Ionic liquids are a unique class of materials with several potential applications in electrochemical energy storage. When used in electrolytes, these highly coordinating solvents can influence device performance through their high viscosities and strong solvation behaviors. In this work, we explore the effects of pyrrolidinium cation structure and Li+ concentration on transport processes in ionic liquid electrolytes. We present correlated experimental measurements and molecular simulations of Li+ mobility and O2 diffusivity, and connect these results to dynamic molecular structural information and device performance. In the context of Li-O2/Li-air battery chemistries, we find that Li+ mobility is largely influenced by Li+-anion coordination, but that both Li+ and O2 diffusion may be affected by variations of the pyrrolidinium cation and Li+ concentration.
This study examines channeling, multiple scattering, and neutralization/re-ionization of ions scattered along the stepped Al(332) plane. Our experimental approach involves probing the surface with 1–2 keV He+ and Ne+ beams, and then systematically mapping the scattered ion fluxes over a large solid angle. This provides comprehensive ion channeling information over all directions, rather than along a few low-index azimuths, as is common practice in ion scattering spectroscopy. We first probe the surface with 2 keV He+ at near-normal incidence, and then map the backscattered particle flux (both ions and neutrals) via time of flight (TOF) spectrometry. The features contained in these maps can be correlated with axial and inter-planar channeling effects, and are reproduced well via binary collision simulations. Sensitivity to the stepped surface topography is heightened considerably for oblique ion incidence in the forward-scattering direction. In this geometry, we used 2 keV Ne+ to probe the surface and mapped the corresponding scattered fluxes of both single and multiply-charged ions. In both cases, the scattering intensity depends strongly on the precise trajectory taken along the surface, and is particularly sensitive to how extensively the incident ions interact with the step edges. We interpret the information contained in these maps by considering several mechanisms for charge transfer and double ion production. The formation of Ne++ appears to be correlated with a previously observed inelastic mechanism that occurs when the collision apsis, Rmin, is less than 0.65 Å. This contributes to an energy loss of 48 ± 8 eV for Ne+ undergoing single scattering; the Rmin threshold for this inelastic step coincides with the emergence of a distinct Ne++ peak. Using the information gained from the maps, we propose methods for extending this approach to chemisorbed layers.
The moisture absorption behavior of two fiber reinforced composite materials was evaluated in a unidirectional manner The flat materials were exposed to varying humidity and temperature conditions inside of an environmental chamber in order to determine their effective moisture equilibrium (M m ) and moisture absorption rate (D z ). Two-ply (thin) and four-ply (thick) materials were utilized to obtain M,,, and Dz, respectively. The results obtained from laboratory work were then compared to modeling data to better understand the material properties. Predictions capabilities were built to forecast the maximum moisture content, time required for saturation, and the moisture content at any given humidity and temperature. A case study was included to demonstrate this capability. Also of interest were cubed samples to investigate directionality preferences in water immersion studies. Several coatings were evaluated for their water permeation properties. Further dissemination authorized to the Department of Energy and DOE contractors only; other requests shall be approved by the originating facility or higher DOE programmatic authority.
Defect formation in LiF, which is used as an observation window in ramp and shock experiments, has significant effects on its transmission properties. Given the extreme conditions of the experiments it is hard to measure the change in transmission directly. Using molecular dynamics, we estimate the change in conductivity as a function of the concentration of likely point and extended defects using a Green-Kubo technique with careful treatment of size effects. With this data, we form a model of the mean behavior and its estimated error; then, we use this model to predict the conductivity of a large sample of defective LiF resulting from a direct simulation of ramp compression as a demonstration of the accuracy of its predictions. Given estimates of defect densities in a LiF window used in an experiment, the model can be used to correct the observations of thermal energy through the window. In addition, the methodology we develop is extensible to modeling, with quantified uncertainty, the effects of a variety of defects on the thermal conductivity of solid materials.
Al-Based Al-Cu alloys have a very high strength to density ratio, and are therefore important materials for transportation systems including vehicles and aircrafts. These alloys also appear to have a high resistance to hydrogen embrittlement, and as a result, are being explored for hydrogen related applications. To enable fundamental studies of mechanical behavior of Al-Cu alloys under hydrogen environments, we have developed an Al-Cu-H bond-order potential according to the formalism implemented in the molecular dynamics code LAMMPS. Our potential not only fits well to properties of a variety of elemental and compound configurations (with coordination varying from 1 to 12) including small clusters, bulk lattices, defects, and surfaces, but also passes stringent molecular dynamics simulation tests that sample chaotic configurations. Careful studies verified that this Al-Cu-H potential predicts structural property trends close to experimental results and quantum-mechanical calculations; in addition, it properly captures Al-Cu, Al-H, and Cu-H phase diagrams and enables simulations of H2 dissociation, chemisorption, and absorption on Al-Cu surfaces.
