THERMODYNAMIC PROPERTIES OF NUCLEIC ACID BASES AND NUCLEOSIDES UNDER
HYDROTHERMAL CONDITIONS
A Thesis
Presented to
The Faculty of Graduate Studies
of
The University of Guelph
by
VANESSA MANN
In partial fulfilment of requirements for the degree of
Master of Applied Science
August, 2009
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1+1 Canada ABSTRACT
THERMODYNAMIC PROPERTIES OF NUCLEIC ACID BASES AND NUCLEOSIDES UNDER HYDROTHERMAL CONDITIONS
Vanessa Lynn Mann Advisor: University of Guelph, 2009 Dr. P. R. Tremaine
This is an investigation of thermodynamic properties of nucleic acid bases and nucleosides under hydrothermal conditions. Standard partial molar volumes have been determined for neutral nucleic acid bases and some nucleosides at temperatures between 15 0C and 90 0C using an Anton Parr DMA 5000 densitometer. Additionally, standard partial molar volumes of neutral uridine, cytidine, and thymidine were calculated from densities measured at temperatures up to 200 0C and pressures up to 6 bar using a custom- built platinum vibrating tube densitometer. Standard partial molar heat capacities were determined at temperatures up to 135 0C using a NDSC-III scanning nanocalorimeter. Standard partial molar properties of nucleic acid base and nucleoside non-electrolyte solutions become progressively more positive as the critical point is approached. Standard partial molar volumes and heat capacities for chloride salts of nucleic acid bases and nucleosides, BH+Cl"(aq) were also determined at temperatures between 15 0C and 90 0C. Partial molar properties of solutions of charged nucleic acid components become increasingly negative as the critical point is reached. These experimental results are in stark contrast with the previous assertions made by LaRowe and Helgeson (2006]. It was also observed that the standard partial molar properties of both neutral and ionic nucleosides had much larger, positive values than their corresponding nucleic acid bases. This difference was attributed to contributions of the ribose group to standard partial molar properties, and was modeled and used to estimate the standard partial molar properties of neutral and positively charged guanine in water. Additionally, the first ionization constant of adenosine was determined at a pressure of 95 bar and temperatures up to 175 0C using a platinum flow-through UV-visible cell. At near-ambient temperatures, measured ionization constants agreed well with values predicted by the Van't Hoff equation, but deviated from this model as temperature increased. The thermal stabilities of adenosine in acidic, neutral, formic acid buffered and phosphate buffered solutions were determined using the UV-visible cell as a stopped flow system at 95 bar between 150 0C and 250 0C. Adenosine formed decomposition products with overlapping spectra, and this necessitated factor analysis techniques to resolve different species. As temperature increased, the number of coloured decomposition products formed increased, indicating multiple decomposition pathways and steps. Above 225 0C, decomposition products were unstable, and decomposed into colourless products quickly. Spectral deconvolution of kinetic measurements using SpecFit/32© indicated that different reaction products were formed in the phosphate buffered system than the formic acid buffered system. It is believed that the phosphate buffered system produced a phosphate-adenosine complex that was unstable at ambient temperatures, and could not be isolated. ACKNOWLEDGEMENTS
I would like to thank my advisor, Dr. Tremarne, for his guidance and leadership on this project. I am especially grateful to Dr. Lilliana Trevani for all of her technical assistance and wisdom, both of which were invaluable contributions to my research. I am also thankful to all past and present members of the Tremaine group, especially Kristy and Melerin, for all of their science and non-science related support for my project. Over these last 26.5 years, I have received seemingly never-ending encouragement and support from my parents and older sister in my personal life as well as my academic career. I know that I could never have reached this point, nor would I be going on to complete my Ph.D., if they had not seen me through it. And finally, I would be truly remiss if I did not thank my husband, Jon. You've seen me through all the late nights and weekends of work, the frustration, the anger, and the good times in these last two years. Truth be told, this document wouldn't exist if I didn't have you in my life, and for this, and for so many other things, I will always be grateful.
? Table of Contents
ACKNOWLEDGEMENTS i
LISTOFFIGURES ?
LISTOFTABLES x
CHAPTERl 1 1.1 General Overview 1 1.2 Deoxyribonucleic Acid and Ribonucleic Acid Constituents 4 1.3 Biomolecules and their Precursors under Hydrothermal Conditions 7 1.3.1 The Nature of Hydrothermal Vents 7 1.3.2 A Prebiotic 'RNA World' 10 1.3.3 The Theory of the Origins of Life at Hydrothermal Vents 12 1.3.4 Abiotic Formation of Biomolecules under Hydrothermal Conditions ..13 1.4 Engineering Applications of Extremophiles and DNA Under Hydrothermal Conditions 14 1.5 Thermodynamics of Aqueous Solutions 17 1.5.1 Reaction Equilibria 17 1.5.2 Thermodynamic Relationships to Gibbs Free Energy 21 1.5.3 Apparent and Standard Partial Molar Properties of Aqueous Solutions21.
1.5.4 Standard Partial Molar Volumes 23 1.5.5 Heat Capacities 25 1.5.6 Extrapolating to Infinite Dilution 26 1.6 Equations of State for Standard Partial Molar Properties 29 1.6.1 The "Density" Model 29 1.6.2 Helgeson-Kirkham-Flowers (HKF) Equations of State 30 1.6.3 OLI Software 35 1.7 Hydrothermal UV-Visible Spectroscopy 36 1.7.1 Background 36 1.7.2 Developments in Hydrothermal UV-visible Spectroscopy 38 1.8 Methods of Kinetic Analysis 39 1.8.1 Chemical Reactions 39 1.8.2 Kinetic Measurement Techniques 41
ii 1.8.3 Data Analysis Al 1.9 Research Objectives 44 CHAPTER 2 46 2.1 Chemicals and Materials 46 2.2 Determination of Standard Partial Molar Properties 47 2.2.1 Density Measurements 47 2.3 Heat Capacity Measurements 57 2.4 UV-visible Spectroscopy 60 2.4.1 High Temperature Apparatus 60 2.5 Batch Reactions of Adenosine with Phosphates at Elevated Temperatures64
CHAPTER 3 66 3.1 Introduction 66 3.2 Standard Partial Molar Properties of Neutral and Positively Charged Nucleic Acid Bases and Nucleosides 70 3.2.1 Standard Partial Molar Volumes 70 3.2.2 Modeling Standard Partial Molar Volumes 72 3.2.3 Standard Partial Molar Heat Capacities 105 3.2.4 Modelling of Standard Partial Molar Heat Capacities 106 3.2.5 Comparison with Literature 131 3.2.6 Discussion 132 3.3 Functional Group Additivity Models 137 3.3.1 Introduction 137 3.3.2 Analysis of Ribose Contribution to Standard Partial Molar Properties138
3.3.3 Determination of the V20 of Guanine 149 3.3.4 Discussion 153 3.4 Standard Partial Molar Properties of Ionization 155 CHAPTER 4 163 4.1 Acid Ionization Constant from 25 to 175 0C 163 4.1.1 Introduction 163 4.1.2 Measurement Uncertainties 169 4.1.3 Comparisons with Literature Data 172 4.1.4 Equations of State 172 4.1.5 Discussion 177
in 4.2 The Kinetics of Adenosine Thermal Decomposition Under Hydrothermal Conditions 178 4.2.1 Decomposition Kinetics of Aqueous Adenosine Solutions from 150 to 250°C 180 4.2.2 Adenosine and Phosphate Reactions from 150 to 225 0C 195 4.2.3 Discussion 203 CHAPTER 5 206 5.1 Conclusions 206 5.2 Areas for Future Work 208 5.3 Engineering Applications 209 CHAPTER 6 211 CHAPTER 7 223
iv LIST OF FIGURES Figure 1.1: General Structure of Pyrimidine and Purine Bases 5 Figure 2.1: Schematic diagram of the high temperature densimeter 52 Figure 2.2: Partial molar volumes of methanol and water solutions 56 Figure 2.3: Schematic Diagram of Nano Differential Scanning Calorimeter 59 Figure 2.4: Schematic diagram of the UV-visible flow cell 62 Figure 2.5: Schematic of the UV-visible high temperature flow system 63 Figure 2.6: Schematic diagram of a general purpose acid digestion bomb 65 Figure 3.1: Acid ionizations of stable nucleic acid base structures 68 Figure 3.2: Acid ionization of stable nucleoside structures 69 Density Models of Standard Partial Molar Volumes Figure 3.3: Standard partial molar volumes, V20, of neutral adenine 76 Figure 3.4: Standard partial molar volumes, V20, of neutral cytosine 77 Figure 3.5: Standard partial molar volumes, V20, of neutral pyrimidine bases 78 Figure 3.6: Standard partial molar volumes, V20, of neutral purine nucleosides 79 Figure 3.7: Standard partial molar volumes, V2°, of neutral cytidine 80 Figure 3.8: Standard partial molar volumes, V2°, of neutral pyrimidine nucleosides81
Figure 3.9: Standard partial molar volumes, V2°, of adenine hydrogen chloride 82 Figure 3.10: Standard partial molar volumes, V2°, of cytosine hydrogen chloride.. 83 Figure 3.11: Standard partial molar volumes, V2°, of adenosine hydrogen chloride84
Figure 3.12: Standard partial molar volumes, V20, of guanosine hydrogen chloride85
Figure 3.13: Standard partial molar volumes, V20, of cytidine hydrogen chloride .. 86
? HKF Models of Standard Partial Molar Volumes Figure 3.14: Standard partial molar volumes, W, of neutral adenine 89 Figure 3.15: Standard partial molar volumes, V2°, of neutral cytosine, uracil and thymine 90 Figure 3.16: Standard partial molar volumes, V20, of neutral adenosine and guanosine 91 Figure 3.17: Standard partial molar volumes, V20, of neutral cytidine 92 Figure 3.18: Standard partial molar volumes, V20, of uridine and thymidine 93 Figure 3.19: Standard partial molar volume, W, of adenine hydrogen chloride 99 Figure 3.20: Standard partial molar volume, V20, of cytosine hydrogen chloride...l00 Figure 3.21: Standard partial molar volume, V20, of adenosine hydrogen chloride..101
Figure 3.22: Standard partial molar volume, V20, of cytidine hydrogen chloride ..102 Figure 3.23: Standard partial molar volume, V20, of guanosine hydrogen chloride..103
Density Models of Standard Partial Molar Heat Capacities Figure 3.24: Standard partial heat capacities, Cp/, of neutral adenine 109 Figure 3.25: Standard partial heat capacities, Cp/, of neutral cytosine 110 Figure 3.26: Standard partial heat capacities, Cp,2°, of neutral uracil and thymineIll
Figure 3.27: Standard partial heat capacities, Cp,2°, of neutral adenosine 112 Figure 3.28: Standard partial heat capacities, Cp,2°, of neutral cytidine 113 Figure 3.29: Standard partial heat capacities, Cp/, of neutral uridine and thymidine114
Figure 3.30: Standard partial heat capacities, Cp/, of adenine hydrogen chloride..115
Figure 3.31: Standard partial heat capacities, Cp/, of cytosine hydrogen chloride.116
vi Figure 3.32: Standard partial heat capacities, Cp/, of adenosine hydrogen chloride and cytidine hydrogen chloride 117 HKF Models of Standard Partial Molar Heat Capacities Figure 3.33: Standard partial molar heat capacities, Cp,2°, of neutral adenine 120 Figure 3.34: Standard partial molar heat capacities, Cp,2°, of neutral cytosine, uracil, and thymine 121 Figure 3.35: Standard partial molar heat capacities, Cp,2°, of neutral adenosine ...122 Figure 3.36: Standard partial molar heat capacities, Cp/, of neutral cytidine 123 Figure 3.37: Standard partial molar heat capacities, Cp/, of neutral thymidine and uridine 124 Figure 3.38: Standard partial molar heat capacity, Cp/, of adenine hydrogen chloride, adenineH+Cl·, in water and excess HCl 126 Figure 3.39: Standard partial molar heat capacity, Cp/, of cytosine hydrogen chloride, cytosineH+Cl·, in water and excess HCl 127 Figure 3.40: Standard partial molar heat capacity, Cp/, of adenosine hydrogen chloride, adenosineH+Cl·, in water and excess HCl 128
Figure 3.41: Standard partial molar heat capacity, Cp/, of cytidine hydrogen chloride, cytidineH+Cl·, in water and excess HCl 129 Figure 3.42: Ribose contribution to the standard partial molar volumes, AV2, Rib", of neutral adenosine, cytidine, thymidine, and uridine 139 Figure 3.43: Ribose contribution to the standard partial molar heat capacities, ACp2,rib°, of neutral adenosine 140 Figure 3.44: Ribose contribution to the partial molar heat capacity, ACp,2, R¡b° of neutral cytidine, thymidine, and uridine 141 Figure 3.45: Ribose contribution to the standard partial molar volumes, UMz, Rib°, of adenosine hydrogen chloride and cytidine hydrogen chloride 144 Figure 3.46: Ribose contribution to the partial molar heat capacity, ACp,2,rib°, of adenosine hydrogen chloride 145 Figure 3.47: Ribose contribution, ACp,2,rib°, to the partial molar heat capacity of cytidine hydrogen chloride 146
vii Figure 3.48: Standard partial molar volume of neutral guanine in water, V20, 151 Figure 3.49: Standard partial molar volume of protonated guanine in water,152V20
Figure 3.50: Partial molar volume of ionization, ?G???°, of adenine and cytosine..l57 Figure 3.51: Partial molar volume of ionization, ArxnV°, of adenosine, guanosine and cytidine 158 Figure 3.52: Partial molar volume of ionization, ArxnV0, of guanine as determined from functional group additivity models 159 Figure 3.53: Partial molar heat capacity of ionization, ArxnCp , of adenine and cytosine 160 Figure 3.54: Partial molar heat capacity of ionization, ?G???°?, of adenosine and cytidine 161 Figure 4.1: Formic acid buffer region (Bell et al, 1993) overlap with predicted first ionization of adenosine 168
Figure 4.2: UV-visible spectra of adenosine at 175 °C and 95 bar 170 Figure 4.3: Experimental values of the ionization of adenosine, logioKia, measured from 25 to 175 0C 175 Figure 4.4: Time evolved decomposition spectra for adenosine in 0.1 mol kg1 HCl and 0.1 mol kg1 NaCl at 225 0C and 95 bar 181 Figure 4.5: Time evolved decomposition spectra for adenosine in a 1 to 1 buffer solution of formic acid/sodium formate with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 182
Figure 4.6: Time evolved decomposition spectra for adenosine in a 10 to 1 buffer solution of formic acid/sodium formate with a total ionic strength of 0.2 mol kg-1 at 225 0C and 95 bar 183
Figure 4.7: Time evolved decomposition spectra for adenosine in 0.2 mol kg1 NaCl at 225 0C and 95 bar 184
Figure 4.8: Residual difference decomposition spectra for adenosine in a solution of 0.1 mol kg1 HCl and 0.1 mol kg1 NaCl at 225 0C and 95 bar 188
viii Figure 4.9: Residual difference decomposition spectra for adenosine in a 1 to 1 buffer solution of formic acid/sodium formate with a total ionic strength of 0.2 mol kg-1 at 225 0C and 95 bar 190 Figure 4.10: Residual difference decomposition spectra for adenosine in a 10 to 1 buffer solution of formic acid/sodium formate with a total ionic strength of 0.2 mol kg-1 at 225 0C and 95 bar 191 Figure 4.11: Residual difference decomposition spectra for adenosine in a solution of 0.2 mol kg1 NaCl at 225 0C and 95 bar 192 Figure 4.12: Time evolved reaction spectra for adenosine in a 10 to 1 buffer solution of H2PO4-/H3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 192 Figure 4.13: Time evolved reaction spectra for adenosine in a 1 to 1 buffer solution OfH2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. ..197 Figure 4.14: Time evolved reaction spectra for adenosine in a 1 to 10 buffer solution of H2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 198 Figure 4.15: Residual difference reaction spectra for adenosine in a 10 to 1 buffer solution of H2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 199 Figure 4.16: Residual difference reaction spectra for adenosine in a 1:1 buffer solution of H2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 200 Figure 4.17: Residual difference reaction spectra for adenosine in a 1 to 10 buffer solution of H2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar 201
Figure 4.18: Reaction mechanism for the solvolysis of adenosine 204
ix LIST OF TABLES
Table 1.1: Structures of Nucleic Acid Bases and Their Corresponding Nucleosides and Nucleotides 6
Table 2.1: Experimentally determined calibration constants for the high temperature and pressure densimeter as a function of temperature 55 Table 3.1: Regression parameters for Equation 3.6, the fitting equation for standard partial molar volumes, V2 ', of nucleic acid bases and nucleosides 87 Table 3.2: Regression parameters for standard partial molar volumes, W of chloride salts of nucleic acid bases and nucleosides 87
Table 3.4: HKF Regression parameters for standard partial molar volumes, V20, of neutral nucleic acid bases and nucleosides 94
Table 3.4: Literature values for the unit cell dimensions, a, b, and c, unit cell volumes, and hypothetical radii of a single ion based on the longest side of the unit cell 96
Table 3.5: HKF Regression parameters for standard partial molar volumes, V20, of chloride salts of nucleic acid bases and nucleosides 104
Table 3.6: Regression parameters for standard partial molar heat capacities, Cp/, of neutral nucleic acid bases and nucleosides 118
Table 3.7: Regression parameters for standard partial molar heat capacities, Cp/ of certain chloride salts of nucleic acid bases and nucleosides 118
Table 3.8: HKF Regression parameters for standard partial molar heat capacities, Cp,2°, of neutral bases and nucleosides 130 Table 3.9: HKF Regression parameters for standard partial molar heat capacities, Cp,2°, of chloride salts of nucleic acid bases and nucleosides 130 Table 3.10: Regression parameters for the ribose contribution to standard partial molar volumes of neutral nucleosides 142
Table 3.11: Regression parameters for the ribose contribution to standard partial molar heat capacities of neutral nucleosides 142 Table 3.12: Regression parameters for the ribose contribution to standard partial molar volumes 147
? Table 3.13: Regression parameters for the ribose contribution to standard partial molar heat capacities of chloride salts of nucleosides 147 Table 3.14: Regression parameters for the standard partial molar volume of ionization, ?G???° of certain nucleic acid bases and nucleosides 162 Table 3.15: Regression parameters for the standard partial molar heat capacity of ionization, ArxnCp" of certain nucleic acid bases and nucleosides 162 Table 4.1: Experimentally determined values of the acid ionization quotients and constants for adenosine 171
Table 4.2: Regression parameters for the density and mean heat capacity of ionization thermodynamic models 176 Table 4.3: Thermodynamic parameters for the ionization of adenosine 176 Table 4.4: Summarized kinetic parameters for the decomposition of adenosine in acidic, buffered, and neutral solutions at 95 bar 194
Table 4.5: Summarized kinetic results from adenosine reactions in sodium dihydrogen phosphate and phosphoric acid buffer solutions at 95 bar 202
xi LIST OF ABBREVIATIONS AND SYMBOLS
Abbreviations
AH adenosine
AH2+ adenosine ion aq aqueous
DNA deoxyribose nucleic acid
EFA evolving factor analysis
HKF Helgeson-Kirkham-Flowers (Model) SVD singular value decomposition
RNA ribonucleic acid
WFA windows factor analysis Symbols
A absorbance a adjustable fitting parameter Ac, Av, ?f, Aj Debye-Hückel coefficients for heat capacity, volume, osmotic
coefficient, and enthalpy ai, a2, a3, a3, ci, species dependent, non-solvation parameters for the HKF
C2 model b path length b constant equal to 1.2 for all electrolytes; adjustable fitting
parameter Bc, Bv adjustable fitting parameters
?f parameter for Pitzer's equations
xu e concentration in moles per litre c adjustable fitting parameter Cp heat capacity
D ratio of concentrations d adjustable fitting parameter E adjustable fitting parameter e charge on an electron
F adjustable fitting parameter
G Gibb's free energy
G adjustable fitting parameter g complex solvent function dependent on temperature and
density
H enthalpy ho fitting parameter / ionic strength of solution; beam intensity after passing though
a sample
I0 beam intensity before passing through a sample
Kt equilibrium constant k adjustable fitting parameter kc calibration constant for the nanocalorimeter kp calibration constant for the vibrating tube densimeter kx wavelength dependent proportionality constant
1 adjustable fitting parameter
xiii adjustable fitting parameter molality effective molality, in moles per kg of solution molar mass number of moles adjustable fitting parameter
Avogadro's number pressure pressure parameter equal to 1 MPa reference pressure, usually atmospheric
Born coefficient; concentration quotient fitting parameters determined by Sharygin and Wood (1997) ideal gas constant reaction rate scanning rate for the nanocalorimeter crystallographic radius effective electrostatic radius entropy temperature in Kelvin temperature parameter equal to 1 K. reference temperature in Kelvin, usually 298.15 K temperature in Celsius volume
xiv AW differential power applied to nanocalorimeter cells
X Born coefficient
Y general extensive property of a solution
Y Born coefficient
? charge of an ion
Greek symbols a constant, equal to 2.0 for 1-1 electrolytes and most other
solutes aw coefficient of thermal expansion of water ßw isothermal compressibility of water ß(°\ R^\ parameters for Pitzer's equations e molar extinction coefficient e dielectric constant of water ? activity coefficient ? wavelength v number of particles/ions from solute 0 solvent parameter equal to 228 K ? density po density parameter equal to 1.0 kg nr3 ? solvent parameter equal to 2600 bar t resonance period of the vibrating tube densimeter s standard deviation ? ? Born coefficients for HKF model for ionic and neutral species
xv Subscripts ex extreme of pH iso isocoulombic hyd hydration
M+ general cation f apparent molar property s solution soin solution w water
?- general anion
? solvent
2 solute
3 solute, usually excess HCl
Superscripts o partial molar property
OO infinite dilution
pure solvent
xvi CHAPTER 1 INTRODUCTION
1.1 General Overview
In a letter to a friend, Charles Darwin once wrote, "...we could conceive in some warm little pond.... that a protein compound was chemically formed ready to undergo still more complex changes..." (Fox and Dose, 1977). The concept of the origins of life emerging from a hydrothermal environment is not an entirely new one, but the study of hydrothermal biogeochemical reactions in deep ocean vents began in relatively recent years. Several studies of the synthesis and decomposition of biomolecules up to 250 0C, particularly of amino acids, under hydrothermal conditions have been undertaken, but with such a broad range of possible starting molecules for life and no clear model of what type of 'prebiotic world' once existed, there is a need for a basis of fundamental research on which further studies can be built. The focus of this study is on the possibility of life originating in deep ocean hydrothermal vents. Hydrothermal vents are mineral rich, high energy environments that provide the necessary chemical energy to enable organic reactions to proceed without an additional catalyst that would not otherwise be able to do so at ambient temperatures without a catalyst. While any biological and prebiological molecules are of interest to the study of pre-biotic environments, this study will focus on the subunits of DNA and RNA. It would be daunting and overwhelming to examine every different hydrothermal reaction scenario through which pre-biological chemical processes
1 could have begun. Instead, it is far more practical to use computer modelling techniques to determine under what conditions reactions are most likely to occur, and then selectively plan experiments accordingly. Experimental data at elevated temperatures and pressures can be used to build insightful predictive models, however thermodynamic data for neutral DNA and RNA components above 55 0C are particularly lacking. The currently accepted model, developed by LaRowe and Helgeson (2006) is based on extrapolations from low temperature data. For several species, sufficient experimental data was not available, so LaRowe and Helgeson (2006) used correlations and group additivity models to estimate values that could be used in their extrapolations. Despite its shortfalls, which the authors discussed in detail, this study became the benchmark for all subsequent research in this field by providing the only extensive set of thermodynamic parameters for neutral nucleic acid bases and nucleosides, as well as neutral and charged nucleotides. While these models did provide a good first estimate for the behaviour of nucleic acid components, experimental data measured above 55 0C are required to determine if the models predicted by LaRowe and Helgeson (2006) adequately represent high temperature behaviour. Moreover, these models were developed only for neutral nucleic acid bases and nucleosides; however models for additional ionic species are also required to predict reaction behaviour. It is my goal for this work to provide some fundamental research on neutral and ionic nucleic acid components under hydrothermal conditions, and develop models that can extend previous work
2 completed by LaRowe and Helgeson [2006) and be useful for additional reaction studies. Overall, the goals for this study extend beyond developing models for chemical engineering software. Previously, three dimensional fluid flow in a hydrothermal vent environment was modelled to incorporate a limited number of mineralogical components (Yang et ai, 1996). The flux and relative concentrations of comparatively simple minerals such as magnesium, sulphur, helium, and methane have been studied in the fracture systems surrounding hydrothermal vents using both sampling and modelling techniques [Elderfield and Schultz, 1996; Lackshewitz et al, 2004). Use of these models to study the dynamics of hydrothermal systems on the early earth is limited, however, because they do not incorporate the behaviour of biological and pre-biological molecules in their analyses. It is our hope that in providing some of the necessary thermodynamic data, hydrogeological models can be extended to include pre-biological environments. Understanding the behaviour of biological and pre-biological molecules under hydrothermal conditions is useful to several fields of engineering. While extremophiles have been modified for various applications, such as radioactive waste treatment, mineral digestion, and synthesis of pharmaceuticals and agrichemicals, relatively little has been done to understand the thermodynamics behind their metabolic processes. Understanding the effects of temperature and pressure on these organisms and their metabolisms requires a knowledge of the thermodynamic properties and stabilities of biological and pre-biological molecules such as amino acids and nucleic acid components under non-ambient conditions.
3 1.2 Deoxyribonucleic Acid and Ribonucleic Acid Constituents Genetic material is passed on from parents to offspring through deoxyribonucleic acid (DNA). Nucleic acids were first isolated by the Swiss physician Friedrich Miescher in 1869, who identified the microscopic material in discarded surgical bandages. He observed that it resided in the nuclei of cells, and thus named it nuclein (Dahm, 2005). Phoebus Levine then isolated DNA bases, sugar groups, and phosphate groups [1919). The X-Ray diffraction images taken by Rosalind Franklin, and the understanding that DNA bases are paired in some way, led James Watson and Francis Crick to the now accepted double helix structure of DNA (Watson and Crick, 1953). Francis Crick then developed a theory of the relationships between DNA, RNA, and proteins and their behaviour in the cell (Crick,
1957). Expression of genes in organisms requires ribonucleic acids (RNA). RNA is coded from DNA and typically is single stranded. Proteins can then be translated from RNA molecules to varying degrees based on the needs of the cell at that time. Severo Ochoa discovered the mechanism of RNA synthesis (1959) and won the Nobel Prize in Medicine. Perhaps the most significant result from this work is the hypothesis of an RNA world, proposed by Carl Woese. This theory is based on the catalytic properties of RNA, and states that the earliest forms of life may have relied on RNA for the passage of genetic material and as an enzyme to catalyze biochemical reactions (Woese, 1967). From this, the theory that life could have evolved from RNA molecules that aggregated and catalyzed reactions necessary to form primitive
life forms was developed.
4 DNA and RNA share three bases in common, cytosine, adenine, and guanine, and each has one unique base, thymine and uracil, respectively. These bases are sorted into two families, the purines, consisting of adenine and guanine, and the pyrimidines, consisting of uracil, cytosine, and thymine. The general structure of purines and pyrimidines are shown in Figure 1.1.
H
1 2
Figure 1.1: General Structure of Pyrimidine (1) and Purine [2) Bases Connected to the five bases is a deoxyribose or ribose moiety, for the DNA or RNA molecules, respectively. When connected to a ribose group, these molecules are called nucleosides, and are given the names adenosine, guanosine, uridine, cytosine, and thymidine. It is onto these ribose groups that one, two, or three phosphates can attach to the individual bases, and form nucleotides. Table 1.1 shows the structures of the nucleic acid bases, nucleosides, and ribonucleotides and deoxyribonucleotides for RNA and DNA.
