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Results for “Chemical Dynamics Initiative”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

UQ4QM: Uncertainty Quantification for Quantum Materials (Chemical Dynamics Initiative Final Report)

The Uncertainty Quantification for Quantum Materials (UQ4QM) LDRD project focused on developing solutions for strategic two project areas the Chemical Dynamics Initiative (CDi) Use Case 3. This included data-driven approaches toward understanding heterogeneous data, such as multi-fidelity data or data with unknown spatial or temporal perturbations. The applications were varied but the project aims pursued solutions which were amenable to common UQ approaches in order to maximize impact.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ambient Tip-Enhanced Photoluminescence with 5 nm Spatial Resolution

We achieve record spatial resolution in ambient tip-enhanced photoluminescence (TEPL) from CdSe/ZnS semiconductor quantum dots (QDs). Our approach only takes advantage of surface roughness at the apex of a sputtered plasmonic gold probe. When irradiated with visible light (633 and 532 nm lasers), nano-corrugated regions of the apex of an Au tip support 5-nm spatial resolution in TEPL imaging of QD aggregates on silicon. The reproducibility of our observations is illustrated using different plasmonic probes and samples. The origin of the observed near-field contrast, underlying the demonstrated high spatial resolution in TEPL, is discussed in the context of field enhancement at the metal tip-fluorophore interface.

Chemical Dynamics Initiative↗
DOE OSTI2022

Predicting initial dissolution rates using structural features from molecular dynamics simulations

Predicting chemical durability of glass materials is important for various applications from daily life such as drink glass and kitchen ware to advanced technologies such as nuclear waste disposal and biomedicine. In this work, we explored prediction of initial dissolution rate through structural features from molecular dynamics (MD) simulations for a wide range of glass compositions (total 28) including borosilicate and aluminosilicate glasses, ZrO 2 -containing and V 2 O 5 -containing boroaluminosilicate glasses. The initial dissolution rates (r 0 ) measured experimentally at 90 °C with varying solution conditions were correlated with structural features (e.g., polyhedral linkages and non-bridging oxygen species) obtained from MD simulations, either from this study or from literature. Since hydrolysis of the glass network through breaking of the network former linkages (e.g., Si-O-Si, Si-O-Al, etc.) is a critical step of network glass dissolution, the statistics of these linkages obtained from MD were correlated to r0 through linear regression, where the coefficient of determination (R 2 ) and root mean square error are found to be 0.949 and 0.681, respectively. This model was compared and discussed with existing models developed by various approaches including machine learning, the kinetic rate equation, topological constraint theory, and other descriptors from MD simulations. The discussion provides insights on future model improvements to predict glass dissolution. In addition, the impact of V 2 O 5 on the glass dissolution was examined in detail, implicating that the impact is not the same across all glass compositions and test conditions.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Chemistry in dynamically evolving clouds

A unified model of chemical and dynamical evolution of isolated, initially diffuse and quiescent interstellar clouds is presented. The model uses a semiempirically derived dependence of the observed cloud temperatures on the visual extinction and density. Even low-mass, low-density, diffuse clouds can collapse in this model, because the inward pressure gradient force assists gravitational contraction. In contrast, previous isothermal collapse models required the low-mass diffuse clouds to be unrealistically cold before gravitational contraction could start. Theoretically predicted dependences of the column densities of various atoms and molecules, such as C and CO, on visual extinction in diffuse clouds are in accord with observations. Similarly, the predicted dependences of the fractional abundances of various chemical species (e.g., CO, H2CO, HCN, HCO(+)) on the total hydrogen density in the core of the dense clouds also agree with observations reported to date in the literature. Compared with previous models of interstellar chemistry, the present model has the potential to explain the wide spectrum of chemical and physical properties of both diffuse and dense clouds with a common formalism employing only a few simple initial conditions.

