SEARCH · Search NASA
Results for “Multiscale simulations”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Alumina – Stabilized SEI and CEI in Potassium Metal Batteries
Aluminum oxide (Al 2 O 3 ) nanopowder is spin-coated onto both sides of commercial polypropene separator to create artificial solid-electrolyte interphase (SEI) and artificial cathode electrolyte interface (CEI) in potassium metal batteries (KMBs). Here, this significantly enhances the stability, including of KMBs with Prussian Blue (PB) cathodes. For example, symmetric cells are stable after 1,000 cycles at 0.5 mA/cm 2 –0.5 mAh/cm 2 and 3.0 mA/cm 2 –0.5 mAh/cm 2 . Alumina modified separators promote electrolyte wetting and increase ionic conductivity (0.59 vs. 0.2 mS/cm) and transference number (0.81 vs. 0.23). Cryo-stage focused ion beam (cryo-FIB) analysis of cycled modified anode demonstrates dense and planar electrodeposits, versus unmodified baseline consisting of metal filaments (dendrites) interspersed with pores and SEI. Alumina-modified CEI also suppresses elemental Fe crossover and reduces cathode cracking. Mesoscale modeling of metal – SEI interactions captures crucial role of intrinsic heterogeneities, illustrating how artificial SEI affects reaction current distribution, conductivity and morphological stability.
A Poromechanical Framework for Internal Interactions Induced by Solid Inclusions
The framework of poromechanics is generalized to simulate the multiscale behavior of porous media subjected to internal loadings stemming from the growth of solid inclusions. This generalization is designed to enable the study of anisotropic internal stress generation from solid growth within the pores, while recovering isotropic fluid-induced loading as a particular case. For this purpose, a mathematical strategy to define constitutive tensors in a thermodynamically consistent form is proposed, thus offering new opportunities for determining the poromechanical properties of a porous solid through advanced experimentation or micromechanical models. The framework is specialized by means of established elastic solutions for single pore–matrix interaction, as well as through homogenization schemes considering the interaction among congruent pores. In particular, the second Eshelby solution and the Tanaka–Mori–Benveniste homogenization scheme are used to derive a microporoelastic model. At an elemental scale, the model is tested under mixed control conditions by replicating different scenarios of geomaterial testing. In addition, the model characteristics are outlined with reference to inelastic microscopic loadings replicating chemo-mechanical forcing, such as expansive crystal formation. Through a series of parametric analyses, it is shown that the microstructure of the pores significantly influences the properties of porous media. Most notably, it is shown that the effects of a solid forming within the pores depend in a highly nonlinear fashion on the constitutive characteristics of the inhomogeneities and can therefore not be readily quantified or predicted without models capturing the diverse multiscale interactions among pores, inhomogeneities, and matrix.
Circumventing mesh bias by r- and h-adaptive techniques for variational eigenfracture
This work introduces and compares mesh r- and h-adaptivity for the eigenfracture model originally proposed in Schmidt et al. (Multiscale Model Simul 7:1237–1266, 2009), Pandolfi and Ortiz (J Numer Methods Eng 92:694–714, 2012), with the goal of suppressing potential mesh bias due to the element deletion. In the r-adaptive approach, we compute the configurational force at each incremental step and move nodes near the crack tip parallel to the normalized configurational forces field such that the crack propagation direction can be captured more accurately within each incremental step. In the h-adapative approach, we introduce mesh refinement via a quad-tree algorithm to introduce more degrees of freedom within the nonlocal ϵ-neighborhood such that a more refined crack path can be reproduced with a higher mesh resolution. Our numerical examples indicate that the r-adaptive approach is able to replicate curved cracks and complex geometrical features, whereas the h-adaptive approach is advantageous in simulating sub-scale fracture when the nonlocal regions are smaller than the un-refined coarse mesh.
Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review
The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.
Split representation of adaptively compressed polarizability operator
The polarizability operator plays a central role in density functional perturbation theory and other perturbative treatment of first principle electronic structure theories. The cost of computing the polarizability operator generally scales as O(Ne4) where Ne is the number of electrons in the system. The recently developed adaptively compressed polarizability operator (ACP) formulation [L. Lin, Z. Xu and L. Ying, Multiscale Model. Simul. 2017] reduces such complexity to O(Ne 3 ) in the context of phonon calculations with a large basis set for the first time, and demonstrates its effectiveness for model problems. In this paper, we improve the performance of the ACP formulation by splitting the polarizability into a near singular component that is statically compressed, and a smooth component that is adaptively compressed. The new split representation maintains the O(Ne 3 ) complexity, and accelerates nearly all components of the ACP formulation, including Chebyshev interpolation of energy levels, iterative solution of Sternheimer equations, and convergence of the Dyson equations. For simulation of real materials, we discuss how to incorporate nonlocal pseudopotentials and finite temperature effects. In this work, we demonstrate the effectiveness of our method using one-dimensional model problem in insulating and metallic regimes, as well as its accuracy for real molecules and solids.
