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NASA NTRS2018

Exploring Li-Air Batteries for High Specific Energy and High Power Applications: A Simulation Study

Commercialization of lithium-air batteries face many challenges, such as electrolyte decomposition, short cycle life, low energy efficiency, low power density, etc. However, commercialization of Li-air batteries for mass sensitive applications such as electric vehicles, portable power source, and drones is more challenging due to additional constraints of safety, electrolyte evaporation, high specific energy requirements, and reliable discharge times. In this presentation, we will present our finite element simulation results comparing Li-O2 and Li-air batteries using power density, energy density, specific power, and discharge times as metrics to evaluate different electrolytes and electrode geometry to reduce total mass and maximize discharge current. We use a finite element model and a discharge product model developed in which is based on porous electrode and concentrated electrolyte theories and the discharge product is modeled using quantum tunneling; for reaction kinetics and oxygen diffusion, an improved model was used. The electrolyte properties such as ion conductivity and ion diffusion were obtained from Molecular Dynamics (MD) simulations while the other parameters for the finite element model were calibrated to match experiments at high discharge current densities (>1.5 mA/cm2). The mass densities of different electrolytes were computed using MD simulations as well. For this presentation, we examine the practical electrochemical mass of a system at different current ratings, the sensitivity of mass to the use of ambient air as compared to pure oxygen as well as the electrolyte, which affects maximum current density and the total mass associated with the electrolyte (which includes the mass of additional components), and, the optimization of battery geometry for total discharge time, average discharge voltage, maximum discharge current, and minimum electrochemical mass.

Mehta, M.↗

NASA NTRS2018

Ionic Liquids at Electrified Interfaces: From Double Layers to Decomposition

Ionic liquids are versatile electrolytes whose properties at electrified interfaces have the potential to enable technologies such as supercapacitors and Li-metal battery anodes. At electrified carbon surfaces, ionic liquids form an electric double layer that stores energy and provides the foundation for supercapacitors. At electrified lithium surfaces, ionic liquids decompose to form a solid electrolyte interphase that has the potential to stabilize Li-metal anodes in rechargable batteries. The behavior of two ionic liquids of technological importance, [pyr14][TFSI] and [EMIM][BF4], are examined at these electrified interfaces through molecular dynamics and ab initio techniques.

Haskins, Justin B.↗

NASA NTRS2018

Ionic Liquids at Electrified Interfaces: from Double Layers to Decomposition

Haskins, Justin B.↗

NASA NTRS2018

Ionic Liquids at Electrified Interfaces: from Double Layers to Decomposition

Haskins, Justin B.↗

NASA NTRS2016

Ab Initio Simulations of Phase Stability and Martensitic Transitions in NiTi

For NiTi based alloys, the shape memory effect is governed by a transition from a low-temperature martensite phase to a high-temperature austenite phase. Despite considerable experimental and computational work, basic questions regarding the stability of the phases and the martensitic phase transition remain unclear even for the simple case of binary, equiatomic NiTi. We perform ab initio molecular dynamics simulations to describe the temperature-dependent behavior of NiTi and resolve several of these outstanding issues. Structural correlation functions and finite temperature phonon spectra are evaluated to determine phase stability. We show that finite temperature, entropic effects stabilize the experimentally observed martensite (B19') and austenite (B2) phases while destabilizing the theoretically predicted (B33) phase. Free energy computations based on ab initio thermodynamic integration confirm these results and permit estimates of the transition temperature between the phases. In addition to the martensitic phase transition, we predict a new transition between the B33 and B19' phases. The role of defects in suppressing phase transformation temperatures is discussed.

