning techniques for the Euler and the Navier-Stokes equations with general finite-rate chemistry models and both equilibrium and nonequilibrium thermodynamics models. We began with the work of Van Leer, Lee, and Roe for inviscid, one-dimensional perfect gases and extended their approach to include three-dimensional reacting flows. The basic steps required to accomplish this task were a transformation to stream-aligned coordinates, the formulation of the preconditioning matrix, incorporation into both explicit and implicit temporal integration schemes, and modification of the numerical flux formulae. In addition, we improved the convergence rate of the implicit time integration schemes in GASP through the use of inner iteration strategies and the use of the GMRES (General Minimized Resisual) which belongs to the class of algorithms referred to as Krylov subspace iteration. Finally, we significantly improved the practical utility of GASP through the addition of mesh sequencing, a technique in which computations begin on a coarse grid and get interpolated onto successively finer grids. The fluid dynamic problems of interest to the propulsion community involve complex flow physics spanning different velocity regimes and possibly involving chemical reactions. This class of problems results in widely disparate time scales causing numerical stiffness. Even in the absence of chemical reactions, eigenvalue stiffness manifests itself at transonic and very low speed flows which can be quantified by the large condition number of the system and evidenced by slow convergence rates. This results in the need for thorough numerical analysis and subsequent implementation of sophisticated numerical techniques for these difficult yet practical problems. As a result of this work, we have been able to extend the range of applicability of compressible codes to very low speed inviscid flows (M = .001) and reacting flows.

Walters, R. W.↗

The Influence of Material Characterization on Thermal Loads Development and Flight Vehicle Design

The thermal management team faces a significant challenge to meet the aggressive thermal loading associated with hypersonic flight. Design strategies require the involvement of many engineering disciplines, as each must design their respective subsystem and then interface with all remaining subsystems to successfully close the vehicle design space. High fidelity thermal solid models will capture the variation in material properties and the effects of chemical reactions associated with hypersonic flight. Selection of the best materials for the mission will be based upon computational fluid dynamics and thermal modeling results. To enhance the probability for success, it is recommended that frequent communication occur between the thermal modeler and the materials scientist regarding design strategies and modeling assumptions. Early in the design process, lower fidelity modeling will be used to narrow the trade space. As promising designs are found, greater fidelity in the modeling process will be required to address more of the flowfield challenges and the material performance under the prescribed flight profile. The end goal is to select the most technically sound and physically advantageous material for the mission while avoiding overdesigning the vehicle due to modeling or material uncertainties. This presentation seeks to give an overview of the key thermal parameters that are affected through materials engineering, the interactions between a thermal engineer and other disciplines, and an example of the thermal design process, the X-43.

hypersonic↗

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as the chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate the activation of methane under realistic operando conditions. Our analysis reveals that methane dissociation occurs predominantly at step-edge nickel atoms. As CH x (where x = 3 or 4) species bind to additional surface nickel atoms, their reduced mobility leads to entropic penalties that suppress certain configurations and transition states. This is reflected in the underlying free energy surfaces, where configurations such as methyl binding to hollow sites and activation routes involving two nickel atoms become unfavorable as temperature increases. At elevated temperatures, methane activation extends from step-edge sites to terrace regions because of reduced free-energy barriers and enhanced surface dynamics. By decomposing the free-energy into enthalpic and entropic contributions, we uncover temperature-dependent shifts in the preferences of methane for the relevant active sites and arrive at a detailed molecular picture of methane activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photo-excitation of long-lived transient intermediates in ultracold reactions

In many chemical reactions, the transformation from reactants to products is mediated by transient intermediate complexes. For gas-phase reactions involving molecules with a few atoms, these complexes typically live on the order of 10 ps or less before dissociating, and are therefore rarely influenced by external processes. Here, we demonstrate that the transient intermediate complex K 2 Rb 2 *, formed from collisions between ultracold KRb molecules, undergoes rapid photo-excitation in the presence of a continuous-wave laser source at 1,064 nm, a wavelength commonly used to confine ultracold molecules. These excitations are facilitated by the exceptionally long lifetime of the complex under ultracold conditions. Indeed, by monitoring the change in the complex population after the sudden removal of the excitation light, we directly measure the lifetime of the complex to be 360 ± 30 ns, in agreement with our calculations based on the Rice–Ramsperger–Kassel–Marcus (RRKM) statistical theory. Furthermore, our results shed light on the origin of the two-body loss widely observed in ultracold molecule experiments. Additionally, the long complex lifetime, coupled with the observed photo-excitation pathway, opens up the possibility to spectroscopically probe the structure of the complex with high resolution, thus elucidating the reaction dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen irradiation-driven computational surface chemistry of lithium oxide and hydroxide

We have investigated, using molecular dynamics, the surface chemistry of hydrogen incident on the amorphous and crystalline lithium oxide and lithium hydroxide surfaces upon being slowed down by a collision cascade and retained in the amorphous surface of either Li 2 O or LiOH. We looked for the bonding of H to the resident structures in the surface to understand a possible chain of chemical reactions that can lead to surface transformation upon H atom impact. Our findings, using Density-Functional Theory (DFT) trained ReaxFF force field/electronegativity equalization method potentials, stress the importance of inclusion of polarization in the dynamics of a Li–O–H system, which is also illustrated by DFT energy minimization and quantum–classical molecular dynamics using tight binding DFT. The resulting polar-covalent chemistry of the studied systems is complex and very sensitive to the instantaneous positions of all atoms as well as the ratio of concentrations of various resident atoms in the surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled chemical–CFD modeling of unsealed dry storage of advanced test reactor spent fuel

We report given the current lack of long-term disposal for spent nuclear fuel storage in the United States, the current inventory of advanced test reactor (ATR) fuel at Idaho National Laboratory (INL) is expected to be stored in a dry storage facility for an extended storage period. As part of an effort to understand the conditions during a 50-year period, a three-dimensional computational fluid dynamics (CFD) of the unsealed canisters packed with spent fuel in the storage facility was constructed, this CFD model is coupled with radiolytic chemical reactions associated with water vapor and other species. The coupled model is simulated over a range of sensitivity parameters for the fuel decay heat, relative humidity, and oxyhydroxide film thickness for undried and fully-dried fuel. The most important parameter was the initial fuel decay heat. Over the range of cases, the hydrogen and nitric acid concentrations are low enough no significant impact is expected.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions

Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Actuating Liquid Crystals Rapidly and Reversibly by Using Chemical Catalysis

Abstract Microtubules and catalytic motor proteins underlie the microscale actuation of living materials, and they have been used in reconstituted systems to harness chemical energy to drive new states of organization of soft matter (e.g., liquid crystals (LCs)). Such materials, however, are fragile and challenging to translate to technological contexts. Rapid (sub‐second) and reversible changes in the orientations of LCs at room temperature using reactions between gaseous hydrogen and oxygen that are catalyzed by Pd/Au surfaces are reported. Surface chemical analysis and computational chemistry studies confirm that dissociative adsorption of H 2 on the Pd/Au films reduces preadsorbed O and generates 1 ML of adsorbed H, driving nitrile‐containing LCs from a perpendicular to a planar orientation. Subsequent exposure to O 2 leads to oxidation of the adsorbed H, reformation of adsorbed O on the Pd/Au surface, and a return of the LC to its initial orientation. The roles of surface composition and reaction kinetics in determining the LC dynamics are described along with a proof‐of‐concept demonstration of microactuation of beads. These results provide fresh ideas for utilizing chemical energy and catalysis to reversibly actuate functional LCs on the microscale.

Chemistry↗