Current-Voltage Modeling of the Enzymatic Glucose Fuel Cells
Author(s)
Vladimir Zeev Rubin
ABSTRACT
Enzymatic fuel cells produce electrical power by oxidation of renewable energy sources. An enzymatic glucose biofuel cell uses glucose as fuel and enzymes as biocatalyst, to convert biochemical energy into electrical energy. The applications which need low electrical voltages and low currents have much of the interest in developing enzymatic fuel cells. An analytical modelling of an enzymatic fuel cell should be used, while developing fuel cell, to estimate its various parameters, to attain the highest power value. In this paper an analytical model for enzymatic glucose membraneless fuel cell with direct electron transfer was developed. The adequacy of the model was estimated by comparison with fuel cells parameters. The electrical characteristics of fuel cells are interpreted using this model, based on theoretical consideration of ions transportation in solution. The influence of the hydrogen ions, glucose and enzyme concentration and also a thickness of enzyme layer on electrical parameters of a fuel cell were investigated. The electrical parameters such as a current, a voltage, a power were calculated by the model, for various parameters of the fuel cells. The model aimed to predict a hydrogen ions current, an electrical voltage and an electrical power in enzymatic fuel cell with direct electron transfer. The model reveals that increasing the rates of hydrogen ions generation and consumption leads to higher value of current, voltage and power.
Enzymatic fuel cells produce electrical power by oxidation of renewable energy sources. An enzymatic glucose biofuel cell uses glucose as fuel and enzymes as biocatalyst, to convert biochemical energy into electrical energy. The applications which need low electrical voltages and low currents have much of the interest in developing enzymatic fuel cells. An analytical modelling of an enzymatic fuel cell should be used, while developing fuel cell, to estimate its various parameters, to attain the highest power value. In this paper an analytical model for enzymatic glucose membraneless fuel cell with direct electron transfer was developed. The adequacy of the model was estimated by comparison with fuel cells parameters. The electrical characteristics of fuel cells are interpreted using this model, based on theoretical consideration of ions transportation in solution. The influence of the hydrogen ions, glucose and enzyme concentration and also a thickness of enzyme layer on electrical parameters of a fuel cell were investigated. The electrical parameters such as a current, a voltage, a power were calculated by the model, for various parameters of the fuel cells. The model aimed to predict a hydrogen ions current, an electrical voltage and an electrical power in enzymatic fuel cell with direct electron transfer. The model reveals that increasing the rates of hydrogen ions generation and consumption leads to higher value of current, voltage and power.
Cite this paper
Rubin, V. (2015) Current-Voltage Modeling of the Enzymatic Glucose Fuel Cells. Advances in Chemical Engineering and Science, 5, 164-172. doi: 10.4236/aces.2015.52018.
Rubin, V. (2015) Current-Voltage Modeling of the Enzymatic Glucose Fuel Cells. Advances in Chemical Engineering and Science, 5, 164-172. doi: 10.4236/aces.2015.52018.
References
[1] Rubin, Z. and Mor, L. (2008) Electrode Resistance Dependence on Alkaline Glucose Fuel Cell Electrolyte Concentration. Proceedings of the International Conference of Fundamentals and Developments of Fuel Cells, Nancy, December 2008, 115-116. [2] Bubis, E., Mor, L., Sabag, N., Rubin, Z., Vaysban, U., et al. (2006) Electrical Characterization of a Glucose-Fueled Alkaline Fuel Cell. Proceedings of the 4th International ASME Conference on Fuel Cell Science, Engineering and Technology, FuelCell2006, Irvine, Vol. 2006, 8p. [3] Mor, L., Rubin, Z. and Schechner, P. (2008) Measuring Open Circuit Voltage in Glucose Alkaline Fuel Cell Operated as a Continuous Stirred Tank Reactor. Journal of Fuel Cell Science and Technology, 5, Article ID: 014503. [4] Rubin, V.(Z.) and Mor, L. (2013) Physical Models of the Conductivity in Glucose Alkaline Fuel Cell. ECS Transactions, 45, 245-257 [5] Mor, L. and Rubin, V.(Z.) (2012) Experimental and Theoretical Considerations of Electrolyte Conductivity in Glucose Alkaline Fuel Cell. Sircuites and Systems, 3, 111-117. [6] Ge, J., Schirhagl, R. and Zare, R.N. (2011) Glucose-Driven Fuel Cell Constructed from Enzymes and Filter Paper. Journal of Chemical Education, 5, 1283-1286.