Simulations↗

NASA NTRS2019

Emergence of Simple Ion Channels by Self-Assembly of Short Peptides

As protocells transitioned from structures bound by membranes made of simple amphiphiles, such as fatty acids, to structures containing phospholipid membranes, they became nearly impermeable to charged species. Yet, the ability to transport ions across membranes was vital to regulating cellular volume, pH homeostasis, generating energy and sensing the environment. For this reason, life evolved ion channels, protein structures surrounding water-filled pores in the membrane that facilitated ion transport. In contemporary cells, ion channels are complex protein assemblies. Could the same function be carried out, even if less efficiently and selectively, by much simpler peptides at the origins of life? To answer this question, we turned to trichogen (GAIV), an 11-residue peptide that was found to permeabilize membrane, causing leakage of the vesicle content including ions. Since GAIV is synthesized non-gnomically, it represents as excellent model for the earliest, poorly optimized channels. Understanding the mechanism by which short peptides, such as GAIV, mediate ion transport across membranes provides crucial information on the emergence, structure and the mechanism of action of the earliest ion channels. In this study, we used extensive molecular dynamics (MD) simulations to investigate directly spontaneous assembly of GAIV peptide and its structural dynamics, the formation of an induced water pore across the membrane and consequently ion conduction through the membrane.

Wei, Chenyu↗

NASA NTRS2019

A Multi-Physics Study on High-Specific Power Li-O2 Batteries for Electric Aircraft

Commercialization of lithium-air batteries faces many challenges, such as electrolyte decomposition, short cycle life, low energy and power density, etc. However, commercialization of Li-O2 batteries for aeronautics is much more challenging due to additional safety constraints on cyclability and performance (high specific power and specific energy). For this presentation, we will discuss inter-related aspects of physics-based modeling of a pack: cell and battery model calibration. In addition, we will evaluate and present optimal battery designs for high discharge current density, high discharge time, and low battery mass using simulation-based optimization.The Finite Element Model (FEM) used to simulate a Li-O2 cell is based on the work of Bevara [1]. The different aspects of the model are based on: porous electrode theory and concentrated electrolyte theory; quantum tunneling model for the resistance of conformal layer of discharge product (Li2O2) [1]; Butler-Volmer kinetics for electrochemical reaction; Fick's diffusion for oxygen transport; and an oxygen dissolution model is applied at the air/electrolyte interface [2]. The electrolyte properties such as ion conductivity, ion diffusion, oxygen diffusion, and mass density of the electrolyte were taken from Molecular Dynamics (MD) simulations [3]; while the other model parameters, which includes mass of cell components, were calibrated to match experiments at high discharge current densities. The cell mass includes the anode, cathode, separator, electrolyte, and other components (such as current collector). This calibrated model is used to perform parametric studies on cathode thickness, porosity, tortuosity, carbon particle size, electrolyte transport and material properties, partial pressure of oxygen, discharge time, and discharge current density to study optimal designs for high specific power and energy. References:1. Bevara, V. & Andrei, P. (2014), J. Electrochem. Soc. 161 (14), A2068-A2079.2.Mehta, M. & Andrei, P. (2015), J. Power Sources. 286, 299-308.3.Liyana-Arachchi, T.; Haskins, J.; Burke, C.; Diederichsen, K.; McCloskey, B.; & Lawson, J. (2018), J. Phys. Chem. B. 122 (36), 8548 - 8559.4.Choi, W.; Kikumoto, H.; Choudhary, R. & Ooka, R. (2018), Applied Energy, 209, 306-321.

Mehta, Mohit↗

NASA NTRS2020

Ion Channels – From Structure to Electrophysiology and Back

A reliable way to establish whether our understanding of a channel is satisfactory is to reproduce its measured ionic conductance over a broad range of applied voltages in computer simulations. In molecular dynamics (MD), this can be done by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. Since this approach is computationally very expensive, we have developed a markedly more efficient alternative in which MD is combined with the electrodiffusion (ED) equation. In this approach, the assumptions of the ED equation can be rigorously tested, and the precision and consistency of the calculated conductance can be determined. We have demonstrated that the full current/voltage dependence and the underlying free energy profile for a simple channel can be reliably calculated from equilibrium or non-equilibrium MD simulations at a single voltage. Free energy profiles can be obtained from non-equilibrium simulations without a loss of accuracy even without the knowledge of diffusion coefficient. To carry out MD simulations, a structural model of a channel has to be assumed, which is an important constraint, considering that high-resolution structures are available for only very few simple channels. If the comparison of calculated ionic conductance with electrophysiological data is satisfactory, it greatly increases our confidence that the structure and the function are described sufficiently accurately. We examined the validity of the ED for several channels embedded in phospholipid membranes - four naturally occurring channels: trichotoxin, alamethicin, p7 from hepatitis C virus (HCV) and Vpu from the HIV-1 virus, a synthetic, hexameric channel, formed by a 21-residue peptide that contains only leucine and serine and a bacterial pentameric ligand-gated ion channel, GLIC. All these channels mediate transport of potassium and chloride ions. It was found that the ED equation is satisfactory for these systems. In some of them, experimental and calculated electrophysiological properties are in good agreement, whereas in others there are strong indications that the structural models are incorrect.

