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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 217 records · Page 12

Benchmark problems for the Mesoscale Multiphysics Phase Field Simulator (MEMPHIS)

This report details the current benchmark results to verify, validate and demonstrate the capabilities of the in-house multi-physics phase-field modeling framework Mesoscale Multiphysics Phase Field Simulator (MEMPHIS) developed at the Center for Integrated Nanotechnologies (CINT). MEMPHIS is a general phase-field capability to model various nanoscience and materials science phenomena related to microstructure evolution. MEMPHIS has been benchmarked against a suite of reported classical phase-field benchmark problems to verify and validate the correctness, accuracy and precision of the models and numerical methods currently implemented into the code.

74 ATOMIC AND MOLECULAR PHYSICS↗

Dynamical phase-field model of coupled electronic and structural processes

Abstract Many functional and quantum materials derive their functionality from the responses of both their electronic and lattice subsystems to thermal, electric, and mechanical stimuli or light. Here we propose a dynamical phase-field model for predicting and modeling the dynamics of simultaneous electronic and structural processes and the accompanying mesoscale pattern evolution under static or ultrafast external stimuli. As an illustrative example of application, we study the transient dynamic response of ferroelectric domain walls excited by an ultrafast above-bandgap light pulse. We discover a two-stage relaxational electronic carrier evolution and a structural evolution containing multiple oscillational and relaxational components across picosecond to nanosecond timescales. The phase-field model offers a general theoretical framework which can be applied to a wide range of functional and quantum materials with interactive electronic and lattice orders and phase transitions to understand, predict, and manipulate their ultrafast dynamics and rich mesoscale evolution dynamics of domains, domain walls, and charges.

36 MATERIALS SCIENCE↗

The Physical and Engineering Limits of Coupled In situ TEM Experiments

Almost all future energy systems (advanced nuclear reactors, fusion energy system, concentrating solar-thermal power (CSP), and wind technologies) are limited by degradation of key material systems exposed to multiple environmental stressors. The degradation during exposure to high temperatures, radiation, mechanical loading, and chemical attack is often dictated by mechanisms active at the microstructural level. The nature of these mechanisms and the associated variations between sequential and concurrent interplay can be explored if the transmission electron microscope (TEM) is utilized as a toolbox for exploration [1]. One such tool developed at Sandia National Laboratories to couple several of these environments is the In situ Ion Irradiation TEM (I3TEM) [2]. Several studies over the last decade utilizing this tool have shown that the scientific intuition developed over decades of sequential experiments is not always a good indicator of concurrent mechanisms or failure routes. This presentation will highlight the recent and planned additions into the I3TEM facility of a Waviks gas injection system and Raman system, respectively, as can be seen in Fig. 1, permitting environmental degradation from gas species leaked into the pole piece region during quantitative mechanical loading (indentation, monotonic loading, high temperature creep, irradiation induced creep, and high-cycle fatigue); multi-beam ion irradiation (energies ranging from 1 keV to 48 MeV and species from H to Au); laser exposure (20 W and 1064 nm), or various combinations thereof that are already possible [3]. This addition permits the facility to explore both sequential or concurrently the four axes of stressors: thermal, mechanical, radiation, and chemical. This information can be directly coupled to modeling, expediting the refinement and validation of both atomistic and mesoscale models.

degradation↗

Examining Ohmic Losses in Fuel-Cell Catalyst Layers with Different Pt/C Ratios

A model of a fuel-cell cathode with distinct proton conductivities at the agglomerate and electrode scales was used to simulate polarization curves under conditions with facile oxygen transport. Here, the model was applied to electrodes containing agglomerates with different ratios of platinum to carbon in order to examine the hypothesis that intra-agglomerate proton conductivity is substantially lower than ionomer conductivity. The model predicts decreasing performance and increasing sensitivity to Pt/C ratio as intra-agglomerate conductivity declines relative to a constant through-electrode conductivity. Experiments on catalyst layers with Vulcan supports do not show the predicted trend indicating that mesoscale intra-agglomerate conductivity is not orders of magnitude lower than bulk ionomer conductivity.