http://dx.doi.org/10.1021/ed100967j [7] Ivanov, I., Vidacovic-Koch, T. and Sundmacher, K. (2010) Recent Advances in Enzymatic Fuel Cells: Experiments and Modeling. Energies, 3, 803-846.
http://dx.doi.org/10.3390/en3040803 [8] Rubin, V.(Z.) and Mor, L. (2013) Physical Modelling of the Enzymatic Glucose Fuelled Fuel Cell. Advances in Chemical Engineering and Science, 3, 218-226.
http://dx.doi.org/10.4236/aces.2013.34028 [9] Shukla, A.K., Suresh, P., Berchmants, S. and Rajendran, A. (2004) Biilogical Fuel Cells and Their Applications. Current Science, 87, 425-467. [10] Zebda, A., Gondran, C., Le Goff, A., Holzinger, M., Cinquin, P. and Cosnier, S. (2011) Mediatorless High-Power Glucose Biofuel Cells Based on Compressed Carbon Nanotube-Enzyme Electrodes. Nature Communications, 2, Article Number: 370. [11] Fapyane, D., Lee, S.J., Kang, S.H., Lim, D.H., Cho, K.K., Nam, T.H., Ahn, J.P., Ahn, J.H., Kim, S.W. and Chang, I.S. (2013) High Performance Enzyme Fuel Cells Using a Genetically Expressed FAD-Dependent Glucose Dehydrogenase α-Subunit of Burkholderia cepacia Immobilized in a Carbon Nanotube Electrode for Low Glucose Conditions. Physical Chemistry Chemical Physics, 15, 9508-9512. [12] Bedekar, A.S., Feng, J.J., Krishanamoorthy, S., Lim, K.G., Palmore, G.T.R. and Sundaram, S. (2008) Oxygen Limitation in Microfluidic Biofuel Cells. Chemical Engineering Communications, 195, 256-266.
http://dx.doi.org/10.1080/00986440701569036 [13] Kjeang, E., Sinton, D. and Harrigton, D.A. (2006) Strategic Enzyme Patterning for Microfluidic Biofuel Cells. Journal of Power Sources, 158, 1-12.
http://dx.doi.org/10.1016/j.jpowsour.2005.07.092 [14] Jeon, S.W., Lee, J.Y., Lee, J.H., Kang, S.W., Park, C.H. and Kim, S.W. (2008) Optimization of Cell Conditions for Enzymatic Fuel Cell Using Statistical Analysis. Journal of Industrial and Engineering Chemistry, 14, 338-343.
http://dx.doi.org/10.1016/j.jiec.2008.01.006 [15] Glycys, D.J. and Banta, S. (2009) Metabolic Control Analysis of an Enzymatic Biofuel Cell. Biotechnology and Bioengineering, 102, 1624-1635.
http://dx.doi.org/10.1002/bit.22199 [16] Bedekar, A.S., Feng, J.J., Lim, K., Krishanamoorthy, S., Palmore, G.T.R. and Sundaram, S. (2004) Computational Analysis of Microfluidic Biofuel Cells. Proceeding of the AIChE, Austin, TX. [17] Zebda, A., Innocent, C., Renaud, L., Cretin, M., Pichot, F., Ferrigno, R. and Tingry, S. (2008) Enzyme-Based Microfluidic Biofuel Cell to Generate Micropower. In: Drapcho, C.M., Ph Nghim, N. and Walker, T.H., Eds., Biofuel’s Engineering Process Technology, McGraw-Hill, New York, 576. [18] Pinto, R.P., Sprinivasan, B., Manuel, M.F. and Tartakovsky, B. (2010) A Two-Population Bio-Electrochemical Model of Microbial Fuel Cell. Bioresource Technology, 101, 5256-5265.