5 Table 1.1: Structures of Nucleic Acid Bases and Their Corresponding Nucleosides and Nucleotides Base Base Nucleoside Ribonucleotide Deoxyribonucleotide
Structure Structure Structure Structure
O NH, Il Adenine V0H -P-OH /N=\ °" \ ' 1. -O. N=\
^-^ HOu/~i OH<-tU "1^N l,X> HO OH N^>
NH, HO « Cytosine O I Hd=- // - ? H2N —//9~Ì O. O o+w Her N'?^O
Guanine H2N H
HN Ì OH H2N HN ^N O,O O /^NX \ "*N HO HO—? OH OH 0,0 O OH OH HO-P^ \ L OH OH
Thymine n/a H0\ °??° HO ~?N^ ^O WX/N^^CH3 >- HO
OH Uracil Ov / ?« HO X0 NH X o= 6 DNA and RNA chains are formed through links between the hydroxyl group of the deoxyribose or ribose groups, respectively, to the phosphate groups. In vivo, these linkages are typically formed by enzymes which selectively connect bases together to get desired DNA or RNA sequences. RNA is most often found as a single stranded polymer, with the exception of certain viral RNA strains, but DNA is a double stranded helix. This double helix is supported by base pairing of adenine with thymine, and cytosine with guanine through two and three hydrogen bonds, respectively. 1.3 Biomolecules and their Precursors under Hydrothermal Conditions 1.3.1 The Nature of Hydrothermal Vents Hydrothermal vents are deep ocean fractures in the ocean floor and occur primarily where tectonic plates meet at mid-ocean ridges. While each vent is unique, they can be found in many locations, including the East Pacific Rise, the Mid- Atlantic Ridge, the Mediterranean Sea, and the Arctic Ocean. Soft rock rises up through fractures from the spreading of the ocean floor, forming basalt rock layers. Sedimentation of detritus occurs simultaneously, forming layers between basalt layers. Surrounding permeable rock layers allow circulating water to pass down through the rock media, close to the hot core, and then travel back upwards out of the vent chimney. Temperatures of output water typically range from 100 to 400 0C, with the highest recorded temperature being 407 0C. System pressures can reach up to 300 bar, depending on the depth at which the vents are found [Van Dover, 2000). 7 An unusual chemical property of calcium sulfate is the key to the formation of vent chimneys. Calcium sulfate is soluble in low temperature sea water, but it precipitates at high temperatures. Dissolved Ca2+ and SO42" ions travel with sea water down into rock media, and as they pass up in the jet of hot fluid, they are deposited around the vent opening. As hydrothermal fluid and cold seawater mix in the pore spaces in the newly forming vent wall, sulfate and sulphide minerals are deposited in the pore spaces and these make the wall progressively less permeable. This provides the base onto which minerals such as anhydrite, iron, zinc and copper sulphide minerals can precipitate (Kingston, 2004]. Most previously known hydrothermal fields are located on young crust along mid-ocean ridges. These areas of young crust are created from the cooling of hot basalts. This cooling drives the hydrothermal flow out of the ridges. When mixing of the high temperature hydrothermal fluid (200 - 400 0C) with the cold, oxygenated surrounding sea water occurs, sulfide and iron rich minerals precipitate out and thus a resulting sulphide chimney is created. Black smoker type systems and their associated diffuse flow were previously thought to produce all hydrothermal activity in the mid-ocean ridge environments solely along their axes. However, more recent studies have found that fluid vents not only along these mid-ocean ridges but also in regions of ocean crust longer distances away from the spreading axis. Given their distant location, these regions of crust were most likely formed decades prior to new crust forming on ridge axes (Blackman et al, 2001]. The term "Black Smoker" was coined to describe high temperature clouds of black colloidal fluids spewing from one particular vent. Later, it was observed that 8 white, grey, and even blue smoking vents exist. The 'smoke' colour is dependent on the specific composition of the vented iron-rich output water, which contains various heavy metal sulfides and trapped gasses like helium and CO2. The geochemistry of the rock surrounding the vent strongly influences the water's chemical composition (Kingston, 2004]. In the late 1970s, an oceanographer named Jack Corliss documented living ecosystems at hydrothermal vents. He observed that without any sunlight, in water at temperatures in excess of 100 0C, there were organisms capable of thriving. Archaea have been found living inside the Lost City Hydrothermal Field, (which is technically a "cold seep", however temperatures still range from 40-90 0C] further supporting the theory that early life forms lived in deep ocean environments (Kelley et al, 2005). From these observations, Corliss et al. (1979) hypothesized that such an environment could have provided the basis from which life could have originated. During times of ecological disaster, such as nuclear winters or ice ages, hydrothermal vents could provide refuge for some organisms. Life could then be re- introduced into the earth's environment. The high acidity of a hydrothermal environment, combined with the toxicity of some chemicals like hydrogen sulfide, yields a very challenging living environment. Many of the species, particularly the microorganisms living in these environments, appear to have evolved and adapted from other neighbouring species, but are distinctly different because of the challenges these environments present (Van Dover, 2000). 9 Several interesting species thave been found in vent ecosystems. Nitrogen fixing bacteria can live in water over 100 °C, but many also exist at ambient temperatures in varying depths of soils. These are an important supporter of other life forms, such as plants and higher organisms. A record-breaking nitrogen-fixing bacterium was found living in 92 0C water (Mehta, 2006). Many vent bacteria and small organisms digest minerals into forms that are either useful or less harmful to other sea organisms, such as the degradation of hydrogen sulfide into other sulfate forms by tubeworms. 1.3.2 A Prebiotic 'RNA World' The earth is approximately 4.5 billion years old and underwent dramatic and hostile chemical changes during the initial 500 million years of its existence, but the first rocks showing chemical evidence of life forms are approximately 3.5 to 3.8 billion years old. Preserved filamentous microbes believed to be capable of photosynthesis were found in 3.465 billion year old basalt from Western Australia, indicating that organisms at that time were already capable of advanced chemical processes (Schopf, 1993). On a geological timescale, life began quickly, but from what chemical systems and processes is a highly researched and contentious issue. One of the beauties of living systems is their ability to replicate themselves. However, the process of replication is highly complex, and it is unlikely that an entire living entity resulted spontaneously from the random association of organic molecules. As a result, postulations have been made about what kinds of prebiotic chemical systems could have developed and eventually initiated the formation of 10 life. The dominant theory is that a prebiotic self-replicating system existed, and was comprised of nucleic acids - RNA specifically - because of its ability to direct self replication of complementary strands (Voet and Voet, 2004). Early prebiotic production of nucleic acid chains was probably quite random in nature, and was not the organized process observed in present day organisms. Nucleic acid chains could have formed that were approximately identical to their parent chains, but with less than optimal structures that were unstable and prone to degradation. Natural selection of chain structures which were more resistant to degradation could have then occurred, allowing them to replicate and produce more stable chains (Voet and Voet, 2004). A few observations led to the theory that the initial self-replicating system was entirely RNA based. First, the RNA of certain species has shown catalytic properties, allowing it to act as an enzyme in biological systems. Second, ribosomes, which are molecules essential to the translation of proteins from RNA, are approximately seventy percent RNA by mass themselves, and only thirty percent protein by mass. Early ribosomes could have been entirely RNA based, enabling the synthesis of proteins to optimize early ribosome structures and the translation process (Voet and Voet, 2004). There is a substantial challenge to the theory of the 'RNA World': how and when the formation of primitive cellular membranes or boundaries occurred. If the RNA based processes described above occurred in a primordial soup of randomly mixed RNA molecules of various structure and stability, the ability of any one optimized structure to predominate and thrive by natural selection would be 11 severely hindered. Even a primitive form of cellular boundaries would enable RNA molecules to replicate and natural selection to preferentially favour cells with optimum chain structures. From an energetic standpoint, cells must invest a substantial amount of energy to the transport of molecules across membranes, so even primitive boundaries would have hindered development in the prebiotic world (Voet and Voet, 2004). It is possible that the original primitive genetic material was neither DNA nor RNA. One recently discovered alternative to RNA is glycol nucleic acid (GNA). GNA consists of nucleic acid bases linked to glycol groups in place of ribose groups. A glycol group is less complex than a ribose group, resulting in simpler oligonucleotides that could more readily associate in a prebiotic world (Zhang et a?, 2006). These molecules have not been found in any modern organisms. As a result, determining how these molecules could behave in prebiotic or living systems must be entirely based on computer models and experimentation. Determining thermodynamic parameters for these species will be essential to modelling the behaviour of GNA-based prebiological systems. 1.3.3 The Theory of the Origins of Life at Hydrothermal Vents Hydrothermal vents have chemical characteristics that could have supported a prebiotic world. Living systems are dependent on water; however, many of the organic reactions believed to be involved in the initiation of life are far better supported by organic solvents which have much lower dielectric constants than water at ambient temperatures and pressures. At elevated temperatures and 12 pressures, the dielectric constant of water decreases substantially, however, and would more readily enable many of these organic reactions (Hazen, 2005]. High temperature and pressure water could provide the kinetic energy necessary to overcome reaction barriers. However, perhaps the greatest obstacle to organic reactions under hydrothermal conditions is thermal decomposition of reaction products. Residence time of seawater inside ocean vents is estimated to be around 22-45 yr, although exact values will be dependent on the nature of the vent in question. At vent openings, water exits at elevated temperatures and contacts cold ocean water which causes a significant temperature gradient. However, many organic species have half lives of only 15-20 minutes or less over 200 0C, and this gradient may not cool reaction products sufficiently to prevent decomposition (Miller and Bada, 1988). In vent walls and along fractures leading away from the vent chimney, however, iron sulfide traps exist which attract hydrophobic organic molecules and could promote reactions such as the polymerization of amino acids (Russell et ai, 1988). Temperatures in these crevasses could also be somewhat milder, slowing decomposition rates further and stabilizing organic reactions. 1.3.4 Abiotic Formation of Biomolecules under Hydrothermal Conditions Under hydrothermal conditions, the synthesis of biomolecules seems to occur in metastable states. Elevated temperatures provide the energy required for oxidation reactions to overcome kinetic barriers and form metastable organic products. Additional kinetic barriers may prevent the conversion of metastable 13 organic reaction products to other less desirable decomposition products (Shock, 1990). No studies that have successfully synthesized nucleic acid bases and nucleosides under hydrothermal conditions have yet been reported. However, amino acids have been synthesized from aqueous solutions of C2H2, H2, O2, and NH4HCO3 at 200-2750C and NH4OH, HCHO, NaCN, and H2 at 2100C (Marshall, 1987; Marshall, 1994; Miller, 1953). No reactions occurred below 1500C, indicating that hydrothermal solutions were needed to provide sufficient energy to overcome kinetic constraints (Marshall, 1994). As reaction time increased, decomposition of the amino acids was observed, suggesting that Shock's (1990) theory of metastable states in organic synthesis is correct. 1.4 Engineering Applications of Extremophiles and DNA Under Hydrothermal Conditions Understanding the behaviour of biological and pre-biological molecules under hydrothermal conditions is also applicable to several areas of engineering. 'Extremophile' is a broad term applying to organisms able to thrive under conditions that are toxic to most other life. They typically belong to the domain of the Achaea, a group of single celled organisms with no cell nucleus or defined cellular organelles; however recently eubacterial and eukaryotic extremophiles have been discovered (Madigan and Marrs, 1997; Rothschild and Mancinelli, 2001). Extremophiles acclimated to high temperatures and acidic conditions, such as those found in hydrothermal vents, are often resistant to heavy metals and can be 14 useful in the digestion of minerals (Demirjian et al., 2001). For instance, genetically modified Deinococcus geothermalis has been used for in situ bioremediation of mixed radioactive material at elevated temperatures (Brim et al, 2003). Organisms have been genetically engineered to produce modified amino acids and other chemicals that enable them to withstand elevated temperatures, allowing them to germinate in harsher environments (Alia et al, 1998; Yang étal, 2005). Recently, a mixture of thermophilic bacteria extracted from acid mine drainage were successfully used to recover copper from chalcopyrite (Wu et ah, 2007). The benefit of using such organism is their ability to digest sulfides and tolerate the elevated temperatures that result from the chemical processes occurring within the reactor (Wu et al, 2007). The synthesis of many pharmaceuticals, agrochemicals, and other organic species often takes place under harsh conditions, and as such, enzymes obtained from extremophiles acclimated to such environments make excellent catalysts (Demirjian et ah, 2001). Enzymes obtained from thermophiles, organisms capable of thriving at elevated temperatures, have been used for many other purposes as well, such as paper bleaching, detergents, and genetic engineering (Demirjian et al, 2001; Sellek and Chaudhuri, 1999). The starch industry is one of the largest users of thermostable amylases, a type of enzyme capable of hydrolyzing starch into glucose and other sugar products (Gomes and Steiner, 2004). Thermostable hemicellulases, enzymes which catalyze hemicellulose hydrolysis, have decreased the need for halogen use in paper bleaching processes, thus decreasing pollution from the pulp and paper industry (Gomes and Steiner, 2004). DNA polymerases, the enzymes 15 responsible for DNA replication, may be particularly interesting for future genetic engineering studies under a broad range of conditions (Aguilar et al, 1998). Extremophiles produce a wide range of proteins and enzymes, often referred to as 'extremozymes', which have special properties not found in other organisms. 'Extremozymes' can be produced synthetically, however it is often easier to harvest them from the extremophiles themselves to minimize contamination from other chemical sources, and maximize specificity of final products. Thermophiles have been successfully cultivated using membrane bioreactors with cell recycling and cross-flow filtration. This maximized biomass yield, and also made it possible to extract protein products such as enzymes (Aguilar et al, 1998; Schiraldi et al, 1999). Enzyme variants more useful for technological purposes can be produced, but to do so requires that the organism's DNA be well understood and appropriately modified. While several studies have been undertaken to modify extremophiles for various applications, relatively little has been done to understand the thermodynamics behind their metabolic processes. DNA is particularly sensitive to high temperatures and radiation, and its stability and function under such conditions are dependent on its structure and composition (Rothschild and Mancinelli, 2001). Understanding the effects of temperature and pressure on these organisms and their metabolisms would be greatly increased by characterizing the thermodynamic properties and stabilities of biological and pre-biological molecules such as amino acids and nucleic acid components. 16 Nucleic acids also have novel applications in nanoengineering. Recently, DNA has been used as a backbone for various nanomaterials. For example, techniques to stabilize DNA junctions with three or more double helices emanating from a single point developed by Seeman and Kallenbach (1983). These have allowed for the construction of complex DNA structures. Following this work, two- dimensional antiparallel structures were constructed that are capable of supporting the assembly of symmetric molecular structures (Li et al, 1996). One of the most beneficial aspects of using DNA as a nanomaterial is its ability to self-assemble. The first study directing the self assembly of two dimensional crystals made it possible to accurately build detailed nanomaterials for use as molecular sieves, catalysts or structural scaffolding for computer chips (Winfree et al, 1998). Most recently, Douglas et al (2009) have developed molecular self-assembly processes to form three dimensional scaffold molecules suitable for use as biosynthetic machines. Kershner et al (2009) have developed lithographically patterned surfaces with DNA binding sites to control the exact location and orientation of molecules for use in electronic micro circuitry. As these technologies develop, studies will focus on a wider range of temperatures, necessitating modelling software and an understanding of how these molecules function under a range of conditions. 1.5 Thermodynamics of Aqueous Solutions 1.5.1 Reaction Equilibria Chemical equilibria are a crucial element of the study of chemistry. For the discussion that follows, we define a general equilibrium: 17 aA + bB ç± cC + dD (1.1) where A, B, C and D are chemical species with corresponding stoichiometric coefficients a, b, c, and d, respectively. The relative concentrations of species at equilibrium can be described by an equilibrium constant, K, written as: K = (accO/0BV) = {(mccrnDd)/(mB»mAa)}{(ycCYDd)/(YBbYAa)} = Q UiYt*0 (1-2) where m denotes species molality, a is activity, ? is the activity coefficient, and ? is the stoichiometric coefficient of species i. The equilibrium quotient is designated Q, and is a product of molalities, only. The activity coefficient term ????® is dependent on the ionic strength of the solution. Ionic strength is described by: / = \UmiZf) (1.3) where m and ? are the molality and charge of each ionic species, respectively. Ionic strength must include contributions from all ionic species in solution. As the ionic strength approaches zero the value of activity coefficients approaches unity. Many models exist to estimate the activity coefficients, such as the Debye- Hiickel limiting law and various extended variations of it (Harned and Owen, 1958). The challenge here is choosing a correct model for the activity coefficients. Many models exist, some of which are more useful at low or high ionic strength while others are better for extrapolation to high temperatures. Ultimately, each model is "best" for a certain purpose. The ion interaction model proposed by Pitzer (1991) includes short and long range Debye-Hückel interactions, and has been effective in modelling electrolyte behaviour over a wide range of concentrations and at high temperatures. The challenge of this model is that it is a fitting model for which 18 experimental data are needed, and thus is not effective for extrapolations. For complex mixed systems, data for the binary systems are required first, and can then be extended to the multi-component systems. The "model substance" approach is commonly used for estimating v¡ between 150 and 250 0C, with molalities limited to 0.01 to 0.1 mol kg1 (Lindsay, 1980]. This model assumes that all ionic species have activity coefficients which can be related directly to those of sodium chloride, yNaci: Sodium chloride has been studied extensively, and values for its activity coefficient are well established up to high temperatures (Archer, 1992). This approach can be used to directly predict activity coefficients to experimental data without any extrapolation. Above 300 0C, however, charged solutes begin to ion pair, and using a model substance such as sodium chloride becomes ineffective. With the model substance estimation for the activity coefficient, equilibrium constants can be determined. The importance of the equilibrium constant lies in its correlation to the Gibb's free energy, AG°: ArG° = -RTInK (1.5) The determination of other related thermodynamic properties is possible through the relationships described in 1.4. Acid-base equilibria can be generally described as: HAaq ^ Alq + H+ (1.6) Ki. = ((mA-)(mH+)/mHA) ((Ka-)(Kh+)/7ha) [1.73 19 Bao + H2O1 ç± BHa+q + OH" (1.8) Klb = ^^0H-)(mBH+)/m \ (to0H-XYBH+)/\ (1.9) where Ku and /fib are the ionization constants for a general acid HA and a general base B. At high temperatures, solvent-ion structure changes and has a dramatic impact on ionization constants. Water is highly ordered, forming structured networks of hydrogen bonds around ions at low temperatures. Increasing the temperature towards the critical point decreases the strength of hydrogen bonds, thus breaking the ordered structure and causing long range solute-solvent interactions to dominate solvation behaviour. Presenting reactions in their isocoulombic forms, meaning that charges on each side of the equation are symmetric, minimizes these effects and simplifies the interpretation of the temperature dependence of ionization constants. To do this, Equations 1.6 to 1.9 are combined with the ionization of water: HAaq + OH" ^ A-q + H2O1 (LIO) tfia,0H = {^a-/(^?a"???-)}{7a-/(??a7??-)} (1-11) Baq + H+ ^ BH+ (1.12) Kib,H = {wBH + /(mBmH+)}{yBH+/(rB7H+)} (1-13) where Ku1OH= Ku/Kw , Kib,n=Kib/Kw, and Kw is the equilibrium constant for the ionization of water. 20 1.5.2 Thermodynamic Relationships to Gibbs Free Energy The relationship between standard Gibb's free energy and the equilibrium constant is described in Equation 1.5. Partial differentiation of the Gibb's energy yields relationships for the standard partial molar volume, entropy, enthalpy, and heat capacity of reaction: ArV° = (dAG°/dp)T [1.14) ArS° = -(dAG°/dT)p (1.15) ArH° = -T2{d(AG°/T)/dT}p (1.16) ArC°P = (dAH°/dT)p (1.17) These properties are discussed in detail below. 1.5.3 Apparent and Standard Partial Molar Properties of Aqueous Solutions Extensive solution properties such as mass, volume, and heat capacity are dependent on the size of the system or the amount of material under study, and are a function of pressure, temperature, and the relative ratios of each solution component. The degree to which an extensive property of a solution or mixture varies with changes in molar concentration at constant temperature and pressure is indicated by its associated standard partial molar property. Generally speaking, a standard partial molar property for a solution can be determined from the partial derivative of a given extensive property as follows: 21 Jí=(0WaA)T.p,n, C1-18) where the subscripted term n\ means that the only solution parameter which varies is the concentration of component i, and all other composition related variables must remain constant. Thus, the standard partial molar property can be described by the change in VSoi when an infinitesimally small amount of the solute i is added. For pure substances, the standard partial molar property is clearly equal to the molar property. Standard partial molar Gibb's energy, also referred to as the chemical potential, is a very important standard partial molar property. Chemical potential is related to the change in the Gibb's free energy of a system, and is described by: µ? = (3G0ZdTi1)P1T1n. [1.19] Standard partial molar properties are typically determined from apparent molar properties. An apparent molar property is the contribution of some solution component to a solution property relative to the solvent property assuming the solvent is a pure liquid. Mathematically, an apparent molar property, ???2, is expressed as: Y^i=(YsOFn1YhIn2 (1-20) where m and m are the numbers of moles of pure solvent and solute, respectively, and Yi* is the property of the pure solvent. If concentrations are measured on the molality scale, then m can be replaced with the moles of solvent in 1 kg of solution, and n2 with the solution molality, m, and Equation 1.20 becomes: 22 ??,2 = [Ysoi - (100OV1VM1)Vm (1.21) where Mi is the molar mass of the solvent. The extensive variable of a binary system consisting of a solvent and a solute can be related to its corresponding standard partial molar property using Euler's theorem (Pitzer, 1995): Ysoi=n~Yi+n2Y2=Ii1 Y*x+n2 ?f,2 (1.22) where Yso\ is the extensive property of a solution, Fis the standard partial molar property, ?? is the apparent molar property, J1 is the property of the pure solvent and m and m are the moles of solvent and solute, respectively. 1.5.4 Standard Partial Molar Volumes Apparent molar volumes of binary aqueous solutions, ??,2, can be determined from relative solution densities using the following relationship: VVi2 = 1000(p; - Ps)/{p*wpsrn) + M2Ip5 (1.23) where m is the solution molality in mol kg1, and Mz is the solute molar mass in kg mol·1. More generally, for higher order solutions, this relationship can be expanded to the following: ?f>? = 1000(p; -Ps)/{p*wPsY.imi) + S?t????; I¿ m;) (1.24) where rm and M¡ are the molalities and molar masses for each solute in the solution. It then follows that for ternary solutions, the apparent molar volume can be determined by: 23 1^,2,3 = IOOOO; - Ps)/(PwPs(.™2 + m3)) + (m2M2 + Tn3M3)Zp5Cm2 + m3) (1.25) For mixtures of a nucleic acid component, XH, with HCl, the following reaction equation holds: XH + HCl ci XH^ + Cl" (1.26) According to Young's Rule, the total measure of a thermodynamic property can be expressed as the sum of the contribution of the components of the solution using the following relationship: mtY,, = (S?t??? + mYrel (1.27) where Yre\ is the "chemical relaxation" contribution (Woolley and Hepler, 1977). Mixing contributions were assumed to be negligible for both the heat capacity and volume studies. Density measurements were done with excess HCl under isothermal and isobaric conditions, so the relaxation term can also be neglected from standard partial molar volume calculations. For the molar volume calculations of protonated species, ™-V molalities of these species, and m is the total molality of all species in solution. Assuming that there is negligible speciation in the presence of excess HCl, so that the nucleic acid base or nucleoside exists as XH2+ only, and using the assumption that the contribution of protons to the standard partial molar property is zero, this expression simplifies to: 24 mVViexpt = (rnXH}cl-V nucleic acid base alone. 1.5.5 Heat Capacities The apparent molar heat capacity for binary aqueous solutions can be determined from the massic heat capacity: CPl9 = M2cPiS + 1000(Cp,s - cPiW)/m (1.30) where cp,s and cp,w are the massic heat capacities of the solution and water, respectively, and Cp, s - c>iW)/Se mÉ (1.31) Cp, 25 In Equation 1.33, the relaxation term and Cp, 1.5.6 Extrapolating to Infinite Dilution Standard partial molar properties are obtained by extrapolating apparent molar properties to infinite dilution. Mathematically, their relationship can be described by: ^2=^,2+777(0^,2/0/77)^ (1.35) Thus, as the molality approaches zero, the apparent molar property approaches the value of the standard partial molar property: y2° = lim ?f>2 Apparent molar properties of ionic species often show strong concentration dependences, and models must be used such as that described above to determine standard partial molar properties. From the extended Debye-Hückel limiting law, at a constant temperature and pressure, the apparent molar volume or heat capacity of an electrolyte measured as a function of ionic strength should produce a constant limiting slope according to the function (Redlich and Meyer ,1964): 26 ?f = Vi + ???3/2??1/2 + ???t? (1.36] Cp,f = C°p,2 + ?f??^t?1^ + Bcœm (1.37) where Av and ?f are the Debye-Huckel limiting slopes for volumes and osmotic 2 coefficients, respectively, ? =~?t^-2 m and Bv and Bc are fitting parameters. Experimentally, a line fitted to concentration dependent data using Equation 1.36 or 1.37 will have an intercept at zero concentration which is equal to the standard partial molar property. These models can only be applied to systems measured at low concentrations because as concentrations increase, points will deviate increasingly from these linear relationships. For neutral species, no concentration dependence is typically observed and measured apparent molar properties are often directly equated to the standard partial molar properties without any extrapolations. Rogers and Pitzer (1982) developed a model to extrapolate apparent molar volumes to infinite dilution. First, Pitzer's parametric equation for the excess Gibb's energy of a binary solution containing 1 kg of solvent is: 1000GeV(niMwÄ70 = -?f(41 / b) ln(l + bl1'2) + 2m2vMvx (^ + (2^/a2/) (l - (1 + alW)e-«lU2)) + m3(vMvx)3/2C^ (1.38) where Vm, and ?? are the numbers of positive and negative ions, respectively; ß^?, and ß^?, and C^x are parameters from Pitzer's equations, ?f is the Debye-Huckel slope for the osmotic coefficient, I is the ionic strength of the solution, a = 2.0 for all 1-1 electrolytes and most other solutes, and b = 1.2 for all electrolytes. 