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NASA NTRS1978

Some studies on a solid-state sulfur probe for coal gasification systems

As a part of a program for the development of a sulfur probe for monitoring the sulfur potential in coal gasification reactors, an investigation was conducted regarding the efficiency of the solid electrolyte cell Ar+H2+H2S/CaS+CaF2+(Pt)//CaF2//Pt)+CaF2+CaS/H2S+H2+Ar. A demonstration is provided of the theory, design, and operation of a solid-state sulfur probe based on CaF2 electrolyte. It was found that the cell responds to changes in sulfur potential in a manner predicted by the Nernst equation. The response time of the cell at 1225 K, after a small change in temperature or gas composition, was 2.5 Hr, while at a lower temperature of 990 K the response time was approximately 9 hr. The cell emf was insensitive to a moderate increase in the flow rate of the test gas and/or the reference gas. The exact factors affecting the slow response time of galvanic cells based on a CaF2 electrolyte have not yet been determined. The rate-limiting steps may be either the kinetics of electrode reactions or the rate of transport through the electrolyte.

Jacob, K. T.↗

NASA NTRS2013

Conductance of Ion Channels - Theory vs. Experiment

Transmembrane ion channels mediate a number of essential physiological processes in a cell ranging from regulating osmotic pressure to transmission of neural signals. Kinetics and selectivity of ion transport is of critical importance to a cell and, not surprisingly, it is a subject of numerous experimental and theoretical studies. In this presentation we will analyze in detail computer simulations of two simple channels from fungi - antiamoebin and trichotoxin. Each of these channels is made of an alpha-helical bundle of small, nongenomically synthesized peptides containing a number of rare amino acids and exhibits strong antimicrobial activity. We will focus on calculating ionic conductance defined as the ratio of ionic current through the channel to applied voltage. From molecular dynamics simulations, conductance can be calculated in at least two ways, each involving different approximations. Specifically, the current, given as the number of charges transferred through the channel per unit of time, can be obtained from the number of events in which ions cross the channel during the simulation. This method works well for large currents (high conductance values and/or applied voltages). If the number of crossing events is small, reliable estimates of current are difficult to achieve. Alternatively, conductance can be estimated assuming that ion transport can be well approximated as diffusion in the external potential given by the free energy profile. Then, the current can be calculated by solving the one-dimensional diffusion equation in this external potential and applied voltage (the generalized Nernst-Planck equation). To do so three ingredients are needed: the free energy profile, the position-dependent diffusion coefficient and the diffusive flux of ions into the channel. All these quantities can be obtained from molecular dynamics simulations. An important advantage of this method is that it can be used equally well to estimating large and small currents. In addition, once the free energy profile becomes available the full current-voltage dependence can be readily obtained. For both channels we carried out calculations using both approaches. We also tested the main assumptions underlying the diffusive model, such as uncorrelated nature of individual crossing events and Fickian diffusion. The accuracy and consistency of different methods will be discussed. Finally we will discuss how comparisons between calculated and measured ionic conductance and selectivity of transport can be used for determining structural models of the channels.

Pohorille, Andrew↗

NASA NTRS2012

Non-Equilibrium Properties from Equilibrium Free Energy Calculations

Calculating free energy in computer simulations is of central importance in statistical mechanics of condensed media and its applications to chemistry and biology not only because it is the most comprehensive and informative quantity that characterizes the eqUilibrium state, but also because it often provides an efficient route to access dynamic and kinetic properties of a system. Most of applications of equilibrium free energy calculations to non-equilibrium processes rely on a description in which a molecule or an ion diffuses in the potential of mean force. In general case this description is a simplification, but it might be satisfactorily accurate in many instances of practical interest. This hypothesis has been tested in the example of the electrodiffusion equation . Conductance of model ion channels has been calculated directly through counting the number of ion crossing events observed during long molecular dynamics simulations and has been compared with the conductance obtained from solving the generalized Nernst-Plank equation. It has been shown that under relatively modest conditions the agreement between these two approaches is excellent, thus demonstrating the assumptions underlying the diffusion equation are fulfilled. Under these conditions the electrodiffusion equation provides an efficient approach to calculating the full voltage-current dependence routinely measured in electrophysiological experiments.

Pohorille, Andrew↗

NASA NTRS1995

A universal steady state I-V relationship for membrane current

A purely electrical mechanism for the gating of membrane ionic channel gives rise to a simple I-V relationship for membrane current. Our approach is based on the known presence of gating charge, which is an established property of the membrane channel gating. The gating charge is systematically treated as a polarization of the channel protein which varies with the external electric field and modifies the effective potential through which the ions migrate in the channel. Two polarization effects have been considered: 1) the up or down shift of the whole potential function, and 2) the change in the effective electric field inside the channel which is due to familiar effect of the effective reduction of the electric field inside a dielectric body because of the presence of surface charges on its surface. Both effects are linear in the channel polarization. The ionic current is described by a steady state solution of the Nernst-Planck equation with the potential directly controlled by the gating charge system. The solution describes reasonably well the steady state and peak-current I-V relationships for different channels, and when applied adiabatically, explains the time lag between the gating charge current and the rise of the ionic current. The approach developed can be useful as an effective way to model the ionic currents in axons, cardiac cells and other excitable tissues.