Tarafdar, S. P.↗
NASA NTRS1993

Metallicity Gradients in Elliptical Galaxies

The study of metalicity gradients is an examination of the relics of the first epoch of star formation and, thus, another issue that metallicity gradients can address is the relationship between chemical and dynamical evolution during the initial phase of star formation.

elliptical galaxies photometry evolution formation↗
NASA NTRS1978

Molecular evolution of contracting clouds - Basic methods and initial results

The relationship between the dynamics of the interstellar gas and the thermal and chemical effects associated with interstellar molecules and dust is investigated. The evolution of a rather massive isolated initially diffuse cloud under self-gravity is studied, using the equations of hydrodynamics; only radial motions are considered, and the heat, chemical, and radiative-transfer equations are solved simultaneously with the hydrodynamic equations. The relevant chemistry is described along with the thermal model, the radiative-transfer process, and the numerical methods employed. Results for a contracting cloud are discussed in terms of the problem of initial conditions, the dynamical evolution of the cloud, its chemical and thermal evolution, time scales, and column densities. It is shown that the chemical evolution of a massive contracting diffuse cloud is sensitive to such physical properties as temperature and ion abundances, that warm and cool versions of a typical cloud evolve differently, and that the physical origin of this effect is the level of heating due to H2 formation on interstellar dust grains.

Gerola, H.↗
DOE OSTI2025

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗
DOE OSTI2021

Fourier-like Thermal Relaxation of Nanoscale Explosive Hot Spots

Hot spots are local regions of high temperature that are widely considered to govern explosive initiation. Hot spot dynamics rests on a delicate balance between heat generation due to chemical reactions and heat loss through thermal conduction, making accurate determinations of the conductivity under extreme conditions a key component of predictive explosive models. We develop here an approach to directly determine the thermal transport properties of explosive hot spots with realistic initial structures through a combination of molecular dynamics (MD) and diffusive heat equation (HEq) modeling. Effective thermal conductivity values are determined by fitting HEq models to MD predictions of long timescale hot spot relaxation. The approach is applied to model hot spots in the molecular crystalline explosive 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) for a range of shock strengths and two limiting cases for impact orientation. Isotropic and anisotropic HEq models yield similar results, despite TATB exhibiting some of the largest and most anisotropic thermal conductivity values for explosive near normal conditions. The conductivity is found to be a strong function of density, which parametrically captures dependence on temperature, pressure, and material state. The associated root-mean-square errors of the fitted HEq models are approximately 5% of MD predicted final equilibrium temperatures. Here, the conductivity values determined here for TATB hot spots are considerably larger than those used in a prior hot spot criticality study, which may significantly impact predictions for critical hot spot sizes. The approach provides a convenient foundation for determining the effective thermal conductivity for hot spot problems in other explosives and directly yields information on reasonable approximations that might be taken in higher-level models for those materials.

36 MATERIALS SCIENCE↗
NASA NTRS2002

The Role of Turbulence in Chemical and Dynamical Processes in the Near-Field Wake of Subsonic Aircraft

During this grant, covering the period from September 1998 to December 2001, we continued the investigation of the role of turbulent mixing in the wake of subsonic aircraft initiated in 1994 for NASA's Atmospheric Effects of Aviation Project. The goal of the research has been to provide sufficient understanding and quantitative analytical capability to assess the dynamical, chemical, and microphysical interactions in the near-field wake that have the greatest potential to influence the global atmospheric impact of the projected fleet of subsonic aircraft. Through large-eddy simulations we have shown that turbulence in the early wake dynamics can have a strong effect on both the ice microphysics of contrail evolution and on wake chemistry. The wake vortex dynamics are the primary determinant of the vertical extent of the contrail; this together with the local wind shear largely determines the horizontal extent. The fraction of the initial ice crystals surviving the wake vortex dynamics, their spatial distribution, and the ice mass distribution are all sensitive to the aircraft type, assumed initial ice crystal number, and ambient humidity and turbulence conditions. Our model indicates that there is a significant range of conditions for which a smaller aircraft such as a B737 produces as significant a persistent contrail as a larger aircraft such as a B747, even though the latter consumes almost five times as much fuel. Large-eddy simulations of the near wake of a B757 provided a fine-grained chemical-dynamical representation of simplified NOx - HOx chemistry in wakes of ages from a few seconds to several minutes. By sampling the simulated data in a manner similar to that of in situ aircraft measurements it was possible to provide a likely explanation for a puzzle uncovered in the 1996 SUCCESS flight measurements of OH and HO2 The results illustrate the importance of considering fluid dynamics effects in interpreting chemistry results when mixing rates and species fluctuations are large, and demonstrate the feasibility of using 3D unsteady LES with coupled chemistry to study such phenomena.