27 Standard partial molar volumes can be described using the excess Gibb's energy using the following relationship: V,¿ = V°2 + (Vn2)WZaP)T (1-39D Substituting Equationl.38 into Equation 1.39 yields: V9 = V°2 + v\zMzx\Avh(0 + 2vMvxRT{mBvMX + m2(vMzM)CvMX) (1.40) where: /i(/) = In(I + b1'2) /2b (1.41) BSx(O = ßS + (2ßS/a2/) (l - (l + alW)e->in) (1.42) CMx = CMX/(2|zMz*|1/2) (1.43) and zm and ?? are the charges of the cations and anions, respectively. An analogous extrapolation has been developed for apparent molar heat capacities (Silvester and Pitzer 1977): Cp, 28 1.6 Equations of State for Standard Partial Molar Properties 1.6.1 The "Density" Model Marshall and Franck (1981) developed the density model to describe the approximately linear relationship between the ionization constant of water and the log of the density of water: logK = A + B/T + C/T2 + ?/?3 + (E + F/T + G/T2)logpw (1.48] where A, B, C, D, E, F, and G are fitting parameters, and pw is the density of liquid water. The behavior of many other aqueous species can be fitted with this expression and species specific parameters (Mesmer et al, 1988]. The equations described in Section 1.4 can be used to relate this model to other thermodynamic parameters such as enthalpy, heat capacity, and entropy. Converting Equation 1.48 to natural logarithms gives: InK = a + b/T + c/T2 + d/T3 + (E + F/T + G/T2)lnpw (1.49] where a, b, c and d are the parameters from Equation 1.48 multiplied by 2.303. Substituting in Equation 1.49 to solve for AG° gives: AG° = -R{aT + b + c/T + d/T2 + ETlnpw + Flnpw + (G/T)lnpw} (1.50] Taking the derivative of Equation 1.50 with respect to temperature at constant pressure gives: ?5° = R[b + 2c/T + 3d/72 - ET2ccw - F(Taw + lnpw) + G{-aw + (2/T)lnpw}] (1.51] where aw is the coefficient of thermal expansion of water. The derivative with respect to pressure of Equation 1.50 yields: Vo = -Rßw (TE + F + G/G) (1.52] 29 where ßw is the isothermal compressibility of water. Combining the relationship between enthalpy and Gibb's free energy described in Section 1.4 and Equation 1.52 gives: AH° = R[-b - 2c/T - 3d/T2 + ET2Ct + ¥(Taw - lnpw) + G{aw - (2/T)lnpw [1.53] Finally, the derivative of Equation 1.53 with respect to temperature yields an expression for the heat capacity: AC°P = -R[2c/T2 + 6d/T3 + E(2Taw + T2 daw/dT) + F(T daw/dT) + G{daw/dT - 2aw/T + (2/G) lnpw}] (1.54) Anderson et al. [1991) proposed that terms c, d, e, and g can often be neglected from the model at temperatures below 573 K, thus simplifying the above equations further. 1.6.2 Helgeson-Kirkham-Flowers (HKF) Equations of State In aqueous solutions at ambient and near-ambient temperatures, short range interactions between solvent and solute dominate solvation behaviour. However, at elevated temperatures, the dielectric constant of water decreases, and long range polarization effects between molecules dominate. Generally, then, a standard partial molar property can be defined by these two interactions; one term to incorporate low temperature behaviour, and one for high temperature behaviour. Helgeson and Kirkham [1976] and Helgeson et al. [1981] observed that at elevated temperatures, standard partial molar volumes and heat capacities can be described quite well by the Born equation, and used this to develop an equation of state. According to the revised HKF equations of state, any standard molar property 30 of an aqueous species, Y0, can be described as a sum of solvation and non-solvation (structural) contributions (Tangerand Helgeson 1988): G = ?£ + AY; (1-55) where ???° and ??5° are the non-solvation (non-Born) and solvation (Born) contributions. The Born component of the equation describes the long range polarization effects which dominate solvent-solute behaviour at high temperatures, and the non-Born terms in the equation describe the short range hydrogen bonding behaviour that dominates low temperature behaviour. The non-Born contributions to volume and heat capacity of aqueous solutions are defined by: àV; = 3l + Si2ZQV + P) + {a3 + 34/(? + P))[IZ(T - T)} (1.56) and àC°Pin = C1 + c2/(T - T)2 - {27/(7 - Q)3Ha3(P - Pr) + a4 ln{( 31 Q = -{d(l/e)/dP}T = l/e2 (de/dP)T (1.60) Y = -(a (1/e)/37% = 1/e2 (de/T?)? (1.61) and X = (ßY/dT)P = (1/e2)[(?2e/0G2)? - (2/e)(3e/3G)?] (1-62) The Born coefficient, ?, is defined for the jth aqueous species as: ?} =œ?bs -Zjcoft (1.63) where 32 It follows that for charged, aqueous species, the HKF standard molai volume and heat capacity expressions are: Vo = B1 + a2/QV + P) + {a3 + 34/(? + P)KV(T - T)} - œQ + (1/e - l)(dœ/dP)T (1.67) and Cp° = C1 + c2/(T - T)2 - {2T/(T - T)3}[33(? - Pr) + a4 In {? + P/(? + Pr)}] + ??? + 2TY(dü)/dT)P - T(I/e - 1)(32?/d?2)? (1.68) The Born coefficient for neutral aqueous species, such as nucleic acid bases in water, is assumed to be independent of temperature and pressure, so the Born contributions simplify to: ?^° = -œeQ (1.69) àCPiS° = ?ß?? (1.70) where ?? is the Born coefficient for neutral species, but cannot be based on effective ionic radius, and is used as a fitting parameter. The standard molai volumes and heat capacities for neutral aqueous species can be expressed as: Vo = 3l + 32/(? + P) + {a3 + a4/(¥ + ?)}{1/(G - T)} - and Cp° = C1 + c2/(T - T)2 - {2T/(T - 0)3}[a3(P - Pr) + a4 In {(? + P)/(? + Pr)}] + ?ß?? (1.72) Experimental thermodynamic data reported in literature for nucleic acid bases and their related molecules are limited to temperatures between 25 0C and 55 0C (Lee and Chalikian, 2001; Patel and Kishore, 1995). These data were used in combination with the HKF revised EOS, correlations and group additivity algorithms 33 to calculate thermodynamic parameters for these molecules at high temperatures and pressures. LaRowe and Helgeson (2006) were the first to predict the behaviour of nucleic acid components at elevated temperatures and pressures, and their models became the benchmark for the research that followed. Due to the lack of reference data, many parameters had to be estimated to build the models proposed by LaRowe and Helgeson (2006), so their validity at high temperatures was suspect. In cases where group additivity models had to be applied, LaRowe and Helgeson (2006) has to use data for very different molecules. Additionally, only neutral species were considered in the proposed models, but models predicting the behaviour of ionic species at high temperatures are needed for studying reaction scenarios. The heat capacity, volume and compressibility non-Born parameters, ai, a2, a3, a4, Ci, and C2, were determined from regressing low temperature experimental data (Lee and Chalikian, 2001; Patel and Kishore, 1995). The non-Born parameters dominate the model behaviour at low temperatures, so this regression technique is typically satisfactory. No high temperature experimental heat capacities were available to determine the Born parameter, ?ß. Instead, a correlation between ?? and the standard molai Gibbs energy of hydration, AG°hyd, was needed (Plasunov and Shock, 2001): œe = {0.624 + 18.51/(Ahyd G° - 21.7)}105 (1.73) This relationship requires values for AhydG0 which are not available for nucleic acid bases or nucleosides. Instead, these values were estimated from the expression: 34 AhydG° = àG°naq)-AG°ng) =AsolG°-AsubG° (1.74) where AG°f(aq) and AG°f(g) are the standard molai Gibbs energies of formation of the aqueous and gas at 298.15 K and 1 bar, respectively, and AsoiG° and ASUbG° are the standard molai Gibbs energies of solution and sublimation. The latter two parameters were determined using extrapolations and literature data where available. The proposed Born parameters and predictions of high temperature behaviour for these species are the current "best guess" estimates, which cannot be accepted with certainty because of the lack of experimentally determined thermodynamic data to support them [LaRowe and Helgeson, 2006). 1.6.3 OLI Software The OLI software package is a series of programs designed to predict aqueous solution, process, and corrosion chemistry, and transport properties for process simulations. It is a convenient tool for modelling industrial and geothermal systems. It uses the HKF equation of state and the Bromley-Zermaitis or Pitzer activity coefficient models, with fitted parameters based on published data for a variety of minerals, ions, and other neutral solutes including amino acids. Several different unit operations using a variety of solid, aqueous, and vapour phases can be combined for process simulations. Currently, no public database exists which includes the DNA and RNA components which are the focus of this study. Private databases can be built for individual use, but cannot be widely used without first being publicly distributed. The inclusion of new experimental data and models into the public OLI system 35 would provide a useful predictive tool for scientists to study geochemical reactions with DNA components under hydrothermal conditions. In completing new HKF models from experimental data measured at elevated temperatures, it is our hope that these new models can be included into the OLI database and used in future reaction simulations. 1.7 Hydrothermal UV-Visible Spectroscopy 1.7.1 Background UV-visible spectroscopy is based on atoms' and molecules' ability to undergo electronic transitions from occupied to unoccupied orbitals when they absorb electromagnetic radiation. Visible light, which is defined as the radiant energy that can be detected by the human eye, has wavelengths in the range of 400 to 750 nm. UV-visible spectroscopy includes ultraviolet radiation as well, which expands the total spectral region to 190-800 nm. When an atom or molecule is exposed to photons in this range, excitations of outer valence electrons and inner shell d-d transitions will occur. The energy of the electronic transition(s) determines at what wavelengths absorption occurs for a given species. The segments of the incident radiation corresponding to these transitions will be absorbed, leaving gaps in the transmitted radiation. Measurement of these gaps in transmitted radiation produces the absorption spectrum (Clark et al, 1993). The fraction of light absorbed, or equally the fraction of light transmitted, is related to the solution concentration and the thickness of the solution sample according to Beer's law. If the intensity, /, of a parallel beam of monochromatic light 36 with wavelength ? is passed through an absorbing sample layer with concentration c, then the change in intensity, al, can be expressed as: dl = -kxIdc (1.75) where k\ is a proportionality constant dependent on wavelength. Rearranging the equation and integrating between /o and / for c from 0 to c gives: Zo0lo(/o//) = -kAc/2.3O3 (1-76) where /0 and / are the intensity before and after passing through a sample, and c is the concentration in mol L1. Integrating an analogous relationship between the change in intensity and the change in path length gives the Lambert law: logwQ0/O = -k'Ab/2.303 (1.77) where b is the path length in cm. Combining these equations gives: log100o/0 = -k'\bc/2.303 (1.78) The term logio(/o/i) is the absorbance of the solution, typically denoted as A, and - kx/2.303 is the molar absorptivity. Simplifying the above equation leaves: A = log(///0) = ecb (1.79) where e is the molar extinction coefficient in L mol1 cm1. This model can be extended for multicomponent systems (Clark et al. 1993): Atotal = S? (fi C1 bt + s2c2b2 + ¦¦¦ + EiCib{) (1.80) In solution, molecules are close together, allowing for interactions which cause a broadening of each molecule's respective energy levels. As a result, the UV-visible spectra of solutions appear as broad bands, without fine structure (Clark et al, 1993). 37 Organic molecules with highly conjugated ring systems also have electrons capable of state transitions in the UV region. Nucleic acid bases, nucleosides and nucleotides all contain at least one conjugated carbon ring, and as such, are UV active, particularly between 200 and 400 nm. 1.7.2 Developments in Hydrothermal UV-visible Spectroscopy As electronics and technology have advanced, single beam UV visible spectrophotometers have been developed as an excellent alternative to their double beam counterparts, especially for hydrothermal studies. Single beam instruments allow the spectrum of a blank solution be measured in sequence with the sample in a single hydrothermal cell that could more easily be installed in a spectrometer. Spectroscopic studies can be carried out in batch or flow cells, depending on the system under study. To ensure that only a single solution phase is maintained, cells must also be capable of holding pressures substantially above the steam saturation pressure at any given temperature. The availability of modern HPLC pumps led to the development of hydrothermal UV-visible flow cells. Cell materials must be selected to withstand the harsh reaction conditions. For example, gold, platinum, sapphire and Teflon were used by Johnston and Chlistunoff (1998) to create a UV-visible cell capable of measuring in situ in supercritical water. Flow studies are particularly useful when thermal decomposition must be minimized; but the progression of hydrothermal reactions over a longer period of time are best studied in batch systems. In this study, both methods were used to study different reaction scenarios. 38 Thermally stable colorimetrie pH indicators suitable for UV-visible experiments have been used to measure equilibrium constants of ionization of simple acid and bases at temperatures up to 400 0C [Ryan et al, 1997; Xiang and Johnston, 1994, 1997; Chlistunoff et al, 1999]. More recently, colorimetrie pH indicators were used to determine ionization constants of glycolic acid, lactic acid, glycine, a-alanine, and proline using UV-visible spectroscopy up to 250 0C (Bulema, 2006; Clarke et al, 2005). Such indicators are used at very low concentrations and measure the activity of H+ in solution, enabling the study of molecules that are not UV-active without interfering with the solution activity. Experiments of this type can be conducted with a series of buffer solutions of the acid or base of interest with a trace amount of indicator to give a measurement of the pH. Determining acid ionization constants of UV active molecules requires a converse measurement process. Buffer solutions of an acid or base whose ionization constants at elevated temperatures are well known are used to set predetermined pH values, and the spectra of the UV-active chromophore gives a measure of its speciation. This method was very effective in measuring the acid ionization constants of adenine and uracil up to 200 0C (Balodis, 2007). 1.8 Methods of Kinetic Analysis 1.8.1 Chemical Reactions To mathematically describe the changes in concentrations of species in a reaction over time, a reaction model and kinetic relationships between species are necessary. A general reaction model can be described by: 39 aA + bB -» cC + dD (1.81) where A, B, C, and D are chemical species with molalities of p?a, mn, me, and p??, respectively, and a, b, c, and d are their respective reaction coefficients. The rates of formation of the products or the rates of consumption of the reactants, r, can then be described by: r = - 1/a (dmjdt) = - 1/b (dmB/dt) = 1/c (dmc/dt) = 1/d (dmD/dt) [1.82) Reaction rate is related to the concentration of the reactants by the following general formula: rA = —kmAml [1.83) where ? and y are exponents which are determined experimentally and k is the reaction rate constant which is dependent on reaction conditions but independent of species concentrations. The order of the reaction is equal to the sum of the exponents of the reactant concentrations. In this case the order would be [x+y). Graphical interpretation of integrated rate laws or non-linear least squares analysis can be used to determine the reaction order. For instance, for a first order reaction with one reactant, A, the integrated rate law would be: InCm4) = -kt + In(Jn4)Q (1-84) where t is time. A plot of In(A) versus time would yield a straight line whose slope is the rate constant, k. The reaction order can provide insightful clues into reaction mechanisms. 40 1.8.2 Kinetic Measurement Techniques Several different techniques for measuring reaction kinetics have been developed, although in general, they involve either batch or flow type systems. Both methods provide certain advantages over the other. Flow systems can be more complex to work with, but flowing solutions minimize reactions with cell components. Batch reactors offer some benefits over flow-type counterparts for slow reactions, because timed experiments can be conducted over longer periods to observe the reaction behaviour. Whatever technique is selected, it must adhere to certain rules to ensure that it produces accurate kinetic results. First, all species must be measurable as a function of time, and individual species should be distinguishable from each other. The speed of the reaction must be sufficiently slow for the chosen technique to be able to track its progress effectively in situ. Quenching of a reaction can alter species concentrations and solubility, and species may react or decompose to form species which are more stable under the changed conditions. Many studies of the kinetics of organic and inorganic reactions by spectroscopic methods have been conducted under hydrothermal conditions. The benefit of using spectroscopy for such experiments is that measurements can be conducted in situ without disturbing the reaction progress. For example, UV-visible spectroscopy has been used to measure hydrothermal reaction kinetics of aspartic acid, alanine, and glycine in situ [Cox and Seward, 2007a, b). A flow through cell was used to load samples of amino acid solutions into the cell and then stopped to take spectra at regular intervals over a chosen range of time. This dual purpose cell 41 allows for either flow or stopped experimentation, thereby broadening the range of systems which can be studied. Flow reactors have been used to determine kinetic parameters for the induction of the rapid exothermic decomposition of (NH30H]N03 from Raman spectroscopy [Schoppelrei et al, 1996]. Rather than determining rates of change of concentrations over time, which is the conventional method for kinetic experiments, spectra were obtained continuously as either temperature or flow rate was changed, and the other parameter was kept constant. Spectra were used specifically to determine the start time of the reaction. FT-IR studies on this reaction system were also studied in batch and flow experiments to confirm the Raman results (Kieke et al., 1996]. The rate and efficiency of the synthesis of e- caprolactam and pinacolone in supercritical water has also been studied using flow systems and Raman and FT-IR cells, respectively (Ikushima et ai, 1999; Ikushima et al, 2003]. 1.8.3 Data Analysis Tracking the concentrations of reactants and products in such a way that each species is distinguishable from the others is a challenge for kinetic experimentation. Spectra of this type of system will be a complex combination of the spectra of each individual species best described by a matrix showing the contributions of each factor in the system. Particularly for stopped flow experiments such as those described above, spectra taken at regular timed intervals show the changes with time of a chemical system, which depends on the kinetic interrelationships between the species. 42 When the reaction order and/or the particular reaction products are not specifically known, factor analysis methods must be employed to determine the number of significant parameters in a reaction system. There are a few methods for applying factor analysis to chemical systems. First, the most robust computationally is Singular Value Decomposition (SVD], which calculates the number of significant factors affecting the spectra. Two other methods, Evolving Factor Analysis (EFA) and Window Factor Analysis (WFA), involve determining the "window" or frame of time in which a chemical species is significant in the spectra. EFA and WFA use different mathematical and visual inspections to determine the changes over time in the number of significant factors by determining the "window" in which a species is significant in the spectra, and can make unambiguous the number of chemical factors being added to or removed from the spectra (Maeder, 1987; Malinowski, 1996). Completing these two methods can be very laborious and time consuming. Several software packages exist to perform these analyses, particularly Specfit, which was used for this study. Ideally, the number of significant factors indicates the number of spectrally active species, for instance, the number of absorbing species in a UV-visible spectrum. SVD and other factor analysis methods determine all of the factors contributing to the spectra, both chemical species and otherwise. For instance, any change in the spectral baseline over the course of the kinetic measurement, such as window etching, would be observed as a factor changing the spectrum. It is not unusual to observe extraneous, unexpected factors in an analysis, particularly at high temperatures. 43 1.9 Research Objectives This project is primarily designed to expand the current thermodynamic data base for nucleic acid bases and nucleosides at elevated temperatures and pressures, particularly by determining standard partial molar volumes and heat capacities. The first goal of this project was to study neutral bases and nucleosides, for which some literature already exists, and the thermodynamic properties of nucleic acid bases and nucleosides in acidic solutions to address the current lack of experimental data for these important systems at elevated temperatures. We also attempted to assess the ribose contribution to standard partial molar properties from measured data, and to develop a model for the standard partial molar volume of guanine, a species whose solubility in water is so low that no previous literature data exist. A second goal of this project was to develop HKF models of measured data that could be utilized by the OLI modelling software. Currently, HKF models for nucleic acid bases and nucleosides have been extrapolated from data measured at temperatures no higher than 55 0C, and in some cases models are extrapolated from 25 0C data or no experimental measurements at all (LaRowe and Helgeson, 2006]. Models based on measured data at higher temperatures provide a better extrapolation, and better predictive models for reactions. Combining the models developed in this study with those previously developed for minerals and amino acids can provide a clearer picture of real world reaction chemistry in these complex environments. The third goal of this project was to study the thermodynamics of ionization of these DNA and RNA components. Standard partial molar properties of ionization 44 were determined for neutral and protonated species, and acid ionization constants of adenosine were measured in situ at elevated temperatures using UV-visible spectroscopy. Finally, this project aimed to study reactions involving adenosine. The decomposition of adenosine in formic acid and phosphate buffers was studied under hydrothermal conditions using UV-visible spectroscopy to observe differences in reaction spectra and assess the possibility of a phosphate-adenosine reaction product as a precursor molecule to AMP. 45 CHAPTER 2 EXPERIMENTAL PROCEDURES 2.1 Chemicals and Materials Nucleic acid bases and nucleosides were obtained from Biochemika with a purity > 98%, formic acid was obtained from Fischer (>98%], hydrochloric acid (-36 wt %), phosphoric acid (85 wt %) and sodium hydroxide (50 wt %) were obtained from Fischer, sodium chloride was obtained from Sigma Aldrich with a purity of >99.5%, and spectroscopic grade methanol (>99%] was obtained from Caledon Laboratories. All organic solids were dried over P2O5 under vacuum for a minimum of three days (Patel and Kishore, 1995]. Sodium chloride was dried for a minimum of three days at 160 0C. Solutions were prepared by mass using milli-Q water with a resistance of no less than 18.5 O/cm3 that was purged with argon for 20 minutes before solutes were added. Solution concentrations were selected to be at least 20 percent below the solubility limits of the species in water (Baba et al, 1990; Constantino and Vitagliano, 1967; Herskovits and Harrington, 1972; Lakshmi and Nandi, 1976; Nakatani, 1964; Neish, 1948; Patel and Kishore, 1995]. Dissolution of nucleic acid bases was enhanced by heating the solutions in a hot water bath set to 40 0C until the solutes were completely dissolved, and then the solutions were cooled back down to room temperature overnight. Solutions of stock acids and bases were prepared by mass to approximately 0.5-0.75 mol kg1 , and then titrated using a Metrohm 794 basic titrino auto-titrator to obtain a molality to within ±0.2% based on a minimum of three titrations. These solutions were then diluted down to achieve desired buffer concentrations for UV- 46 visible experiments. Stock adenosine solutions were prepared to approximately 0.025 mol kg1, and were diluted down to approximately of 104 mol kg1 to obtain maximum absorbances between 1 and 1.5. Solutions of nucleic acid components for density measurements were prepared by mass to concentrations below published solubility limits which varied significantly for bases and nucleosides. Methanol solutions were prepared by mass to molalities with relative densities comparable to those of the three nucleoside solutions studied. For protonated nucleic acid bases and nucleosides in solution, hydrochloric acid solutions were prepared by mass and titrated a minimum of three times by a Titrino Autotitrator to obtain an average molality. Hydrochloric acid was added by mass in small excess, approximately 10-20%, respectively, to ensure that the nucleic acid bases and nucleosides were reacted completely and would not form equilibrium species when solutions were heated. Only a small amount of excess acid was used to ensure that this contribution did not dominate the measured apparent molar properties. Organic species were limited to a maximum molality of 0.05 mol kg1 to ensure that Young's rule would hold and to facilitate extrapolations to infinite dilution. 2.2 Determination of Standard Partial Molar Properties 2.2.1 Density Measurements The density of a solution is accurately measured in modern densimeters by determining the resonant frequency of a tube containing the sample (Kratky et al, 1969; Picker et al, 1974]. This study made use of two types of vibrating tube 47 densimeters. The instruments are calibrated by measuring the resonant frequency when filled with a fluid of well known density, such as water, relative to the frequency when filled with an aqueous solution of unknown density. The relationship between the resonant frequency and the relative solution density was described by (Kratky et al, 1969): ps = p;+kp(rs2-T¿) (2.1] where pw and ps are the densities of water and the solution in g cm3, respectively, tw and Ts are the periods of vibration of the tube containing water and solution, respectively, at a selected temperature and pressure and kp is the calibration constant for the densimeter which can be determined using solutions with well known densities, such as NaCl in water. Low molality solutions have very small differences in their densities with respect to water, and as such are especially sensitive to uncertainties in calculated apparent molar volumes. As a consequence, the water correction discussed below in Section 2.2.1 becomes particularly relevant. Errors in this correction could be caused by non-linear instrument drift; however it is assumed that this contribution is negligible because of frequent instrument calibrations. Errors in measurements caused by sample impurities were minimized by drying samples before use, as water was the most abundant impurity. Fluctuations in system temperature and pressure, particularly for the elevated temperature measurements, could provide an additional source of error. 48 2.2.1.1 Low Temperature Density Measurements Measurements were taken using a commercially available Anton-Paar DMA 5000 borosilicate vibrating tube densimeter at 5 degree increments from 15 to 90 0C. Once each target temperature was reached, samples were allowed ten minutes to equilibrate before measurements were made. Measurements were taken as the sample was heated and cooled, and data were compared to ensure consistency. Solutions were degassed three times by suction prior to injection, and three separate injections were used to obtain averaged values at each temperature. Temperatures inside the densimeter are measured by two 100O platinum thermometers and controlled to a precision of ±0.001 0C. Densities up to 3 g cm3 can be measured with a precision of 1.0 ? IO'6 g cm3. The equipment software is designed to determine the calibration constant kp at 20 0C using Equation 2.1 and two reference fluids, air and water. It then internally determines the density of an unknown solution relative to water. The density is then calculated from Kell's equation of state (KeIl, 1975), using the measured period of oscillation and the calibration constant. PDMA5000 = (P — Pw) + Pw1KeIl (2-2) where pdmasooo is the solution density given by the densimeter and pw,Keii is the density of water as determined by Kell's equation of state. To make sure all calculated parameters use one consistent equation of state, all measurements were corrected to be consistent with Hill's (1990) EOS for water using the following equation: 49 d? = Pw1HiIl — (Pw.before + Pw1after )/2 [2.3] where pw, Hm is the density of water from Hill's equation of state, and pw, before and pw, after are the water densities measured immediately before and after the sample density measurements, respectively. This correction was completed separately for every sample at every temperature, and added to the measured solution density as follows: Ps = Pdmasow + Sp (2.4) where ps is the solution density used to determine the apparent molar volume. Calibrations were conducted regularly, approximately once every one to two weeks. In these calibrations, the densities of air and water were compared to data tables derived from Kell's equations of state (Spieweck and Bettin, 1992). In addition to the calibration procedure, the water density was compared to reference data at 20 0C every one to two days to ensure agreement within 106 g cm3. If the density was not in good agreement with literature data, additional calibrations were conducted. 