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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Twin nucleation and growth mechanism in Ni-based superalloys

While micro-twinning is the dominant creep deformation mechanism in Ni-based superalloys at temperatures above 700 C, many aspects of twin nucleation and growth remain unexplored. Kolbe mechanism for micro-twinning, based on thermally activated reordering, is probably the only concept currently widely accepted by the scientific community. We propose a qualitatively different mechanism for nucleation and growth of twins. The mechanism can be briefly described as follows. Penetration of a   precipitate by two 1/2(110) edge dislocations travelling on adjacent {111} glide planes triggers nucleation (at the interface of the precipitate and the matrix) and emission of Shockley partial of screw character on the glide plane of the edge dislocation, which entered the precipitate first (generating trailing high-energy anti-phase boundary (APB)). Propagation of this Shockley partial into the precipitate converts the APB into super intrinsic stacking fault (SISF). The recurring arrival of additional edge dislocations on the glide planes adjacent to the configuration described above leads to formation of super extrinsic stacking fault SESF, subsequent micro-twin formation, and growth of the twinned region. We demonstrate the proposed mechanism via molecular dynamics simulations.

Ni-based superalloys↗
NASA NTRSDate not supplied

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗
NASA NTRSDate not supplied

Electrochemical Recycling of CO2

Carbon dioxide (CO2) is a molecule that plays multiple roles in our universe. Currently, its impact on global warming has rightfully given CO2 a label as a harmful waste product that must be amply handled. Nonetheless, under other circumstances, and from other perspectives, CO2 could be regarded as a valuable resource. As example, in nature CO2 is an essential building block in photosynthesis ultimately yielding molecules and materials that we harvest for numerous applications ranging from energy storage and construction to medicines and food. In a similar manner, there is a growing interest to utilize atmospheric CO2 to generate renewable fuels and platform chemicals through artificial processes. These processes can replace fossil based industrial processes on earth alleviating climate impact, but they can also find uses far away from our planet. In space, CO2 is an important source of precious oxygen, however, it can also serve as feedstock for carbon-based molecules and materials that are needed to sustain societies at distant planets such as Mars. In this presentation, I will discuss the contemporary understanding of electrochemical reduction of CO2 for selective production of desired molecules. We will zoom in to the very atomic scale to gain mechanistic understanding of how the structure and composition of the cathode electrode affects product distributions. This information is used as guide in the design of new materials that convert CO2 more efficiently and more selectively. On this basis, opportunities for recycling CO2 under different conditions will be discussed, as will remaining challenges for the ultimate application towards the sustainable human living on earth and in space.

electrochemistry↗
NASA NTRSDate not supplied

Effect of Alloying Additions on Twinning in Ni-Based Superalloys

Micro-twinning is the dominant creep deformation mechanism in Ni-based superalloys at temperatures above 700 C. We use atomistic simulations to study two mechanisms of twin nucleation and growth that are characterized by qualitatively different rate limiting processes. In case of the mechanism proposed by Kolbe, the rate limiting process is diffusion-mediated atomic reshuffling. In case of the other mechanism, we proposed recently, the rate limiting process is nucleation of Shockley partial dislocation. We demonstrate the effects of alloying additions on functionality of these mechanisms.

Ni-based superalloys↗
DOE OSTI2023

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↗
DOE OSTI2020

Learning Coarse-Grained Potentials for Binary Fluids

Even though atomistic and CG models have been used to simulate liquid nanodroplets in vapor, very few rigorous studies of the liquid-liquid interface structure are available, and most of them are limited to planar interfaces. In this work, we evaluate several existing force fields (FF)s, including two atomistic and three CG FFs, with respect to modeling the interface structure and thermodynamic properties of the water-hexane interface. Both atomistic FFs are able to quantitatively reproduce the interfacial tension and the coexisting densities of the experimentally-observed planar interface. We use the atomistic FFs to model water droplets in hexane and use these simulations to test the CG FFs. We found that the tested CG FFs cannot reproduce the interfacial tensions of planar and/or curved interfaces. Finally, we propose a new approach for learning coarse-grained (CG) potentials within the CG SDK (Shinoda-DeVane- Klein) FF framework from atomistic simulation data. We demonstrate that the new potential significantly improves the prediction of both the interfacial tension and structure of water-hexane planar and curved interfaces.

Gao, Peiyuan↗
NASA NTRS2016

Multiscale Modeling of Carbon/Phenolic Composite Thermal Protection Materials: Atomistic to Effective Properties

Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.