Lewellen, D. C.↗
NASA NTRSDate not supplied

Improving Regional Air Quality Forecasting Through Chemical Data Assimilation and Dynamic Emissions Adjustment

Poor air quality (AQ) is one of the most important human-health and environmental problems facing the United States (US). In addition to the detrimental impacts on human- and environmental-health, poor AQ has an economic cost of ~5% of the US gross domestic product (~$790 billion). AQ managers use AQ analyses and modeling to better understand, anticipate, and avoid poor AQ events. Our research focuses on improving AQ analysis/forecast skill, predictability, and emission estimates through improved and more efficient: (i) modeling and data assimilation strategies; (ii) dynamic emissions adjustment strategies; and (iii) use of satellite remote-sensing Earth observations (e.g., MOPITT, IASI, MODIS, OMI, TROPOMI, TEMPO, etc.). This seminar will review: (i) regional chemical weather forecasting/data assimilation with dynamic emissions adjustment with WRF-Chem/DART; (ii) strategies for efficiently assimilating satellite retrieval profiles with ‘compact phase space retrievals’ (CPSRs); (iii) results from joint assimilation of multiple satellite retrievals at medium (12 km × 12 km) and high (4 km × 4 km) spatial resolutions; and (iv) results from observing system simulation experiments (OSSEs) to investigate whether we can recover COVID-period anthropogenic emissions by assimilating synthetic TEMPO NO2 tropospheric column retrievals with dynamic emissions adjustment. Biographical Sketch: Dr. Mizzi is a Senior Research Fellow working and Dr. Johnson at the NASA Ames Research Center. He holds BA and MS degrees in Environmental Science from the University of Virginia, MS and PhD degrees in Applied Mathematics from the University of Colorado at Boulder (CUB), and a JD degree (with an emphasis in Environmental Law) from the University of Colorado School of Law. He worked at the National Center for Atmospheric Research for nearly 25 years on global atmospheric modeling, dynamic and physical initialization, regional hybrid data assimilation, and most recently on regional chemical data assimilation. He also worked as an environmental attorney and consultant for nearly 15 years. He is an expert in numerical modeling and is recognized internationally as a leading expert in regional, chemical data assimilation with dynamic emissions adjustment. Dr. Mizzi became affiliated with NASA Ames in March 2020 to work on improving AQ analysis/forecast skill, predictability, and ‘top-down’ emissions adjustment though the assimilation of Earth observations. An emphasis of his current work is developing methods for assimilating synthetic TEMPO retrievals to quantify the expected benefits of TEMPO relative to existing AQ observations.

Arthur P. Mizzi↗
DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

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

Crack nucleation and growth during dynamic indentation of chemically-strengthened glass

Dynamic point impact loading is a primary cause of fracture of glass screens on mobile devices. An improved understanding of crack initiation and evolution under high-speed indentation could contribute to the development of materials with better performance, but experimental observations are challenging due to the short timescales and limited depth-of-field of optical microscopy. To address this need, we have observed fracture of a chemically-strengthened glass during dynamic indentation using in situ x-ray phase-contrast imaging (XPCI). Median cracks initiate below the surface of the glass, at a depth approximately corresponding to the depth at which the surface residual compressive stress diminishes to zero. These cracks initially propagate at ~10ms –1 , rapidly accelerating to > 100ms –1 . We also observe some evidence for rate-dependent behavior, in that indentation at the lowest rates studied here (below about ~0.15ms –1 ) fails to initiate cracks regardless of the depth of the indentation (up to 18μm), while indentation at higher rates produces median cracks that either arrest or cause complete fracture, depending on the depth of indentation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The “Hole” Story in Ionized Water from the Perspective of Ehrenfest Dynamics