NASA Discipline Regulatory Physiology↗

NASA NTRS2005

Removal of organic contaminants by RO and NF membranes

Rejection characteristics of organic and inorganic compounds were examined for six reverse osmosis (RO) membranes and two nanofiltration (NF) membranes that are commercially available. A batch stirred-cell was employed to determine the membrane flux and the solute rejection for solutions at various concentrations and different pH conditions. The results show that for ionic solutes the degree of separation is influenced mainly by electrostatic exclusion, while for organic solutes the removal depends mainly upon the solute radius and molecular structure. In order to provide a better understanding of rejection mechanisms for the RO and NF membranes, the ratio of solute radius (r(i,s)) to effective membrane pore radius (r(p)) was employed to compare rejections. An empirical relation for the dependence of the rejection of organic compounds on the ratio r(i,s)/r(p) is presented. The rejection for organic compounds is over 75% when r(i,s)/r(p) is greater than 0.8. In addition, the rejection of organic compounds is examined using the extended Nernst-Planck equation coupled with a steric hindrance model. The transport of organic solutes is controlled mainly by diffusion for the compounds that have a high r(i,s)/r(p) ratio, while convection is dominant for compounds that have a small r(i,s)/r(p) ratio. c2005 Elsevier B.V. All rights reserved.

NASA Discipline Life Sciences Technologies↗

NASA NTRS2011

Molecular Dynamics Simulation of the Antiamoebin Ion Channel: Linking Structure and Conductance

Molecular dynamics simulations were carried out in order to ascertain which of the potential multimeric forms of the transmembrane peptaibol channel, antiamoebin, is consistant with its measured conductance. Estimates of the conductance obtained through counting ions that cross the channel and by solving the Nernst-Planck equation yield consistent results, indicating that the motion of ions inside the channel can be satisfactorily described as diffusive.The calculated conductance of octameric channels is markedly higher than the conductance measured in single channel recordings, whereas the tetramer appears to be non-conducting. The conductance of the hexamer was estimated to be 115+/-34 pS and 74+/-20 pS, at 150 mV and 75 mV, respectively, in satisfactory agreement with the value of 90 pS measured at 75 mV. On this basis we propose that the antiamoebin channel consists of six monomers. Its pore is large enough to accommodate K(+) and Cl(-) with their first solvation shells intact. The free energy barrier encountered by K(+) is only 2.2 kcal/mol whereas Cl(-) encounters a substantially higher barrier of nearly 5 kcal/mol. This difference makes the channel selective for cations. Ion crossing events are shown to be uncorrelated and follow Poisson statistics. keywords: ion channels, peptaibols, channel conductance, molecular dynamics

Wilson, Michael A.↗

NASA NTRS2023

Multiphysics Modeling of Electrode Dissolution under Hydrodynamic Conditions in Low Conductivity Water

Efficient plug-flow electrochemical reactors are characterized by their ability to effectively convert species with significant ionic strength and/or with the assistance of a well-behaved electrolyte. Because of the classic electroconductivity requirement, electrochemical reactors are not particularly attractive options for applications with low-conductivity conditions, especially for low-pressure feeds. However, these reactors can still find application in dedicated processes such as ultra-clean water conditioning and biological-coupled separation systems. Consequently, a multi-physics model was developed using COMSOL Multiphysics to characterize different reactor-design conditions based on the Tertiary Current Distribution which accounts for the effects of expected variations in electrolyte composition and ionic strength on the electrochemical process, as well as solution resistance and electrode kinetics. The modelling framework presented here employs single-phase laminar fluid flow, the Nernst-Planck equation, the water-based electroneutrality condition, and concentration-dependent overpotentials. This investigation particularly explores the electrolysis process of “anodic dissolution,” in which elemental species dissociate from the solid matrix of the electrode and enter the liquid phase of the electrolyte as soluble ions. The reactor configuration of interest has a rectangular parallel-electrode design and is operated galvanostatically. A series of parametric studies are carried out to inspect the response of the system when hydrodynamic, kinetic, and geometric conditions are changed. The parametric sweep resulted in variable effluent concentrations and system voltage, which reveal underlaying optimization patterns for electrode dissolution in low conductivity water.

Multiphysics↗

NASA NTRSDate not supplied

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery↗