Pohorille, Andrew↗

NASA NTRS2019

Toward Ultralight High Strength Structural Materials via Collapsed Carbon Nanotube Bonding

The growing commercial availability of carbon nanotube (CNT) macro-assemblies such as sheet and yarn is making their use in structural composite components increasingly feasible. However, the mechanical properties of these materials continue to trail those of state-of-the-art carbon fiber composites due to relatively weak inter-tube load transfer. Forming covalent links between adjacent CNTs promises to mitigate this problem, but it has proven difficult in practice to introduce them chemically within densified and aligned CNT materials due to their low permeability. To avoid this limitation, this work explores the combination of pulsed electrical current, temperature, and pressure to introduce inter-CNT bonds. Reactive molecular dynamics simulations identify the most probable locations, configurations, and conditions for inter-nanotube bonds to form. This process is shown to introduce covalent linkages within the CNT material that manifest as improved macroscale mechanical properties. The magnitude of this effect increases with increasing levels of prealignment of the CNT material, promising a new synthesis pathway to ultralight structural materials with specific strengths and stiffnesses exceeding 1 and 100 GPa/(g/cu.cm), respectively.

Jensen, Benjamin D.↗

NASA NTRS2019

Physically-Informed Artificial Neural Networks for Atomistic Modeling of Materials

A new approach is presented for the development of classical interatomic potentials using physically-informed neural networks (PINN) combined with an analytical bond-order atomic interaction model. Due to the strong physical underpinnings, the PINN potentials demonstrate much better transferability than the existing machine-learning potentials while drastically improving the accuracy in comparison with traditional potentials. PINN potentials can be constructed for both metallic and covalent materials in a unified manner. A number of applications of PINN potentials to large-scale molecular dynamics and Monte Carlo simulations and calculation of thermal and mechanical properties of diverse materials are demonstrated. Some of the specific materials systems include silicon and aluminum, as well as alloys and compounds. Computational aspects of PINN potentials are discussed and future developments in this field are outlined.

J Hickman↗

NASA NTRS2020

A Multiscale Cohesive Law for Carbon Fiber Networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. Here, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

W. SCHILL↗

NASA NTRS2022

Simulating the Diffusion of Hydrogen in Amorphous Silicates: A ‘Jumping’ Migration Process and its Implications for Solar Wind Implanted Lunar Volatiles

We use molecular dynamics (MD) simulations to better explain the movement of atomic hydrogen in amorphous silica and quantify the planetary science implications of these findings. Previous MD simulations had a large range of predicted values and did not agree well with experiment. Our simulations sample atomic motion for a longer duration and consider a wider range of temperatures than previous simulations. In contrast to constant atomic motion, the hydrogen atoms were shown to undergo random intermittent jumps from one oxygen atom to another, the number of which increase with temperature. Predicted diffusion coefficients had a better agreement to experimental values than previous MD simulations, suggesting the importance of longer simulation durations for better statistics. The low activation energy and jumps observed at lunar temperatures do not support the theory of diurnal variations in OH content for an undamaged amorphous silica surface. Instead, we conclude that energetic solar wind impacts can induce two competing atomic hydrogen motion processes in the exposed surface: A prompt effect that induces jumps in the temperature spike volume, but also a long term effect of damage in the structure that traps atomic hydrogen. We then use SDTrimSP to quantify the damage created during exposure and MD to demonstrate the H retention and trapping near these defects. Damage was shown to be dependent on impact energy, with defects easily retaining implanted hydrogen. MD results like those presented herein on unweathered surfaces are therefore most relevant to magnetic anomalies. As a result, we demonstrate the importance of lunar volatile models to account for the damage state of the substrate when modelling hydrogen diffusion, retention, and subsequent OH/water production.

