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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 37 records · Page 2

Automated potentiometric electrolyte analysis system

The feasibility is demonstrated of utilizing chemical sensing electrode technology as the basis for an automatically-controlled system for blood gas and electrolyte analyses under weightlessness conditions. The specific measurements required were pH, pCO2, sodium, chloride, potassium ions, and ionized calcium. The general electrode theory, and ion activity measurements are described along with the fluid transport package, electronics unit, and controller for the automated potentiometric analysis system.

Source record↗

Status of the Electroforming Shield Design (ESD) project

The utilization of a digital computer to augment electrodeposition/electroforming processes in which nonconducting shielding controls local cathodic current distribution is reported. The primary underlying philosophy of the physics of electrodeposition was presented. The technical approach taken to analytically simulate electrolytic tank variables was also included. A FORTRAN computer program has been developed and implemented. The program utilized finite element techniques and electrostatic theory to simulate electropotential fields and ionic transport.

Fletcher, R. E.↗

Electrical double layers at the oil/water interface

This review presents the historical development and current status of the theory of the electrical double layer at a liquid/liquid interface. It gives rigorous thermodynamic definitions of all basic concepts related to liquid interfaces and to the electrical double layer. The difference between the surface of a solid electrode and the interface of two immiscible electrolyte solutions (ITIES) is analyzed in connection to their electrical properties. The most important classical relationships for the electrical double layer are presented and critically discussed. The generalized adsorption isotherm is derived. After a short review of the classical Gouy-Chapman and Verwey-Niessen models, more recent developments of the double layer theory are presented. These include effects of variable dielectric permittivity, nonlocal electrostatics, hydration forces, the modified Poisson-Boltzmann equation and the ion-dipole plasma. The relative merits of different theories are estimated by comparing them with computer simulation of the ITIES and electrical double layer. Special attention is given to the structure of ITIES and its variation due to adsorption of ions and amphiphilic molecules.

Non-NASA Center↗

Electrodeposition of Metals in Microgravity Conditions

Metal electrodeposition may introduce various morphological variations depending on the electrolytic conditions including cell configurations. For liquid electrolytes, a precise study of these deposits may be complicated by convective motion due to buoyancy. Zero-gravity (0-G) condition provided by drop shaft or parabolic flight gives a straightforward mean to avoid this effect: we present here 0-G electrodeposition experiments, which we compare to ground experiments (1-G). Two electrochemical systems were studied by laser interferometry, allowing to measure the concentration variations in the electrolyte: copper deposition from copper sulfate aqueous solution and lithium deposition from an ionic liquid containing LiTFSI. For copper, concentration variations were in good agreement with theory. For lithium, an apparent induction time was observed for the concentration evolution at 1-G: due to this induction time and to the low diffusion coefficient in ionic liquid, the concentration variations were hardly measurable in the parabolic flight 0-G periods of 20 seconds.

Nishikawa, K.↗

Elucidation of Electrolyte Decomposition Pathways in Li--O2 Batteries using Ab Initio Computations

Li-O2 batteries offer exciting possibilities for energy-storage applications requiring higher energy content than current Li-ion battery technologies. However, development of commercial Li-O2 batteries faces many challenges including electrolyte decomposition in order to realize the full potential of this emerging technology. In this work, we present ab initio calculations that probe the role of reactive oxygen species including singlet oxygen, superoxide, and peroxides on electrolyte decomposition for potential organic electrolytes for use in Li-O2 batteries. We investigate the influence that the harsh electrochemical environment near the cathode plays in promoting electrolyte decomposition by using increasingly detailed computational models. Our results highlight existing problems with organic electrolytes for Li-O2 battery development and suggest potential design strategies for reducing electrolyte decomposition.

Li-O2 Batteries↗

A theory of electrophoresis of emulsion drops in aqueous two-phase polymer systems

An electrophoresis study has been carried out in an emulsion formed from an electrically neutral aqueous mixture of dextran and polyethylene glycol equilibrated at sufficient concentrations in the presence of electrolytes. Electrophoresis of a drop of one phase suspended in the other is observed, and the direction of the drop's motion is reversed when the disperse phase and the continuous phase are interchanged. In the presence of sulfate, phosphate, or citrate ions, an electrostatic potential difference of the order of a few mV exists between the two phases. The potential implied by the direction of the electrophoretic motion is opposite to the Donnan potential observed between the two phases. The mobility of an emulsion drop increases with the drop radius and depends on ion concentration. These results are explained in terms of a model postulating an electric dipole layer associated with a mixture of oriented polymer molecules at the surface of a drop, with a potential difference between the interiors of the two phases resulting from the unequal ion distribution.

