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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Interplay of Gas-phase Reactions and Multi-phase Processes on Phase State and Growth Dynamics of Secondary Organic Aerosols

The formation, growth and evolution of secondary organic aerosols (SOA) are complex multiphase chemical processes, which represent one of the most challenging and demanding problems in research on atmospheric aerosol processes. The research goal of this project was to advance the fundamental understanding of the interplay between gas-phase chemistry and multiphase processes on phase state and growth dynamics of SOA for better predictivity of aerosol effects on climate and air quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Imaging Valence Electron Rearrangement in a Chemical Reaction Using Hard X-Ray Scattering

We have observed the signatures of valence electron rearrangement in photoexcited ammonia using ultrafast hard x-ray scattering. Time-resolved x-ray scattering is a powerful tool for imaging structural dynamics in molecules because of the strong scattering from the core electrons localized near each nucleus. Such core-electron contributions generally dominate the differential scattering signal, masking any signatures of rearrangement in the chemically important valence electrons. Ammonia represents an exception to the typically high core-to-valence electron ratio. Here, we measured 9.8 keV x-ray scattering from gas-phase deuterated ammonia following photoexcitation via a 200 nm pump pulse to the 3s Rydberg state. We observed changes in the recorded scattering patterns due to the initial photoexcitation and subsequent deuterium dissociation. Ab initio calculations confirm that the observed signal is sensitive to the rearrangement of the single photoexcited valence electron as well as the interplay between adiabatic and nonadiabatic dissociation channels. The use of ultrafast hard x-ray scattering to image the structural rearrangement of single valence electrons constitutes an important advance in tracking valence electronic structure in photoexcited atoms and molecules.

Gabalski, Ian [SLAC National Accelerator Laborator↗
DOE OSTI2024

A reactive electrochemomechanical theory for growth and remodeling of polyelectrolyte hydrogels and application to dynamic polymerization of $\text{DNA}$ hydrogels

Here this study develops a framework for growth and remodeling of active polyelectrolyte hydrogels that accounts for effects of compositional changes on the mechanical response. By developing a reactive electrochemomechanical theory, thermodynamical constraints upon reactive and remodeling processes are elucidated within a general framework that allows any number of chemical reactions to evolve the response of the gel and transfer mass and charge between constituents. Fully coupled, nonlinear constitutive relations are adopted for molar fluxes, allowing exploration of effects including cross-diffusion, electrophoresis, and electro-osmosis. A robust finite element implementation is developed in the open source FEBio software (febio.org) by exploiting an equivalence between electrochemomechanics and mixture theory. The implementation is verified against analytical solutions for free swelling, and a proper reduction to a prior chemomechanical theory is demonstrated for neutral gels swollen only by a solvent with no solutes. The theory and implementation are then applied to model the tunable large swelling achieved through dynamic polymerization of DNA crosslinkers seen in our recently developed experimental hydrogel system (Cangialosi et al., 2017). A novel constitutive model for reaction-driven evolution of the locking stretch λ L in a non-Gaussian mechanical free energy was developed, where the increasing concentration of DNA crosslinkers makes further swelling energetically favorable. With a single free parameter, excellent agreement was found between measured and predicted equilibrium swelling ratios. This study demonstrated the ability to extend the electrochemomechanical framework to include chemical reactions and composition-aware constitutive models, and showed that development of reactive models allows simulation of complex dynamic polymerization phenomena not treated before. The theoretical frame here can be further expanded in scope to incorporate additional non-ideal and nonlinear phenomena.

42 ENGINEERING↗
DOE OSTI2025

Probing exciton diffusion dynamics in photosynthetic supercomplexes via exciton–exciton annihilation

Photosynthesis converts solar energy into chemical energy through coordinated energy transfer between light-harvesting complexes and reaction centers (RCs). Understanding exciton motion, particularly the exciton diffusion length, is essential for optimizing energy efficiency in photosystems. In this work, we combine intensity-cycling transient absorption spectroscopy with kinetic Monte Carlo (kMC) simulation to investigate exciton motion in the C2S2 photosystem II supercomplex of spinach. Using exciton–exciton annihilation, revealed in the fifth-order response, we experimentally estimate an exciton diffusion length of 10.9 nm based on a 3D normal diffusion model, suggesting the ability of excitons to traverse the supercomplex. However, kMC simulations reveal that exciton motion is sub-diffusive because of spatial constraints and the strong RC traps. An anomalous diffusion model analysis of the experimental data yields a diffusion length of 9.7 nm, while the simulated diffusion length is 7.4 nm. The variable exciton residence time across subunits, partly influenced by their connectivity to the trap, indicates inhomogeneous annihilation probability and suggests how plants balance efficient light harvesting with photoprotection. We also explore the influence of specific assumptions in the annihilation simulation, which are challenging to access in more complex environments, such as the thylakoid membrane. Our study provides a framework for studying exciton dynamics using exciton–exciton annihilation, which can be extended to understand the light-harvesting efficiencies of larger, more complex photosynthetic assemblies.

Zhang, Kunyan (ORCID:000000026830409X)↗
DOE OSTI2023

Asynchronous domain dynamics and equilibration in layered oxide battery cathode

To improve lithium-ion battery technology, it is essential to probe and comprehend the microscopic dynamic processes that occur in a real-world composite electrode under operating conditions. The primary and secondary particles are the structural building blocks of battery cathode electrodes. Their dynamic inconsistency has profound but not well-understood impacts. In this research, we combine operando coherent multi-crystal diffraction and optical microscopy to examine the chemical dynamics in local domains of layered oxide cathode. Our results not only pinpoint the asynchronicity of the lithium (de)intercalation at the sub-particle level, but also reveal sophisticated diffusion kinetics and reaction patterns, involving various localized processes, e.g., chemical onset, reaction front propagation, domains equilibration, particle deformation and motion. These observations shed new lights onto the activation and degradation mechanisms of state-of-the-art battery cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2023

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↗
DOE OSTI2020

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2021

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↗
DOE OSTI2023

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↗
DOE OSTI2026

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↗
DOE OSTI2020

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↗
DOE OSTI2025

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↗
DOE OSTI2020

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↗
DOE OSTI2023

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↗
DOE OSTI2022

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↗