The fast multi-frame X-ray diffraction detector at the Dynamic Compression Sector
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Sinclair, N.W.↗
SEARCH · Engineering Papers
Results for “Dynamical”
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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Dynamics of plasma atomic layer etching: Molecular dynamics simulations and optical emission spectroscopy
Atomic layer etching is intrinsically dynamic as it involves sequential and repeated exposures of a surface to be etched with different species at different energies. The composition and structure of the near surface region change in both time and depth. Full understanding of this process requires resolving both temporal and spatial variations. In this work, we consider silicon (Si) atomic layer etching (ALE) by alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ). Molecular dynamics (MD) simulations are compared to experimental measurements with the aim of better understanding the dynamics of ALE and to test the simulation procedure. The simulations help to more fully interpret the experimental measurements. Further, optical emission measured just above the surface being etched can be related to etch products and can, therefore, be directly compared to simulation predictions. The simulations capture the measured initial product distribution leaving the surface and match the measured etch per cycle reasonably well. While simulations demonstrate the importance of ion-induced surface damage and mixing into a layer below the surface, the depth of which depends mainly on ion energy, the experiments suggest there is more Cl mixed into the layer than the MD procedure predicts.
74 ATOMIC AND MOLECULAR PHYSICS↗
Data Projection of the High Temperature Electrolysis System in the Dynamic Energy Transport and Integration Laboratory using Dynamic System Scaling
For nuclear power to be flexible in a functioning Integrated Energy System (IES), excess produced heat must be stored or utilized during times of low power demand to ensure a load factor of 1 while load balancing. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility that is under development to emulate IES conditions on the engineering-scale, planned to conduct virtual real time operations with industry-scale facilities, and is currently testing thermal storage and high temperature electrolysis. As part of the study to develop a method to preprocess input signals or postprocess output signals between systems of different scales via Dynamical System Scaling (DSS), the current research is one of the continued efforts branching from the data projection activity conducted for the Thermal Energy Distribution System and currently engages the High Temperature Electrolysis (HTE) System in DETAIL. The HTE SOEC electrical, fluid, and thermal dynamics Figure of Merits (FOM) were identified, governing equations and closure relations were successfully scaled, and relations between FOM scaling ratios were determined. Setting the scaling objectives to reform existing data to project a data set that doubly accelerated the electrolysis process while preserving the produced amount of hydrogen was generated for the full transient. The calculated boundary conditions were inlet temperature, stack current, and inlet steam mass flow rate at 1470 K, 121.1 A, and 1.886 g/s, respectively. The research outcomes demonstrated an output signal postprocessing case accelerating the hydrogen production without changing geometry, number of cells, and partial pressures.
08 HYDROGEN↗
Computational Fluid Dynamics Simulations of the Transonic Dynamics Tunnel Airstream Oscillator System
This paper presents a Computational Fluid Dynamics (CFD) model of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with the Airstream Oscillator System (AOS) in operation. The TDT is a continuous-flow, closed circuit wind tunnel with a 16- by 16-foot slotted test section with cropped corners. The tunnel was originally built as the 19-ft Pressure Tunnel in 1938, but it was converted to the current transonic tunnel in the 1950s, with capabilities to use either air or heavy gas (R-134a) as the test medium. The TDT was also fitted with an AOS which can be used to create a gust field in the test section. To date, no computational analyses of the TDT involving the AOS have been performed. In this study, experimental data acquired of an oscillating airstream in the tunnel will be used to calibrate the computational analyses. A significant motivation of this work is to attempt to compare computational gust velocities to those recorded in the TDT literature. In addition to a validation of this model with experimental data, it may also be possible to supplement the experimental data with computational data. The experimental data is rather sparse and at only a few Mach numbers. Computational results may be able to expand the AOS data set. Another motivation for this work is that the Integrated Adaptive Wing Technology Maturation (IAWTM) semi-span model of the high-aspect-ratio CRM with 10 trailing edge control surfaces is currently being fabricated and will be delivered to the NASA Langley Transonic Dynamics Tunnel (TDT) for testing in late 2020. Among tests to be conducted, gust load alleviation (GLA) will be demonstrated at transonic conditions using the AOS.
Computational Fluid Dynamics↗
Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition
Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.
Hanson, Joshua↗
Fast robust power system dynamic state estimation using model transformation
Not Available
Wang, Xueyuan↗
Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation
Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.
42 ENGINEERING↗
237 Np Mössbauer Isomer Shifts: A Lesson About the Balance of Static and Dynamic Electron Correlation in Heavy Element Complexes
A large set of neptunium compounds with different oxidation states (III to VII) was assembled to study the Mössbauer isomer shift by wave function calculations and better understand covalency in f-elements complexes. The contact density approach was used to calculate the isomer shift using complete active space self-consistent field (CASSCF) multiconfiguration wave functions, as well as matrix product states [from Density Matrix Renormalization Group (DMRG) algorithms] for large active spaces. Dynamic correlation effects for the isomer shifts were treated via CASPT2 energy derivatives with respect to the nuclear radius. The CASSCF calculations appear to produce different orbital overlocalization errors for low and high Np oxidation states. For compounds with low Np oxidation numbers, the errors can be attributed to the overlocalization of the 5f orbitals. For the compounds with high Np oxidation numbers, the main errors arise from an overlocalization of ligand orbitals and concomitant to weak donation bonding. Attempts to mitigate the overlocalization errors with large active spaces using DMRG were only partially successful, showing that explicit treatment of dynamic correlation is necessary for accurate predictions of Mössbauer isomer shifts. The CASPT2 calculations perform very satisfactorily. For a subset of Np compounds, both static and dynamic correlation effects were substantial. Furthermore, a rational active space selection based on orbital entanglement diagrams proved beneficial for determining the optimal reference wave function.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Nonadiabatic Dynamics in a Continuous Circularly Polarized Laser Field with Floquet Phase-Space Surface Hopping
Non-adiabatic chemical reactions involving continuous circularly polarized light (cw CPL) have not attracted as much attention as dynamics in unpolarized/linearly polarized light. However, including circularly (in contrast to linearly) polarized light allows one to effectively introduce a complex-valued time-dependent Hamiltonian, which offers a new path for control or exploration through the introduction of Berry forces. Here, we investigate several inexpensive semiclassical approaches for modeling such nonadiabatic dynamics in the presence of a time-dependent complex-valued Hamiltonian, beginning with a straightforward instantaneous adiabatic fewest-switches surface hopping (IA-FSSH) approach (where the electronic states depend on position and time), continuing to a standard Floquet fewest switches surface hopping (F-FSSH) approach (where the electronic states depend on position and frequency), and ending with an exotic Floquet phase-space surface hopping (F-PSSH) approach (wherethe electronic states depend on position, frequency, and momentum). Using a set of model systems with time-dependent complex-valued Hamiltonians, we show that the Floquet phase- space adiabats are the optimal choice of basis as far as accounting for Berry phase effects and delivering accuracy. Furthermore, the F-PSSH algorithm sets the stage for modeling nonadiabatic dynamics under strong externally pumped circular polarization in the future.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations
The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.