A new procedure for implementing the modified inherent strain method with improved accuracy in predicting both residual stress and deformation for laser powder bed fusion
As a metal additive manufacturing (AM) process, laser powder bed fusion (L-PBF) has been widely used to produce parts with complex geometries. The large thermal gradient caused by the fast, intense, and repeated laser scanning induces significant residual deformation and stress to the as-built parts, which increase manufacturing difficulty and geometrical inaccuracy as a result. The modified inherent strain (MIS) method exploiting multiscale process simulations was developed to simulate residual deformation accurately and efficiently. However, the existing procedure of implementing the MIS method is found to give inaccurate residual stress prediction. Here in this work, a new implementation procedure for the MIS method is proposed to improve the simulation accuracy of residual stress without degrading the residual deformation prediction. The new procedure concerns the application of inherent strains to the part-scale layer-by-layer finite element model to obtain residual stress and deformation field. While the existing implementation of the part-scale MIS model involves only mechanical properties at ambient temperature, the new procedure adds one more solution step employing mechanical properties at an elevated temperature determined from the inherent strain extraction step. Both numerical and experimental studies are conducted to validate the proposed new implementation procedure. It shows that by using the new procedure, the MIS-based simulation can predict both residual stress and deformation of as-built L-PBF metal parts with good accuracy.
Multiscale Concurrent Atomistic-Continuum (CAC) modeling of multicomponent alloys
We report strengthening in complex multicomponent systems such as solid solution alloys is controlled primarily by the dynamic interactions between dislocation lines and heterogeneously distributed solute species. Modeling of extended defect length scales in such multicomponent systems becomes prohibitively expensive, motivating the development of reduced order approaches. This work explores the application of the Concurrent Atomistic-Continuum (CAC) method to model dislocation mobility in random alloys at extended length scales. By employing recently developed average-atom interatomic potentials, the average “bulk” material response in coarse-grained regions interacts with true random solute species in the atomistic-scale domain. We demonstrate that spurious stresses in domain resolution transition regions are eliminated entirely due to the CAC formulation. Simultaneously, the key details of local stress fluctuation due to randomness in the dislocation core region are captured, and fluctuating stress smoothly decays to the long-range dislocation stress field response. Dislocation mobility calculations, for line lengths over 400 nm, are computed as a function of alloy composition in the model FeNiCr system and compared to full molecular dynamics (MD). The results capture the composition-dependent trends, while reducing degrees of freedom by nearly 40%. This approach can be readily extended to any system described by an EAM potential and facilitates the study of large-scale defect dynamics in complex solute environments to support computational alloy design.
Simulations of grain growth in tungsten armor materials under ARC plasma edge operation conditions using an integrated plasma-edge/materials model
An integrated model of grain growth deuterium-exposed tungsten polycrystals, consisting of a two-dimensional vertex dynamics model fitted to atomistic data, has been developed to assess the grain growth kinetics of deuterium-exposed polycrystalline tungsten (W). The model tracks the motion of grain boundaries under the effect of driving forces stemming from grain boundary curvature and differential deuterium concentration accumulation. Here, we apply the model to experimentally synthesized tungsten polycrystals under deuterium-saturated conditions relevant to the ARC concept design. The results indicate rapid grain growth kinetics in the near-surface region adjacent to the plasma, where the temperature reaches 1400 K, whereas the microstructure remains stable deeper in the material with the lower temperature of 1000 K. The combined modeling and analysis further reveal that monolithic tungsten produced via conventional fabrication routes is highly susceptible to grain coarsening at temperatures exceeding 1000 K, largely independent of the magnitude of the applied driving force. Moreover, the accumulation of deuterium near grain boundaries has a pronounced inhibitory effect on grain boundary migration. High-angle grain boundaries ( > 50°) contribute more significantly to the overall grain growth process.
