Theoretical performance of hydrogen-bromine rechargeable SPE fuel cell

A mathematical model was formulated to describe the performance of a hydrogen-bromine fuel cell. Porous electrode theory was applied to the carbon felt flow-by electrode and was coupled to theory describing the solid polymer electrolyte (SPE) system. Parametric studies using the numerical solution to this model were performed to determine the effect of kinetic, mass transfer, and design parameters on the performance of the fuel cell. The results indicate that the cell performance is most sensitive to the transport properties of the SPE membrane. The model was also shown to be a useful tool for scale-up studies

Network Analysis of Intermediary Metabolism Using Linear Optimization. I. Development of Mathematical Formalism

Analysis of metabolic networks using linear optimization theory allows one to quantify and understand the limitations imposed on the cell by its metabolic stoichiometry, and to understand how the flux through each pathway influences the overall behavior of metabolism. A stoichiometric matrix accounting for the major pathways involved in energy and mass transformations in the cell was used in our analysis. The auxiliary parameters of linear optimization, the so-called shadow prices, identify the intermediates and cofactors that cause the growth to be limited on each nutrient. This formalism was used to examine how well the cell balances its needs for carbon, nitrogen, and energy during growth on different substrates. The relative values of glucose and glutamine as nutrients were compared by varying the ratio of rates of glucose to glutamine uptakes, and calculating the maximum growth rate. The optimum value of this ratio is between 2-7, similar to experimentally observed ratios. The theoretical maximum growth rate was calculated for growth on each amino acid, and the amino acids catabolized directly to glutamate were found to be the optimal nutrients. The importance of each reaction in the network can be examined both by selectively limiting the flux through the reaction, and by the value of the reduced cost for that reaction. Some reactions, such as malic enzyme and glutamate dehydrogenase, may be inhibited or deleted with little or no adverse effect on the calculated cell growth rate

Optimal Selection of Metabolic Fluxes for in Vivo Measurement. I. Development of Mathematical Methods

The measurement of uptake and secretion rates is often not sufficient to allow the calculation of all internal metabolic fluxes. Measurements of internal fluxes are needed and these additional measurements are used in conjunction with mass-balance equations to calculate the complete metabolic flux map. A method is presented that identifies the fluxes that should be selected for experimental measurement, and the fluxes that can be computed using the mass-balance equations. The criterion for selecting internal metabolic fluxes for measurement is that the values of the computed fluxes should have low sensitivity to experimental error in the measured fluxes. A condition number indicating the upper bound on this sensitivity, is calculated based on stoichiometry alone. The actual sensitivity is dependent on both the flux measurements and the error in flux measurements, as well as the stoichiometry. If approximate physiologic ranges of fluxes are known a realistic sensitivity can be computed. The exact sensitivity cannot be calculated since the experimental error is usually unknown. The most probable value of the actual sensitivity for a given selection of measured fluxes is estimated by selecting a large number of representative error vectors and calculating the actual sensitivity for each of these. A frequency distribution of actual sensitivities is thus obtained giving a representative range of actual sensitivities for a particular experimental situation

Optimal Selection of Metabolic Fluxes for in Vivo Measurement. I. Development of Mathematical Methods

The measurement of uptake and secretion rates is often not sufficient to allow the calculation of all internal metabolic fluxes. Measurements of internal fluxes are needed and these additional measurements are used in conjunction with mass-balance equations to calculate the complete metabolic flux map. A method is presented that identifies the fluxes that should be selected for experimental measurement, and the fluxes that can be computed using the mass-balance equations. The criterion for selecting internal metabolic fluxes for measurement is that the values of the computed fluxes should have low sensitivity to experimental error in the measured fluxes. A condition number indicating the upper bound on this sensitivity, is calculated based on stoichiometry alone. The actual sensitivity is dependent on both the flux measurements and the error in flux measurements, as well as the stoichiometry. If approximate physiologic ranges of fluxes are known a realistic sensitivity can be computed. The exact sensitivity cannot be calculated since the experimental error is usually unknown. The most probable value of the actual sensitivity for a given selection of measured fluxes is estimated by selecting a large number of representative error vectors and calculating the actual sensitivity for each of these. A frequency distribution of actual sensitivities is thus obtained giving a representative range of actual sensitivities for a particular experimental situation

Optimal Selection of Metabolic Fluxes for in vivo Measurement. II. Application to Escherichia coli and Hybridoma Cell Metabolism

A method of analysis was presented in part I of this series for determining the fluxes in a biochemical network that are the optimal choices for experimental measurement. This algorithm is applied to two important biological models: Escherichia coli and a hybridoma cell line (167.4G5.3). Our results show that potentially poor choices for in vivo measurement of metabolic fluxes exist for both model systems. For the subset of reactions in E. coli that was studied, the condition number of the augmented stoichiometric matrix reveals that a 60-fold amplification of experimental error during computations is possible. The biochemical network of the hybridoma cell is more compelex than the E. coli system, and thus results in much larger possible error amplification—up to 100 000-fold. The physiological situations appear to have sensitivities that are less than 1/4 to 1/10 of those estimated by the condition number, and the maximum sensitivities are proportional to the condition number. These maximum sensitivities calculated using estimates of the fluxes and the worst possible error vector are upper bounds on the system\u27s actual sensitivity. By examining the effect of measurement error on the sensitivity, the most probable sensitivity is calculated. These results indicate that an approximate two-fold increase in sensitivity of the E. coli system is likely when the worst set of fluxes are measured rather than the best set. The most likely sensitivity of the hybridoma system can range three orders of magnitude, depending on the set of fluxes that are measured. The propagation of experimental error during computations can be diminished for both systems by increasing the number of flux measurements over and above the minimum number of experimental measurements. The findings from these two model systems indicate that the calculation of the condition number can be a useful method for efficient experimental design, and that the usefulness of this method increases as the order of the system increases

