臺灣博碩士論文加值系統

甲醇蒸氣重組反應已經成為近年來研究燃料電池的重要課題之一，因為其可以提供有效率的氫氣來源。對重組反應適當的動力學反應速率式，是提供整體燃料電池設計的重要資訊。由於甲醇蒸氣重組反應為高溫的非均相觸媒反應，其反應機構顯得相當複雜，而引起廣泛的研究與探討。本研究利用通用速率式法，來分析甲醇蒸氣重組反應的複雜網路反應。由文獻中之資訊提出五種可能的反應機構，經由網路簡化技術來推導分別之反應速率式。再由不同文獻中所發表的實驗數據與結果比較，決定合理的反應機構。並且利用非線性迴歸工具推估最好的動力學參數，包括各反應路徑之速率常數因子和活化能。
結果顯示本研究提出的第五種反應機構與文獻發表的實驗數據有較佳的吻合性，推導出的結果與原始參考文獻中各成分濃度有相似的動力學行為。不同文獻使用不同的反應觸媒，所以回歸的速率參數有所不同，但預測值與實驗值皆有相似的動力學趨勢。雖然部份物質預測的濃度曲線與實驗數據有明顯的偏差，可能導因於過於複雜的非均相反應機構與系統中一氧化碳與二氧化碳濃度相對較低，造成非線性回歸分析更加困難。本研究最後並針對最佳反應機構，進行動力學參數之敏感性分析。藉由所有反應路徑之速率常數對反應速率之敏感度，可以比較出每一反應路徑之相對重要性。此一分析之結果，可以提供後續對過於複雜之反應速率式簡化研究之重要參考。

The study on methanol steam reforming reaction has become an important issue in research for development of fuel cells. However, a suitable kinetic rate expression for the methanol steam reforming reaction is key information for global design of fuel cells. Due to the heterogeneous and high temperature reaction for methanol steam reforming, the mechanisms for the system are very complicated and hard to analyze. In this study, the general rate equation method for complex reaction network was applied to investigate the complicated reaction mechanisms. Five possible mechanisms for methanol steam reforming were proposed and the related reaction rates were derived by network reduction techniques. The feasibilities of the mechanisms were identified by comparison of experimental data published in different literatures. The kinetic parameters, including the pre-exponential factors and activity energies were fitted by nonlinear regression tools.
The advantages of using general rate equations method is that no need to assume any rate determined steps and the explicit rate of reaction can be derived systemically. The results showed that the mechanism model 5 proposed in this study presented the best consistency with the experimental data in different literatures. The kinetic behaviors of the best mechanism showed the same tendency with the experimental data. Due to the different experimental data used the different catalysts; the fitted kinetic parameters were also different for various systems. However, the predicted curve of model has same outcome. Though some concentration profiles showed apparent deviations with the experimental data, it maybe caused by the too complicated mechanisms and the concentrations of carbon oxide and carbon dioxide were too low compared with other species. It would make the nonlinear regression more difficult. Finally, the sensitivity analysis for individual rate constants to reaction rate was performed for the best kinetic model. From the analyses, we can identify the reaction pathway which would affect the formation of carbon oxide and carbon dioxide. The results of sensitivity analysis can be used to supply important information for the simplification of too complicated rate expressions for methanol steam reforming in further investigations.

TABLE OF CONTENTS

Page
ACKNOWLEDGMENTS i
ABSTRACT (English) ii
ABSTRACT (Chinese) iii
TABLE OF CONTENTS iv
LIST OF TABLES vii
LIST OF FIGURES ix
CHAPTER 1 INTRODUCTION 1
1.1 Background 1
1.2 Objectives and Scope 3
CHAPTER 2 LITERATURE REVIEW 5
2.1 Methanol Steam Reforming 5
2.1.1 Methanol Steam Reforming for the Fuel Cell 5
2.1.2 The Development of Methanol Steam Reforming 6
2.1.3 The Catalysts 10
2.2 The Kinetics Studies of Methanol Steam Reforming 11
2.2.1 Methanol Steam Reforming Reactions 11
2.2.2 Related Kinetics Studies for Methanol Steam Reforming 12
2.3 Network Reduction Techniques 11
2.3.1 The Development of Network Reduction Techniques 20
2.3.2 Related Studies 25
CHAPTER 3 Methods 28
3.1 Network Reduction Techniques for Methanol Steam Reforming 28
3.2 Reaction Rate Expressions 40
3.3 The Equilibrium Constants and Rate Constants 49
3.4 Algorithm for Comparison of the Mechanisms 51
CHAPTER 4 RESULTS AND DISCUSSION 53
4.1 Comparison of Models 53
4.2 Results of the Kinetics for Best Model 57
4.3 Results of Kinetics Parameters Estimation 73
4.4 Comparison of Models for the Other Experiment 79
4.5 Sensitivity Analysis for Rate constants 81
CHAPTER 5 CONCLUSIONS 89
REFERENCES 91
APPENDIX 1 Codes for Nonlinear Regression Wizard in Sigmaplot 97
APPENDIX 2 Fortran Source Codes for Solving Kinetic Parameters by Nonlinear Regression 99