Materials Science↗
DOE OSTI2020

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Bicrystallography-informed Frenkel–Kontorova model for interlayer dislocations in strained 2D heterostructures

In recent years, van der Waals (vdW) heterostructures and homostructures, which consist of stacks of two-dimensional (2D) materials, have risen to prominence due to their association with exotic quantum phenomena originating from correlated electronic states harbored by them. Atomistic scale relaxation effects play an extremely important role in the electronic scale quantum physics of these systems, providing means of manipulation of these materials and allowing them to be tailored for emergent technologies. We investigate such structural relaxation effects in this work using atomistic and mesoscale models, within the context of twisted bilayer graphene — a well-known heterostructure system that features moiré patterns arising from the lattices of the two graphene layers. For small twist angles, atomic relaxation effects in this system are associated with the natural emergence of interface dislocations or strain solitons, which result from the cyclic nature of the generalized stacking fault energy (GSFE), that measures the interface energy based on the relative movement of the two layers. Here, in this work, we first demonstrate using atomistic simulations that atomic reconstruction in bilayer graphene under a large twist also results from interface dislocations, although the Burgers vectors of such dislocations are considerably smaller than those observed in small-twist systems. To reveal the translational invariance of the heterointerface responsible for the formation of such dislocations, we derive the translational symmetry of the GSFE of a 2D heterostructure using the notions of coincident site lattices (CSLs) and displacement shift complete lattices (DSCLs). The workhorse for this exercise is a recently developed Smith normal form bicrystallography framework. Next, we construct a bicrystallography-informed and frame-invariant Frenkel–Kontorova model, which can predict the formation of strain solitons in arbitrary 2D heterostructures, and apply it to study a heterostrained, large-twist bilayer graphene system. Our mesoscale model is found to produce results consistent with atomistic simulations. We anticipate that the model will be invaluable in predicting structural relaxation and for providing insights into various heterostructure systems, especially in cases where the fundamental unit cell is large and therefore, atomistic simulations are computationally expensive.

2D heterostructures↗
NASA NTRS2007

Elastic Response and Failure Studies of Multi-Wall Carbon Nanotube Twisted Yarns

Experimental data on the stress-strain behavior of a polymer multiwall carbon nanotube (MWCNT) yarn composite are used to motivate an initial study in multi-scale modeling of strength and stiffness. Atomistic and continuum length scale modeling methods are outlined to illustrate the range of parameters required to accurately model behavior. The carbon nanotubes yarns are four-ply, twisted, and combined with an elastomer to form a single-layer, unidirectional composite. Due to this textile structure, the yarn is a complicated system of unique geometric relationships subjected to combined loads. Experimental data illustrate the local failure modes induced by static, tensile tests. Key structure-property relationships are highlighted at each length scale indicating opportunities for parametric studies to assist the selection of advantageous material development and manufacturing methods.

Gates, Thomas S.↗
NASA NTRS2003

Alloy Design Workbench-Surface Modeling Package Developed

NASA Glenn Research Center's Computational Materials Group has integrated a graphical user interface with in-house-developed surface modeling capabilities, with the goal of using computationally efficient atomistic simulations to aid the development of advanced aerospace materials, through the modeling of alloy surfaces, surface alloys, and segregation. The software is also ideal for modeling nanomaterials, since surface and interfacial effects can dominate material behavior and properties at this level. Through the combination of an accurate atomistic surface modeling methodology and an efficient computational engine, it is now possible to directly model these types of surface phenomenon and metallic nanostructures without a supercomputer. Fulfilling a High Operating Temperature Propulsion Components (HOTPC) project level-I milestone, a graphical user interface was created for a suite of quantum approximate atomistic materials modeling Fortran programs developed at Glenn. The resulting "Alloy Design Workbench-Surface Modeling Package" (ADW-SMP) is the combination of proven quantum approximate Bozzolo-Ferrante-Smith (BFS) algorithms (refs. 1 and 2) with a productivity-enhancing graphical front end. Written in the portable, platform independent Java programming language, the graphical user interface calls on extensively tested Fortran programs running in the background for the detailed computational tasks. Designed to run on desktop computers, the package has been deployed on PC, Mac, and SGI computer systems. The graphical user interface integrates two modes of computational materials exploration. One mode uses Monte Carlo simulations to determine lowest energy equilibrium configurations. The second approach is an interactive "what if" comparison of atomic configuration energies, designed to provide real-time insight into the underlying drivers of alloying processes.

Abel, Phillip B.↗
DOE OSTI2026

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.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Role of Local Inhomogeneities on Dendrite Growth in LLZO-Based Solid Electrolytes

The majority of the ceramic solid electrolytes (LLZO, LATP) demonstrate polycrystalline grain/grain-boundary (G/GB) microstructure. Higher lithium (Li) concentration and lower mechanical stiffness result in current focusing at the GBs. Growth of Li dendrites through local inhomogeneities and subsequent short circuit of the cell is a major concern. Recent studies have revealed that bulk Li metal is a viscoplastic material that has low (~0.3 MPa) and high (~1.0 MPa) yield strength during deformation at smaller and larger rates of strain, respectively. It has been argued that during deposition at smaller current densities, due to its lower yield strength, Li metal should demonstrate plastic flow against stiff ceramic electrolytes, and Li dendrites will be prevented from penetrating through solid electrolytes. In this manuscript, a multiscale modeling framework has been developed for predicting properties of GBs and the bulk of ceramic electrolytes using atomistic calculations for input to mesoscale models. Using the parameters obtained from the atomistic simulations, the mesoscale model reveals that, given enough time, even at low charge rates, lithium dendrites can grow through the GBs of LLZO. The present multiscale model results also provide information regarding the dendrite growth velocity through LLZO.