2.2.1.2 High Temperature Density Measurements Density measurements over 90 0C and 1 bar of pressure were taken using a custom built high-temperature and pressure vibrating tube densimeter (Xiao et a/., 1997). A schematic diagram of the system layout is shown in Figure 2.1. (1) Cell Configuration The vibrating tube is a 925 mm long Pt-10% Ir U-tube with 2 mm O.D. and 0.2 mm wall thickness, and it was mounted with silver solder to a cylindrical brass 50 block. Two inconel rods were cemented to each end of the tube in such a way as to prevent any electrical contact between the tube and rods. A permanent horseshoe magnet was also connected to the brass block, and the inconel rods were positioned between it. Outside the densimeter body, a phase-locked loop system is connected to these rods by fine silver wires. It was the interaction of the permanent magnetic field and an alternating current through one inconel rod that force the U-tube to vibrate, while the second inconel rod was used to sense the vibration. The tube was oscillated close to its resonant frequency of 152 Hz, and the period of vibration was measured using a Hewlett Packard, model 5316A, counter. 51 nnnnnis r,¿ nonnftfiooonaooooo Figure 2.1: Schematic diagram of the high temperature densimeter with [I) vibrating platinum u-tube, [2] densimeter cell body, (3) Inconel rods for sensing and driver current, (4) permanent magnet, (5) RTD, (6) brass oven, (7) thermal insulation, (8) stainless steel container, (9) heat exchanger, (10) aluminum preheater, (11) aluminum heat shield, (12) brass shield, (13) back pressure regulator, (14) stainless steel, waste reservoir, (15) sampling loop, (16) injection loop, (17) pump, and (18) nitrogen tank. 52 (2) Flow System Components Samples were injected into the system through two six port valves and a 15 cm3 injection loop from a syringe immediately before injection. It was force-filled with sample solutions that were degassed by suction. An Iseo 260D syringe pump was used to pump water into the densimeter at a constant flow rate of 0.5 cm3 min1. In between the nitrogen cylinder and the back pressure regulator was a stainless steel waste container which was filled with nitrogen to maintain pressure through the back pressure regulator, and was connected to the rest of the flow system. This waste container was periodically emptied by flowing nitrogen through a check valve below the container. Although a second Iseo 260D syringe pump was previously connected to the sample loop to stabilize the pressure when the solution was injected; however, it was not found to be necessary. (3) System Assembly and Controls System pressure was maintained by flowing the effluent into a nitrogen filled cylinder and controlled by a Tescom model 26-1700 back pressure regulator. It was measured with an Omega PX-623 pressure transducer and an Omega DP41-E panel meter. The pressure was maintained to within ±0.1 MPa; however a small pressure drop was observed when injecting solutions. This pressure drop corrected itself quickly after injection, and the system pressure remained stable during the period of measurement. The high temperature densimeter had two heaters, one for inlet preheating, and one for temperature control of the cell. The pre-heater was a Chromalox 53 catridge heater, and was connected to the inlet tubing, measured by a calibrated 100 O platinum RTD, model Omega PR-17-2-100-1/8-9-E, and controlled by an Omega CN76122 temperature controller. The cell temperature was measured using a calibrated 100 O platinum RTD, model Omega PR-11-3-100-1/8-9-E, which was connected to a Hewlett Packard, HP 3478A multimeter with a four lead configuration. The multimeter communicated temperature information to the data acquisition interface in Ohms. This RTD was placed near the U-tube in a hole in the brass cylinder to monitor the temperature of the solution as it passed through the tube. The system temperature was maintained to within ±0.02 0C throughout any one experimental measurement. While the system could be safely run up to 350 0C and 20 MPa, the nucleosides under study underwent thermal decomposition at or below 250 0C. System pressures were chosen well above the vapour pressure of water at the selected temperatures to ensure that no bubbling occurred inside the platinum tube. (4] Calibration Methods Calibrations can be conducted using any two fluids with well known densities. To determine the calibration constant, kp, in Equation 2.1, water and solutions of sodium chloride at a concentration of approximately 2.0 mol kg1 were measured a minimum of three times throughout the day to minimize calibration errors due to drift. The calibration constant was then determined using reference density data for water and sodium chloride solutions determined from Hill (1990) and Archer (1992). Typical calibration constant values are shown in Table 2.1. 54 Table 2.1: Experimentally determined calibration constants for the high temperature and pressure densimeter as a function of temperature calculated from reference data for water and a sodium chloride solution with a concentration of 1.88 mol kg-1. t/°C P/MPa kp/gscm3 90~8 L21 352593 134.9 1.21 350102 147.9 3.87 347105 174.7 3.89 346188 196.9 6.31 345107 223.7 6.11 341901 In addition to this calibration method, solutions of methanol in water of comparable relative density to the uridine, cytidine, and thymidine solutions were measured in alternating runs to the nucleoside solutions to ensure that solution concentrations were sufficient to obtain reproducible results. Methanol solutions with comparable relative densities rather than comparable concentrations were measured because these solutions will have similar differences in their periods of oscillation relative to water. Methanol was selected because it is a simple, well studied organic molecule that is stable in water at elevated temperatures and reference density data are well accepted at high temperatures. The error on the solution densities divided by the measured solution densities of methanol were then plotted with accepted reference data and are shown in Figure 2.2. These parameters lie within the same range as those determined in literature, and indicate that the relative density measurements made for methanol as well as the nucleosides are within an acceptable level of uncertainty. 55 0.004 0.0035 0.003 0.0025 0.002 0.0015 0.001 0.0005 20 70 120 170 220 Temperature/ 0C Figure 2.2: Standard partial molar volumes of methanol and water solutions from 20 to 225 0C showing: (? ) this work, 1.1 MPa; (+) this work, 2.1MPa; (A ) this work, 3.5 MPa; (-) this work, 4.0 MPa; (X] this work, 6.0 MPa; (*) Xiao et al (1997) 7.0 MPa; (O) Hyncica étal. (2004) 2.0 MPa; and ( · ) Hyncica étal. (2004) 6.0 MPa. 56 (5) Sampling for Thermal Decomposition After leaving the platinum tube, but before heading to the waste cylinder, effluent was passed through a sampling loop connected to a six port valve. Two tubes were connected to the valve and were open to the atmosphere. Effluent was forced out of the loop opening the six port valve to an air filled syringe on one tube, subsequently forcing air into the loop and solution out through the other tube. From this loop, approximately 1-2 ml solution samples were obtained and analyzed using H1 NMR to ensure that no measurable decomposition had occurred during the experimental runs. 2.3 Heat Capacity Measurements Experiments were conducted with a fixed cell, power compensation, differential-output, temperature-scanning nanocalorimeter (Calorimetery Sciences NDSC III, Model 6300T with cylindrical cells). This is a relatively new experimental method developed by Earl Woolley (1997), and our research group is the currently the only other one using this technique. Measurements were obtained as relative differences between the power applied to the solution to increase its temperature, àWs, and the power applied to increase a standard water reference to the same temperature, AWW. Sensors are placed between the cells to ensure that the temperature difference between them is as close to zero as possible. Measurements were taken as the temperature is scanned over the desired temperature range. A hysteresis was observed between up and down scans, but averaging an equal number of scans as temperature increased and decreased cancalled out this effect. 57 This method is useful because data can be measured over a range of temperatures during each experiment and measurement time for one system is relatively short. Each cell has a volume of approximately 0.9 cm3. Pressure in the cell is increased by decreasing the volume of the vapour phase above the solution until the desired pressure is reached. A diagram of the cell is shown in Figure 2.3. The thermal jacket is heated and cooled at a constant rate, and controlled using feedback control comparing a known reference voltage to that of the platinum thermometer. Ideally, temperature control of the cells would be identical, but due to inevitable slight variations in equipment, power compensation heaters need to be used to minimize the temperature differences. The cells are maintained at a constant pressure, and narrow necks connecting the cells to the manostat allow for volume expansion. A piston inside the instrument body controls the excess pressure in the manostat, and a piezoelectric sensor measures the cell pressure. The system can be run up to 160 0C and 6 bar. 58 T Figure 2.3: Schematic Diagram of Nano Differential Scanning Calorimeter (NDSC II) showing (1) manostat, (2) pressure sensor, (3) heating and cooling peltier elements, (4) platinum thermometer, (5) thermal jacket, (6) power compensation heaters, (7) sample cell, (8) thermosensor, (9) reference cell [CSC, 2005). 59 Massic heat capacities can be determined from the differences in the power applied to the solution relative to that applied to water from the following expression: CpiS = kc(AWs - àWw)/rps + cPiWpw/ps (2.5) where cp,s and ps are the massic heat capacity and density of the sample, cp,w and pw are the massic heat capacity and density of water which were obtained from Hill (1990), r is the temperature scan rate, and kc is the calibration constant determined from measurements of a well studied solution, in this study NaCl, using Equation 2.5 and reference heat capacity and density data. Measurements were made from 15 0C to 90 0C at 1.25 bar, and 90 to 135 0C at 6 bar. Data points were collected every five degrees at constant pressure, and 6 heating and 6 cooling curves were measured. It was observed that the first up and first down scans show slightly different behaviour than subsequent scans, so only 5 of the 6 up scans and 5 of the 6 down scans were averaged by the system software to obtain the reported measurements for each run. 2.4 UV-visible Spectroscopy 2.4.1 High Temperature Apparatus This work made use of a newly designed high-temperature and high pressure UV visible flow cell (Trevani eta/.,2001; Búlemela amd Tremaine 2009). The cell design was quite effective under oxidizing conditions; however the new cell was constructed using a 90%-Pt-10%-Ir cylindrical liner inside a two piece titanium casing to minimize corrosion under reducing conditions, as shown in Figure 2.4 60 (Búlemela, 2006]. Sapphire windows placed at both ends of the platinum cell were sealed with gold washers, and held in place with a titanium disk bolted with belleville washers to hold tension as the bolts expand. The entire titanium housing was held inside a brass oven containing two Chromalux CIR-20203 120 V 200 W cartridge heaters. Sample solutions were preheated and fed into the cell through a Im segment of narrow diameter platinum tubing coiled around a machined groove in the brass block oven. The temperature of the cell was maintained to ±0.1°C of the target temperature with an Omega CN76000 temperature controller and measured by a Chromega-Alomega thermocouple located in the oven, as near to the solution as possible. The brass block was then encased in ceramic insulation, and placed inside a brass and aluminum casing cooled by water circulation to maintain the temperature of the outer casing at approximately 10 to 20 0C. The entire assembly could be placed directly in a Cary 50 UV/Vis spectrophotometer without damaging it. Solutions were degassed by suction inside a syringe and injected by force into an HPLC sample injection loop, then introduced into the UV-visible cell by a Gibson 305 HPLC piston pump supplying milli-Q water at a constant rate of 1.0 ml min1. Pressure in the system was maintained by the flow from the pump and a back pressure regulator connected to the effluent tube, and measured by a Gibson 805 manometric module placed beside the spectrometer. A schematic diagram of the flow system is shown in Figure 2.5. 61 (D- HD ¦@ F- ¦iL ©- Figure 2.4: Schematic diagram of the UV-visible flow cell with components: (I] thermocouple (2) inlet tube (3) bolted end cap (4) gold seals (5) titanium cell casing (6) platinum cell compartment (7) sapphire windows and (8) outlet tube (Trevani et al, 2001). 62 -® -® -© _,—7 -,—-H F 7 7 T { ' \ µ^'"???t^* -® -© -© -© %W&tf$Ä '*tt 4P -® K^M fi fi fi o fi a a OO ? fi fi O ft ? II O O © Figure 2.5: Schematic of the UV-visible high temperature flow system with components as follows: (I] water reservoir (2] HPLC piston pump (3) manometric module (4) injection loop and 6-port valve [5) preheater (6) thermocouple (7) brass/aluminum casing with water circulation (8) ceramic insulation (9] cartridge heaters (10] sapphire windows (11) platinum flow cell in a titanium casing (12) end-cap and bolts (13) sampling loop and six port valve (14) backpressure regulator (15) effluent reservoir. Figure is taken from Trevani et al (2001) , with permission. 63 2.5 Batch Reactions of Adenosine with Phosphates at Elevated Temperatures Due to the limited solubility of adenosine in water, 13C NMR spectra could not be measured directly from the effluent of the UV-visible experiments. As a result, separate batch experiments were undertaken to determine the products from the phosphate-adenosine reactions studied with UV-visible spectroscopy. Buffer solutions of H2PO4-/H3PO4 in ratios of 10:1, 1:1, and 1:10 and of formate/formic acid in ratios of 10:1 and 1:1 were over-saturated with approximately 7 g of solid adenosine in 200 mL of water, and allowed to react for 30 minutes at 200 0C, and then the vessel was quenched rapidly to 25 0C (5 minutes). The solubility of adenosine increases dramatically at elevated temperatures, so this method maximized the concentration of reaction products. These experiments were conducted in commercially available Parr Instruments Model 4744 general purpose acid digestion bombs with Teflon liners whilst they were heated in a convection oven. The reactor is designed so that the chemically inert Teflon liner and lid form a seal, thus maintaining the internal reactor pressure as temperature increases and preventing the solution from boiling. Rupture disks prevent overpressure and subsequent explosion of the cell. A schematic diagram of the reactor is shown in Figure 2.6. 64 •f V -f -f -f -f -(D 1 Ë -® Figure 2.6: Schematic diagram of a general purpose acid digestion bomb with (1) spring, (2) upper pressure plate, (3) lower pressure plate, (4] rupture disk, (5) corrosion disk, (6) Teflon lid, (7) screw cap, (8) reactor body, (9) Teflon cup and (10) bottom disk. 65 CHAPTER 3 STANDARD PARTIAL MOLAR PROPERTIES OF NUCLEIC ACID BASES AND NUCLEOSIDES 3.1 Introduction Currently, solvent-solute behaviour of nucleic acid components in water is poorly understood, especially at elevated temperatures. Understanding such behaviour gives insights into DNA and RNA structure and stability in hydrothermal environments. HKF models for these species have been developed to predict their behaviour under hydrothermal conditions using low temperature and low pressure data and extrapolations (LaRowe and Helgeson, 2006). Nucleic acid bases are divided into two classes, purines and pyrimidines, and we have designed the experiments so that the thermodynamic properties of at least one molecule of each class be determined. In the first part of this chapter, the standard partial molar properties of neutral and positively charged nucleic acid bases and nucleosides will be reported and both HKF and "density" model analyses will be used to predict the behaviour of these properties at high temperature. Nucleic acid components are challenging to work with in aqueous solutions because of their limited solubility in water. Guanine is especially difficult, and cannot be dissolved sufficiently to determine apparent molar properties from accurate density measurements. The second section of this chapter will focus on developing a basic functional group additivity model to assess the contribution of the ribose group to the standard partial molar properties of nucleosides and 66 determine the standard partial molar volume of neutral and positively charged guanine. Nucleic acid components contain multiple nitrogen and oxygen groups that make tautomerism possible. The most stable tautomeric forms of the nucleic acid bases and nucleosides have been determined (Estrin et al, 1994; Civcir, 2000; Guerra étal, 2006; and Shugar and Kierdaszuk, 1985). Nucleic acid components can undergo multiple acid ionizations, but only those consisting of the deprotonation of a positively charged amino group to a neutral amino group were studied in the third section of this chapter. Adenine, guanine, and cytosine can undergo two ionizations, all of which are described in Figure 3.1. Adenosine can only undergo one ionization, whereas guanosine and cytidine are each capable of two, as is shown in Figure 3.2. It has been suggested that guanosine can undergo deprotonation of its ribose group as well. However, the titrimetric studies performed by Levene and Simms (1925) suggest that only the two ionizations described actually occur. Uracil and thymine each undergo one ionization consisting of two steps: a tautomeric step followed by deprotonation (Shugar and Fox, 1952). Additionally, their corresponding nucleosides, uridine and thymidine, undergo deprotonation of their ribose groups (Ganguly and Kundu, 1995). There is no positively charged protonated uracil or thymine based species, so neither Reaction 4 nor Reaction 8 in Figure 3. land Figure 3.2 will be considered here. 67 NH, NH, \> \»r^^N > K13 H. -N K N 1^a ?,??^? „„AAfi hAV NH, NH, NH, ^NH ^ [T ^N 2a N' 0 A0 X" ^nAH H NH K1a Figure 3.1: Acid ionizations of stable nucleic acid base structures: (1) adenine; [2) guanine; (3) cytosine; (4] R= CH3, thymine and R=H, uracil. K3, Ki3, and foa denote acid ionizations, and Kt denotes a tautomeric exchange. 68 N=i H3N ?,? OH OH 5 HN^/N HO OH N^N HO OH O H*N ^ OH v / N OH H2N HO' K-a H2N H0 OH OH O" N HN OH K23 H*N HO OH --ttó¿^ ' \??\-^ —Hitó»\s HO K23 HO^ H H0 0"yNY° HO ??"^ -O^ /N^NCH3 HO HO o" o^N^° K2, V-o N\-i^ CH, HO HO 0?? ^^ "Oho ^oy-NY° HO7Ih H00 oh K23 O^ /"^^H HO OH Figure 3.2: Acid ionization of stable nucleoside structures: (5) adenosine; [6) guanosine; (7] cytidine; (8) thymidine; and (9) uridine. 69 3.2 Standard Partial Molar Properties of Neutral and Positively Charged Nucleic Acid Bases and Nucleosides 3.2.1 Standard Partial Molar Volumes Three experimental density measurements of each solution with the low temperature equipment. Using separate cell loadings, these were then averaged to calculate the relative densities and the resulting apparent molar volumes. Due to the greater uncertainty of the high temperature equipment, for each species studied, three separately prepared solutions were measured. A minimum of three experimental runs of each solution was conducted. Samples were retrieved after every measurement and analyzed by 1H NMR to ensure that no appreciable thermal degradation had occurred, the results of which are shown in Appendix D. Thymidine was found to decompose appreciably at 175 0C, cytidine at 200 0C, and uridine at 225 0C. The relative solution densities and apparent molar volumes of nucleic acid bases and nucleosides in water and water with excess HCl were calculated from Equations 1.23 and 1.25 and are listed in Appendices A and B along with the uncertainties in calculated values. Uncertainties in density measurements taken at low temperatures were approximately 2.0 ? IO5 g cm3, and uncertainties of those measured at high temperatures were approximately 4.0 ? IO4 g cm3. These uncertainties were determined from the standard deviation of all experimental density measurements at each temperature and the uncertainties of molalities using standard error propagation techniques (Taylor, 1982). 70 For neutral species, apparent molar properties were taken to be equal to the standard partial molar properties, owing to the low concentrations, non-ionic character of the molecules and lack of observed concentration dependence reported in the literature. Thus, the standard partial molar volume can be taken to be approximately equal to the apparent molar volume: V°2 « V9j (3.1) For the chloride salts of positively charged species, the determination of standard partial molar volumes was carried out in a small excess of HCl to avoid hydrolysis. Corrections for the excess HCl contribution had to be made in order to determine the contribution of the nucleic acid ions to the apparent molar volume of the total solution. The standard partial molar volumes of ionized nucleic acid components were calculated from Young's Rule, as described in Section 1.5.4. The contribution of HCl(aq) was calculated using Sharygin and Wood's (1997) model (Appendix B). As previously mentioned, the standard partial molar properties of neutral aqueous species typically do not display any concentration dependence, a behaviour which has been confirmed in literature for nucleic acid bases and nucleosides (Lee and Chalikian, 2001; Patel and Kishore, 1995). As a result, standard partial molar volumes can be directly determined from density measurements of dilute solutions which is very convenient experimentally. Unlike neutral species, apparent molar properties of charged species are typically very dependent on the solution molality. There are two common methods utilized to determine standard partial molar volumes from apparent molar 71 properties. The first requires that the dependence of Vv on molality be determined. A line can be fitted to these data according to Equation 1.36, the intercept of which at m=0 gives the standard partial molar volume. The species under study have low solubility in acidic solution, and as such this method could not be undertaken effectively. Instead, data were measured at a single molality and extrapolated to infinite dilution using the expression (Rogers and Pitzer 1982): V9 = V2' + v\zMzx\Avh{l) + 2vMvxRT(mBlx + m2(vMzM)Clx) (3.2) where: ?(/) = In(I + b/1/2)/2b (3.3) ??4? and C^x are interaction parameters described in Section 1.5.6 but whose contributions are minimal at lowlow molality and thus were set to zero; Vm, and ?? are the number of positive and negative ions, respectively, Av is the Debye-Hückel slope for volumes, I is the ionic strength of the solution, b is equal to 1.2 for all electrolytes, and zm and ?? are the charges of the cations and anions, respectively. Values of V20 are listed in Appendix B. 3.2.2 Modeling Standard Partial Molar Volumes The HKF and density models described in Section 1.6 were used to model the temperature-dependent standard partial molar volume data. The benefits of each model and a comparison of results will be discussed below. For neutral cytidine, uridine, and thymidine, data from the high temperature densimeter were included in regression models. However, these measurements were given lesser weight in the model because of the higher uncertainties estimated 72 for measurements, which results from the lower sensitivity of the high temperature instrument relative to the Anton Parr commercial instrument. Weighted regressions were performed using the following relationship: ^weighted = ^measured I G \??) where ^measured is the measured apparent molar property, ^weighted is the weighted factor for regression, and s is the standard deviation of the data point. Clearly, the high-temperature values will have lower weighting factors because of their larger standard deviations. 3.2.2.1 'Density' Model The density model for thermodynamic properties proposed by Marshall and Franck (1981) is shown in Equation 1.49. From this model, a modified density model relationship is proposed: V^ = ho-R(ET + F + G/T)ßw + mT (3.5) where h0, E, F, m, and G are fitting parameters, R is the gas constant in J mol·1 K1, T is the temperature in Kelvins, and /?w is the isothermal compressibility of water, determined from the ASME program (Harvey et al, 1996). The linear regression function in the Microsoft Excel© software package was used to determine all regression parameters. The linear regression tool in the Excel© package uses a least-squares method to find a curve through a set of data points. This method assumes that the errors on a given set of ? parameters are substantially smaller than those for the corresponding y parameters, and that the standard deviations of all y parameters are similar. The function is fitted to the data 73 by minimizing the function residuals, that is, the vertical deviations between data points and the curve itself. To apply 'linear' regression methods, the fitting equation must be expressed as a linear combination of all fitting parameters (Harris, 1999). If an expression includes non-linear fitting parameters, then the equation must be manipulated into a linear expression, or non-linear regression must be conducted. Non-linear regression of data is done using a least-squares approach with successive approximation methods such as the Levenberg-Marquardt algorithm (Hamming, 1987). In these cases, minimizing the residuals will not have a closed solution, so initial values must be selected, and solutions obtained iteratively (Harris, 1999). To avoid over-fitting, unnecessary parameters were selectively excluded from the model fits. There were several steps to determine the best combination of parameters. First, all possible combinations of two or three parameters from the density model equation were regressed, to provide values for all equation parameters, their corresponding standard errors, and the overall standard error of the fit. The absolute value of the vertical deviations between the models and experimental data were calculated, and the average vertical deviation was determined. The best fit was then determined to be the one with the lowest combined standard error from the parameters and the overall fit and the lowest average vertical deviation. Separate models for neutral and positively charged species were selected to optimize data fitting. 74 Neutral Species Using linear regression tools in Excel, a three parameter fit of standard partial molar volumes of neutral bases and nucleosides was selected, and is described by the following relationship: V°2 = ho - R(ET + F)/?w (3.6] Fitting parameters for Equation 3.6 are listed in Table 3.1. Density models of the standard partial molar volumes of neutral bases and nucleosides in water are shown in Figures 3.3 to 3.8. Positively Charged Species Positively charged nucleic acid bases and nucleosides were best fitted with the following 'density' model: V°2 = ho - RETßw + mr (3.7] Regression parameters are tabulated in Table 3.2, and Figures 3.9 to 3.13 display the modelled data. All regression parameters presented in Tables 3.1 and 3.2 were determined with standard errors of no more than ten percent. The average difference between the fitted model and the experimental data points measured up to 90 0C were no more than 0.3 cm3 mol1 with the exception of neutral guanosine with an average difference of 0.6 cm3 mol1, and guanosine hydrogen chloride with an average difference of 1.9 cm3 mol1. 75 10 30 50 70 90 110 130 150 Temperature/ ("C) Figure 3.3: Standard partial molar volumes, V20, of neutral adenine in water collected at 5 0C increments from 15-90 0C (?), plus literature data from: (x) Balodis (2007); (+) Lee and Chalikian (2001); (^) Buckin (1987); (-) Kishore et al. (1989). The solid line represents the proposed density model fitted to Equation 3.6. 76 t G 10 30 50 70 90 110 130 150 170 Temperature/ ("C) Figure 3.4: Standard partial molar volumes, V20, of neutral cytosine in water collected at 5 0C increments from 15-90 °C (A), plus literature data from: O) Lee and Chalikian (2001); (a) Buckin (1987); (-) Kishore et al. (1989); and (·) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.6. 77 10 30 50 70 90 110 Temperature/ ("C) Figure 3.5: Standard partial molar volumes, V20, of neutral pyrimidine bases in water collected at 5 0C increments from 15-90 0C: this work, uracil (·) and thymine (¦); plus literature data from (x) Balodis (2007); (+) Lee and Chalikian (2001); (a) Buckin (1987); (-) Kishore et al. (1989); and (·) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.6. 78 195 190 185 o E mE 180 ? 175 170 165 10 30 50 70 90 110 130 150 Temperature/ ("C) Figure 3.6: Standard partial molar volumes, V20, of neutral purine nucleosides in water collected at 5 C increments from 15-90 0C: this work, adenosine (?) and guanosine (*); plus literature data from Balodis (2007) (x); Lee and Chalikian (2001) (+); Buckin (1987) (a); Kishore et al. (1989) (-); and Patel and Kishore (1995) (·). The solid line represents the proposed density model fitted to Equation 3.6. 79 175 170 "d 165 e ? 0^ 160 155 150 50 100 150 200 Temperature/ ("C) Figure 3.7: Standard partial molar volumes, V20, of neutral cytidine in water collected at 5 0C increments from 15-90 0C with the low temperature equipment, and up to 175 0C with the high temperature equipment (A), along with literature data: (+) Lee and Chalikian (200I]; (a) Buckin (1987); (-) Kishore et al. (1989); and (·) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.6. 80 190 185 - 180 - 175 m e 170 + £ 165 160 155 ? +· * 150 10 60 110 160 Temperature/ ("C) Figure 3.8: Standard partial molar volumes, V20, of neutral pyrimidine nucleosides in water collected at 5 0C increments from 15-90 0C on the low temperature equipment, and up to 200 0C on the high temperature equipment: this work, uridine (·) and thymidine (¦); along with literature data from: (+) Lee and Chalikian [2001]; (a) Buckin (1987); (-) Kishore et al. (1989); (·) Patel and Kishore (1995), and ( ? ) Holland et al. (1984). The solid line represents the proposed density model fitted to Equation 3.6. 81 10 30 50 70 90 110 130 150 Temperature/ ("C) Figure 3.9: Standard partial molar volumes, Vz, of adenine hydrogen chloride, adenineH+Cl-, in water and excess HCl at 5 0C increments from 15-90 0C (?). The solid line represents the proposed density model fitted to Equation 3.7. 82 10 60 110 160 Temperature/ ("C) Figure 3.10: Standard partial molar volumes, Vz, of cytosine hydrogen chloride, cytosineH+Cl-, water and excess HCl at 5 0C increments from 15-90 0C (A ). The solid line represents the proposed density model fitted to Equation 3.7. 83 180 170 160 o e 150 m E U 140 130 120 10 60 110 160 Temperature/ (0C) Figure 3.11: Standard partial molar volumes, V20, of adenosine hydrogen chloride, adenosineH+Cl-, in water and excess HCl at 5 0C increments from 15-90 0C (? ). The solid line represents the proposed density model fitted to Equation 3.7. 