LIST OF TABLES

Table Page
2.1 Two-type active site surface reaction mechanism for methanol steam reforming system proposed by Patel and Pant, (2007) 16
2.2 The parameters of kinetics model (from Patel and Pant, 2007) 18
2.3 The reaction mechanism and the meaning of rate constant 26
3.1 The equilibrium constant and related rate constants of each mechanism 50
4.1 Comparison of fitted r-square value for five models by nonlinear regression tool in Sigmaplot software with experimental data from Purnama et al. (2004) 55
4.2 Comparison of fitted r-square value for five models by nonlinear regression tool in Sigmaplot software with experimental data from Mastalir et al. (2005) 56
4.3 The rate constants of model 5 at different temperatures by fitting the experimental data from Purnama et al. (2004) 74
4.4 The rate constants of model 5 at different temperatures by fitting the experimental data from Mastalir et al. (2005) 75
4.5 The pre-exponential factor and activity energy of model 5 (experimental data from Purnama et al. 2004) 77
4.6 The pre-exponential factor and activity energy of model 5 (experimental data from Mastalir et al. 2005) 78
4.7 Comparison of kinetic model and method with related studies 80


LIST OF FIGURES

Figure Page
2.1 The schematic mechanism of methanol synthesis. (Thomas et al. 1997) 7
2.2 Schematic diagram of the mechanism of methanol decomposition. (Chioa and Stenger, 2002 ) 8
2.3 Single loop reaction network with arbitrary number of intermediates (Chern, 2000 ) 24
2.4 Reaction network of dye decomposition with co-reactants shown above arrows and co-products below the arrows. (Chang and Chern, 2010) 27
3.1 Reaction network mechanism 1 for methanol steam reforming reaction. (a) Cyclic multi-pathway reaction, (b) reduced single cycle network 29
3.2 Reaction network mechanism 2 for methanol steam reforming reaction. (a) Cyclic multi-pathway reaction, (b) reduced single cycle network 32
3.3 Reaction network mechanism 3 for methanol steam reforming reaction. (a) Cyclic multi-pathway reaction, (b) reduced single cycle network 35
3.4 Reaction network mechanism 4 for methanol steam reforming reaction. (a) Cyclic multi-pathway reaction, (b) reduced single cycle network 36
3.5 Reaction network mechanism 5 for methanol steam reforming reaction. (a) Cyclic multi-pathway reaction, (b) reduced single cycle network 37
4.1 Comparison of concentration profiles for each component of the model 5 at temperature 503K. (experimental data from Purnama et al. 2004) 59
4.2 The parity plot for the concentration of individual component at temperature 503K.The fitted value r2=0.77 (experimental data from Purnama et al. 2004) 60
4.3 Comparison of concentration profiles for each component of the model 5 at temperature 523K. (experimental data from Purnama et al., (2004) 61
4.4 The parity plot for the concentration of individual component at temperature 523K.The fitted value r2=0.81(experimental data from Purnama et al. 2004) 62
4.5 Comparison of concentration profiles for each component of the model 5 at temperature 543K. (experimental data from Purnama et al. 2004) 63
4.6 The parity plot for the concentration of individual component at temperature 543K.The fitted value r2=0.85 (experimental data from Purnama et al. 2004) 64
4.7 Comparison of concentration profiles for each component of the model 5 at temperature 573K. (experimental data from Purnama et al. 2004) 65
4.8 The parity plot for the concentration of individual component at temperature 573K.The fitted value r2=0.88 (experimental data from Purnama et al. 2004) 66
4.9 Comparison of concentration profiles for each component of the model 5 at temperature 503K. (experimental data from Mastalir et al. 2005) 67
4.10 The parity plot for the concentration of individual component at temperature 503K.The fitted value r2=0.87 (experimental data from Mastalir et al. 2005) 68
4.11 Comparison of concentration profiles for each component of the model 5 at temperature 523K. (experimental data from Mastalir et al. 2005) 69
4.12 The parity plot for the concentration of individual component at temperature 523K.The fitted value r2=0.82 (experimental data from Mastalir et al., (2005) 70
4.13 Comparison of concentration profiles for each component of the model 5 at temperature 543K. (experimental data from Mastalir et al.,(2005)) 71
4.14 The parity plot for the concentration of individual component at temperature 543K.The fitted value r2=0.71 (experimental data from Mastalir et al.,2005) 73
4.15 Sensitivity analyses for reaction rate with rate constants k01, k10, k12 and k21 at temperature 573 K by increasing the individual rate constant 100 times or 1/10 times 82
4.16 Sensitivity analyses for reaction rate with rate constants k30, k03, k23 and k32 at temperature 573 K by increasing the individual rate constant 100 times or 1/10times 83
4.17 Sensitivity analyses for reaction rate with rate constants k34, k43, k40 and k04 at temperature 573 K by increasing the individual rate constant 100 times or 1/10 times 84
4.18 Sensitivity analyses for reaction rate with rate constants k01, k10, k12 and k21 at temperature 523 K by increasing the individual rate constant 100 times or 1/100 times 86
4.19 Sensitivity analyses for reaction rate with rate constants k30, k03, k23 and k32 at temperature 523 K by increasing the individual rate constant 100 times or 1/100 times 87
4.20 Sensitivity analyses for reaction rate with rate constants k34, k43, k40 and k04 at temperature 523 K by increasing the individual rate constant 100 times or 1/100 times 88

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