Anions↗
Nuclear–Electronic Orbital QM/MM Approach: Geometry Optimizations and Molecular Dynamics
Hybrid quantum mechanical/molecular mechanical (QM/MM) methods allow simulations of chemical reactions in atomistic solvent and heterogeneous environments such as proteins. Herein, the nuclear–electronic orbital (NEO) QM/MM approach is introduced to enable the quantization of specified nuclei, typically protons, in the QM region using a method such as NEO-density functional theory (NEO-DFT). This approach includes proton delocalization, polarization, anharmonicity, and zero-point energy in geometry optimizations and dynamics. Expressions for the energies and analytical gradients associated with the NEO-QM/MM method, as well as the previously developed polarizable continuum model (NEO-PCM), are provided. Geometry optimizations of small organic molecules hydrogen bonded to water in either dielectric continuum solvent or explicit atomistic solvent illustrate that aqueous solvation can strengthen hydrogen-bonding interactions for the systems studied, as indicated by shorter intermolecular distances at the hydrogen-bond interface. We then performed a real-time direct dynamics simulation of a phenol molecule in explicit water using the NEO-QM/MM method. Furthermore, these developments and initial examples provide the foundation for future studies of nuclear–electronic quantum dynamics in complex chemical and biological environments.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Exact-Factorization-Based Surface Hopping for Multistate Dynamics
A surface-hopping algorithm recently derived from the exact factorization approach, SHXF, introduces an additional term in the electronic equation of surface hopping that couples electronic states through the quantum momentum. Furthermore, this term not only provides a first-principles description of decoherence, but here we show it is crucial to accurately capture nonadiabatic dynamics when more than two states are occupied at any given time. Using a vibronic coupling model of the uracil cation, we show that the lack of this term in traditional surface-hopping methods, including those with decoherence corrections, leads to failure to predict the dynamics through a three-state intersection, while SHXF performs similarly to the multiconfiguration time-dependent Hartree quantum dynamics benchmark.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Role of Intradomain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: Investigating Interfacial Mobility and Ion-Specific Dynamics and Transport
Block polymers show promise as solid-state battery electrolytes due to the optimization of conductive and mechanical properties enabled via tuning of block chemistry and length. We investigate a polystyrene-block-poly(oligo-oxyethylene methacrylate) (PS-b-POEM) electrolyte doped with various lithium salts to investigate the role of molecular structure on ion transport properties and on local ion dynamics and associations. Anion charge becomes more delocalized with increasing size, reducing the coupling between salt ions while increasing coupling between ion and polymer chain motions and creating a more mobile overall environment. We observe support for this ion-polymer coupling via 1 H, 7 Li and 19 F NMR spectroscopy, from which we obtain ion-specific mobility transition temperatures that differ from the polymer glass transition temperature. We also note faster transport and weaker local energetic interactions with anion size using temperature-dependent NMR diffusometry. 1 H NMR spectroscopy further elucidates polymer chain dynamics and enables quantification of the temperature-dependent fraction of the conducting block that is immobile near the PS-POEM domain interface. As a result, NMR thus represents a species-specific and timescale-specific platform to quantify phase and interface behavior, and to correlate ion-specific transport with polymer chain dynamics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Role of Intra-Domain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: An Approach for Spatially Resolving Dynamics and Ion Transport
The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Modulating the dynamics of Brønsted acid sites on PtWOx inverse catalyst
Here metal-metal oxide (M-MO) inverse catalysts are broadly applied. Brønsted acid sites on the oxide overlayers are often hypothesized to drive selective C-O bond activation. However, the Brønsted acid site nature and dynamics under working conditions remain poorly understood due to multiple materials functionalities. Here, we investigate the formation and the dynamics of Brønsted acid and redox sites on PtWO x /C under working conditions. DFT-based thermodynamic calculations and microkinetic modeling reveal a complex interplay between Brønsted acid and redox sites and potentially fast catalyst dynamics at comparable time scales to the chemistry. Combining in situ characterization and probe chemistry, we demonstrate that the density of Brønsted acid sites on the PtWO x /C inverse catalyst could be modulated by up to two orders of magnitude by altering the reaction parameters and by the chemistry itself. We elicit an order of magnitude increase in the acid-catalyzed dehydration average reaction rate by periodic hydrogen pulsing.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Insight into the coordinated jetting behavior in periodic lattice structures under dynamic compression
Abstract not provided
Lind, Jonathan↗