84 170 H 150 o 130 e ? 0N 110 > 90 70 10 60 110 160 Temperature/ ("C) Figure 3.12: Standard partial molar volumes, V20, of guanosine hydrogen chloride, guanosineH+Cl·, in water and excess HCl at 5 0C increments from 15-90 0C (*). The solid line represents the proposed density model fitted to Equation 3.7. 85 180 175 170 165 O E m 160 E U 155 150 145 10 60 110 160 Temperature/ (0C) Figure 3.13: Standard partial molar volumes, V20, of cytidine hydrogen chloride, cytidineH+Cl-, in water and excess HCl at 5 0C increments from 15-90 0C (A). The solid line represents the proposed density model fitted to Equation 3.7. 86 Table 3.1: Regression parameters for Equation 3.6, the fitting equation for standard partial molar volumes, V20, of nucleic acid bases and nucleosides. All systems are fitted to data taken between 15 and 90 0C, except for thymidine, which was fitted with data up to 150 0C, cytidine, which was fitted with data up to 175 0C, and uridine, which was fitted to data up to 200 0C. Species h0 10,-4 -F cm3 mol1 K Bases Adenine 111.28 ± 5.58 1.669 ± 0.169 -36.615 ± 1.418 Cytosine 92.19611.385 1.13610.042 -23.840 + 0.352 Thymine 95.53111.775 1.096 + 0.054 -30.345 + 0.451 Uracil 86.415 + 1.006 1.205 + 0.030 -27.188 1 0.256 Nucleosides Adenosine 195.4212.70 2.016 + 0.082 -45.84510.687 Guanosine 168.74 + 11.49 1.030 + 0.348 -40.428 + 2.919 Cytidine 185.12 + 2.74 1.917 + 0.133 -36.68111.936 Thymidine 210.48 + 0.99 -1.20210"5+ 1.08-10"6 58.871 + 2.466 Uridine 187.27 + 2.98 2.090 + 0.153 -39.738 + 2.309 Table 3.2: Regression parameters for standard partial molar volumes, V20 of chloride salts of nucleic acid bases and nucleosides, XH+Cl", in water and excess HCl between 15 and 90 0C. The data were fitted to Equation 3.7. Species h0 m cm33KYiOi1mol cm3 mol 1K"1 Bases Adeninerfcr 56.799 + 0.997 0.3027 + 0.0109 52.63812.483 CytosinehTcr 42.927 + 0.813 0.2623 + 0.0089 39.979 + 2.024 Nucleosides AdenosinehTcr 109.75 + 1.40 0.4137 + 0.0153 61.480 + 3.499 GuanosineH+CI" 90.660+1.026 0.6515 + 0.1117 108.57 + 2.56 CytidineH+Cr 104.71 + 0.55 0.3914 + 0.0060 48.327 + 1.380 87 The average differences between experimental data points measured at elevated temperatures and their corresponding fits were no more than 1.25 cm3 mol·1. Based on these models, as temperature increases towards the critical point, standard partial molar volumes of neutral species approach positive infinity, and those of ionic species approach negative infinity. This is consistent with the behaviour of many common neutral and ionic species, but opposes the models predicted by LaRowe and Helgeson (2006). 3.2.2.2 HKF Model Analysis Neutral Species The HKF model was described in detail in Section 1.6.2. The equation for V° as a function of temperature and pressure is: V° = Z1 + a3{l/(T -&)}-CDeQ (3.8) where ai, and a3 are fitting parameters, ?e is the Born coefficient but is used as a fitting parameter for neutral species, T is temperature in K, and T = 228.15 K. The low temperature, pressure-dependent terms, a2 and a4, were excluded from the model because measurements were only taken as a function of temperature, not pressure. The ? term is common to the standard partial molar heat capacity model, and as a result the same value must be used for both models. Regressions were conducted on both sets of data, and the value which provided the best overall fit for both systems was used. 88 Fitted parameters for Equation 3.8 are listed in Table 3.3. Models for neutral species are shown in Figures 3.14 to 3.18 along with HKF models from the parameters estimated by LaRowe and Helgeson (2006], using correlation methods. 89 10 60 110 160 Temperature / ("C) Figure 3.14: Standard partial molar volumes, V20, of neutral adenine in water collected at 5 0C increments from 15-90 0C (? ). The solid line represents the HKF model fitted to Equation 3.13. The dashed line is the HKF model proposed by LaRowe and Helgeson [2006), fitted with the literature data used from: (+) Lee and Chalikian (2001); [-) Kishore et al. (1989). 90 10 30 50 70 90 110 130 150 Temperature / (0C) Figure 3.15: Standard partial molar volumes, V20, of neutral cytosine (* ), uracil (·), and thymine (¦ ) in water collected at 5 °C increments from 15-90 0C. The solid line represents the HKF model fitted to Equation 3.13. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006), fitted with the literature data used from: (+) Lee and Chalikian (2001); (-) Kishore et al. (1989). 91 170 H 10 60 110 160 Temperature /(0C) Figure 3.16: Standard partial molar volumes, V20, of neutral adenosine ( ? ) and guanosine ( * ) in water collected at 5 0C increments from 15-90 0C. The solid line represents the HKF model fitted to Equation 3.13. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006), fitted with the literature data used from: (+) Lee and Chalikian (2001); (-) Kishore et al. (1989). 92 190 Ö 170 E 165 ? 160 10 60 110 160 Temperature /(0C) Figure 3.17: Standard partial molar volumes, V2, of neutral cytidine in water collected at 5 0C increments from 15-90 0C and then up to 175 0C with high temperature equipment (A]. The solid line represents the HKF model fitted to Equation 3.13. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006], fitted with the literature data used from: (+] Lee and Chalikian (200I]; (-] Kishoreeta/. (1989]. 93 190 185 180 175 H ¡ 170 en E ¦ü 165 160 155 150 10 60 110 160 Temperature /0C Figure 3.18: Standard partial molar volumes, V20, of uridine (·) and thymidine (¦ ) in water collected at 5 0C increments from 15-90 0C and then up to 150 0C and 200 0C, respectively, using high temperature equipment. The solid line represents the HKF model fitted to Equation 3.13. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006), fitted with the literature data used from: (+) Lee and Chalikian (2001); (-) Kishore et al. (1989). 94 Table 3.3: HKF Regression parameters for standard partial molar volumes, V20, of neutral nucleic acid bases and nucleosides, fitted to Equation 3.8. All systems are fitted to data taken between 15 and 90 0C, except for thymidine, which was fitted with data up to 150 0C, cytidine, which was fitted with data up to 175 0C, and uridine, which was fitted to data up to 200 0C. Compound Formula v° a! a3 10"5u> ______cm3mol-1 J mol1 Mpa"1 J K mol 1MPa * J mol1 Pyrimidines Uracil C4H4N2O2 71.432 83.567 ±0.264 -848.83 ± 23.49 -2.1121 ± 0.4747 Thymine C5H6N2O2 88.340 96.006 ± 0.328 -727.74129.13 -4.4997 ± 0.4032 Cytosine C4H5N3O 74.967 82.830 ± 0.665 -589.55125.89 -2.9880 ± 0.5153 Purines Adenine C5H5N5 89.609 102.84 ±0.52 -1020.6 ±46.1 -3.6675 ± 1.1826 Nucleosides Uridine C9H12N2O6 154.55 155.54 ±0.75 -431.38 ± 70.08 -8.5414 ± 0.0294 Thymidine C10H14N2O6 167.88 173.04 ±0.026 -753.12 ± 2.31 -9.3212 ±0.0197 Guanosine C10H13N5O5 175.48 170.99 ±5.56 -412.73 ± 213.49 -16.9518 ± 4.3844 Cytidine C9H13N3O5 154.29 167.78 ±0.47 -1049.7 ± 45.6 -2.2045 ± 0.5103 Adenosine C10H13N5O4 171.00 186.37 ±0.38 -1234.3 ± 33.4 -3.7476 ± 1.3700 95 Protonated Species As previously discussed, the HKF model for standard partial molar volumes of positively charged species is different from that for neutral species, and is described by: V°2 =ai+ 33(1/(7- - T)} - O)Q + (l/e - 1)(0?/3?)G (3.9] where e is the dielectric constant of water, and ? is the Born coefficient as defined in Section 1.6.2. As with the neutral species, the pressure dependent terms here were excluded because measurements were not conducted as a function of pressure. To calculate values of the Born coefficient, crystallographic radii of all species under study are needed. A value of 1.81 Á was used for the crystallographic radius of the chloride ion, as published by Shock and Helgeson (1992}. No radii have been published for protonated nucleic acid bases and nucleosides for use in the HKF equations, therefore the ionic radius had to be estimated. These species are not spherically shaped, so several different radius approximations were tested. One approximation used the length of the longest side of a single molecule, determined based on the configuration and number of molecules within the unit cell. The radius of a hypothetical sphere with the same volume as the unit cell was also tested using a 0.74 packing factor based on close-packed spheres (Atkins and DePaula, 2002]. This approximation produced values of ? that more closely resembled those from the unconstrained model regressions, and as a result better represented the data at high temperatures. The unit cell dimensions and estimated radii are listed in Table 3.4. 96 Table 3.4: Literature values for the unit cell dimensions, a, b, and c, unit cell volumes, and hypothetical radii of a single ion based on the volume of the unit cell, and a packing factor of 0.74 for close-packed spheres. When appropriate electrolyte dimensions could not be found, the nearest approximation was used [Broomhead 1948; Bernal and Crowfoot 1933; Shikata et al. 1972; Furberg étal. 1965; Chen and Craven 1995; Mandel 1976; and Thewalt et al 1970). Species a b c # molecules Radius ______Á Á Á /unit cell Á Adenine hydrochloride 8.591 4.817 19.730 4 3.304 Cytosine 13.041 9.494 3.815 4 2.753 Adenosine 4.825 10.282 11.823 2 3.728 Cytidine 13.989 14.781 5.116 4 3.601 Guanos i ne di hydrate 17.518 11.502 6.658 2 4.912 97 The value of ? calculated from ionic radii had two components, one for the positively charged nucleic acid base, and one for the chloride ion, which are added to get the final ? term used in HKF models. The change in ionic radius as a result of the positively charge proton is assumed to be negligible, and ionic radii of the neutral nucleic acid were used for the ? calculation. However, only the radii of adenine hydrochloride and guanosine dihydrate were found in literature. Subtracting the radius of the chloride and water components, respectively, were attempted, however, models were more successful when the ? term was calculated directly from the radii as they are presented in Table 3.4. The derivative of ? is dependent on the derivative of g, which is the temperature and pressure dependent solvent function used to describe high temperature behaviours of solvent compressibility and dielectric saturation (Shock and Helgeson 1992). At low pressures and low to moderate temperatures, the value of g and its derivatives are equal to zero, so the pressure derivative of the Born coefficient is also zero, simplifying Equation 3.9. Aside from the value determined from Equations 1.63 to 1.65, regressions were conducted on the standard partial molar volumes and heat capacities using ? as a fitting parameter, as was done for neutral species. In cases where volumes and heat capacities produced substantially different values, the values were averaged. A simple average was used rather than a weighted inverse variance. Standard partial molar volumes have lower errors, and thus the ? term determined from fitting this data would be weighted more heavily than that determined from fitting standard partial molar heat capacity data. However, the standard partial molar heat capacity 98 model is more strongly affected by the ? term, which would not be best represented by an inverse variance approach. The fitted models are shown in Figures 3.19 to 3.23 and regression parameters are shown in Table 3.5. For both the neutral and protonated species, regression parameters were determined using the linear regression function in the Microsoft Excel© software package. Parameters were determined with errors of no more than thirty percent, a substantial increase in comparison to the density models. The average differences between the fitted models and the experimental data points measured up to 90 0C were no more than 0.6 cm3 mol·1, except for guanosine hydrochloride, with an average difference of 1.6 cm3 mol·1. Average differences between experimental data measured at higher temperatures and their corresponding fits of no more than 2.5 cm3 mol·1. 99 ~ 90 H 10 60 110 160 Temperature / (0C) Figure 3.19: Standard partial molar volume, V20, of adenine hydrogen chloride, adenineH+Cl-, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (?), modeled with the HKF equations for ions and different values of ?): (----) calculated from the ionic radii; (....) obtained by regressing calculated V20 values; (-.-.-) from Cp/ regression; and ( —) averaged from V20 and Cp/ regressions. 100 76 H 74 H 72 10 60 110 160 Temperature /(0C) Figure 3.20: Standard partial molar volume, V20, of cytosine hydrogen chloride, cytosineH+Cl-, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (A), modeled with the HKF equations for ions and different values of ü>j: (-—) calculated from the ionic radii; (....) obtained by regressing calculated W values; (-.-.-] from Cp/ regression; and ( —) averaged from VY and Cp,2° regressions. 101 10 60 110 160 Temperature /(0C) Figure 3.21: Standard partial molar volume, V20, of adenosine hydrogen chloride, adenosineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (?], modeled with the HKF equations for ions and different values of ?): (----) calculated from the ionic radii; (....) obtained by regressing calculated V20 values; (-.-.-) from Cp/ regression. 102 175 ^ >Ni6o ^ 10 60 110 160 Temperature /(0C) Figure 3.22: Standard partial molar volume, V20, of cytidine hydrogen chloride, cytidineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (A ), modeled with different values of ?): (—) calculated from the ionic radii; (....) obtained by regressing calculated V'¦£ values; (-.-.-) from Cp,2° regression; and ( —) averaged from V20 and Cp,2° regressions. 103 Ji,- -¦ ...... -J.-..*.'* /*' / « / ? . ?.·"' r i i i i i —I , —_ ,—.. 10 30 50 70 90 110 130 150 Temperature / (0C) Figure 3.23: Standard partial molar volume, V20, of guanosine hydrogen chloride, guanosineH+Cl", in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (*), modeled with the HKF equations for ions and different values of coj: (-—) calculated from the ionic radii; and (....) obtained by regressing calculated VY values. 104 Table 3.5: HKF Regression parameters for standard partial molar volumes, V20, of chloride salts of nucleic acid bases and nucleosides, fitted to Equation 3.9. All systems are fitted to data taken between 15 and 90 °C. The term ? denotes the values of the Born coefficient used in the model, and ?* denotes the values determined from Equations 1.51 to 1.53. Vo at a3 10"6U) 10" ·?* Compound Formula cm3mol"1 J mol"1 Mpa"' J K HiOl1MPa1 J mol"1 J mol _1 Bases AdenineH+CI" (C5H6Ns)+CI" 88.08 137.67 ± 0.72 -2187.02 1 64.35 3.0113 ± 0.4411 5.4747 CytosineH+CI" (C4H6N3O)+CI" 76.45 97.19 ±0.39 -1161.92 134.59 0.680010.1327 5.7189 Nucleosides AdenosineH+CI" (C10H14N5O4I+CI" 164.33 203.67 ± 3.56 -2099.70 ± 139.60 1.5325 ± 0.2748 5.3260 GuanosmeH+CI" (C1OH14N5Os)+CI" 163.48 195.3013.03 -2031.48 1268.90 0.4554 5.0249 CytidineH+CI" (C9H14N3Os)+CI" 167.34 207.03 10.51 -2228.62 + 45.18 1.2865 + 0.2182 5.3676 105 3.2.3 Standard Partial Molar Heat Capacities The massic and apparent molar heat capacities of nucleic acid bases and nucleosides in water and with excess hydrochloric acid were calculated from Equations 1.30 and 1.32 and are shown in Appendix C. Standard partial molar heat capacities of neutral and positively charged species were determined from apparent molar heat capacities in an analogous fashion to that explained in Section 3.2.1. The corrections for excess hydrochloric acid and the extrapolations to infinite dilution are shown below. Using Young's Rule as described in Section 1.5.5, the apparent molar heat capacity contributions by excess HCl were determined from the regression parameters of Patterson et al. (2001). An analogous extrapolation to that described in Section 3.2.1 has been developed for apparent molar heat capacities (Silvester and Pitzer, 1977): CPlV = C°Pi2 + v\zMzx\(Aj /3.6) In(I + 1.2/1/2) - 2vMvxRT2(mB'MX + m2CMX) (3.10) where Aj = idAH/dT)p (3.11) and Ah and Aj are the Debye-Huckel slopes for enthalpy and heat capacity, respectively. The interaction parameters B'mx and C^x were assumed to have negligible contributions and thus their values were set to zero. Standard partial molar heat capacities determined from our nanocalorimeter are also dependent on measured densities. These have an effect on the experimental error for heat capacities because density errors become compounded in calculations with errors in the power determination. Standard deviations in the 106 measured power were approximate 1.0 µ??, but varied slightly with temperature. Uncertainties in heat capacities were calculated from the standard deviations of the measured power and density at each temperature and the uncertainties in solution molalities using standard propagation of errors techniques (Taylor, 1982). 3.2.4 Modelling of Standard Partial Molar Heat Capacities As with the standard partial molar volumes discussed above, standard partial molar heat capacities were modelled using "density" and HKF models. Heat capacity measurements at 135 0C were dependent on high temperature density data, and as such were given less weight in the models as described in the Section 3.2.2. Given that volume and heat capacity are indirectly related to each other through their relationships to the Gibb's free energy described in Section 1.4, their models must be correlated to each other. Standard partial molar heat capacities were calculated for neutral cytidine, thymidine, and uridine up to 135 0C. Even though the same instrument was used, apparent molar heat capacity is also dependent on the density measurements made with the high temperature equipment, so the weighted analysis described in Equation 3.4 was used to model data. 3.2.4.1 "Density" Model Analysis An extended model for heat capacities can be derived from the density model proposed by Marshall and Franck (1981), and is described by: 107 àC°P = -R[2c/T2 + 6d/T3 + E{2Taw + T2 (daw/dT)} + V{T(daw/dT)} + G{(daw/dT) - 2aw/T + (2/T)InPw)] + n. (3.12] where n0, c, d, E, F, and G are fitting parameters, pw is the density of water at temperature T, crw is the thermal expansivity of water, determined from the ASME formulation (Harvey et al. 1996). As in the previous section, the experimental data cannot be reasonably fitted using all of the parameters included in the density model. Several parameters were excluded from the model fits to minimize regression parameter error and the scatter between the fit and the experimental data. The selection technique described in Section 3.2.2.1 was used to determine the best models. Separate models for neutral and positively charged species were selected to optimize data fitting. Neutral Species Linear regression tools in Excel were used to develop a three parameter fit for standard partial molar heat capacities of neutral bases and nucleosides, which is described by the following relationship: C'Pi2 = no - R(2c/T2 - 2Gaw/T) (3.13] where n, c and G are the fitting parameters determined from the regression. Density models of the standard partial molar heat capacities of neutral bases and 108 nucleosides in water are shown in Figures 3.24 to 3.29. Fitting parameters for Equation 3.13 are shown in Table 3.6. Positively Charged Species The positively charged nucleic acid bases and nucleosides studied were best fitted with the following relationship: c;,2 = ?» - R{2EawT + ¥(Saw/ST)PT} [3.14] where n0, E, and F are fitting parameters obtained from linear regression. Regression parameters are presented in Table 3.7, and Figures 3.30 to 3.32 plot the modelled data. The linear regression function in the Microsoft Excel© software package was used to determine all regression parameters with errors of no more than twenty five percent, with one exception for the intercept of cytosine hydrogen chloride. The average vertical deviations between the fitted models and the experimental data points were no more than 2.5 J mol? K1 for neutral species and no more than 6.0 J mol·1 K1 for species in acidic solution. One exception is adenine hydrogen chloride, with an average vertical deviation of 12.0 J mol·1 K1. 109 325 275 o E 225 a. u 175 125 -r 10 60 110 160 Temperature/ (eC) Figure 3.24: Standard partial heat capacities, Cp,2°, of neutral adenine in water collected at 5 0C increments from 15-90 0C (?), plus literature data from: (*) Kishore et al. (1989). The solid line represents the proposed density model fitted to Equation 3.13. 110 325 — 245 H 10 60 110 160 Temperature/ ("C) Figure 3.25: Standard partial heat capacities, Cp,2°, of neutral cytosine in water collected at 5 0C increments from 15-90 °C (A), plus literature data from: (*) Kishore et ai (1989); (?) Kilday (1978b); and ( O ) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.13. Ill 350 300 * 250 o E 200 a. u 150 100 70 90 110 Temperature/ (0C) Figure 3.26: Standard partial heat capacities, Cp/, of neutral uracil (·) and thymine (¦ ) in water collected at 5 0C increments from 15-90 0C, plus literature data from: (*) Kishore et al. (1989); (?) Kilday (1978a); (?) Szeminske étal. (1979); (—) Alvarez (1973); and (O) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.13. 112 625 575 »H 525 u 475 425 375 10 30 50 70 90 110 130 150 Temperature/ (0C) Figure 3.27: Standard partial heat capacities, Cp,2°, of neutral adenosine in water collected at 5 0C increments from 15-90 0C (?), plus literature data from: (*) Kishore et al. (1989); (·) Stern and Oliver (1980); and ( O ) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.13. 113 600 550 £ 500 o E 450 a. u 400 350 10 60 110 160 Temperature/ (0C) Figure 3.28: Standard partial heat capacities, Cp/, of neutral cytidine in water collected at 5 0C increments from 15-90 0C and at 135 0C ( A ), plus literature data from: plus literature data from: (*) Kishore et al. (1989); ( + ) Stern and Swanson (1985); and (O) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.13. 114 650 ^ 550 Temperature/ ("C) Figure 3.29: Standard partial heat capacities, Cp,2°, of neutral uridine ( · ) and thymidine (¦) in water collected at 5 0C increments from 15-90 0C and at 135 0C, plus literature data from: plus literature data from: (*) Kishore et al. (1989]; ( + ) Stern and Swanson (1985); and ( O ) Patel and Kishore (1995). The solid line represents the proposed density model fitted to Equation 3.13. 115 200 e -100 70 90 150 Temperature/ ("C) Figure 3.30: Standard partial heat capacities, Cp,2°, of adenine hydrogen chloride, adenineH+Cl·, in water and excess HCl collected at 5 0C increments from 15-90 0C [ ? ). The solid line represents the proposed density model fitted to Equation 3.14. 116 40 H -100 10 60 110 160 Temperature/ ("C) Figure 3.31: Standard partial heat capacities, Cp,2°, of cytosine hydrogen chloride, cytosineH+Cl-, in water and excess HCl collected at 5 0C increments from 15-90 0C (A ). The solid line represents the proposed density model fitted to Equation 3.14. 117 390 340 £ 290 o E 240 a 190 140 90 10 30 50 70 90 110 130 Temperature/ ("C) Figure 3.32: Standard partial heat capacities, Cp,2°, of adenosine hydrogen chloride, adenosineH+Cl· (?], and cytidine hydrogen chloride, cytidineH+Cl" (A) in water and excess HCl collected at 5 0C increments from 15-90 0C. The solid line represents the proposed density model fitted to Equation 3.14. 118 Table 3.6: Regression parameters for standard partial molar heat capacities, Cp/, of neutral nucleic acid bases and nucleosides in water between 15 and 90 0C. The data were fitted to Equation 3.13. Species 10"6C 10"7G J K"1 mol1 K2 Bases Adenine -262.93 ± 72.23 -1.5931 ± 0.1342 1.0155 ± 0.1013 Cytosine -284.24 ± 57.02 -1.6664 ± 0.1059 1.0229 ± 0.0800 Thymine 133.02 ± 33.15 -0.1993 ± 0.0616 0.4481 ± 0.0465 Uracil -158.65 ± 24.60 -1.0692 ± 0.0457 0.7867 ± 0.0345 Nucleosides Adenosine -183.26 ± 76.60 -2.4663 ± 0.1402 1.5348 ± 0.1101 Cytidine 235.03 ± 16.15 -0.3435 ± 0.0300 0.7250 ± 0.0227 Thymidine 499.10 ± 19.39 0.5061 ± 0.0360 0.4090 ± 0.0272 Uridine 364.84 ± 97.13 0.2323 ± 0.0178 0.5174 ± 0.0140 Table 3.7: Regression parameters for standard partial molar heat capacities, Cp,2° of certain chloride salts of nucleic acid bases and nucleosides in water and excess HCl between 15 and 90 0C. The data were fitted to Equation 3.14. Species IO"4^ J K"1 mol"1 K Bases AdeninehTcr 1356.37 ± 126.80 41.53 ± 12.84 6.4299 ± 0.5012 CytosinehTci" 78.71 ± 37.14 -21.97 14.14 0.7313 ± 0.1402 Nucleosides Ade nos i ne H+C G 901.71 ± 67.23 -5.194 ±6.156 3.1017 ± 0.2775 Cyt¡d¡neH+CI" 846.35 ± 54.02 21.64 ± 6.02 2.3900 ± 0.2039 119 As temperature increases towards the critical point, standard partial molar heat capacities of neutral nucleic acid components approach positive infinity, and those for ionic nucleic acid components negative infinity. These trends agree with those observed for the standard partial molar volumes discussed previously. 3.2.4.2 HKF Model Neutral Species A simplified version of the HKF model for standard partial molar heat capacities described in Section 1.6.2 was fitted to experimental data, and is given by: Cp = C1 + c2/(T - T)2 + ?6G? (3.15) where Ci and C2 are fitting parameters, and ?ß, the Born coefficient, is used as a fitting parameter for neutral species. The pressure dependent terms were omitted from the model regression because no pressure dependence was measured. Values of oie were determined from regressing volume and heat capacity data, and the value providing the best fit for both models was selected. Regression parameters for Equation 3.15 are shown in Table 3.8. 120 325 £ 275 o E ? 225 o a u 175 125 10 60 110 160 Temperature / (0C) Figure 3.33: Standard partial molar heat capacities, Cp/, of neutral adenine in water collected at 5 0C increments from 15-900C (?]. The solid line represents the HKF model fitted to Equation 3.15. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006), fitted with the literature data used from: (*) Kishore et ai. (1989). 121 IN ? 160 110 10 30 50 70 90 110 130 150 Temperature / (0C) Figure 3.34: Standard partial molar heat capacities, Cp/, of neutral cytosine (a), uracil (·), and thymine ( ¦ ) in water collected at 5 0C increments from 15-90 0C. The solid line represents the HKF model fitted to Equation 3.15. The dashed line is the HKF model proposed by LaRowe and Helgeson [2006), fitted with the literature data used from: [O) Patel and Kishore (1995) and (*) Kishore et al. (1989). 122 p G 10 30 50 70 90 110 130 150 Temperature/ (0C) Figure 3.35: Standard partial molar heat capacities, Cp,2°, of neutral adenosine in water collected at 5 0C increments from 15-900C (?). The solid line represents the HKF model fitted to Equation 3.15. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006), fitted with the literature data used from: (O) Patel and Kishore (1995) and (*) Kishore et al. (1989). 123 600 550 500 ? O 450 S- 400 350 50 70 90 150 Temperature/ (0C) Figure 3.36: Standard partial molar heat capacities, Cp/, of neutral cytidine in water collected at 5 0C increments from 15-900C and 135 0C ( a ). The solid line represents the HKF model fitted to Equation 3.15. The dashed line is the HKF model proposed by LaRowe and Helgeson (2006], fitted with the literature data used from: (O] Patel and Kishore (1995] and (*] Kishore et al. (1989]. 124 = 500 A R- 450 -\ 10 30 50 70 90 110 130 150 Temperature/ (0C) Figure 3.37: Standard partial molar heat capacities, Cp/, of neutral thymidine (¦) and uridine (·) in water collected at 5 0C increments from 15-90 0C and 135 0C. The solid line represents the HKF model fitted to Equation 3.15. The dashed line is the HKF model proposed by LaRowe and Helgeson [2006], fitted with the literature data used from: (O) Patel and Kishore (1995) and (*) Kishore et al. (1989). 125 Protonated Species The HKF model for ionic species was described previously. The simplified model used to fit data in this section is described by: C0P = C1 + c2/(T - T)2 + ?G? + 2TY(do)/dT)p - G(1/e - 1)(02?/?G2)? (3.16] where the first and second derivatives of ? are equal to zero, as explained in the previous section. For ionic species, ? is a calculated parameter based on the crystal radius of the ions. Radii used to determine the Born coefficient are shown in Table 3.4. Calculated standard partial molar heat capacities of protonated species were modeled using different values of ?, as was done for volumes in Section 3.2.2, and are presented in Figures 3.38 to 3.41. Aside from the value determined from Equations 1.63 to 1.65, ? was used as a fitting parameter, and in cases where volumes and heat capacities produced substantially different values, the values were averaged. A simple average was used rather than a weighted inverse variance. Standard partial molar volumes have lower errors, and thus the ? term determined from fitting this data would be weighted more heavily than that determined from fitting standard partial molar heat capacity data. However, the standard partial molar heat capacity model is more strongly affected by the ? term, which would not be best represented by an inverse variance approach. 126 290 -? 190 -\ 1 e 90 \ ? N ? i \ i S > ? \ w -10 \ \ \ \ 110 \ \ \ 210 / 310 10 60 110 160 Temperature / (0C) Figure 3.38: Standard partial molar heat capacity, Cp/, of adenine hydrogen chloride, adenineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (?], modeled with Equation 3.16 and different values of ooj: (-—) calculated from the ionic radii; (....) obtained by regressing calculated V20 values; (-.-.-) from Cp,2° regression; and ( —) averaged from V20 and Cp,2° regressions. 127 u -40 -100 10 60 110 160 Temperature / (0C) Figure 3.39: Standard partial molar heat capacity, Cp/, of cytosine hydrogen chloride, cytosineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (A ), modeled with Equation 3.16 and different values of ?): (-—) calculated from the ionic radii; (....) obtained by regressing calculated VY values; (-.-.-) from Cp,2° regression; and [ —) averaged from W and Cp/ regressions. 128 10 30 50 70 90 110 130 150 Temperature / 0C Figure 3.40: Standard partial molar heat capacity, Cp,2°, of adenosine hydrogen chloride, adenosineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (?), modeled with Equation 3.16 and different values of ?): (----) calculated from the ionic radii; (....) obtained by regressing calculated V20 values; [-.-.-) from Cp,2° regression; and [ —] averaged from V20 and Cp,2° regressions. 129 400 350 ^ ? N \ N 300 \ \ \ ? 250 \ \ \ \ ì «? 200 i i i 150 i ? \ i 100 10 60 110 160 Temperature / (0C) Figure 3.41: Standard partial molar heat capacity, Cp/, of cytidine hydrogen chloride, cytidineH+Cl·, in water and excess HCl, collected between 15 and 90 0C at 5 0C intervals (A), modeled with the Equation 3.25 and different values of ?]: (—-) calculated from the ionic radii; (....) obtained by regressing calculated V20 values; (-.