http://dx.doi.org/10.1016/j.biortech.2010.01.122 [19] Weber, A.Z. and Newman, J. (2004) Modeling Transport in Polymer Electrolyte Fuel Cells. Chemical Reviews, 104, 4679-4726.
http://dx.doi.org/10.1021/cr020729l [20] Barlett, P.N., Toh, C.S., Calvo, E.J. and Flexer, V. (2008) Modeling Biosensor Responses. In: Bioelectrochemistry, Wiley, England, 267-325. [21] Osman, M.H., Shah, A.A. and Wills, R.G.A. (2013) Detailed Mathematical Model of an Enzymatic Fuel Cell. Journal of the Electrochemical Society, 160, F806-F814.
http://dx.doi.org/10.1149/1.059308jes [22] Baronas, R. and Kulys, J. (2008) Modelling Amperometric Biosensors Based on Chemically Modified Electrodes. Sensors, 8, 4800-4820.
http://dx.doi.org/10.3390/s8084800 [23] Hagen, J. (2006) Industrial Catalysis: A Practical Approach. 2nd Edition, WILEY-VCH, Weinheim.
http://dx.doi.org/10.1002/3527607684 [24] eBio World: Enzyme Kinetics.www.ebioworld.com/2012/02/enzyme-++kinetics.html [25] Kuby, S.A. (2000) A Study of Enzymes. Vol. 1, CRC Press, Florida. [26] Bard, A.J. and Faulkner, L.R. (2010) Electrochemical Methods. 2nd Edition, John Wiley & Sons, UK.
[1] Rubin, Z. and Mor, L. (2008) Electrode Resistance Dependence on Alkaline Glucose Fuel Cell Electrolyte Concentration. Proceedings of the International Conference of Fundamentals and Developments of Fuel Cells, Nancy, December 2008, 115-116. [2] Bubis, E., Mor, L., Sabag, N., Rubin, Z., Vaysban, U., et al. (2006) Electrical Characterization of a Glucose-Fueled Alkaline Fuel Cell. Proceedings of the 4th International ASME Conference on Fuel Cell Science, Engineering and Technology, FuelCell2006, Irvine, Vol. 2006, 8p. [3] Mor, L., Rubin, Z. and Schechner, P. (2008) Measuring Open Circuit Voltage in Glucose Alkaline Fuel Cell Operated as a Continuous Stirred Tank Reactor. Journal of Fuel Cell Science and Technology, 5, Article ID: 014503. [4] Rubin, V.(Z.) and Mor, L. (2013) Physical Models of the Conductivity in Glucose Alkaline Fuel Cell. ECS Transactions, 45, 245-257 [5] Mor, L. and Rubin, V.(Z.) (2012) Experimental and Theoretical Considerations of Electrolyte Conductivity in Glucose Alkaline Fuel Cell. Sircuites and Systems, 3, 111-117. [6] Ge, J., Schirhagl, R. and Zare, R.N. (2011) Glucose-Driven Fuel Cell Constructed from Enzymes and Filter Paper. Journal of Chemical Education, 5, 1283-1286.
http://dx.doi.org/10.1021/ed100967j [7] Ivanov, I., Vidacovic-Koch, T. and Sundmacher, K. (2010) Recent Advances in Enzymatic Fuel Cells: Experiments and Modeling. Energies, 3, 803-846.
http://dx.doi.org/10.3390/en3040803 [8] Rubin, V.(Z.) and Mor, L. (2013) Physical Modelling of the Enzymatic Glucose Fuelled Fuel Cell. Advances in Chemical Engineering and Science, 3, 218-226.