Predicted Structures of the Active Sites Responsible for the Improved Reduction of Carbon Dioxide by Gold Nanoparticles
Gold (Au) nanoparticles (NPs) are known experimentally to reduce carbon dioxide (CO 2 ) to carbon monoxide (CO), with far superior performance to Au foils. To obtain guidance in designing improved CO 2 catalysts, we want to understand the nature of the active sites on Au NPs. Here, we employed multiscale atomistic simulations to computationally synthesize and characterize a 10 nm thick Au NP on a carbon nanotube (CNT) support, and then we located active sites from quantum mechanics (QM) calculations on 269 randomly selected sites. The standard scaling relation is that the formation energy of *COOH (ΔE*COOH) is proportional to the binding energy of *CO (Ebinding*CO); therefore, decreasing ΔE*COOH to boost the CO 2 reduction reaction (CO 2 RR) causes an increase of Ebinding*CO that retards CO 2 RR. We show that the NPs have superior CO 2 RR because there are many sites at the twin boundaries that significantly break this scaling relation.
Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides
Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.
Atomistic Explanation of the Dramatically Improved Oxygen Reduction Reaction of Jagged Platinum Nanowires, 50 Times Better than Pt
Pt is the best catalyst for the oxygen reduction reactions (ORRs), but it is far too slow. Huang and co-workers showed that dealloying 5 nm Ni 7 Pt 3 nanowires (NW) led to 2 nm pure Pt jagged NW (J-PtNW) with ORRs 50 times faster than Pt/C. They suggested that the undercoordinated surface Pt atoms, mechanical strain, and high electrochemically active surface area (ECSA) are the main contributors. We report here multiscale atomic simulations that further explain this remarkably accelerated ORR activity from an atomistic perspective. We used the ReaxFF reactive force field to convert the 5 nm Ni 7 Pt 3 NW to the jagged 2 nm NW. We applied quantum mechanics to find that 14.4% of the surface sites are barrierless for O ads + H 2 O ads → 2OH ads , the rate-determining step (RDS). The reason is that the concave nature of many surface sites pushes the OH bond of the H 2 O ads close to the O ads , leading to a dramatically reduced barrier. We used this observation to predict the performance improvement of the J-PtNW relative to Pt (111). Assuming every surface site reacts independently with this predicted rate leads to a 212-fold enhancement at 298.15 K, compared to 50 times experimentally. The atomic structures of the active sites provide insights for designing high-performance electrocatalysts for ORR.
Hydrogen-induced degradation dynamics in silicon heterojunction solar cells via machine learning
Abstract Among silicon-based solar cells, heterojunction cells hold the world efficiency record. However, their market acceptance is hindered by an initial 0.5% per year degradation of their open circuit voltage which doubles the overall cell degradation rate. Here, we study the performance degradation of crystalline-Si/amorphous-Si:H heterojunction stacks. First, we experimentally measure the interface defect density over a year, the primary driver of the degradation. Second, we develop SolDeg, a multiscale, hierarchical simulator to analyze this degradation by combining Machine Learning, Molecular Dynamics, Density Functional Theory, and Nudged Elastic Band methods with analytical modeling. We discover that the chemical potential for mobile hydrogen develops a gradient, forcing the hydrogen to drift from the interface, leaving behind recombination-active defects. We find quantitative correspondence between the calculated and experimentally determined defect generation dynamics. Finally, we propose a reversed Si-density gradient architecture for the amorphous-Si:H layer that promises to reduce the initial open circuit voltage degradation from 0.5% per year to 0.1% per year.
Verification of an improved equation-free projective integration method for neoclassical plasma-profile evolution in tokamak geometry
A brute-force, long-time gyrokinetic simulation of plasma profile evolution in magnetic fusion devices is not desirable due to large computational resource requirements and a possible accumulation of numerical error. The equation-free projective integration method of Keverekidis et al. [Commun. Math. Sci. 1(4), 715–762 (2003)] is one of the outstanding candidates in projecting micro-scale simulations to a longer timescale. However, its application to tokamak plasma has not been fruitful due to the appearance of spurious transient oscillations in the lifting process, which are present when the kinetic simulations are initialized with a simplified model distribution function and which make the kinetic simulations to deviate from the desired paths. In this work, a kinetically informed lifting algorithm is added to the equation-free projective integration method, which is then verified in the electrostatic gyrokinetic particle-in-cell code XGCa [R. Hager and C. S. Chang, Phys. Plasmas 23, 042503 (2016)] for a neoclassical ion heat transport problem with adiabatic electrons. This new lifting operator is demonstrated to control spurious transients, enabling an over four-times reduction in the overall computing time in the time-evolution of the ion temperature profile in an axisymmetric toroidal plasma. Further reduction in the computing time is found to be limited due to the stability properties of the linear least squares projective integrator.