-.-) from Cp,2° regression; ( —) averaged from V20 and Cp,2° regressions. 130 Table 3.8: HKF Regression parameters for standard partial molar heat capacities, Cp,2°, of neutral bases and nucleosides, fitted to Equation 3.15. All systems are fitted to data taken between 15 and 90 0C. 105C2 105·? Compound Formula J mol"1!«"1 J ITiOr1K"1 J K mol"1 J mol"1 Pyrim idines Uracil C4H4N2O2 154.83 220.88 ± 6.56 -4.0899 ± 0.1356 -2.1121 ± 0.4747 Thymine C5H6N2O2 235.33 256.27 ± 5.57 -2.8418 ± 0.1152 -4.4997 ± 0.4032 Cytosine C4H5N3O 172.81 238.11 ± 1.53 -4.3210 ± 0.1076 -2.9880 ± 0.5153 Purines Adenine C5H5N5 181.12 252.95 ± 15.57 -4.9659 ± 0.2913 -3.6675 ± 1.1830 Nucleosides Uridine C9H12N2O6 397.01 407.42 ± 0.41 -3.9537 ± 0.0084 -8.5414 ± 0.0294 Thymidine C10H14N2O6 464.32 460.02 ± 0.27 -3.5474 ± 0.0057 -9.3212 + 0.0197 Cytidine C9H13N3O5 404.22 512.98 ± 7.93 -5.6882 ± 0.2179 -2.2045 ± 0.5103 Adenosine C10H13N5O4 502.34 603.48 ± 18.92 -6.4695 ± 0.3913 -3.7476 ± 1.3700 Table 3.9: HKF Regression parameters for standard partial molar heat capacities, Cp,2°, of chloride salts of nucleic acid bases and nucleosides, fitted to Equation 3.16. All systems are fitted to data taken between 15 and 90 0C. The term ? denotes the values of the Born coefficient used in the model, and ?* denotes the values determined from Equations 1.63 to 1.65. C ° Cl 10"6C2 Formula Compound j HWr1K"1 J mol'1«"1 J K mol"1 J mol'1 J mol'1 Bases AdenineH+Cr (C5H6N5)+Cr -214.74 752.79 ±12.82 -3.5268 ± 0.1099 3.0113 ± 0.4411 5.4747 CytosineH^Cr (C4H6N3O)+Cr -84.21 193.27 ± 3.87 -1.0855 ± 0.0320 0.6800 ± 0.1327 5.7189 Nucleosides AdenosineH+Cr (C10H14N5O4^Cr 161.92 747.24 ±4.73 -2.2502 ± 0.0369 1.5325 ± 0.2748 5.3260 CytidineH+Cr (C9H14N3Q5)+Cr 249.75 620.98 ± 4.98 -1.3003 ± 0.0350 1.2865 ± 0.2182 5.3676 131 For both the neutral and protonated species, regression parameters were determined using the linear regression function in the Microsoft Excel© software package. Parameters were determined with standard errors of no more than thirty percent, a substantial increase in comparison to the density models. This upper limit is very high, and indicates that density models better represent experimental data. The average differences between the fitted models and the measured heat capacities were no more than 3.2 J mol * K^for neutral species and 6.2 J mol·1 K1 for species in acidic solution. There is one exception, adenine hydrogen chloride, with an average difference of 14.3 J mol·1 K1. 3.2.5 Comparison with Literature Standard partial molar properties of neutral nucleic acid bases and nucleosides have been determined previously at low temperatures (<55 0C] (Patel and Kishore, 1995; Kishore et al, 1989; Buckin, 1987; Lee and Chalikian, 2001; etc.]. Calculated standard partial molar properties of neutral species agree well with the most recent low-temperature literature data within stated error limits; standard partial molar volumes to within 1 cm3 mol·1, and standard partial molar heat capacities to within 5 J K1 mol·1 (Patel and Kishore, 1995; Kishore et al, 1989]. There are a few notable exceptions, particularly for standard partial molar heat capacities. First, the only literature value for neutral adenine reports a value of 242 J K1 mol·1 at 25 °C(Kishore et al., 1989], whereas in this study a value of 178.8 J K1 mol·1 was found, as shown in Figure 3.24. For adenosine at 25 0C, Patel and Kishore (1995] report a value of 507 J K1 mol·1, Kishore et al. (1989] report a value of 506 J 132 K1InOl-1 and Stern and Oliver (1980) report a value of 397 J K1 mol1, but in this study we determined a value of 495.4 J K1 mol·1, as shown in Figure 3.27. There was generally a large range amongst literature values for standard partial molar heat capacities, owing to the difficulty of these measurements and the low solubility of these molecules in water. Kishore et al. (1989) used a Picker flow calorimeter, Patel and Kishore (1995) used a micro DSC calorimeter, and Stern and Oliver (1980) used an adiabatic calorimeter that was custom built in 1977. The NDSC-III scanning nanocalorimeter used in this study is newer than these systems, and we believe provides more reproducible and accurate results. At present, no literature data for standard partial molar properties of protonated nucleic acid bases and nucleosides could be found to which we could compare the values determined here. 3.2.6 Discussion As temperatures were increased, decomposition of nucleosides during high temperature density measurements was expected to occur. Appreciable decomposition of thymidine occurred at 175°C, cytidine at 2000C, and uridine at 2250C. Structurally, the difference between thymidine and uridine is that thymidine is missing an hydroxyl group on the 2' carbon of ribose, and it also has an extra methyl group on its pyrimidine ring. It is believed that the hydroxyl group is especially important to stabilizing nucleosides (Garrett and Mehta, 1972a), and it is the loss of this group that makes thymidine particularly unstable. The Born coefficient, ?, in the HKF equations should reflect the limiting high temperature behaviour of standard partial molar properties of aqueous electrolytes 133 and ions. It is expected that as the critical point of water is approached, long range polarization effects will dominate solute-solvent interactions in solution. The dielectric constant of water decreases substantially with increasing temperature, while the isothermal compressibility of water increases to infinity at the critical point. As a result, hydrophobic species will repel very large numbers of water molecules while ions will attract large numbers of water molecules. These opposing hydrophobic and hydrophilic hydration effects are reflected in the behaviour of standard partial molar properties of aqueous species observed at the critical point. Typically, standard partial molar properties of neutral species approach positive infinity, indicated by a negative ? in the HKF model, and those of ions approach negative infinity, indicated by a positive ? (Levelt et al., 1994). For neutral species, the 'density' and HKF models derived from our data do approach positive infinity at the critical point. This trend was confirmed with high temperature data for neutral uridine, thymidine, and cytidine and applied to all neutral bases and nucleosides. This is in stark contrast to the proposed HKF models from LaRowe and Helgeson (2006) which approach negative infinity. Their models are based on experimental data measured to T < 55 °C, and less for some species, which are not sufficient to model the behaviour at high temperature. Instead, their values of ? for nucleic acid bases were predicted from the Gibb's energy of hydration, AhydG" (Plyasunov and Shock, 2001): 134 o>base = {0.624 + 18.51/(AÄydCe - 21.7)} * IO5 (3.17] and (¿nucleoside was predicted from the general group additivity model: (¿nucleoside = (¿base "¦" (¿sugar l_á.loJ where (¿sugar was taken as the value for ribose for all nucleosides, including thymidine, because values for deoxyribose were not available. Additionally, literature values for AhydG" were also not available and had to be calculated from the Gibb's energies of formation of the aqueous and gaseous nucleic acid bases. While this method of approximation can be quite effective for small, neutral molecules, it is not based on data characteristic of these larger molecules. Nucleic acid bases and nucleosides are neutral molecules, and although polar groups dominate their solute- solvent interactions at low temperatures (Zielenkiewicz, 1999), the interactions are not strong enough to attract water molecules near the critical point as ions would. Their behaviour, as reported in this thesis, is consistent with other neutral aqueous species (Búlemela and Tremarne, 2008). The value of ? for charged, aqueous species was estimated from the crystallographic radius of the ion(s) under study, as described in Section 1.6.2. Typically, monatomic ions with smaller radii have larger, more positive ? values than do larger, monatomic ions of the same charge. The relationship between ionic radii and the value of ? becomes more complex for polyatomic ions. Large, organic ions, such as those under study, can bend and functional groups within the species can interact with each other. As a result, the radii of these species in solution are not so obviously related to their crystallographic radii. 135 Several fitting methods were attempted to determine the best representation of the calculated data. First, approximations of ? were determined from literature values of crystallographic radii for nucleic acid components. A value of 1.81 Á was used for the radius of the chloride ion (Tanger and Helgeson, 1988). This fit followed the correct downward trend of the data, but seemed to be too broad and overestimated volumes and heat capacity, even at temperatures as low as 90 0C. Second, the data were modelled using ? as a fitting parameter. Values for ? are required to be consistent between the volume and heat capacity models. However, with the exception of adenosine, substantial differences in ? between data sets made it difficult to fit both sets with one consistent value. In such cases, values were averaged to obtain a better approximate fit, and generally these values were an order of magnitude larger than those determined from crystallographic radii. Overall, these models best represented the downward trend as well as the low temperature behaviour of the data. It is not surprising that neither the calculated value of ? nor the value common to 1:1 electrolytes adequately represented the data. Solutions of small electrolytes, such as sodium chloride in water, consist of two relatively small ions with what could be considered point charges. These point charges will have tightly packed solvation spheres organized around them. For solutions of protonated nucleic acid bases and chloride ions, positive charges can be shared around the conjugated systems, and other electron rich functional groups in the molecules will also interact with these charges. Consequently, solvent molecules will not be able to pack around the ion in the same organized fashion as for simple ions, and 136 calculating a value for the Born coefficient based on radius data will not be an effective representation of the behaviour of protonated nucleic acid bases and nucleosides in solution. 3.3 Functional Group Additivity Models 3.3.1 Introduction Several functional group additivity models for biomolecules have been proposed in literature to predict the thermodynamic parameters of molecules based on the functional groups from which they are composed (Holland, 1986; Gianni and Lepori, 1996). Such models assume that any functional group's behaviour is independent of the other groups around it, implying that they do not interact or influence each other in any substantial way. However, the contribution of a functional group to a thermodynamic parameter can never be defined as an independent, absolute contribution because interactions with other groups will affect its behaviour. Depending on the nature of the functional group under study, and the neighbouring groups, interactions may be minimal, or more substantial, resulting in a varying degree of deviation from the additivity model. It is the goal of this section to attempt a crude estimation of the contribution of the ribose functional group to standard partial molar properties of nucleosides, assess the differences in the contribution to pyrimidines and purines, and estimate the standard partial molar volume of guanine. 137 3.3.2 Analysis of Ribose Contribution to Standard Partial Molar Properties For a general nucleic acid base, N, and its corresponding nucleoside, the dissociation of the ribose group from the nucleoside can be described by the reaction: N - ribose + H2O ^ N + ribose (3.19) From this equation, the difference between a standard partial molar property of a nucleoside and a nucleic acid base is the standard partial molar property of ribose minus the property of water. Thymidine serves as the exception to this is, as it only exists in a deoxynucleoside form, and as a result the nucleoside is missing one oxygen atom needed to produce the nucleic acid base and ribose. The ribose contribution will still be assessed for thymidine to compare it to the contributions made to other pyrimidine nucleosides. Because we are more concerned with the differences between nucleoside and nucleic acid base behaviour, the contribution of the ribose group will be defined as the difference between a standard partial molar property of a nucleoside and its corresponding base as shown in Equation 3.20. SY2rib' = (AY2ribose + YH20 + &Y ) = ^2MUcieoside ~~ Y2 nucleic acid base C3·20) where ??° is the change in a standard partial molar property as a result of the reaction, and is assumed to be a constant. This expression is consistent with previous work completed by Patel and Kishore (1995), who also attempted to elucidate a relationship between the standard partial molar properties of nucleosides and nucleic acid bases. However, Patel and Kishore assumed that ??° is equal to zero. The ÖY2°rib contributions to standard partial molar volumes and heat 138 capacities of neutral uridine and thymidine, as well as neutral and protonated adenosine and cytidine were determined. Due to large errors and scatter in the HKF modelling parameters, particularly for protonated species, only density models were fitted to data. 3.3.2.1 Density Model Analysis Neutral Species The density models of 5Ylrib used here for the volumes and heat capacities of neutral nucleosides are described by: SV¡iRib. = -EfiwRT + ho (3.21) and SCp2Mb. = no - R{2EawT - F (^ T) [3.22) where h0, n0, x, F and E are fitting parameters, and all other parameters have been described previously in this chapter. Volume and heat capacity models are shown in Figure 3.42, Figure 3.43, and Figure 3.44 and regression parameters for Equations 3.21 and 3.22 are shown in Table 3.10 and Table 3.11. Parameters were determined with errors of no more than fifteen percent for volumes, and no more than forty percent for heat capacities. The average differences between the fitted volume models and the experimental data points were 0.3 cm3 mol1 or less, those between experimentally determined heat capacities and fits were 2.5 J mol·1 K1 or less. 139 89 87 H o 85 E e Ä 83 81 ¦a S 79 77 75 10 30 50 70 90 110 130 150 Temperature/ (0C) Figure 3.42: 8V°2rib of neutral adenosine (?), cytidine (A], thymidine (¦], and uridine (·) as calculated in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.21. 140 400 ^ 360 8 350 300 10 30 50 70 90 110 130 150 Temperature/ ("C) Figure 3.43: 6Cp2ribOf neutral adenosine (?), as calculated in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.23. 141 330 310 O E 290 S 270 S 250 H ü 230 210 10 30 50 70 90 110 130 150 Temperature/ ("C) Figure 3.44: 6Cp 2 rib of neutral cytidine (A), thymidine (¦), and uridine (·), as calculated in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.22. 142 Table 3.10: Regression parameters for 5I^ rib of neutral nucleosides in water measured between 15 and 90 0C. The data were fitted to Equation 3.21. Species h0 E ______J mol? K1 Adenosine 73.07 ± 1.46 7.6039 ± 1.1850 Cytidine 67.0010.91 9.99178 ± 0.7360 Thymidine 72.10 ±0.97 6.8163 ± 0.7870 Uridine 76.15 ± 0.30 5.7602 ± 0.2449 Table 3.11: Regression parameters for6Cp2ribOf neutral nucleosides in water measured between 15 and 90 0C. The data were fitted to Equation 3.22. 10"3F Species J mol"1 K"1 K Adenosine 348.03 ± 20.02 -8.4591 ± 2.4490 1.5976 ± 0.7196 Cytidine 186.03 ± 12.90 -12.738 ± 1.578 -1.1416 ± 0.4636 Thymidine 241.97 ± 5.95 -9.7354 ± 0.6627 1.1326±0.2245 Uridine 197.56 ± 5.09 -14.156 ± 0.568 -1.0933 ± 0.1923 143 Protonated species Density models were determined for 8Y¡rib of chloride salts of the protonated nucleosides: 8V°2,Rib = -EßwRT + mí + h0 [3.23] and SC"p,2 Rib = n- - R{~2zccw + 2EawT + F (^f-)p T] (3.24) where h", k', y, z, E and F are fitting parameters determined from linear regression techniques. Volume and heat capacity models of protonated species are shown in Figure 3.45, Figure 3.46, and Figure 3.47 and regression parameters for Equations 3.23 and 3.24 are shown in Table 3.12 and Table 3.13. Parameters were determined with errors of no more than twenty five percent for volumes, and no more than ten percent for heat capacities. The average differences between the fitted volume models and the experimental data points were 0.4 cm3 mol·1 or less. Average differences between experimentally determined heat capacities and their corresponding fits were 3.0 J mol·1 K1 or less. 144 100 95 O E m e 90 ? 85 8 80 H 75 70 10 30 50 70 90 110 130 150 170 Temperature/ ("C) Figure 3.45: 8V°2 rib of adenosine hydrogen chloride, adenosineH+Cl· (?), and cytidine hydrogen chloride, cytidineH+Cl·, (A] as calculated in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.23. 145 500 450 » 400 > 350 300 vi rg 250 200 10 30 50 70 90 Temperature/ (0C) Figure 3.46: 5Cp 2 rib of adenosine hydrogen chloride, adenosineH+Cl· (?] as calculated in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.24. 146 360 340 o .1 320 300 ? 280 °? 260 ? 240 H 220 10 30 50 70 90 Temperature/ (0C) Figure 3.47: 6Cp 2 r¡b of elidine hydrogen chloride, cytidineH+Cl· (A] as calculated in 5 0C increments from 15 to 90 °C. Solid lines denote regression models of Equation 3.24. 147 Table 3.12: SV°2ribof chloride salts of nucleosides in water and excess HCl measured between 15 and 90 0C. The data were fitted to Equation 3.23. Species h0 m E ______J mol1 K1 * AdenosineH+cr 52.96 ±1.45 0.1110 ±0.0158 -8.8415 ± 3.6030 CytidineH+CI" 61.78 ±0.74 0.1291 ±0.0081 -8.3473 ± 1.8428 Table 3.13: 5Cp2ribOf chloride salts of nucleosides in water and excess HCl measured between 15 and 90 0C. The data were fitted to Equation 3.24. c · n° I·0"6'2 4Ä3r 10"5-F SpeCieS Jm0I-1K-1 K 10E AdenosineH+cr -5115.02 ± 469.30 1.7836 ± 0.1758 1.8360 ± 0.1849 -1.6928 ± 0.1384 CytidineH+CI' 6254.33 ± 430.80 -2.1184 ± 0.1661 -2.1972 ± 0.1757 1.7624 ± 0.1255 148 In Figure 3.42, there does not appear to be a significant difference in SV°2 rib for neutral adenosine as it lies amongst the values of SV2 rib for neutral pyrimidine nucleosides cytidine and uridine. However, comparing Figure 3.43 and Figure 3.44, OCp 2 „h for neutral adenosine is substantially different than that for the pyrimidines. Patel and Kishore (1995) determined that 6Cp 2 rib for neutral species deviated considerably from one another, most likely due to interactions between the nucleic acid base and the hydroxyl groups of ribose, and as a result, the proposed additivity rule does not hold. Our results for OCp 2 rib for neutral pyrimidines are consistent with their findings at 25 0C: 225 J mol·1 K1, 247 J mol·1 K1, and 228 J mol·1 K1 for cytidine, uridine, and thymidine, respectively. For ionic species, the comparison of OV2" r¡b is more difficult because only cytidine and adenosine were studied, yet the contributions to their respective volumes and heat capacities appear to differ. As temperature increases, values of SV2 rib follow consistent trends, however, the difference between the adenosine and cytidine models are quite substantial. The values of OCp 2 rib for ionic species and the differences between the models appear to be very unrealistic over the temperature range studied, and indicate that the interactions between the nucleic acid base and the hydroxyls of ribose are more pronounced when a positive charge is added to the nucleic acid base. In the following section, the partial molar volume of guanine hydrogen chloride will be estimated using OV2 rib for adenosine; however, this model should be taken as a very rough approximation given the suggested interactions. 149 Based on the overall observations for neutral and ionic purines and pyrimidines, and the thermodynamic relationship between volumes and heat capacities, the effect of the ribose group on purines and pyrimidines will be considered as separate and distinct contributions in subsequent sections. The standard partial molar volume of guanine will be determined from OV2" rib for the adenosine-adenine system. 3.3.3 Determination of the V2" of Guanine Guanine is not sufficiently soluble in water to measure its standard partial molar volume by the methods used here. Instead, a simple functional group additivity model for nucleosides and nucleic acid bases was developed to obtain an estimate of the contribution of the ribose group to the standard partial molar volume of guanosine. Due to the solubility limits of the scanning nanocalorimeter, guanosine measurements could not be completed, and a similar treatment for the heat capacity of guanine proved impossible. The ribose contributions in the pyrimidine and purine studies were found to be significantly different in the previous section, thus the ribose contribution to the standard partial molar volume guanosine was taken to be equivalent to the contribution to adenosine. The ribose volume contribution was then subtracted from the standard partial molar volume of guanosine, giving an estimate for the standard partial molar volume of guanine. Standard partial molar volumes of neutral guanine were determined from HKF and density models, and produced very similar fits, as is shown in Figure 3.48. The proposed models are described by: 150 V¡ = (8.4598 * IO1) - (6.8257 * 103)ßwR + (3.1199 * 10^ßwRT (3.25) and V¡ = (8.7460 * IO1) + (-1.9898 * 102){1/(T - T)} - (-1.6872 * 106)? (3.26) Estimates for protonated guanine were developed from the density model only due to significant deviations observed in the HKF models for protonated species. This model is described by: V°2 = (3.7704 * 101) + (5.4052 * 10_1)G - (9.9732 * IO1)ßwRT (3.27) and is shown in Figure 3.49. 151 ¦s 110 E 105 H 10 60 110 160 Temperature/ ("C) Figure 3.48: Standard partial molar volume of neutral guanine in water, V20, estimated from a functional group additivity model for the ribose contribution to purine nucleosides using [—) the density model and (---) the HKF revised equation of state proposed in Equations 3.25 and 3.26, respectively. 152 -t 10 30 50 70 90 110 130 150 170 Temperature/ (0C) Figure 3.49: Standard partial molar volume of protonated guanine in water, Vi, estimated from a functional group additivity model for the ribose contribution to purine nucleosides using the density model proposed in Equation 3.27 (—). 153 3.3.4 Discussion As previously mentioned, the ribose contribution to the standard partial molar volumes of neutral species did not show significant differences between the purine nucleoside (adenosine] and the pyrimidine nucleosides (cytidine and uridine]. The largest average deviation between ribose contribution models occurs between cytidine and uridine, and is approximately 4.5 cm3 mol?. The ribose contribution to neutral adenosine was found to lie within this deviation. Typically, functional group additivity models assess the contribution of smaller functional groups, such as methyl or amino groups. Considering the nature of these models and the size of the ribose 'functional group' used for the model, this difference is considered inconsequential. The differences in ribose contributions to standard partial molar heat capacities were more substantial between neutral purine and pyrimidine bases. Ribose contributions to adenosine and cytidine showed the greatest average difference, approximately 90 Jmol 1K1. This is quite large compared to 14 J moHK1, the average difference between the ribose contributions to the standard partial molar heat capacities of the pyrimidine ribonucleosides (uridine and cytidine]. Deviations amongst the ribose contributions to standard partial molar properties of neutral ribonucleosides could be due to interactions between the ribose group and different functional groups within each respective base. Patel and Kishore (1995] suggested that the differences in the ribose contributions to nucleosides are significantly different, and functional group models for ribose cannot adequately predict thermodynamic parameters of nucleosides, particularly standard partial 154 molar heat capacities. The results in this section appear to be consistent with their observations. The ribose contributions to the standard partial molar volumes and heat capacities of neutral thymidine, the deoxyribonucleoside, followed a slightly different, although still upwardly deviating, trend compared to the two pyrimidine ribonucleosides. While the calculated contributions fell within the same range as the ribonucleosides, they crossed over with the uridine and cytidine ribose contributions for both thermodynamic parameters. These deviations most likely result from the loss of one hydroxyl on the ribose group. Deviations in the ribose contributions to standard partial molar properties of protonated adenosine and cytidine are more larger than are those for neutral species. The contributions to their volumes show an average difference of 15 cm3 mol1, and the contributions to their heat capacities follow similar general trends although they do not have a consistent average difference. These observed differences provide additional evidence that ribose and nucleic acid base groups interact with each other within nucleoside molecules. These observations have considerable implications for the proposed guanine model. Contributions to the standard partial molar volumes of neutral species show relatively small deviations, and it is believed that the molar volume model for guanine is an adequate estimation. For protonated cytidine and adenosine, the greater differences in volume contributions suggest that a larger error is associated with this model. Ribose contributions to standard partial molar heat capacities vary for each species, even within the neutral pyrimidines, indicating that a group 155 additivity model for heat capacities of neutral or protonated guanine would contain considerable errors. 3.4 Standard Partial Molar Properties of Ionization Generally, the first ionization reaction of nucleic acid bases and nucleosides can be expressed as: BH + H+ <-» BH^ (3.28) where B denotes any nucleic acid base or nucleoside capable of undergoing an ionization to a positively charged, protonated species. From Equation 3.28, the change in a standard partial molar property due to an ionization reaction, AY2°reaction, can be determined from: AY reaction = Y2 (BH}cr) ~ Y2 (HCl) ~ ^2 (BH) (3'29^ where Y2°(hci) was determined from Sharygin and Wood's (1997) model for volumes and Patterson etal.'s (2001) model for heat capacities. Equation 3.29 was used to determine the standard partial molar volumes and heat capacities of reaction for adenine, cytosine, adenosine, cytidine, guanosine, and guanine, the last of which was obtained from the proposed group additivity model in the previous section. Density models were used to describe the standard partial molar properties of ionization, according to the following equations: AV°rxn = h» + mT + ERßwT (3.30) and AC°P „ = no + cR/T2 - R{2EccwT - F(Sctw/ÔT)PT} (3.31) 156 where h0, n0, m, c, E, and F are fitting parameters, and all other parameters have been described previously in the chapter. Models of standard partial molar volume of ionization are plotted in Figure 3.50 and Figure 3.51. The standard partial molar volume of ionization for guanine, as determined from the functional group additivity model determined in the previous section, is plotted in Figure 3.52. Standard partial molar heat capacities of ionization are plotted in Figure 3.53 and Figure 3.54. Regression parameters and standard errors determined using Excel© for Equations 3.30 and 3.31 are presented in Table 3.14 and Table 3.15. Model equations were selected using the technique described in previous sections. Parameters were determined with errors of no more than twenty five percent for volumes, and no more than forty percent for heat capacities, with the exception of one parameter in the adenosine fit. The average differences between the fitted volume models and the experimental data points were 0.25 cm3 mol·1 or less, with the exception of guanosine with an average difference of 1.9 cm3 mol·1. Average differences between experimentally determined heat capacities and corresponding fits were 5.0 J mol·1 K" 1 or less, with the exception of adenine, whose average deviation was 13 J mol·1 K-1. Volumes and heat capacities of ionization deviate toward negative infinity. The purine bases and nucleosideshave more negative ?G???0 and ArxnCp" than the only pyrimidine base and nucleoside studied here (cytosine and cytidine). There is no clear correlation between the behaviour of ArxnV for nucleic acid bases and corresponding nucleosides, as adenine is less negative than adenosine, but cytosine is more negative than cytidine, nor for ArXnCp°; adenine data cross the adenosine data, and cytosine data are more negative than cytidine. 157 10 30 50 70 90 110 130 150 Temperature/ (0C) Figure 3.50: Standard partial molar volume of ionization, ?,™Vo, of adenine (?) and cytosine (A), as calculated from data measured in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.30. 158 10 60 110 160 Temperature/ (0C) Figure 3.51: Standard partial molar volume of ionization, ArxnV, of adenosine (? ), guanosine (*) and cytidine [A), as calculated from data measured in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.30. 159 -100 -120 10 30 50 70 90 no 130 150 170 T/°C Figure 3.52: Standard partial molar volume of ionization, ArxnV°, of guanine as determined from functional group additivity models using regression parameters for Equation 3.30. 160 10 30 50 70 90 110 T/eC Figure 3.53: Standard partial molar heat capacity of ionization, Am1C0P , of adenine (? ) and cytosine (A), as calculated from data measured in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.31. 161 -225 H 10 30 50 70 90 110 T/°C Figure 3.54: Standard partial molar heat capacity of ionization, ArxnCp, of adenosine (?) and cytidine (A), as calculated from data measured in 5 0C increments from 15 to 90 0C. Solid lines denote regression models of Equation 3.31. 