Levine, S.↗

Fluid and electrolyte control in simulated and actual spaceflight

Effects of microgravity on body fluid distribution and electrolyte and hormonal levels of astronauts have been studied since the early manned space missions. Bedrested subjects have been used as controls to separate effects of microgravity from those of hypokinesia. These investigations have led to documentation of the physiological effects of spaceflight and to a unified theory of response to microgravity. During flight, crewmembers have decreased thirst and a net loss of body water, sodium, and potassium. These changes seem to be initiated by passive transfer of extracellular fluid resulting in increased central venous pressure (CVP), to which the homeostatic mechanisms respond. A new equilibrium state is maintained during flight; it does not change in response to negative calcium and nitrogen balances during flight. On reexposure to gravity, profound water and salt retention occurs to replete extracellular fluid. Attempts to avoid cardiac deconditioning by repleting water and salt before leaving microgravity have somewhat ameliorated postural hypotension but have had little effect on CVP, cardiac chamber size or electrolyte dynamics.

Leach, C. S.↗

A materials-informatics based study of solid electrolytes and protective coatings for Li batteries

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes and protective coatings simultaneously possessing high ionic conductivity and wide electrochemical stability has proven to be a challenge. Here, we present a data-driven approach to explore the Li compound space for promising solid electrolytes and coatings. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds by computing Li+ migration barriers using bond-valence-based pair potentials, and stability windows using density functional theory energies. Using this database, we implement machine learning models that can accurately predict migration barriers and electrochemical stability windows for any new Li compound. Through feature engineering, we ensure that our models are both accurate and interpretable. We perform feature importance analysis on our models to highlight materials properties that can be tuned for future design of coatings/electrolytes. Our database and informatics approach provide a valuable tool for the rapid discovery of new solid-state battery chemistries.

Solid state batteries↗

Decomposition of hydrazine by high frequency glow electrical discharges

Originally, de Groot et al. examined electrical conductivity phenomena in terms of the thermodynamics of irreversible processes. They considered the system to be discontinuous and calculated only the differences between the opposing ends of the process. Thus these theories are phenomenological. In the present work, thermodynamics is developed as a continuous system based on hydrodynamics and the entropy production for a thin capillary. It is shown that electroconductivity can be interpreted without difficulty. For the electric double layer, the effects of electrolytes and surface conductivity and the gap width were calculated for the Gouy model.

Suzuki, M.↗

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗

Simulations of Li+ in Ionic Liquids: Structure, Transport, and Electrochemical Windows

Ionic liquids have been proposed as candidate electrolytes for a number of electrochemical applications. The Li+ solvation structure in these liquids is of central importance to electrolyte properties, like ionic conductivity and electrochemical stability. To this point, we employ simulations at three different size scales to better understand various aspects of the interplay between Li+ solvation structure and dynamics. The smallest systems are Li(Anion)n clusters that are treated with high-accuracy density functional theory (DFT) techniques to provide insight into solvation shell structure through energetics and comparisons to experimental IRRaman spectra. Mid-range sized liquid-phase systems (12-24 ion pairs) are treated with DFT molecular dynamics (MD) to provide temperature-dependent insight into Li+ solvation structure, diffusion, and electrochemical window. The largest systems (144-216 ion pairs) are treated with polarizable MD simulations to evaluate the influence of Li-networks on structure and provide size independent values of transport properties. We perform this procedure on three technologically important ionic liquids and comment on property correlations with solvation structure.