A High-Speed Rotational Diamond Anvil Cell for In Situ Analysis of Hierarchical Microstructural Evolution of Metallic Alloys during Extreme Shear Deformation
High speed shear deformation is ubiquitous in engineering applications, ranging from material processing methods such as friction stir processing/extrusion and in tribological contacts. However, analyzing the microstructural evolution of materials while they are undergoing high speed shear deformation have been a long-standing challenge. This led to predominant reliance on ex situ microscopy before and after shear deformation. But ex situ microscopy lacks the ability to analyze dynamic and transient hierarchical microstructural evolution mechanisms that could occur during shear deformation of materials. Therefore, to better understand the dynamic mechanisms of mass and energy transfer in materials under shear deformation, we developed a first of its kind high-speed rotational diamond anvil cell (HS-RDAC) for synchrotron-based in situ high-energy x-ray diffraction (XRD). We studied the time resolved lattice strain evolution, XRD peak broadening and changes in spatial variation of shear deformation induced alloying in pure metal and metal alloy sheets and powder mixture using the HS-RDAC. These in situ results were combined with detailed ex situ microstructural characterization before and after the shear deformation using transmission electron microscopy and atom probe tomography, which revealed the different stages of evolution of a shear deformation induced hierarchical nanostructure. Multiscale computational simulations including computational fluid dynamics, crystal plasticity, molecular dynamic simulation and density functional theory uncovered the mechanisms behind morphological changes, evolution of defect structures and changes in driving force for shear deformation induced intermixing. In conclusion, this in situ HS-RDAC capability, in combination with ex situ microstructural characterization and computational simulations, can provide new insights into the hierarchical microstructural evolution pathway during shear deformation.
Potential quantum advantage for simulation of fluid dynamics
Numerical simulation of turbulent fluid dynamics needs to either parametrize turbulence—which introduces large uncertainties—or explicitly resolve the smallest scales—which is prohibitively expensive. Here, we provide evidence through analytic bounds and numerical studies that a potential quantum speedup can be achieved to simulate fluid dynamics using quantum computing. Specifically, we provide a lattice Boltzmann formulation of fluid dynamics for which we give evidence that low-order Carleman linearization is much more accurate than previously believed for these systems. This is achieved via a combination of reformulating the Navier-Stokes nonlinearity (u·$\triangledown$u) to lattice-Boltzmann nonlinearity (u 2 ) and accurately linearizing the dynamical equations, which effectively trades nonlinearity for additional degrees of freedom that add negligible expense in the quantum solver. Based on this, we apply a quantum algorithm for simulating the Carleman-linearized lattice Boltzmann equation and provide evidence that its cost scales logarithmically with system size compared with polynomial scaling in the best known classical algorithms. In this paper, we suggest that a quantum advantage may exist for simulating fluid dynamics, paving the way for simulating nonlinear multiscale transport phenomena in a wide range of disciplines using quantum computing.
Trilinos: Enabling Scientific Computing across Diverse Hardware Architectures at Scale
Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has undergone substantial changes to support new applications and new hardware architectures, this document is an update to “An Overview of the Trilinos project” by Heroux et al. (ACM Transactions on Mathematical Software, 31(3):397–423, 2005). It describes the design of Trilinos, introduces its new organization in product areas, and highlights established and new features available in Trilinos. Particular focus is put on the modernized software stack based on the Kokkos ecosystem to deliver performance portability across heterogeneous hardware architectures. This article also outlines the organization of the Trilinos community and the contribution model to help onboard interested users and contributors.
Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale
The thrust of the proposal was to exploit modern data-mining tools in a way that will create a systematic, computer-assisted approach to the representation of random media -- and also to the representation of the solutions of an array of important physicochemical processes that take place in/on such media. A parsimonious representation/parametrization of the random media links directly (via uncertainty quantification tools) to good sampling of the distribution of random media realizations. It also links directly to modern multiscale computational algorithms (like the equation-free approach that has been developed in our group) and plays a crucial role in accelerating the scientific computation of solutions of nonlinear PDE models (deterministic or stochastic) in such media – both solutions in particular realizations of the random media, and estimation of the statistics of the solutions over multiple realizations (e.g. expectations).