162 Table 3.14: Regression parameters for the standard partial molar volume of ionization, ArXnV° of certain nucleic acid bases and nucleosides from data measured between 15 and 90 0C. The data were fitted to Equation 3.30. Species h0 102m E ______cm3 mol"1 cm3 K1 mol1 Bases Adenine -11.05 ± 1.55 6.524 ± 1.685 -24.875 ± 3.854 Cytosine -25.88 ± 0.92 8.801 ± 1.001 -16.372 ± 2.289 Guanine** -42.11 ± 10.06 42.547 ± 10.96 -97.611 ± 2.506 Nucleosides Adenosine -28.85 ± 1.20 13.657 ± 1.304 -32.731 ± 2.983 Cytidine -28.92 ± 0.60 17.597 10.658 -25.536 ± 1.505 Guanosine -59.92 ± 9.71 49.679 ± 10.58 -105.47 ± 24.19 Table 3.15: Regression parameters for the standard partial molar heat capacity of ionization, ArxnCp" of certain nucleic acid bases and nucleosides measured between 15 and 90 0C. The data were fitted to Equation 3.31. n0 10"6-c E ifZ-F Species J K1. mol1- IO2 cm3iK mol ? K Adenine 854.95 ± 115.05 - 26.192 + 12.820 4.5732 ± 0.4343 Cytosine 2479.811153.44 -1.8041 + 0.0987 245.73 + 15.16 -2.1783 + 0.0851 Adenosine 272.72 + 52.80 - 4.7616 + 5.3459 2.0390 + 0.2087 Cytidine -1330.58 + 636.07 1.0685 + 0.4090 -132.37 + 62.86 2.2076 + 0.3529 163 CHAPTER 4 ADENOSINE REACTIONS UNDER HYDROTHERMAL CONDITIONS 4.1 Acid Ionization Constant from 25 to 175 0C 4.1.1 Introduction The absorption maxima of nucleosides are highly pH dependent (Shugar and Fox, 1952). Using thermally stable buffers, a series of solutions can be prepared with controlled pH, and by measuring changes in their absorption spectra relative to spectra at the extremes of pH, equilibrium constants at elevated temperatures can be determined. The first acid ionization of adenosine and its equilibrium constant can be written as: AdenosineHj <-* AdenosineH + H+ (4.1) K = (???+t???/t???+)(??+???/???+) (4.2) where mx and ?? represent the molalities and activity coefficients of each species in the reaction. For this system, formic acid/formate was chosen as the buffer system because its buffer region overlaps sufficiently with the projected K3 of adenosine. The reaction equation and equilibrium quotient for this system are: CHCOOH «-> CHCOO" + H+ (4.3) and Qformic = mH+mCHCOO-/mCHCooH (4-4J Values of Qformic were taken from Bell et al. (1993). 164 Rearranging Equation 4.4 to isolate the molality of hydrogen ions and then substituting into Equation 4.2 yields: Ka = (rnAH/mAH+)(QformicmCHCOOH/mCHCoo-)(y?+ì??/???}) C4-5) In Equation 4.5, the adenosine buffer ratio, mAH/mAH+ , can be determined from the UV-visible spectrum. The formic acid buffer ratio, {sAH(X)bmAH + eAH+(A)bm*AH+}, can be estimated from the original solution composition, assuming there is minimal hydrolysis of the acid or base species. Beer's Law for a two component mixture of acidic and basic forms of adenosine can be written as: A(X) = {eAH(X)bmAH + eAH+(X)bm*AH+}psoin (4.6) where A(X) is the absorbance of a solution at each wavelength and b is the path length. The specific molality, m*, of each of the acidic and neutral species, expressed in mol kg"1 of solution, is more convenient than the more common mol kg-1 water because specific molality can be easily converted to molarity using the solution density, pSoin. The molar absorptivity of the acidic and neutral adenosine components of the buffer solutions can be expressed in terms of the absorptions of solutions at pH extrema ('ex') chosen so that adenosine is fully protonated and deprotonated, respectively: ZÄH} W = AAHi,ex (X)/bm*AHt,ex PAH^,ex C4"7) £ah W = AAHfiX (X)/bmAHexpAHiex (4.8) 165 Substituting Equations 4.7 and 4.8 into Equation 4.6 and rearranging gives the following expression: A{X)/bpsoln = (AAH+ex(X)/mAH+expAH+ex) {rnAH} + (m*AHt,exPAH},exAAH,exW/m*AH,exPAH,exAAH+iexWj mAH) (4.9) Given that the solutions used were very dilute, it is safe to assume that the density ratio, pAH+iex/PAH,ex . is equal to one. Equation 4.9 can be simplified using D, k, and / to represent the following molality ratios: D=m*AH},eX/m*AH,eX (4-10) k = m*AH}/m*AH}ex (4.11) I = m*AH/mAui,ex C4·12) Using Equations 4.10 to 4.12, Equation 4.9 becomes: AW = AAHtex (X)k + AAH>ex (A)Dl (4.13) where k and / are fitting parameters that can be determined from a least squares regression of each buffer solution spectrum to the spectra of the acid and base extremes. Together, these parameters give the adenosine buffer ratio, which is simply: k/l = m*AH+/mAH = mAH+/mAH (4.14) Once this ratio was determined at each temperature, ionization quotients were calculated from Equation 4.5. Methods for optimizing the regression parameters are discussed in Appendix E. 166 At /=0 mol kg1, ionization constants are equivalent to ionization quotients because all activity coefficients of ions are equal to 1. To determine the ionization constants from ionization quotients when /*0, activity coefficients must be estimated. The model substance approach (Lindsay, 1980) was used to estimate activity coefficients of ions: Yz= YNaCi zZ (4-15) Activity coefficients for NaCl were obtained from Archer (1992). For neutral species, activity coefficients were assumed to be one. Equation 4.1 represents an isocoulombic reaction, therefore when activity coefficients determined from Equation 4.12 are substituted into Equation 4.5, their values will cancel out and render the ionization constants and quotients equivalent. For the ionization of adenosine, a solution of adenosine in 0.1 mol kg1 HCl /O.lmol kg1 NaCl was very effective as the acid extreme, and a solution of adenosine in 0.2 mol kg"1 NaCl was very effective as the basic extreme. Total formic acid concentrations were set to 0.2 mol kg1 for all buffer solutions, and base to acid buffer ratios were set between 10 and 0.1 to maintain buffering capacity at elevated temperatures. Speciation calculations using ionization constants of formic acid measured by Bell et al. (1993) confirmed these ratios at each temperature. Spectra were obtained from 190 nm < ? < 600 nm at a rate of 10 nm sec1 until a well defined, stable peak was achieved. Then the range of wavelengths was decreased to 190nm Equilibrium constants can be estimated using the van't Hoff equation: 1Og10Ka(O = log1QKa(Tr) + (Ar//;r/2.303/?)(l/rr - 1/G) (4.16) 167 where /G[Tr)is the ionization constant and ?G//tG is the standard molar enthalpy of reaction at the reference temperature, Tr=298.15 K, and K3(T) is the ionization constant at temperature T, in Kelvins. The ionization constants predicted from Equation 4.16 and the formic acid buffer region are shown in Figure 4.1. 168 -2 -4.5 -5 -5.5 -6 —?— 25 75 125 175 225 Temperature/ (0C) Figure 4.1: Formic acid buffer region (Bell étal, 1993) overlap with predicted first ionization of adenosine (—) from literature data at 298 K (Christensen et al, 1970). 169 Spectra for this equilibrium system at 175 0C and 95 bar are shown in Figure 4.2. Spectra of the acid and base extremes, taken in (0.1 mol kg1 HCl/O.lmol kg1 NaCl] and 0.2 mol kg1 NaCl, respectively, are indicated. The additional spectra were obtained in formic acid/formate buffer solutions of intermediate pH. Experimentally determined buffer ratios of adenosine, ionization quotients and ionization constants are plotted in Figure 4.2 and listed in listed in Table 4.1. Measurements were attempted up to 250 0C, however, decomposition was substantial above 175 0C and consequently results at higher temperatures were excluded. 4.1.2 Measurement Uncertainties Only solutions whose calculated buffer ratios, mAH/mAH+ , were between 10 and 0.1 (pKa ±1) were included in the ionization constant determinations. This assured that calculated data were obtained from solutions containing appreciable amounts of both adenosine species, and decreased the uncertainty of calculated values. Statistical uncertainties listed in Table 4.1 were estimated using Excel© from the standard errors of the fitting parameters k and 1, shown in Table F.l. The absorbance precision at the peak maxima deviated by approximately 0.1% between spectra. A factor of 10% was added to the uncertainty estimates to account for systematic errors resulting from drift in absorbance measurements. 170 0.8 - 320 Figure 4.2: UV-visible spectra of adenosine at 175 0C and 95 bar. Acid and base extremes, as well as intermediate pH buffer solutions of formic acid/sodium formate are shown. 171 Table 4.1: Experimentally determined values of the acid ionization quotients and constants for adenosine, Q3 and K3, respectively. t CHCOO" Avg. logQfc mAH2t/mAH logQa logKa °c /CHCQOH mol kg" lOgQa 10.80 0.2019 0.1380 -3.797 2.685 0.2053 0.4692 -3.732 1.103 0.2096 1.153 -3.719 25 -3.544 ± 0.003 -3.726 ± 0.10 -3.726 ± 0.10 0.8332 0.2061 1.596 -3.697 0.4977 0.2057 2.308 -3.689 0.2817 0.2091 4.397 -3.721 1.000 0.2096 0.5546 -3.418 0.7994 0.2061 0.7205 -3.435 50 -3.555 ± 0.003 0.5043 0.2057 1.165 -3.443 -3.434 ± 0.06 -3.434 ± 0.06 0.2508 0.2091 2.460 -3.465 0.1019 0.2043 5.323 -3.409 1.103 0.2096 0.1697 -3.025 0.8332 0.2061 0.2250 -3.028 100 -3.689 ± 0.004 0.4977 0.2057 0.3931 -3.086 -3.035 ± 0.07 -3.035 ± 0.07 0.2817 0.2091 0.6668 -3.062 0.1023 0.2043 1.550 -2.975 0.4977 0.2057 0.0914 -2.667 150 -3.922 ± 0.009 0.2817 0.2091 0.1555 -2.650 -2.636 ± 0.07 -2.636 ± 0.07 0.1023 0.2043 0.3724 -2.590 175 -4.062 ± 0.0018 0.1019 0.2043 0.1820 -2.407 -2.407 + 0.08 -2.407 ± 0.08 172 4.1.3 Comparisons with Literature Data No experimental values for high temperature ionization constants of adenosine were found in literature. Several literature values at 25 0C were found, including 3.63 (Alberty et al, 1951], 3.6 ± 0.1 (Ogston., 1936], 3.50 ± 0.02 and 3.56 ± 0.02 (Christensen et al., 1970; Izatt and Christensen, 1962]. Alberty et al. (1951] Christensen étal. (1970], and Izatt and Christensen (1962] measured the log K3. of adenosine by titration using glass and calomel electrodes, and Ogston (1936] used a Potentiometrie titration method. These agree well with the value obtained here at 25 0C and 95 bar, log K3 = 3.73 ± 0.10, despite the fact that the high temperature In- visible method employed in this study is less sensitive than titration methods. 4.1.4 Equations of State 'Density' Model Analysis Ionization constant data were modeled with the density model to estimate values for the thermodynamic parameters of the reaction. Marshall and Franck (1981] represented the ionization of water with the following expression: log K = A + B/T + C/T2 + ?/?3 + (E + F/T + G/T2)log pw (4.17] where A, B, C, D, E, F, and G are fitting parameters, and pw is the density of water. This model was then applied to electrolyte solutions (Mesmer et al., 1988]. Anderson étal. (1991] modified this model to use natural logarithms and include only A,B, and F terms below 573 K: lnK = a + b/T + Flnpw/T (4.18] 173 where a, b, and F are constants related to the enthalpy and heat capacity of reaction. This model gives ionization constants as a function of density, and as a result is thermodynamically equivalent to equations that describe the Gibb's energy as a function of temperature and pressure. This then allows the constants in Equation 4.17 to be related to all standard state thermodynamic parameters. The Gibb's energy, AG", is related to a, b, and F through the following relationship: AG° = -RTInK = -R(aT + b + F/npJ (4.19) ??° can be obtained by differentiating Equation 4.17 with respect to temperature at constant pressure: AH" = -R{b + F(Tccw + In pw)} [4.20] where ocw is the coefficient of thermal expansion of water determined from the ASME formulation (Harvey et a?, 1996]. AS" can then be found from AG" and AH° using the relationship AS° = (AH°- AG0] /T, resulting in the following expression: AS° = R(a-Fctw) (4.21) An expression for ACp° can be obtained from the derivative of Equation 4.19 with respect to temperature at constant pressure: ACp = -RTF(dctw/dT)P (4.22) Rearranging for the constant F gives: F = (-AC°P/RT)(daw/dT)P = {-ArC;.so/RTr)(daw/dT)Pr (4.23) where the subscript Pr denotes the reference pressure of 1 bar. The constants a and b are equal to: 174 a = lnKa(Tr) + àrH°Tr/RTr - àC°PaWir/RTr(daw/dT)Pr (4.24) b = -àrH°Tr/R + (TraWir + lnpw,r)àCPr/RTr(daw/dT)Pr (4.25) Using these equations, two models were fitted to the experimental data using the linear regression function from Excel©. The first used In Ka(Tr) as the only forced parameter, leaving two free parameters, and the second used InK3(Tr) and A1-H0Tr as forced parameters, leaving one parameter for regressing. This model fit very well to the data, and is presented in Figure 4.3. Fitting parameters for the density model described in Equation 4.18 are listed in Table 4.2. Thermodynamic parameters can then be determined from Equations 4.23, 4.24, and 4.25 and density model parameters are tabulated in Table 4.3. Extended van't Hoff Model Analysis Another simple model is based on the assumption that the heat capacity of ionization for an isocoulombic reaction is independent of temperature, and thus ionization constants for the reaction described in Equation 4.1 can be fitted to an extended Van't Hoff equation: log /? (G) = log Ka (Tr)- (ArH°Tr/2.303R)(l/Tr - 1/70 + (AC^n /2.303/?){ln (T/Tr) + 7yrr-l} (4.26) The values of K0(TV) and ??p at 250C and 0.1 MPa were obtained from Christensen et al. (1970). The only fitting parameter in this equation is ACp°,mem, the mean heat capacity of reaction over the temperature range of the study, which was determined to be 44.36 J K1 mol·1. The data were fairly well represented by this model which is presented in Figure 4.3. Regression parameters are listed in Table 4.2. 175 0.0018 0.0023 0.0028 0.0033 t1 1 ?-1 Figure 4.3: Experimental values of the ionization of adenosine, logioKia, measured from 25 to 175 0C: (·) experimental; (*) Christensen et al (1970); and (+) Alberty et al (1951). Data were modelled with: (—) the mean heat capacity of ionization model described in Equation 4.26 and (—) the density model of Equation 4.18. Additionally, the Van't Hoff equation was used extrapolate low temperature literature data ( ). 176 Table 4.2: Regression parameters for the density and mean heat capacity of ionization thermodynamic models, Equations 4.18 and 4.26, respectively for the ionization of adenosine, described by: AH^ <-> AH + H+. Model log/Ca,iso ArH°iS0 (298.15) ArC°P,iso (298.15) ArC°P(mean) (298.15) kl mol1 J K"1 mol"1 J K"1 mol"1 Mean Heat Capacity of -3.50 ± 0.02a 16.36 ± 0.08a — 44.358 ± 1.25 Ionization Density Model -3.50 ± 0.02a 16.36 ± 0.08 96.260 ± 15.03 1 parameter Density Model -3.50 ± 0.02a 17.054 ± 2.17 99.645 ± 17.29 2 parameter a: From Christensen et al. 1970. Table 4.3: Thermodynamic parameters for the ionization of adenosine, AH^ «-> AH + H+, determined as a function of temperature using Equations 4.16, 4.17 and 4.18, which were derived from the density model.* Temperature . ,, \G° ûrH° d?$ 0C -log Ka kJ mol _1. kJ mol1, J K" 25 3.71 ± 0.56 21.17613.19 17.054 12.57 -13.823 12.08 50 3.46 + 0.52 21.432 + 3.23 19.159 1 2.98 -7.034 ± 1.06 100 3.011 0.45 21.524 + 3.25 22.629 13.41 2.963 + 0.45 150 2.61+0.39 21.145 + 3.19 26.354 + 3.98 12.311 + 1.86 175 2.42 1 0.37 20.77213.13 28.686 + 4.33 17.659 + 2.66 200 2.24+ 0.34 20.254 + 3.05 31.634 + 4.77 24.054 + 3.63 225 2.05+ 0.31 19.555 + 2.95 35.581 + 5.37 32.172 + 4.85 250 1.86+ 0.28 18.619 + 2.81 41.313 + 6.23 43.380 + 6.54 *Errors were estimated from the standard errors of A1-C0PJs0, which was used to determined A, B, and F parameters. 177 4.1.5 Discussion Previously, experimental ionization constants for adenosine had only been measured at ambient temperature, making it difficult to assess the trends observed. Ionization constants at high temperatures were predicted using the van't Hoff equation and literature data measured under ambient conditions. This model was in fair agreement with our experimental data up to 100 0C, but above this temperature the predicted model underestimates the measured values and does not fall within experimental errors. This observation is consistent with the work of Clarke (2001) and Balodis (2007). The van't Hoff extrapolation does not include a heat capacity term. This does not have a significant impact at lower temperatures, but becomes increasingly important in the model as temperature increases. Overall, the density model best represents the experimental data. Fitting using the extended van't Hoff model with a mean heat capacity of ionization deviated from experimental data at low and high temperatures, as can be seen in Figure 4.3. The density model incorporates the variation with temperature of the heat capacity of ionization, whereas the extended van't Hoff model assumes a constant mean heat capacity value, so this is not a surprising outcome. The extended van't Hoff model deviates at 1/298.15 K (0.00354 K1 ), as shown in Figure 4.3. This is coincidental because all models were fitted to experimental data at ambient temperature data. Minimal differences were observed between the goodness of fit of the one and two parameter density model fits. This is reflected in the similarity of the determined parameters compared to those of Christensen et al. (1970). In this 178 study, values of ?G//°(298.15) = 17.05 ± 2.57 kj mol1 and A¿"(298.15) = -13.82 ± 2.08 J K1 were determined, versus ?G?°(298.15) = 16.36 ± 0.08 kj mol1 and ?G5°(298.15) = -12.22 ± 0.25 J K1 (Christensen et al, 1970). The two parameter density model represented the data well at low and high temperatures, because ?G?°(298.15) is used as an additional fitting parameter rather than a fixed value. Overall, the one parameter model with ?G?° (298.15) and log Ka (298.15) taken from Christensen et al. (1970) provides the best fit and remains consistent with previous work. 4.2 The Kinetics of Adenosine Thermal Decomposition Under Hydrothermal Conditions It is our goal in this section to determine if the decomposition of adenosine occurs by different pathways in acidic, buffered, and neutral solutions and to assess whether different reaction products are obtained from formic acid/sodium formate and phosphoric acid/dihydrogen phosphate buffers, respectively. Two different reaction systems involving adenosine were analyzed. First, the decomposition of adenosine in solutions of hydrochloric acid, sodium chloride, and 10:1 and 1:1 formic acid/formate and phosphoric acid/dihydrogen phosphate buffers identical to those prepared for equilibrium constant determinations were studied. Second, the reaction(s) between adenosine and buffer solutions of H2PO4" /H3PO4 in ratios of 10:1, 1:1, and 1:10 with total phosphate concentrations of 0.2 mol kg"1 were studied. 179 Solutions were degassed and injected in an analogous fashion to the equilibrium measurements. Once a stable, well defined peak was achieved, flow to the reaction cell was stopped while simultaneously sealing it off to maintain pressure in the cell. The process of stopping flow to the cell caused a small temperature increase, which stabilized within the first 2 minutes. Each reaction was allowed to proceed for thirty minutes, with each spectrum taken exactly one minute apart between 200 nm < ? < 600 nm. The spectra took 40 seconds to collect with a 20 second delay between each spectrum. This broader range of wavelengths was chosen to ensure that no information was lost as spectra evolved and Àmax changed over time. Solutions were degassed by suction, as previously mentioned. The effects of dissolved gasses in solutions were assessed by comparing two experiments. In the first experiment, an adenosine-phosphate buffer solution was degassed and injected as usual, and a stopped flow experiment was conducted for 30 minutes. In the second experiment, the same solution was injected directly into the system without degassing, and allowed to react for 30 minutes. Adenosine was found to decompose more quickly in the solution containing dissolved gasses, with fewer stable coloured reaction products. This experiment is shown in Appendix G. Adenosine is known to decompose with UV light. To determine the effects of light on our adenosine solutions, two experiments were compared. First, a stopped flow experiment of a phosphate buffered adenosine solution was conducted at 2000C, and spectra were taken every 40 seconds for 30 minutes. Second, a stopped experiment with the same solution at the same temperature was conducted, but 180 only one spectrum was obtained after 30 minutes of reaction time. The absorbance at Amax was observed to change by less than 0.05, which is slightly greater than the expected difference based on timing errors between the two experiments and temperature fluctuations of the system. The results of this experiment are shown in Appendix H. 4.2.1 Decomposition Kinetics of Aqueous Adenosine Solutions from 150 to 2500C The results of the decomposition of adenosine in solutions of sodium chloride, hydrochloric acid/sodium chloride, and formic acid/formate buffers at 225 0C and 95 bar are shown in Figures 4.4 to 4.7. As previously mentioned, thermal decomposition experiments yield a complex set of time-dependent data. However, these data can still be represented by Beer's law: A = ECb (4.27) where A is a matrix of i ? j absorbances, e is a matrix of j ? k molar extinction coefficients, and c is a matrix of k ? j concentrations of each species over time for i wavelengths, j solutions and k aqueous species. 181 230 250 270 290 310 330 350 370 A/(nm) Figure 4.4: Time evolved decomposition spectra for adenosine in 0.1 mol kg1 HCl and 0.1 mol kg1 NaCl at 225 0C and 95 bar. The initial [—), maximum absorbing (t=2 minutes) ( ), and final (—) spectra are noted. 182 0.4 H 0.2 -\ 235 255 275 295 315 335 \/(nm) Figure 4.5: Time evolved decomposition spectra for adenosine in a 1 to 1 buffer solution of sodium formate/ formic acid with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The initial (---}, maximum absorbing intermediate at t=7 minutes (·-¦-) and final (—) spectra are noted. Spectra were collected every minute, but only one every three minutes is shown to simplify the figure. 183 235 255 A/(nm) Figure 4.6: Time evolved decomposition spectra for adenosine in a 10 to 1 buffer solution of sodium formate/ formic acid with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The initial (---) and final (—) spectra are noted. 184 1.4 0.8 I i h E?? 0.6 260 270 280 290 300 0.4 0.2 230 250 270 290 310 330 350 370 390 ?/nm Figure 4.7: Time evolved decomposition spectra for adenosine in 0.2 mol kg1 NaCl at 225 0C and 95 bar. The initial (---) and final [—) spectra are noted. The inset indicates an isobestic point at ? = 283 nm which occurs in the first eight minutes of the reaction. 185 Factor analysis methods can resolve this matrix into its corresponding eigenvectors and eigenvalues, which represent the orthonormal factors and their loadings, respectively. There are several different methods for factor analysis; however, singular value decomposition (SVD) will be used here because of its robustness and stability (Cox and Seward, 2007a). The series of eigenvectors and eigenvalues can be described by: A = USVT (4.28) where U is the basis spectra of A whose significance is indicated by the square of the non-negative diagonal entries of S. The number of significant absorbing species relative to the amount of noise in experimental data can then be determined by visually examining these matrices. SVD analysis will account for all significant factors affecting the spectrum, including window etching, pH changes, and temperature fluctuations, so care must be taken when considering which factors are significant. Our kinetic analysis of each set of solution spectra was conducted using SpecFit/32 analysis software (Spectrum Software Associates). SpecFit/32 conducts SVD analyses, reports the Factor Indication Function, and produces plots of U and S. For acidic, formic acid buffered, and neutral solutions, the wavelength regions of 250 nm > ? < 310 nm , 240 nm > ? < 290 nm, and 240 nm > ? < 290 nm were selected for analysis. The number of significant factors determined from this analysis was used as a general guideline for the maximum amount of absorbing species present in the solution. There is a upper limit cut-off to the number of 186 significant factors that the Factor IND function will return. It can be user selected between 2 and 14, however, the default cut off of 10 was used for all analyses. When flow to the UV-visible cell was stopped, an initial temperature increase of approximately 0.5-1 0C was observed. Equilibrium was quickly re-established within roughly 3 minutes, however, this may have appeared as a factor in the SVD analysis, particularly at higher temperatures when the temperature rise was more pronounced. The most important factors affecting the spectra result from the decrease in absorbance of adenosine as it decomposes and the creation of coloured intermediates whose spectra overlap with adenosine. To crudely resolve the intermediate products from the original adenosine spectra, the decomposition spectrum at time j, A¡[h~), was normalized with the ratio of the maximum absorbance at time zero, A0(kmax), over the maximum absorbance of the spectrum at time j, ^j(Amax). The spectrum at time zero, A0, was then subtracted from the normalized spectrum, giving the residual spectra: AAUi) = [A0 OU* )/Aj (Amax )}A}- (A1) - A0 (X1) (4.29] The residual spectra are plotted in Figures 4.8 to 4.11. 187 0.5 0.3 0.2 \ \ 0.1 N V. \ 0 0.1 265 285 305 325 345 365 ?/nm Figure 4.8: Residual difference decomposition spectra for adenosine in a solution of 0.1 mol kg-1 HCl and 0.1 mol kg1 NaCl at 225 0C and 95 bar. The t=l minute (™), intermediate at t=13 minutes (·-·-) and final (—) spectra are noted. The spectra were normalized at 265 nm. 188 0.34 H 0.29 0.24 0.19 0.14 0.09 0.04 / y "«« 0.01 260 270 280 290 300 310 320 330 340 350 ?/nm Figure 4.9: Residual difference decomposition spectra for adenosine in a 1 to 1 buffer solution of sodium formate/formic acid with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The t=l minute (—), intermediate at t=7 minutes ( ) and final (—) spectra are noted. The spectra were normalized at 260 nm. 189 0.11 0.09 0.07 0.05 0.03 0.01 V 0.01 260 280 300 320 340 360 380 ?/nm Figure 4.10: Residual difference decomposition spectra for adenosine in a 10 to 1 buffer solution of sodium formate/formic acid with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The t=l minute (---), intermediate at t=14 minutes ( ) and final [—) spectra are noted. The spectra were normalized at 260 nm. 190 0.09 0.07 0.05 0.03 0.01 W\ ?**- 0.01 260 280 300 320 340 360 380 400 ?/nm Figure 4.11: Residual difference decomposition spectra for adenosine in a solution of 0.2 mol kg1 NaCl at 225 0C and 95 bar. The t=l minute (—) and final (—) spectra are noted. The spectra were normalized at 260 nm. 191 There are several steps to analyze decomposition results. First, using SVD analysis of the decomposition spectra, the maximum number of significant factors contributing to a set of spectra was determined. Then, bearing in mind the maximum number of factors, visual inspection of residual spectra was used to estimate the number of possible UV-absorbing species. With an estimate of the number of absorbing species, different kinetic reaction models were then fitted to the spectra by a least squares regression analysis using Specfit/32®. Multiple models were analyzed and compared to assess which best fit the spectra at all temperatures, based on the standard deviation of the model fits and the calculated rate constants. From these analyses, the following reaction model is proposed for protonated, formic acid buffered, and neutral adenosine: A -> Produce (UV abs) + Product2 (UV abs) (4.30) Produce (UV abs) -> Product^ (UV abs) [4.3 1) and the formation of Products is given by: d(Product3)/dt = k2(Product1) (4.32) where k\ and fa are the reaction rate constants for Equations 4.30 and 4.31. The reaction described by Equation 4.31 did not appear to take place below 225 0C for any of the reaction systems studied, most likely due to the stability of Producti at such temperatures. Product2 did not appear to form at the lowest temperatures studied. It should also be noted that the neutral adenosine solution at 250 0C appears to have produced a colourless decomposition product in the second reaction step. This is most likely an error from the fitting as a result of the rapid decomposition of adenosine at this temperature. It should also be noted that formic 192 acid and formate decompose above 200 0C (Bell étal, 1993], decreasing the stability of the solution's pH and increasing the rate of decomposition of adenosine. Reaction rate constants and half lives of adenosine for the proposed reactions are tabulated in Table 4.4. 193 Table 4.4: Summarized kinetic parameters for the decomposition of adenosine in acidic, buffered, and neutral solutions at 95 bar. Temperature „...., IND ^1 t1/2 (adenosine) Reaction System „, Reaction Model . C Function minutes minutes minutes 150 A->B 1.95xl0"2 ± 2.8x10 3 35.5 AH2 175 A->B 9.9IxIO"2 ± 6JxIO"3 7.0 (0.1 mol kg'1 NaCI, 200 A->B+C 4.66xl0'2 + 9XlO"4 14.9 0.1 mol kg'1 HCl) 225 A->B+C,B-*D 4.78X10"2 ± 2.1xl0"3 5.50 XlO"2 ± 1.9xl0"3 14.5 250 A->B+C,B-»D 0.474 ± 3.0x10 0.544 + 4.1x10 1.5 150 A4B 3.35X10"2 ± 7.8xl0"3 20.7 AH2 :AH (lHCOONa:l 200 A->B 1.72XlO'1 ± 7.72xl0'3 4.0 HCOOH, 0.2 mol kg"1 total HCOOH) 225 A->B+C 1.39 ± 0.43 0.5 AH2 :AH 175 A->B 6.92xl0"3 ± 1.2xl0"2 100 (10HCOONa:l 200 A->B 5.42X10"2 ± 4.6xl0"3 12.8 HCOOH, 0.2 mol kg"1 total HCOOH) 225 A>B+C,B->E* 0.281 ± 4.4xl0"2 2.36xl0'2 ± 7.69xl0"3 2.47 150 A4B 2.28xl0"2 ± 2.7xl0"3 30.4 175 A->B+C 6.6IxIO"2 ± l.lxlO"3 10.5 AH 200 A-»B+C 4.66X10"2 ± 9x10^ 14.9 (0.2 mol kg"1 NaCI) 225 A-»B+C 0.144 ± 6x10 4.81 250 A->B+C, B->E* 1.93 ± 0.39 1.39xl0"2 ± 1.7xl0"3 0.360 non-UV absorbing reaction product. 194 4.2.2 Adenosine and Phosphate Reactions from 150 to 225 0C Analysis of the phosphate reactions was analogous to those of the formic acid buffered adenosine solutions. Solutions of adenosine in three phosphate buffers with H2PO4-/H3PO4 ratios of 10, 1, and 0.1 were allowed to decompose for 30 minutes, with spectra being taken every minute. Time evolved reaction spectra taken at 225 0C are shown in Figures 4.12 to 4.14. Residual spectra were determined from Equation 4.26, and are shown in Figures 4.15 to 4.17. Kinetic analysis of spectra using Specfit showed that 1:10 and 1:1 H2PO4" /H3PO4 buffer solutions decomposed by the same reaction steps as those in the formate/formic acid buffer solutions described above. This was confirmed by visual inspection of residual spectra. Decomposition spectra for the 10:1 H2PO4/H3PO4 buffer could not be modelled by these reaction steps, and residual spectra confirmed that additional coloured products appeared to be forming. For the decomposition studies of buffered solutions of adenosine, the reaction scenario is given by: (AH+: A) -» Product4 (W abs) + Product5(UV abs) + Product^ UV abs) [4.33] Product4(UV abs) -* Product7(UV abs) [4.34] Equations 4.33 and 4.34 have reaction rate constants &? and K 2. The rate of formation of Product? is analogous to that in Equation 4.29. Although the reaction products for these equations have been numbered differently for clarity, it is believed that there are common products to both reaction systems. Reaction rate constants and half lives of adenosine under these conditions are tabulated in Table 4.5. 195 230 280 330 380 ?