batteries↗

Semiconductor photoelectrochemistry

Semiconductor photoelectrochemical reactions are investigated. A model of the charge transport processes in the semiconductor, based on semiconductor device theory, is presented. It incorporates the nonlinear processes characterizing the diffusion and reaction of charge carriers in the semiconductor. The model is used to study conditions limiting useful energy conversion, specifically the saturation of current flow due to high light intensity. Numerical results describing charge distributions in the semiconductor and its effects on the electrolyte are obtained. Experimental results include: an estimate rate at which a semiconductor photoelectrode is capable of converting electromagnetic energy into chemical energy; the effect of cell temperature on the efficiency; a method for determining the point of zero zeta potential for macroscopic semiconductor samples; a technique using platinized titanium dioxide powders and ultraviolet radiation to produce chlorine, bromine, and iodine from solutions containing their respective ions; the photoelectrochemical properties of a class of layered compounds called transition metal thiophosphates; and a technique used to produce high conversion efficiency from laser radiation to chemical energy.

Buoncristiani, A. M.↗

A mathematical model for the iron/chromium redox battery

A mathematical model has been developed to describe the isothermal operation of a single anode-separator-cathode unit cell in a redox-flow battery and has been applied to the NASA iron/chromium system. The model, based on porous electrode theory, incorporates redox kinetics, mass transfer, and ohmic effects as well as the parasitic hydrogen reaction which occurs in the chromium electrode. A numerical parameter study was carried out to predict cell performance to aid in the rational design, scale-up, and operation of the flow battery. The calculations demonstrate: (1) an optimum electrode thickness and electrolyte flow rate exist; (2) the amount of hydrogen evolved and, hence, cycle faradaic efficiency, can be affected by cell geometry, flow rate, and charging procedure; (3) countercurrent flow results in enhanced cell performance over cocurrent flow; and (4) elevated temperature operation enhances cell performance.

Fedkiw, P. S.↗

Theory of electrophoretic separations. I - Formulation of a mathematical model

A generally applicable model of electrophoretic processes is presented. The model describes the chemical reactions, treating the chemical processes as reactions at equilibrium and accounting for convection, conservation, diffusion, and electromigration of individual species as well as the relation between charge and potential. Conservation relations are described and simplified, taking advantage of the speed of the chemical reactions as compared to the transport processes to adapt the model to the electrophoretic processes involving weak electrolytes. As an application example, isotachophoresis in a one-dimensional column is considered in detail.

Saville, D. A.↗

The behavior of renal-regulating hormones during hypogravic stress

The regulation of fluid and electrolyte behavior during space flight is believed to be under control, in large part, of a group of hormones which have their major effects on renal excretion. The hormones studied include renin-angitensin, aldosterone, and antidiuretic hormone (ADH). The regulatory systems of these renal-regulating hormones as they act individually and in concert with each other are analyzed. The analysis is based on simulations of the mathematical model of Guyton. A generalized theory is described which accounts for both short-term and long-term behavior of this set of hormones.

Leonard, J. I.↗

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗

Hierarchical Screening for Li-Based Solid Electrolytes Using Fast, Interpretable Machine-Learned Potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates.

Materials discovery↗

New approach to the design of Schottky barrier diodes for THz mixers

Near-ideal GaAs Schottky barrier diodes especially designed for mixing applications in the THz frequency range are presented. A diode fabrication process for submicron diodes with near-ideal electrical and noise characteristics is described. This process is based on the electrolytic pulse etching of GaAs in combination with an in-situ platinum plating for the formation of the Schottky contacts. Schottky barrier diodes with a diameter of 1 micron fabricated by the process have already shown excellent results in a 650 GHz waveguide mixer at room temperature. A conversion loss of 7.5 dB and a mixer noise temperature of less than 2000 K have been obtained at an intermediate frequency of 4 GHz. The optimization of the diode structure and the technology was possible due to the development of a generalized Schottky barrier diode model which is valid also at high current densities. The common diode design and optimization is discussed on the basis of the classical theory. However, the conventional fomulas are valid only in a limited forward bias range corresponding to currents much smaller than the operating currents under submillimeter mixing conditions. The generalized new model takes into account not only the phenomena occurring at the junction such as current dependent recombination and drift/diffusion velocities, but also mobility and electron temperature variations in the undepleted epi-layer. Calculated diode I/V and noise characteristics are in excellent agreement with the measured values. Thus, the model offers the possibility of optimizing the diode structure and predicting the diode performance under mixing conditions at THz frequencies.

Jelenski, A.↗