http://dx.doi.org/10.4236/aces.2013.34028 [9] Shukla, A.K., Suresh, P., Berchmants, S. and Rajendran, A. (2004) Biilogical Fuel Cells and Their Applications. Current Science, 87, 425-467. [10] Zebda, A., Gondran, C., Le Goff, A., Holzinger, M., Cinquin, P. and Cosnier, S. (2011) Mediatorless High-Power Glucose Biofuel Cells Based on Compressed Carbon Nanotube-Enzyme Electrodes. Nature Communications, 2, Article Number: 370. [11] Fapyane, D., Lee, S.J., Kang, S.H., Lim, D.H., Cho, K.K., Nam, T.H., Ahn, J.P., Ahn, J.H., Kim, S.W. and Chang, I.S. (2013) High Performance Enzyme Fuel Cells Using a Genetically Expressed FAD-Dependent Glucose Dehydrogenase α-Subunit of Burkholderia cepacia Immobilized in a Carbon Nanotube Electrode for Low Glucose Conditions. Physical Chemistry Chemical Physics, 15, 9508-9512. [12] Bedekar, A.S., Feng, J.J., Krishanamoorthy, S., Lim, K.G., Palmore, G.T.R. and Sundaram, S. (2008) Oxygen Limitation in Microfluidic Biofuel Cells. Chemical Engineering Communications, 195, 256-266.
http://dx.doi.org/10.1080/00986440701569036 [13] Kjeang, E., Sinton, D. and Harrigton, D.A. (2006) Strategic Enzyme Patterning for Microfluidic Biofuel Cells. Journal of Power Sources, 158, 1-12.
http://dx.doi.org/10.1016/j.jpowsour.2005.07.092 [14] Jeon, S.W., Lee, J.Y., Lee, J.H., Kang, S.W., Park, C.H. and Kim, S.W. (2008) Optimization of Cell Conditions for Enzymatic Fuel Cell Using Statistical Analysis. Journal of Industrial and Engineering Chemistry, 14, 338-343.
http://dx.doi.org/10.1016/j.jiec.2008.01.006 [15] Glycys, D.J. and Banta, S. (2009) Metabolic Control Analysis of an Enzymatic Biofuel Cell. Biotechnology and Bioengineering, 102, 1624-1635.
http://dx.doi.org/10.1002/bit.22199 [16] Bedekar, A.S., Feng, J.J., Lim, K., Krishanamoorthy, S., Palmore, G.T.R. and Sundaram, S. (2004) Computational Analysis of Microfluidic Biofuel Cells. Proceeding of the AIChE, Austin, TX. [17] Zebda, A., Innocent, C., Renaud, L., Cretin, M., Pichot, F., Ferrigno, R. and Tingry, S. (2008) Enzyme-Based Microfluidic Biofuel Cell to Generate Micropower. In: Drapcho, C.M., Ph Nghim, N. and Walker, T.H., Eds., Biofuel’s Engineering Process Technology, McGraw-Hill, New York, 576. [18] Pinto, R.P., Sprinivasan, B., Manuel, M.F. and Tartakovsky, B. (2010) A Two-Population Bio-Electrochemical Model of Microbial Fuel Cell. Bioresource Technology, 101, 5256-5265.
http://dx.doi.org/10.1016/j.biortech.2010.01.122 [19] Weber, A.Z. and Newman, J. (2004) Modeling Transport in Polymer Electrolyte Fuel Cells. Chemical Reviews, 104, 4679-4726.
http://dx.doi.org/10.1021/cr020729l [20] Barlett, P.N., Toh, C.S., Calvo, E.J. and Flexer, V. (2008) Modeling Biosensor Responses. In: Bioelectrochemistry, Wiley, England, 267-325. [21] Osman, M.H., Shah, A.A. and Wills, R.G.A. (2013) Detailed Mathematical Model of an Enzymatic Fuel Cell. Journal of the Electrochemical Society, 160, F806-F814.
http://dx.doi.org/10.1149/1.059308jes [22] Baronas, R. and Kulys, J. (2008) Modelling Amperometric Biosensors Based on Chemically Modified Electrodes. Sensors, 8, 4800-4820.
http://dx.doi.org/10.3390/s8084800 [23] Hagen, J. (2006) Industrial Catalysis: A Practical Approach. 2nd Edition, WILEY-VCH, Weinheim.
http://dx.doi.org/10.1002/3527607684 [24] eBio World: Enzyme Kinetics.www.ebioworld.com/2012/02/enzyme-++kinetics.html [25] Kuby, S.A. (2000) A Study of Enzymes. Vol. 1, CRC Press, Florida. [26] Bard, A.J. and Faulkner, L.R. (2010) Electrochemical Methods. 2nd Edition, John Wiley & Sons, UK.