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

BISON Capability to Account for Dopant Sensitivity in Relevant UO 2 Material Models

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. Incorporation of more physics-based models in BISON for the accident tolerant fuel applications motivated this study. This document details integration of new modeling capabilities in BISON, including: a tensile strength model for uranium dioxide (UO 2 ) fuel to incorporate the microstructural effects (e.g., grain size, fabrication pore size, and porosity), and atomistic-informed creep model for UO 2 fuel that is developed by Los Alamos National Laboratory. Sensitivity analyses are conducted on these models separately as well as a two-dimensional full rod application under normal operating conditions. Lastly, these new modeling capabilities in BISON are exercised in Halden IFA-677.1 and IFA-716.1 assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Empirical and mechanistic transient fission gas release model for high-burnup LOCA conditions

In response to the nuclear industry desire to extend burnup beyond current licensing practices, the US Nuclear Regulatory Commission (NRC) released a research information letter (RIL) that provides a basis for analyzing fuel fragmentation, relocation, and dispersal (FFRD) in light-water reactors. Of the five elements discussed, the most ambiguous is the significance of transient fission gas (FG) release (FGR) (tFGR) and its effects on fuel performance under loss-of-coolant accident conditions. In fresh fuel, FG migration and eventual release is primarily governed by diffusion-based mechanisms at higher temperatures (>1,000 °C). However, the mechanisms governing FGR changes as burnup increases. More recent research indicates that FGR increases as burnup increases, specifically under temperature transient conditions, and this release occurs at lower temperatures with a new release mechanism. This behavior has been attributed to microcracking in the fuel and is likely related to microstructure embrittlement with the presence of over pressurized FG bubbles. The NRC RIL outlines the complexity of the phenomenon and a need for a deeper understanding to adequately address FFRD for regulatory application. Here, therefore, this manuscript intends to summarize the publicly available tFGR data and discuss the observed dependencies (e.g., burnup, heating rate, sample geometry, terminal temperature). An empirical model has been developed and benchmarked against recently published experimental data. However, this empirical model is limited to conditions for which fitting data exist and, therefore, a high-level discussion is included to provide a roadmap for atomistically-informed multiscale modeling in conjunction with experimental data collection to develop a mechanistic tFGR model widely applicable to a broad range of nuclear fuel conditions at high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Continuum-Level Modeling of Li-Ion Battery SEI by Upscaling Atomistically Informed Reaction Mechanisms

Understanding and controlling solid-electrolyte interphase (SEI) formation to stabilize cell performance is a significant challenge for next-generation Li-ion battery technologies. In recent years, computational modeling has become an essential tool in providing fundamental insights into SEI properties and dynamics. However, neither atomistic nor continuum-level approaches alone can capture the complexities of SEI chemistry across all relevant length and time scales. In this work, a continuum-level model is developed that is informed by reaction mechanisms obtained from first-principle calculations. The atomistically informed continuum-level model is used to understand electrolyte degradation, including the decomposition of ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). The model presented here is the most chemically complex continuum-level SEI model in the literature to date. The SEI model is calibrated against experimental irreversible leakage currents and shows qualitative agreement with expected SEI growth trends. The model framework is expected to accelerate fundamental understanding of SEI formation, facilitate mechanism development feedback, and dynamically interact with experimental insights.

continuum-level model↗
DOE OSTI2025

Systematic improvement of redox potential calculation of Fe(III)/Fe(II) complexes using a three-layer micro-solvation model

Electrochemical transformations of metal ions in aqueous media are challenging to model accurately due to the dynamic solvation structure surrounding ions at different charge states. Predictive modeling at the atomistic scale is essential for understanding these solvation architectures but is often computationally prohibitive. In this contribution, we present a simple, fast, and accurate three-layer micro-solvation model to evaluate the redox potential of metal ions in aqueous solutions. Our model, developed and validated for Fe 3+ /Fe 2+ redox potentials, combines the DFT-based geometry optimizations of the octahedral Fe complex with two layers of explicit water molecules to capture solute–solvent interactions and an implicit solvation model to account for bulk solvent effects. This approach yields accurate predictions for Fe 3+ /Fe 2+ redox potentials in water, achieving errors of 0.02 V with ωB97X-V, 0.01 V with ωB97X-D3, 0.04 V with ωB97M-V, and 0.02 V with B3LYP-D3 functionals. We further demonstrate the generality of our model by applying it to additional metal complexes, including the challenging Fe(CN) 6 3−/4− system, where our model successfully achieves close agreement with experimental values, with an error of 0.07 V and an average error of 0.21 V for all five systems. In summary, the presented simple solvation model has broad applicability and potential for enhancing computational efficiency in redox potential predictions across various chemical and industrial processes of metal ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