The radiolysis of liquid water and the radiation-matter interactions that happen in aqueous environments are important to the elds of chemistry, materials, and environmental sciences, as well as biological and physiological response to extreme conditions and medical treatments. The initial stage of radiolysis is the ultrafast response, or hole dynamics, that trigger chemical processes within complex energetic landscapes that may include reactivity. A fundamental understanding necessitates the use of theoretical methods that are capable of simulating both ultrafast coherence and non-adiabatic energy transfer pathways. In this work, we carry out an ab initio Ehrenfest dynamic study in order to provide a more complete description of the ultrafast dynamics and reactive events initiated by photoionization of water. Furthermore, after sudden ionization, the range of processes that include hole trapping and transfer, large OH oscillations, proton transfer and subsequent relay, formation of the metastable Zundel complex, and long-lived coherence, are identied and new insight into their driving forces are elucidated.

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

Site-specific generation of excited state wavepackets with high-intensity attosecond x rays

High-intensity attosecond x rays can produce coherent superpositions of valence-excited states through two-photon Raman transitions. The broad-bandwidth, high-field nature of the pulses results in a multitude of accessible excited states. Multiconfigurational quantum chemistry with the time-dependent Schrödinger equation is used to examine population transfer dynamics in stimulated x-ray Raman scattering of the nitric oxide oxygen and nitrogen K-edges. Two pulse schemes initiate wavepackets of different characters and demonstrate how chemical differences between core-excitation pathways affect the dynamics. The population transfer to valence-excited states is found to be sensitive to the electronic structure and pulse conditions, highlighting complexities attributed to the Rabi frequency. The orthogonally polarized two- color-pulse setup has increased selectivity while facilitating longer, less intense pulses than the one-pulse setup. Population transfer in the 1s → Rydberg region is more effective but less selective at the nitrogen K-edge; the selectivity is reduced by double core-excited states. Result interpretation is aided by resonant inelastic x-ray scattering maps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiscale Strategy for Predicting Radiation Chemistry in Polymers

A primary mode for radiation damage in polymers arises from ballistic electrons that induce electronic excitations, yet subsequent chemical mechanisms are poorly understood. We develop a multiscale strategy to predict this chemistry starting from subatomic scattering calculations. Nonadiabatic molecular dynamics simulations sample initial bond-breaking events following the most likely excitations, which feed into semiempirical simulations that approach chemical equilibrium. Application to polyethylene reveals a mechanism explaining the low propensity to cross-link in crystalline samples.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing reaction channels via reinforcement learning

Abstract Chemical reactions are dynamical processes involving the correlated reorganization of atomic configurations, driving the conversion of an initial reactant into a result product. By virtue of the metastability of both the reactants and products, chemical reactions are rare events, proceeding fleetingly. Reaction pathways can be modelled probabilistically by using the notion of reactive density in the phase space of the molecular system. Such density is related to a function known as the committor function, which describes the likelihood of a configuration evolving to one of the nearby metastable regions. In theory, the committor function can be obtained by solving the backward Kolmogorov equation (BKE), which is a partial differential equation (PDE) defined in the full dimensional phase space. However, using traditional methods to solve this problem is not practical for high dimensional systems. In this work, we propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths. By shooting multiple trajectories from these configurations, we can generate an ensemble of states that concentrate on the transition path ensemble. This configuration ensemble can be effectively employed in a neural network-based PDE solver to obtain an approximation solution of a restricted BKE, even when the dimension of the problem is very high. The resulting solution provides an approximation for the committor function that encodes mechanistic information for the reaction, paving a new way for understanding of complex chemical reactions and evaluation of reaction rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