Network Analysis of Intermediary Metabolism Using Linear Optimization. II. Interpretation of Hybridoma Cell Metabolism

Analysis of metabolic networks using linear optimization theory allows one to quantify and understand the limitations imposed on the cell by its metabolic stoichiometry, and to understand how the flux through each pathway influences the overall behavior of metabolism. A stoichiometric matrix accounting for the major pathways involved in energy and mass transformations in the cell was used in our analysis. The auxiliary parameters of linear optimization, the so-called shadow prices, identify the intermediates and cofactors that cause the growth to be limited on each nutrient. This formalism was used to examine how well the cell balances its needs for carbon, nitrogen, and energy during growth on different substrates. The relative values of glucose and glutamine as nutrients were compared by varying the ratio of rates of glucose to glutamine uptakes, and calculating the maximum growth rate. The optimum value of this ratio is between 2–7, similar to experimentally observed ratios. The theoretical maximum growth rate was calculated for growth on each amino acid, and the amino acids catabolized directly to glutamate were found to be the optimal nutrients. The importance of each reaction in the network can be examined both by selectively limiting the flux through the reaction, and by the value of the reduced cost for that reaction. Some reactions, such as malic enzyme and glutamate dehydrogenase, may be inhibited or deleted with little or no adverse effect on the calculated cell growth rate

Network Analysis of Intermediary Metabolism Using Linear Optimization. I. Development of Mathematical Formalism

Analysis of metabolic networks using linear optimization theory allows one to quantify and understand the limitations imposed on the cell by its metabolic stoichiometry, and to understand how the flux through each pathway influences the overall behavior of metabolism. A stoichiometric matrix accounting for the major pathways involved in energy and mass transformations in the cell was used in our analysis. The auxiliary parameters of linear optimization, the so-called shadow prices, identify the intermediates and cofactors that cause the growth to be limited on each nutrient. This formalism was used to examine how well the cell balances its needs for carbon, nitrogen, and energy during growth on different substrates. The relative values of glucose and glutamine as nutrients were compared by varying the ratio of rates of glucose to glutamine uptakes, and calculating the maximum growth rate. The optimum value of this ratio is between 2-7, similar to experimentally observed ratios. The theoretical maximum growth rate was calculated for growth on each amino acid, and the amino acids catabolized directly to glutamate were found to be the optimal nutrients. The importance of each reaction in the network can be examined both by selectively limiting the flux through the reaction, and by the value of the reduced cost for that reaction. Some reactions, such as malic enzyme and glutamate dehydrogenase, may be inhibited or deleted with little or no adverse effect on the calculated cell growth rate

Nano-crystalline porous tin oxide film for carbon monoxide sensing

A tin oxide sol is deposited on platinum electrodes (12) of a sensor (10). The sol is calcined at a temperature of 500 to 800.degree. C. to produce a thin film of tin oxide with a thickness of about 150 nm to 2 .mu. and having a nano-crystalline structure with good stability. The sensor rapidly detects reducing gases, such as carbon monoxide, or hydrocarbons and organic vapors. Sensors using films calcined at around 700.degree. C. have high carbon monoxide selectivity with a response time of around 4 minutes and a recovery time of 1 minute, and therefore provide good detection systems for detection of trace amounts of pollutants such as toxic and flammable gases in homes, industrial settings, and hospitals

Electrode Kinetics of Vanadium Flow Batteries: Contrasting Responses of V\u3csup\u3eII\u3c/sup\u3e-V\u3csup\u3eIII\u3c/sup\u3e and V\u3csup\u3eIV\u3c/sup\u3e-V\u3csup\u3eV\u3c/sup\u3e to Electrochemical Pretreatment of Carbon

Electrochemical impedance spectroscopy and cyclic voltammetry were used to investigate the electrode kinetics of VII-VIII and VIV-VV in H2SO4 on glassy carbon, carbon paper, carbon xerogel, and carbon fibers. It was shown that, for all carbon materials investigated, the kinetics of VII-VIII is enhanced by anodic, and inhibited by cathodic, treatment of the electrode; in contrast, the kinetics of VIV-VV is inhibited by anodic, and enhanced by cathodic, treatment. The potential region for each of these effects varied only slightly with carbon material. Rate constants were always greater for VIV-VV than for VII-VIII except when anodized electrodes were compared, which may explain discrepancies in the literature. The observed effects are attributed to oxygen-containing functional-groups on the electrode surface. The considerable differences between the potentials at which enhancement of VII-VIII and inhibition of VIV-VV occur indicates that they do not correspond to a common oxidized state of the electrode. Likewise inhibition of VII-VIII and enhancement of VIV-VV do not correspond to a common reduced state of the electrode. It is possible that enhancement of both VII-VIII and VIV-VV is due to the same (active) state of the electrode