A robust molecular-dynamics simulation method for calculating dislocation core energies has been developed. This method has unique advantages: It does not require artificial boundary conditions, is applicable for mixed dislocations, and can yield converged results regardless of the atomistic system size. Utilizing a high-fidelity bond order potential, we have applied this method in aluminium to calculate the dislocation core energy as a function of the angle β between the dislocation line and the Burgers vector. These calculations show that, for the face-centered-cubic aluminium explored, the dislocation core energy follows the same functional dependence on β as the dislocation elastic energy: Ec=Asin2β+Bcos2β, and this dependence is independent of temperature between 100 and 300 K. By further analyzing the energetics of an extended dislocation core, we elucidate the relationship between the core energy and the core radius of a perfect versus an extended dislocation. With our methodology, the dislocation core energy can accurately be accounted for in models of dislocation-mediated plasticity.
Li-air or Li-oxygen batteries promise significantly higher energies than existing commercial battery technologies, yet their development has been hindered by a lack of suitable electrolytes. In this article, we evaluate the physical properties of varied electrolyte compositions to form generalized criteria for electrolyte design. We show that oxygen transport through non-aqueous electrolytes has a critical impact on the discharge rate and capacity of Li-air batteries. Through experiments and molecular dynamics simulations, we highlight that the choice of salt species and concentration have an outsized influence on oxygen solubility, while solvent choice is the major influence on oxygen diffusivity. The stability of superoxide reaction intermediates, key to the oxygen reduction mechanism, is also affected by variations in salt concentration and the choice of solvent. The importance of reactant transport is confirmed through Li-air cell discharge, which demonstrates good agreement between the observed and calculated mass transport-limited currents. These results showcase the impact of electrolyte composition on transport in metal-air batteries and provide guiding principles and simulation-based tools for future electrolyte design.
In this work we use estimates of ionic transport properties obtained from molecular dynamics to rank lithium electrolytes of different compositions. We develop linear response methods to obtain the Onsager diffusivity matrix for all chemical species, its Fickian counterpart, and the mobilities of the ionic species. We apply these methods to the well-studied propylene carbonate/ethylene carbonate solvent with dissolved LiBF4 and O2. The results show that, over a range of lithium concentrations and carbonate mixtures, trends in the transport coefficients can be identified and optimal electrolytes can be selected for experimental focus; however, refinement of these estimation techniques is necessary for a reliable ranking of a large set of electrolytes.
Given the unique optical properties of LiF, it is often used as an observation window in high-temperature and -pressure experiments; hence, estimates of its transmission properties are necessary to interpret observations. Since direct measurements of the thermal conductivity of LiF at the appropriate conditions are difficult, we resort to molecular simulation methods. Using an empirical potential validated against ab initio phonon density of states, we estimate the thermal conductivity of LiF at high temperatures (1000-4000 K) and pressures (100-400 GPa) with the Green-Kubo method. We also compare these estimates to those derived directly from ab initio data. To ascertain the correct phase of LiF at these extreme conditions, we calculate the (relative) phase stability of the B1 and B2 structures using a quasiharmonic ab initio model of the free energy. We also estimate the thermal conductivity of LiF in an uniaxial loading state that emulates initial stages of compression in high-stress ramp loading experiments and show the degree of anisotropy induced in the conductivity due to deformation.
Carbon nanostructures, such as nanotubes and graphene, are of considerable interest due to their unique mechanical and electrical properties. The materials exhibit extremely high strength and conductivity when defects created during synthesis are minimized. Atomistic modeling is one technique for high resolution studies of defect formation and mitigation. To enable simulations of the mechanical behavior and growth mechanisms of C nanostructures, a high-fidelity analytical bond-order potential for the C is needed. To generate inputs for developing such a potential, we performed quantum mechanical calculations of various C structures.
Current austenitic stainless steel storage reservoirs for hydrogen isotopes (e.g. deuterium and tritium) have performance and operational life-limiting interactions (e.g. embrittlement) with H-isotopes. Aluminum alloys (e.g.AA2219), alternatively, have very low H-isotope solubilities, suggesting high resistance towards aging vulnerabilities. This report summarizes the work performed during the life of the Lab Directed Research and Development in the Nuclear Weapons investment area (165724), and provides invaluable modeling and experimental insights into the interactions of H isotopes with surfaces and bulk AlCu-alloys. The modeling work establishes and builds a multi-scale framework which includes: a density functional theory informed bond-order potential for classical molecular dynamics (MD), and subsequent use of MD simulations to inform defect level dislocation dynamics models. Furthermore, low energy ion scattering and thermal desorption spectroscopy experiments are performed to validate these models and add greater physical understanding to them.
In this project we developed t he atomistic models needed to predict how graphene grows when carbon is deposited on metal and semiconductor surfaces. We first calculated energies of many carbon configurations using first principles electronic structure calculations and then used these energies to construct an empirical bond order potentials that enable s comprehensive molecular dynamics simulation of growth. We validated our approach by comparing our predictions to experiments of graphene growth on Ir, Cu and Ge. The robustness of ou r understanding of graphene growth will enable high quality graphene to be grown on novel substrates which will expand the number of potential types of graphene electronic devices.