08 HYDROGEN↗

Synchrotron infrared nano-spectroscopy and -imaging

Infrared (IR) spectroscopy has evolved into a powerful analytical technique to probe molecular and lattice vibrations, low-energy electronic excitations and correlations, and related collective surface plasmon, phonon, or other polaritonic resonances. In combination with scanning probe microscopy, near-field infrared nano-spectroscopy and -imaging techniques have recently emerged as a frontier in imaging science, enabling the study of complex heterogeneous materials with simultaneous nanoscale spatial resolution and chemical and quantum state spectroscopic specificity. Here, we describe synchrotron infrared nano-spectroscopy (SINS), which takes advantage of the low-noise, broadband, high spectral irradiance, and coherence of synchrotron infrared radiation for near-field infrared measurements across the mid- to far-infrared with nanometer spatial resolution. This powerful combination provides a qualitatively new form of broadband spatio-spectral analysis of nanoscale, mesoscale, and surface phenomena that were previously difficult to study with IR techniques, or even any form of micro-spectroscopy in general. We review the development of SINS, describe its technical implementations, and highlight selected examples representative of the rapidly growing range of applications in physics, chemistry, biology, materials science, geology, and atmospheric and space sciences.

47 OTHER INSTRUMENTATION↗

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗

LES ARM Symbiotic Simulation and Observation Scenario for CACTI

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI scenario consists of a library of mesoscale and LES simulations spanning grid spacings from 7.5 km to 100 m for convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. Supporting skill scores and observation comparisons complement the simulations in addition to subsets of the model output for various categories of model output variables. More information can be found at https://www.arm.gov/capabilities/modeling/lasso.

54 ENVIRONMENTAL SCIENCES↗

Combined Experimental and Computational Study of Molybdenum and Niobium for Nuclear Sensor Application

Due to their novel electromagnetic and thermal properties, molybdenum (Mo) and niobium (Nb) become optimal temperature sensor materials for nuclear energy applications. We leveraged voltage recorded during a heat ramp to tune a computational method to predict the Seebeck electromotive force (EMF) of Mo and Nb. Using a combined Density Functional Theory (DFT) and Boltzmann Transport Equations (BTE) method the voltage was predicted but did not include the effects of temperature on atomic structure. Combining Ab Initio Molecular Dynamics (AIMD) and BTE included temperature effects on structure optimization and yielded voltages in a good agreement with experiment. Lanthanum (La) and Phosphorus (P) additives in Mo and Nb, respectively, could increase the EMF compared to those of the pure metals. The presence of oxygen (O) in Mo increases the EMF while O in Nb slightly reduces the EMF. Furthermore, our studies suggested that heat treatment-induced structural changes that lead to a reduction in voltage occur not only at the mesoscale as previously understood but also at the atomic scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Growth of Mesoscale Convective Systems in Observations and a Seasonal Convection-Permitting Simulation over Argentina

Abstract A 6.5-month, convection-permitting simulation is conducted over Argentina covering the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations and Clouds, Aerosols, and Complex Terrain Interactions (RELAMPAGO-CACTI) field campaign and is compared with observations to evaluate mesoscale convective system (MCS) growth prediction. Observed and simulated MCSs are consistently identified, tracked, and separated into growth, mature, and decay stages using top-of-the-atmosphere infrared brightness temperature and surface rainfall. Simulated MCS number, lifetime, seasonal and diurnal cycles, and various cloud-shield characteristics including growth rate are similar to those observed. However, the simulation produces smaller rainfall areas, greater proportions of heavy rainfall, and faster system propagations. Rainfall area is significantly underestimated for long-lived MCSs but not for shorter-lived MCSs, and rain rates are always overestimated. These differences result from a combination of model and satellite retrieval biases, in which simulated MCS rain rates are shifted from light to heavy, while satellite-retrieved rainfall is too frequent relative to rain gauge estimates. However, the simulation reproduces satellite-retrieved MCS cloud-shield evolution well, supporting its usage to examine environmental controls on MCS growth. MCS initiation locations are associated with removal of convective inhibition more than maximized low-level moisture convergence or instability. Rapid growth is associated with a stronger upper-level jet (ULJ) and a deeper northwestern Argentinean low that causes a stronger northerly low-level jet (LLJ), increasing heat and moisture fluxes, low-level vertical wind shear, baroclinicity, and instability. Sustained growth corresponds to similar LLJ, baroclinicity, and instability conditions but is less sensitive to the ULJ, large-scale vertical motion, or low-level shear. Growth sustenance controls MCS maximum extent more than growth rate.

54 ENVIRONMENTAL SCIENCES↗