Liam S. Morrissey↗

NASA NTRS2022

Free Energy Landscapes for Elucidating the Structural Consequences of Exon-20 mutations on the ErbB Family of Protein Kinases

The ErbB family of protein kinases plays an important role in major cellular functions and consequently mutations in the functional regions of these proteins are implicated in several types of cancer growths. To envision rational design of small molecule drugs that target the diseased proteins it is important to quantify the structural effects of the mutations, as some of these mutants render the protein resistant to tyrosine kinase inhibitors (TKIs). Herein we use advanced sampling techniques and long-timescale molecular dynamics simulations to predict the effect of major exon 20 mutations on the ErbB family, specifically EGFR and HER2 proteins. Exon 20 mutations have been clinically known to induce TKI resistance, though the mechanisms of such an effect is poorly understood. By mapping out the free energy landscape of the mutants and comparing them against the wild-type, we elucidate the structural differences in the binding pocket region that alter the nature of drug-protein interactions. We believe that these insights will play a pivotal role in developing small molecule drugs that overcome the TKI resistance.

Ashwin Ravichandran↗

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 gamma prime 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-superalloys↗

NASA NTRS2022

The Influence of surface binding energy on sputtering in models of the sodium exosphere of Mercury

We have simulated the sodium (Na) exosphere of Mercury to show how the exosphere is affected by the assumed surface binding energy (SBE) of Na in the sputtered component. We constrained ion precipitation onto the surface using distributions for the cusp regions that are consistent with measurements by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging Fast Imaging Plasma Spectrometer instrument. We have simulated sputtering with SBEs of 0.27, 2.6, 4.4, and 7.9 eV, with the lowest value commonly used in exosphere models and the highest from recent molecular dynamics calculations for the Na-bearing feldspar end-member, albite. A gradual change in the exosphere is seen as the yield decreases and the ejecta energy increases with increasing SBE. We describe the corresponding exosphere source functions for ion sputtering (IS), as well as for the previously studied processes of micrometeoroid impact vaporization and photon-stimulated desorption (PSD), along with their release energy distributions and spatial distributions. We have summed the contributions of the various source processes to explain how and when the different sources can be distinguished by observations. The modeled exosphere scale heights range from 72 km for PSD to over 1000 km for IS using a SBE of 7.9 eV. We find that the processes responsible for generating Mercury's Na exosphere are separable by measuring line-of-sight column densities tangent to the planet at various altitudes and positions around the planet. Our initial results are consistent with the Na being sputtered from a high-SBE material such as feldspar, which has been predicted to be abundant on the Mercury's surface.

Rosemary M. Killen↗

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

Overview of Ablative TPS Modeling at NASA Ames

Over the past decade, NASA has invested in efforts to build predictive thermal protection system (TPS) material models from the micro-scale to the macro-scale. To complement the mission design cycle process and reduce the need for extensive testing, NASA is developing modeling and simulation tools that enable characterizing material properties and response to hot plasma experienced during atmospheric entry. Traditional material response and ablation modeling tools, such as the heritage code FIAT, and its multidimensional siblings, TITAN and 3dFIAT, are being complemented with newly developed software such as Icarus and PATO. Both of these programs are three-dimensional, finite-volume solvers that use unstructured meshes and 21st century programming paradigms to allow for efficient parallel simulations. FIAT and Icarus are also used for TPS sizing purposes. Today, these traditional tools are being supplemented with computational materials models at the atomistic level. The scales of interest range from computational chemistry (Density Functional Theory [DFT]), to atomistic simulations (Molecular Dynamics [MD]), to the microscale with the Porous Microstructure Analysis (PuMA) software that was recently awarded the 2022 NASA Software of the Year award. Finally, thermo-structural modeling is also of interest to the TPS Materials branch and done using commercial tools such as MSC MARC, MENTAT, NASTRAN and PATRAN. The present talk will also link the use of these computational tools to current NASA missions and projects associated with challenging and complex vehicles entries/reentries.

materials modeling↗

NASA NTRS2022

Resolving the fine structure in the energy landscapes of repeat proteins

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.

Murilo N. Sanches↗