/tnm) Figure 4.12: Time evolved reaction spectra for adenosine in a 10 to 1 buffer solution of H2PO4-/H3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The initial (---), intermediate ( ) and final (—] spectra are noted, and only one of every three spectra after the intermediate maxima are plotted for clarity. The inset indicates an isobestic point at ? = 290 nm which occurs in the first eight minutes of the reaction. 196 1.8 m < 0.8 265 285 305 325 345 0.6 0.2 0 230 250 270 290 310 330 350 370 X/(nm) Figure 4.13: Time evolved reaction spectra for adenosine in a 1 to 1 buffer solution of H2PO4-/H3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The initial (---), intermediate ( ) and final (—) spectra are noted. The inset indicates an isobestic point at ? =287 nm which occurs in the first seven minutes of the reaction. 197 230 250 270 290 310 330 350 370 \/{nm) Figure 4.14: Time evolved reaction spectra for adenosine in a 1 to 10 buffer solution OfH2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The initial (—), intermediate maximum ( ) and final (—) spectra are noted. 198 0.25 0.15 \ \ \ 0.05 \ \ ^s. 0 263 283 303 323 343 363 383 403 ?/nm Figure 4.15: Residual difference reaction spectra for adenosine in a 10 to 1 buffer solution OfH2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The t=l minute (—], intermediate at t=4 minutes ( ) and final (— ) spectra are noted. The spectra at t=2 and 3 minutes are dashed for clarity. The spectra were normalized at 260 nm. 199 0.45 0.35 0.25 / 0.15 N \ \ SSSgKSSsS / \ 0.05 -0.05 4 1 ¦ 1 1 ' ' 263 283 303 323 343 363 ?/nm Figure 4.16: Residual difference reaction spectra for adenosine in a 1:1 buffer solution of H2PO4-/H3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The t=l minute (---], intermediate att=ll minutes ( ) and final {—) spectra are noted. The spectra were normalized at 263 nm. 200 0.S5 0.4S 0.35 d 0.25 0.15 y 0.05 0.05 266 286 306 326 346 366 ?/nm Figure 4.17: Residual difference reaction spectra for adenosine in a 1 to 10 buffer solution OfH2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 225 0C and 95 bar. The t=l minute (—), intermediate att=12 minutes ( ) and final (—) spectra are noted. The spectra were normalized at 266 nm. 201 Table 4.5: Summarized kinetic results from adenosine reactions in sodium dihydrogen phosphate and phosphoric acid buffer solutions at 95 bar. Reaction System Temperature Reaction„„.„__ Model„_.,„, „ IND Ic1 , k2 , t1/2 (adenosine) C Function minutes minutes'1 minutes 150 A->B 3.68xl0"2 ± 8.9xl0"3 18.9 AH2 :AH (1 NaH2PO4IO 175 A->B 4.58xl0"2 ± 2.2xl0"3 15.1 H3PO4, 0.2 mol kg"1 200 A->B 0.300 ± 5.7x10"' 2.31 total phosphate) 225 A->B+C, B->D 0.152 ± 9x10" 0.138 ± 7x10" 4.55 150 A->B 0.124 + 1.5x10"' 5.57 AH2 :AH (1 NaH2PO4I 200 A->B 0.335± 3.4x10 2.07 H3PO4, 0.2 mol kg"1 total phosphate) 225 A->B+C, B->D 0.124 + 2.4x10"' 0.126 ±1.4x10 5.60 150 A->F+G 4.76xl0"2 ± 3.3xl0"3 14.6 AH2 :AH 175 A-»F+G+H 7.39X10'2 ± 1.4xl0"3 9.4 (10 NaH2PO4I H3PO4, 0.2 mol kg"1 200 A^F+G+H 0.289 ± 2.2x10•2 2.4 total phosphate) 225 A^F+G+H, F->J 9.24X10"2 ± 3.8xl0"3 1.02 ± 9x10 7.5 202 4.2.3 Discussion The SVD analysis provided by Specfit gave an unrealistically high number of factors for both reaction schemes, particularly above 2000C. SVD is a sensitive analysis technique, and is most likely detecting ? H effects, window etching, and other temperature effects in addition to legitimate chemical species. Analysis of multiple reaction schemes based on observed spectra and suggested decomposition products (Garrett and Mehta 1972 a,b) was necessary to determine which factors could actually be attributed to reaction products. Our analysis of reaction models was prone to additional errors at 2500C. Adenosine and its reaction products decomposed much more quickly at this temperature, resulting in fewer useful spectra for analysis, and a greater degree of noise in the results. For this reason, kinetic parameters determined at this temperature are suspect. Conversely, reactions occurring at 1500C were quite slow comparatively, producing only small amounts of coloured products and increasing fitting errors for reaction rate constants. The slight decomposition of adenosine with UV light during this timeframe, as shown in Appendix H, could have accounted for some of the behaviour observed at 1500C. Such fitting errors are believed to account for unusual values for rate constants, and, by extension, half lives at these extremes of temperature, rather than actual chemical behaviour. Our proposed reaction schemes are consistent with the previous observation that pH affects the solvolysis of adenosine; ie. the reaction rate decreases as alkalinity increases (Garrett and Mehta 1972a,b). Additionally, residual spectra were found to achieve stable maxima, particularly at and below 2000C. This 203 suggests that steady state reaction products are forming, which agrees well with the findings of Lemke and Seward [2006] who observed that adenosine forms a stable equilibrium with adenine and ribose at high temperatures. There is not a clear correlation between reaction rates in phosphate versus formic acid buffers. The slight differences observed could be the result of differences in solution pH as a result of differences in pKa value of the acids. Below 200 0C, adenosine appears to be more stable in the formic acid buffer. However, above 200 0C, the opposite is true. A two-pathway reaction mechanism for the solvolysis of adenosine has been reported (Garrett and Mehta 1972b), which is supported by our observations and kinetic analysis. This mechanism can be generally described by: NH2 NH2 NH2 NH2 /Ti °^NHTfS VVS H!"yS OH OH OH OH OH OH QH ¿H NH, - NH2 OO NH2V ^ *" Non-chromophoric products Figure 4.18: Reaction mechanism for the solvolysis of adenosine Adenine is a UV-active molecule with a Xmax between 260-280 nm, depending on pH. It has been suggested that adenine produces an additional coloured intermediate (Balodis, 2007), which could explain the second step in the first 204 proposed reaction system, shown in Equations 4.27 and 4.28. Regardless of mechanism and pH, triaminopyrimidine is typically produced from this hydrolysis reaction. The value of Àmax for 4,5,6 triaminopyrimidine has been found to shift with pH; Àmax = 265, 287, and 277 nm for pHs of -0.75, 3.77, and 7.98, respectively (Mason 1954). The spectral overlap of these chemical species with the spectrum of adenosine is consistent with the complex spectra observed. No reaction mechanisms for the 10:1 phosphate-buffered system could be discovered in literature. In light of this challenge, we attempted to determine the reaction products by experiment. Adenosine solutions used in the UV-visible experiments were very dilute, making 13C NMR of reaction products impossible. However, for the phosphate buffered solutions particularly, analysis by 31P NMR was conducted to determine if any appreciable changes in phosphate peaks could be observed, particularly for the 10:1 dihydrogen phosphate/phosphoric acid buffered solutions. Additionally, batch experiments were conducted with phosphate buffered solutions saturated with adenosine to perform 13C and 31P NMR in the hopes of identifying the same reaction products. NMR results are shown in Appendix I. Unfortunately, no significant changes in phosphate peaks were observed, and 13C NMR was largely unsuccessful, even with concentrated solutions. It is believed that at least one reaction intermediate or product involving phosphate may have been formed, but it was not stable under ambient conditions, and thus could not be isolated. 205 CHAPTER 5 CONCLUSIONS AND FUTURE WORK 5.1 Conclusions It was the goal of this study to extend upon the work of Balodis (2007) and provide additional research regarding the behaviour of nucleic acid components under hydrothermal conditions. This study marks the first successful attempt to determine volumetric properties and heat capacities of ionic nucleic acid bases and nucleosides up to 900C. Additionally, properties of neutral nucleosides measured at temperatures above 900C have never been published in literature, but their usefulness for high temperature predictive models cannot be overstated. Standard partial molar heat capacity measurements completed at 135 0C and standard partial molar volumes up to 200 0C were the first of their kind for neutral pyrimidine molecules. Differences in the ribose contributions to the standard partial molar properties of pyrimidine and purine nucleosides relative to their corresponding nucleic acid bases indicate that interactions between bases and the ribose group differ between the two families of compounds. From this observation, a functional group additivity model specific for purines was proposed. The standard partial molar volume of neutral guanine in water up to 90 0C cannot be measured directly due to solubility limitations, even with sensitive measurement techniques, so this functional group model provided the only means to estimate these data. The fitting parameters for the revised HKF previously determined by LaRowe and Helgeson (2006) were developed from extrapolations of data measured 206 at low temperatures only. We determined that the trends predicted, particularly at high temperatures, oppose the trends of experimental data. Incorporating the experimental values from this study into the work by LaRowe and Helgeson (2006) provides a better model to describe the behaviour of these systems, and will provide better predictive models for chemical reaction systems. This study also provides the first experimental values for the acid ionization constant of adenosine up to 175°C, and hydrolysis kinetics of adenosine up to 250 0C at various values of pH in buffered, protonated, and neutral solutions. Extending these experiments to other biomolecules in conjunction with mineral and ionic species will provide a more accurate picture of the chemical behaviour in hydrothermal vents on the early Earth. Kinetic studies confirmed previous observations that nucleosides decompose at high temperatures into stable concentrations of adenine and ribose (Garrett and Mehta, 1972a; Seward and Lemke, 2006). Phosphate-buffered and formic acid- buffered solutions appeared to go through different reaction pathways, the phosphate system producing additional stable intermediates. It has been observed that adenine-related species behave differently in phosphate solutions (White, 1984; Balodis, 2007). Batch reactions could not identify reaction products from the adenosine and phosphate systems; however, the appearance of additional intermediates suggests the possibility of a stable adenosine phosphate species at high temperatures. 207 5.2 Areas for Future Work Given the limited amount of research involving these molecules under hydrothermal conditions, there is a tremendous opportunity to develop future research projects. Extending the techniques outlined in this study to single nucleotides and oligonucleotides would improve upon existing knowledge and be very useful for modelling purposes. Volumes and heat capacities of negatively charged nucleic acid components, as well as nucleotides under acidic, neutral, and basic conditions should be determined, and, where possible, measurements at elevated temperatures should be conducted. Ionization constants for the remaining nucleic acid bases and nucleosides should also be determined. Developing HKF models for these species would be particularly useful in predicting reaction behaviour using the OLI software package, which can be used to model mineral interactions, solid-liquid behaviour, and other biological reactions involving amino acids. Modelling these reactions will help future researchers direct their studies and simplify other experimental work. The adenosine-phosphate study conducted here should be extended to include buffer solutions at all values of pH. Possible stable equilibriums and reaction products between phosphate species and nucleosides appear to exist, and determining the changes in the reaction mechanism as a function of pH will assist in determining when these equilibriums and products are most stable. The stability of adenosine in other buffered solutions at a full range of pH values should also be examined in order to compare mechanisms and assess changes in stability under varying conditions. 208 Hydrothermal spectroscopic methods such as FT-IR and Raman have been effective in studying other organic reactions. These techniques could be used to track reaction progress, and study interactions between biomolecules and minerals or other ions present in hydrothermal vents. Determining reaction products from kinetic studies proved to be challenging. Successful identification of reaction products can be used to confirm reaction mechanisms. The use of NMR, particularly 31P NMR, to monitor nucleotide hydrolysis and formation could be very promising. While 1H NMR could be useful in product identification, 13C NMR would be of limited use given the low solubility of these species. Development of in situ techniques for identifying reaction products with NMR at high temperatures would be important based on the observations made in this study. Chromatographic techniques and mass spectroscopy have also been used for similar studies to determine reaction products, and should be applied to future studies. 5.3 Engineering Applications Ionization constants and kinetic decomposition studies of adenosine are particularly interesting for engineering applications. Adenosine is a building block for DNA and RNA, and as such, the effects of temperature and pressure on this molecule has important implications to high temperature genetic engineering studies, and the study and use of extremophiles that live under such harsh conditions. Genetic engineering of plants to produce modified amino acids and other chemicals that enable them to withstand elevated temperatures, allowing 209 them to germinate in harsher environments (Alia et al, 1998; Yang et al, 2005). Extremophiles particularly acclimated to high temperatures and acidic conditions are often resistant to heavy metals, such as those found in hydrothermal vents, and are particularly useful in the digestion of minerals (Demirjian et al, 2001). For instance, genetically modified Deinococcus geothermalis has been used for in situ bioremediation of mixed radioactive material at elevated temperatures (Brim et al, 2003). 'Extremozymes' can be produced directly from extremophiles, minimizing contamination from other chemical sources, and maximizing specificity of final products. Thermophiles have been successfully cultivated using membrane bioreactors and protein products such as enzymes have been subsequently harvested for industrial use (Aguilar et al, 1998; Schiraldi et al, 1999). Thermophiles have unusually stable DNA and proteins that allow them to survive under hostile conditions, and understanding the reasons for this stability will make it easier to modify and exploit these organisms. Recently, DNA has been used as a self-assembling backbone for various two and three dimensional structural nanomaterials and electronic microcircuitry (Douglas et ah 2009; Kershner et al. 2009; Li étal, 1996; Winfree étal, 1998) As these technologies develop, studies will focus on a wider range of temperatures, necessitating modelling software and an understanding of how these molecules function under a range of conditions. 210 CHAPTER 6 BIBLIOGRAPHY Aguilar ?., Ingemansson T., and Magnien E., 1998. Extremophile microorganisms as cell factories: support from the European Union. Extremophiles, 2, 367-373. Albert H.J. and Wood R.H., 1984. High precision flow densimeter for fluids at high temperatures to 700 K and pressures to 40 MPa. Rev. Sei. Instrum., 55, 589-593. 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Chem., 71, 1285-1290. 222 CHAPTER 7 APPENDICES Table A.1: Apparent molar volumes, V 223 t P 1000·(?-?*) ?F,2 0C MPa mol'kg" g*cm"3 Cm3^mOl"1 64.995 0.10 0.01672 0.618 75.8 ±0.2 64.999 0.10 0.01746 0.639 76.2 ±0.2 64.999 0.10 0.02579 0.953 75.8 ±0.2 69.997 0.10 0.01672 0.616 76.0 ±0.1 69.999 0.10 0.01746 0.637 76.4 ±0.1 69.999 0.10 0.02579 0.948 76.1 ±0.1 75.001 0.10 0.01672 0.611 76.5 ±0.1 74.998 0.10 0.01746 0.636 76.6 ±0.1 74.999 0.10 0.02579 0.944 76.4 ±0.1 79.999 0.10 0.01672 0.603 77.1 ±0.2 79.999 0.10 0.01746 0.624 77.4 ±0.2 79.999 0.10 0.02579 0.938 76.7 ±0.2 84.999 0.10 0.01672 0.602 77.3 ±0.1 85.000 0.10 0.01746 0.628 77.3 ±0.1 85.001 0.10 0.02579 0.925 77.4 ±0.1 90.003 0.10 0.01672 0.597 77.7 ±0.2 90.003 0.10 0.01746 0.625 77.7 ±0.2 90.003 0.10 0.02579 0.912 78.1 ±0.2 Cytosine 14.999 0.10 0.04256 1.527 75.15 ±0.16) 14.996 0.10 0.04290 1.577 74.27 ±0.16) 20.001 0.10 0.04256 1.502 75.77 ±0.15) 20.000 0.10 0.04290 1.549 74.95 ±0.15) 25.001 0.10 0.04256 1.480 76.34 ±0.15) 25.000 0.10 0.04290 1.524 75.57 ±0.15) 30.001 0.10 0.04256 1.461 76.84 ±0.13) 29.999 0.10 0.04290 1.498 76.25 ±0.13) 35.000 0.10 0.04256 1.440 77.41 ±0.26) 34.999 0.10 0.04290 1.487 76.57 ±0.26) 39.999 0.10 0.04256 1.429 77.74 ±0.10) 39.999 0.10 0.04290 1.444 77.66 ±0.10) 45.001 0.10 0.04256 1.407 78.37 ±0.15) 45.001 0.10 0.04290 1.428 78.15 ±0.15) 50.000 0.10 0.04256 1.397 78.70 ±0.14) 50.001 0.10 0.04290 1.413 78.58 ±0.14) 55.001 0.10 0.04256 1.380 79.23 ±0.12) 55.000 0.10 0.04290 1.407 78.85 ±0.12) 60.001 0.10 0.04256 1.364 79.73 ±0.10) 59.998 0.10 0.04290 1.393 79.30 ±0.10) 65.002 0.10 0.04256 1.355 80.09 ±0.15) 64.999 0.10 0.04290 1.377 79.81 ±0.15) 70.001 0.10 0.04256 1.354 80.25 ±0.15) 70.000 0.10 0.04290 1.380 79.86 ±0.15) 75.001 0.10 0.04256 1.346 80.57 ±0.10) 74.999 0.10 0.04290 1.382 79.97 ±0.10) 80.001 0.10 0.04256 1.336 80.97 ±0.10) 79.999 0.10 0.04290 1.370 80.39 ±0.10) 85.002 0.10 0.04256 1.325 81.41 ±0.10) 84.999 0.10 0.04290 1.357 80.86 ±0.10) 90.002 0.10 0.04256 1.326 81.54 ±0.10) 90.002 0.10 0.04290 1.353 81.14 ±0.10) t ? m 1000·(?-?*) ?f>2 "C MPa mol'kg'1 g»cm'3 Cm3TnOl1 Thymine 15.000 0.10 0.020179 0.793 86.8 (±0.1) 20.000 0.10 0.020179 0.775 87.7 (±0.1) 25.001 0.10 0.020179 0.761 88.5 (±0.2) 29.999 0.10 0.020179 0.750 89.1 (±0.3) 34.999 0.10 0.020179 0.742 89.6 (±0.2) 39.999 0.10 0.020179 0.734 90.1 (±0.1) 45.000 0.10 0.020179 0.724 90.7 (±0.1) 50.002 0.10 0.020179 0.717 91.2 (±0.2) 54.999 0.10 0.020179 0.707 91.8 (±0.1) 59.999 0.10 0.020179 0.694 92.6 (±0.1) 64.999 0.10 0.020179 0.692 92.9 (±0.1) 69.999 0.10 0.020179 0.686 93.4 (±0.2) 74.999 0.10 0.020179 0.680 93.9 (±0.2) 80.000 0.10 0.020179 0.663 94.9 (±0.5) 85.000 0.10 0.020179 0.661 95.2 (±0.2) 90.002 0.10 0.020179 0.656 95.7 (±0.3) 225 Table A.2: Apparent molar volumes, V 226 t ? m 1000·(?-?*) ?f,2 °C MPa mol »kg1 g»cnï3 cm3»mol"1 85.001 0.10 0.08382 7.163 161.8 (±0.1) 85.000 0.10 0.1251 10.447 161.4 (±0.1) 90.002 0.10 0.08382 7.139 162.4 (±0.1) 90.003 0.10 0.1251 10.418 161.9 (±0.1) Cytidine 15.000 0.10 0.05871 5.289 152.4 (±0.1) 20.000 0.10 0.05871 5.235 153.4 (±0.1) 24.999 0.10 0.05871 5.191 154.2 (±0.1) 29.999 0.10 0.05871 5.152 155.0 (±0.1) 34.999 0.10 0.05871 5.109 155.8 (±0.1) 39.999 0.10 0.05871 5.079 156.5 (±0.1) 45.000 0.10 0.05871 5.048 157.1 (±0.1) 50.001 0.10 0.05871 5.021 157.8 (±0.1) 54.998 0.10 0.05871 4.985 158.6 (±0.1) 59.999 0.10 0.05871 4.961 159.2 (±0.1) 64.998 0.10 0.05871 4.941 159.7 (±0.2) 70.000 0.10 0.05871 4.920 160.3 (±0.2) 74.999 0.10 0.05871 4.902 160.8 (±0.1) 80.000 0.10 0.05871 4.879 161.5 (±0.2) 85.000 0.10 0.05871 4.867 161.9 (±0.1) 90.002 0.10 0.05871 4.859 162.3 (±0.1) Thymidine 14.999 0.10 0.080558 6.057 166.1 (±0.1) 19.999 0.10 0.080558 5.993 167.0 (±0.1) 24.999 0.10 0.080558 5.932 167.9 (±0.1) 29.998 0.10 0.080558 5.872 168.8 (±0.1) 34.997 0.10 0.080558 5.825 169.5 (±0.1) 39.999 0.10 0.080558 5.777 170.3 (±0.1) 45.000 0.10 0.080558 5.736 171.0 (±0.1) 50.001 0.10 0.080558 5.698 171.7 (±0.1) 55.000 0.10 0.080558 5.655 172.5 (±0.1) 59.999 0.10 0.080558 5.620 173.2 (±0.1) 64.998 0.10 0.080558 5.588 173.9 (±0.1) 69.999 0.10 0.080558 5.563 174.5 (±0.1) 74.999 0.10 0.080558 5.532 175.2 (±0.1) 80.000 0.10 0.080558 5.511 175.8 (±0.1) 85.001 0.10 0.080558 5.477 176.6 (±0.1) 90.002 0.10 0.080558 5.451 177.3 (±0.1) Guanosine 14.998 0.10 0.002026 0.220 175 (±1.0) 19.997 0.10 0.002026 0.218 176 (±1.0) 24.997 0.10 0.002026 0.220 175 (±0.5) 29.998 0.10 0.002026 0.217 176 (±1.0) 34.996 0.10 0.002026 0.214 178 (±1.1) 39.998 0.10 0.002026 0.218 176 (±0.8) 44.998 0.10 0.002026 0.215 178 (+1.4) 49.999 0.10 0.002026 0.216 177 (±1.7) 54.999 0.10 0.002026 0.210 181 (±0.8) 59.999 0.10 0.002026 0.211 180 (±0.5) 64.998 0.10 0.002026 0.207 182 (±1.0) 69.998 0.10 0.002026 0.207 183 (±1.0) 227 t ? m 1000·(?-?*) ?f,2 "C MPa mol'kg1 g«cm3 cm^mol1 74.998 0.10 0.002026 0.208 183 (±1.4) 80.000 0.10 0.002026 0.203 186 (±1.6) 84.999 0.10 0.002026 0.202 186 (±0.5) 90.003 0.10 0.002026 0.203 186 (±0.5) 228 Table A.3: Apparent molar volumes, ?f,2, of uridine, cytidine, and thymidine in water at elevated temperatures and pressures. t P 1000·(?-?*) ?F,2 °c MPa mol»kg" g'cm"3 cm^mol"1 Uridine t= (91.096 ± 0.049) 0C, ? = (1.212± 0.001) Mpa 91.157 1.211 0.09614 8.155 160 .6 (±0.8 91.023 1.212 0.1034 8.884 159 .4 (±0.8 91.109 1.214 0.1101 9.357 160 .2 (±1.1 t= (134.954 ± 0.045) 0C, ? = (2.102± 0.004) Mpa 134.843 2.100 0.09614 7.971 165 2 (±0.9 134.953 2.107 0.1034 8.494 166 0(±0.5 134.993 2.093 0.1034 8.534 165 6 (±0.6 134.978 2.103 0.1034 8.612 164 7 (±0.4 135.004 2.106 0.1101 8.992 166 4 (±0.5 t= (152.454 ± 0.018) 0C, ? = (3.762± 0.024) Mpa 152.471 3.725 0.09614 7.960 166 4 (±0.6 152.427 3.791 0.1034 8.298 169 4 (±0.6 152.464 3.769 0.1101 8.856 169 0(±0.6 t= (175.262 ± 0.051) 0C, ? = (4.046± 0.155) Mpa 175.284 4.163 0.09614 7.816 169 9 (±0.9 175.317 4.161 0.1101 8.829 171 1(±0.9 175.185 3.813 0.1034 8.405 170 0(±0.8 t= (196.997 ± 0.004) 0C, ? = (5.869± 0.037) MPa 197.003 5.815 0.09614 8.174 166 7 (±0.7 196.996 5.868 0.1101 8.912 171 8 (±0.7 196.994 5.924 0.1034 8.396 171 7 (±0.7 Cytidine t= (90.297 ± 0.013) 0C, ? = (1.397± 0.046) Mpa 90.286 1.340 0.05087 4.215 162.3 (± 1.2 90.310 1.373 0.05721 4.616 164.6 (± 1.3 90.281 1.441 0.05871 4.767 164.0 (± 1.2 90.313 1.477 0.06590 5.387 163.3 (± 1.2 t= (134.986 ± 0.005) °C, ? = (1.002± 0.011) Mpa 134.992 0.987 0.05087 4.173 165.9 (±0.5 134.979 1.002 0.05721 4.692 165.8 (±0.5 134.988 1.018 0.06590 5.362 166.4 (± 0.5 t= (152.347 ± 0.032) 0C, ? = (3.325± 0.048) Mpa 152.298 3.265 0.05087 4.099 168.7 (±0.5 152.371 3.314 0.05721 4.467 171.6 (±0.5 152.371 3.397 0.06590 5.336 168.0 (±0.5 t= (174.848 ± 0.194) °C, ? = (3.972± 0.129) Mpa 174.683 3.8729042 0.05721 4.878 168.1 (±0.5 174.722 3.8787415 0.05871 4.384 167.6 (±0.5 175.139 4.1653236 0.06590 5.438 166.5 (±0.6 Thymidine t= (90.963 ± 0.072) 0C, ? = (1.179+ 0.029) Mpa 90.856 1.136 0.07820 5.249 178.0 (±0.6 91.040 1.222 0.08031 5.584 175.3 (±0.5 90.994 1.182 0.08972 6.146 176.3 (±0.6 229 t ? m 1000·(?-?*) ?f,2 °C MPa mol'kg'1 g«cm3 cm^mol1 t= (134.992 ± 0.006) 0C, ? = (1.112± 0.049) Mpa 135.001 1.117 0.07820 5.156112965 183.1 (±0.4) 134.987 1.038 0.08031 5.099263583 185.9 (±0.4) 134.988 1.180 0.08972 5.612790169 186.9 (±0.4) t= (147.870 ± 0.007) 0C, ? = (3.770± 0.038) Mpa 147.872 3.713 0.07820 5.144 184.4 (±0.4) 147.878 3.827 0.08031 5.350 183.4 (±0.5) 147.859 3.770 0.08972 5.856 184.9 (±0.5) t= (175.198 ± 0.025) °C, ? = (3.979± 0.126) Mpa 175.183 3.859 0.07820 5.000 189.9 (±0.8) 175.235 3.910 0.08031 5.172 189.3 (±0.8) 175.176 4.168 0.08972 5.504 193.0 (±0.8) 230 Appendix B: Standard Partial Molar Volumes of Chloride Salts of Nucleic Acid Bases and Nucleosides The contributions of hydrochloric acid to the experimental apparent molar volume were obtained from Sharygin and Wood's regression parameters and the expression [1997): ?f = V° + {Av /b) In (l + OmV2) + 2RTm(Bv + mCv) (7.1) where: V = <7i + ßwp°(q2 + R3(TfT0) + q,(T/T°)2 + q5(.T/T°)3) (7.2) Bv = q6 + q7 ln(pw/p°) + q8(pw/p°) + q9(J'/T0) + q10(T/T°)2 + qn/Tx + qu/Tc (7.3) Cv = fe + qu(T/T°) + q15(T/T°)2 + ql6/Tc + dp/p°Kq17 + qw(T/T°) + ql9TT°2 +q20TC (7.4) and qi to q2o are fitting parameters, b= 1.2 kgV2 mol1/^ p° = ? MPa, T° = 1 K, p° = 1 kg m3, pw is the density of water at T, Tx= (T/T°)-227 and Tc= 647.13-(T/T°). Using Young's Rule as described in Section 1.5.5, the apparent molar heat capacity contributions by excess HCl were determined from the regression parameters of Patterson et al. (2001) using the following models: Cp°,2 = C0 + C1 In(T) + C2IT + cJT2 + C5T3 (7.5) C-?,f — £p,2 + Acmos + cBm + c9mT + c10m2 (7.6) where co to cio are fitting parameters and Ac is the Debye-Huckel limiting slope for heat capacities. 231 Table B.l: Apparent and standard partial molar volumes, ?f,2 and W, of nucleic acid bases in water and excess hydrochloric acid measured from 15 to 90 0C P t 1000*(p-p*) ?F, expt ?F,2 V2 °c MPa gem"3 cm3 mol"1 cm3 mol"1 cm3 mol"1 cm3 mol"1 AdenmeH+, m2 = 0.01072 molkg-1 m3= 0.0003848 molkg" 14.999 0.10 0.931 72.0 ±0.1 -6.3 (±0.1 91.5 ±0.3 91.3 20.001 0.10 0.921 72.4 ±0.1 -6.4 (±0.1 92.0 ±0.4 91.8 25.001 0.10 0.909 72.9 ±0.1 -6.5 (±0.1 92.6 ±0.2 92.4 29.999 0.10 0.898 73.3 ±0.1 -6.5 (±0.1 93.1 ±0.3 92.9 34.999 0.10 0.891 73.3 ±0.1 -6.5 (±0.1 93.1 ±0.2 92.9 40.000 0.10 0.882 73.5 ±0.1 -6.5 (±0.1 93.3 ±0.3 93.1 45.000 0.10 0.878 73.3 ±0.1 -6.5 (±0.1 93.1 ±0.3 92.8 50.000 0.10 0.875 72.9 ±0.1 -6.5 (±0.1 92.5 ±0.2 92.3 55.000 0.10 0.869 72.7 ±0.1 -6.5(±0.1 92.3 ±0.3 92.0 60.000 0.10 0.865 72.3 ±0.1 -6.5 (±0.1 91.8 ±0.4 91.6 65.001 0.10 0.857 72.2 ±0.1 -6.4(±0.1 91.8 ±0.3 91.5 70.001 0.10 0.866 70.8 ±0.2 -6.3 (±0.1 89.9 ±0.4 89.6 75.000 0.10 0.863 70.3 ±0.2 -6.3 (±0.1 89.3 ±0.4 89.0 79.999 0.10 0.858 69.8 ±0.3 -6.2 (±0.1 88.7 ±0.8 88.4 85.001 0.10 0.865 68.5 ±0.2 -6.1 (±0.1 87.1 ±0.6 86.7 90.002 0.10 0.870 67.3 ±0.3 -6.0 (±0.1 85.4 ±0.7 85.1 CytosineH+, m2 = 0.03203 mo kg 1 m3= 0.01834 molkg"1 14.999 0.10 2.491 57.98 ±0.06) -10.18 (±0.12) 81.01 ±0.28) 80.68 20.000 0.10 2.460 58.41 ±0.07) -10.31 (±0.12) 81.55 ±0.30) 81.21 25.000 0.10 2.436 58.65 ±0.05) -10.41 (±0.12) 81.84 ±0.25) 81.47 30.000 0.10 2.416 58.76 ±0.06) -10.48 (±0.12) 81.94 ±0.27) 81.56 34.999 0.10 2.394 58.85 ±0.05) -10.52 (±0.12) 82.03 ±0.25) 81.63 39.999 0.10 2.380 58.77 ±0.05) -10.55 (±0.12) 81.88 ±0.25) 81.46 45.000 0.10 2.372 58.52 ±0.06) -10.55 (±0.12) 81.49 ±0.27) 81.05 49.998 0.10 2.359 58.35 ±0.08) -10.52 (±0.12) 81.24 ±0.32) 80.77 55.000 0.10 2.350 58.03 ±0.12) -10.48 (±0.12) 80.79 ±0.40) 80.29 59.999 0.10 2.346 57.61 ±0.05) -10.42 (±0.12) 80.18 ±0.24) 79.66 64.999 0.10 2.337 57.25 ±0.08) -10.35 (±0.12) 79.69 ±0.32) 79.14 70.001 0.10 2.343 56.55 ±0.06) -10.25 (±0.12) 78.69 ±0.28) 78.11 75.001 0.10 2.355 55.70 ±0.11) -10.13 (±0.12) 77.47 ±0.38) 76.85 79.999 0.10 2.346 55.26 ±0.11) -10.00 (±0.12) 76.90 ±0.37) 76.25 85.003 0.10 2.354 54.43 ±0.10) -9.85 (±0.12) 75.75 ±0.36) 75.06 90.003 0.10 2.345 53.77 ±0.12) -9.68 (±0.12) 74.89 ±0.39) 74.16 232 Table B.2: Apparent and standard partial molar volumes, ?f,2 and Vi, of nucleosides in water and excess hydrochloric acid measured from 15 to 90 °C t 1000*(p-p*) V(J), expt "FsV4,, 3 V,F- 2 V2 0C MPa gem"3 cm3 mol1 cm3 mol"1 cm3 mol"1 cm3 mol"1 Adenos¡neH+, m2 = 0.02030 molkg"1 m3= 0.003086 molkg"1 15.002 ' 0.10 ' 2.758 151.1 ±0.3 -2.7 (±0.1 171.4 (±0.5 20.000 " 0.10 ' 2.723 152.2 ±0.1 -2.7 (±0.1 172.6 (±0.4 24.999 ' 0.10 " 2.698 152.7 ±0.1 -2.8 (±0.1 173.1 (±0.3 29.999 " 0.10 ' 2.681 152.7 ±0.2 -2.8 (±0.1 173.1 (±0.4 34.999 ' 0.10 ' 2.662 152.7 ±0.2 -2.8 (±0.1 173.1 (±0.4 39.999 " 0.10 " 2.645 152.5 ±0.1 -2.8 (±0.1 172.9 (±0.3 44.999 " 0.10 ' 2.636 151.9 ±0.2 -2.8 (±0.1 172.2 (±0.4 49.999 ' 0.10 r 2.622 151.4 ±0.1 -2.8 (±0.1 171.7 (±0.2 54.999 " 0.10 " 2.615 150.6 ±0.2 -2.8 (±0.1 170.7 (±0.4 59.999 " 0.10 " 2.606 149.7 ±0.2 -2.7 (±0.1 169.7 (±0.4 64.999 ' 0.10 " 2.596 148.8 ±0.2 -2.7 (±0.1 168.7 (±0.5 69.998 ' 0.10 ' 2.593 147.5 ±0.2 -2.7 (±0.1 167.2 (±0.5 74.999 " 0.10 ' 2.589 146.2 ±0.2 -2.7 (±0.1 165.8 (±0.3 79.999 " 0.10 2.580 145.1 ±0.2 -2.6 (±0.1 164.5 (±0.4 85.000 0.10 2.572 143.8 ±0.2 -2.6 (±0.1 163.1 (±0.4 90.002 0.10 2.577 141.9 ±0.2 -2.5 (±0.1 161.0 (±0.4 GuanosineH+, m2 = 0.001949 molkg"1 m3= 0.0006274 molkg"1 15.002 0.10 0.298 134.9 ±0.5 -5.6 (±0.12) 172.5 (±1.3 20.002 0.10 0.290 137.3 ±0.3 -5.7 (±0.12) 175.6 (±0.8 25.003 0.10 0.292 136.2 ±1.0 -5.7 (±0.12) 174.2 (±2.2 30.000 0.10 0.290 136.4 ±0.8 -5.8 (±0.12) 174.4 (±1.9 35.001 0.10 0.294 134.1 ±1.1 -5.8 (±0.12) 171.2 (±2.5 40.002 0.10 0.290 134.5 ±1.0 -5.8 (±0.12) 171.8 (±2.2 45.002 0.10 0.289 133.9 ±1.0 -5.8 (±0.12) 171.0 (±2.3 50.002 0.10 0.286 134.1 ±1.1 -5.8 (±0.12) 171.4 (±2.4 55.002 0.10 0.275 137.6 ±1.1 -5.7 (±0.12) 176.0 (±2.5 60.002 0.10 0.279 134.8 ±1.0 -5.7 (±0.12) 172.3 (±2.3 65.002 0.10 0.280 132.9 ±1.1 -5.7 (±0.12) 169.8 (±2.5 70.003 0.10 0.281 131.2 ±0.5 -5.6 (±0.12) 167.7 (±1.1 75.003 0.10 0.273 133.3 ±0.9 -5.5 (±0.12) 170.5 (±2.1 80.001 0.10 0.279 129.2 ±1.0 -5.4 (±0.12) 165.2 (±2.3 85.000 0.10 0.284 125.4 ±1.9 -5.3 (±0.12) 160.3 (±4.2 90.003 0.10 0.294 119.7 ±0.7 -5.2 (±0.12) 152.9 (±1.6 233 t P 1000*(p-p*) Vf, expt -F3V4^3 ?F,2 V2 0C MPa gem"3 cm3 mol"1 cm3 mol"1 cm3 mol"1 cm3 mol"1 Cytid¡neH+, m2 ; 0.04131 molkg"1 m3= 0.01904 molkg"1 15.002 0.10 5.423 82.76 (±0.04; -8.17 (±0.13 177.7 I ±0.2) 20.002 0.10 5.371 83.04 (±0.04; -8.28 (±0.13 178.11 ±0.2) 24.999 0.10 5.340 83.06 (±0.04; -8.36 (±0.13 177.9 1 ±0.2) 30.002 0.10 5.303 83.08 (±0.04 -8.42 (±0.13 177.8 ? ±0.2) 35.003 0.10 5.287 82.85 (±0.04 -8.45 (±0.13 177.1 1 ±0.2) 40.002 0.10 5.254 82.74 (±0.04; -8.47 (±0.13 176.8 1 ±0.2) 45.001 0.10 5.231 82.47 (±0.04; -8.47 (±0.13 176.1 1 ±0.2) 50.002 0.10 5.212 82.14 (±0.04; -8.45 (±0.13 175.4 ±0.2) 55.003 0.10 5.201 81.68 (±0.04; -8.42 (±0.13 174.3 ±0.2) 60.003 0.10 5.186 81.23 (±0.04; -8.37 (±0.13 173.4 ±0.2) 65.000 0.10 5.177 80.68 (±0.04; -8.30 (±0.13 172.2 ±0.2) 70.001 0.10 5.182 79.96 (±0.04; -8.22 (±0.13 170.7 ;±0.2) 75.000 0.10 5.173 79.33 (±0.04 -8.13 (±0.13 169.5 ;±0.2) 80.004 0.10 5.180 78.51 (±0.04 -8.02 (±0.13 167.8 ;±o.2) 85.002 0.10 5.178 77.75 (±0.04 -7.90 (±0.13 166.3 ;±o.2) 90.000 0.10 5.195 76.76 (±0.04; -7.76 (±0.13 164.3 ;±o.2) 234 Table Cl: Apparent molar heat capacities, Cp, 235 t ? m Cp4>,2 0C MPa mol »kg' J K1TTiOl1 15.0 0.1267 0.02018 0.998470 209.7 (±1.8] 20.0 0.1267 0.02018 0.998545 225.1 (±2.2] 25.0 0.1267 0.02018 0.998605 237.5 (±2.3] 30.0 0.1267 0.02018 0.998640 244.7 (±3.1] 35.0 0.1267 0.02018 0.998674 251.6 (±3.0] 40.0 0.1267 0.02018 0.998703 257.6 (+2.8] 45.0 0.1267 0.02018 0.998732 263.8 (±2.6] 50.0 0.1267 0.02018 0.998756 268.8 (±2.4] 55.0 0.1267 0.02018 0.998784 274.8 (±2.2] 60.0 0.1267 0.02018 0.998810 280.2 (±2.2] 65.0 0.1267 0.02018 0.998827 284.0 (±2.3] 70.0 0.1267 0.02018 0.998843 287.6 (±2.2] 75.0 0.1267 0.02018 0.998861 291.5 (±2.2] 80.0 0.1267 0.02018 0.998884 296.5 (±2.2] 85.0 0.1267 0.02018 0.998891 298.3 (±2.0] 90.0 0.1267 0.02018 0.998901 300.8 (±2.1] 236 Table C.2: Apparent molar heat capacities, Cp, 237 t m P Cp,s/cP, -?f,2 0C MPa mol «kg-1 J K1TTIOl1 75.0 0.1267 0.05871 0.992748 494.4 (±0.5) 80.0 0.1267 0.05871 0.992826 500.6 (±0.6) 85.0 0.1267 0.05871 0.992883 505.3 (±0.5) 90.0 0.1267 0.05871 0.992933 509.4 (±0.8) 90.0 0.6029 0.05087 0.994163 534.0 (±30.9) 90.0 0.6029 0.05721 0.994376 550.9 (±29.3) 135.0 0.6029 0.05087 0.993672 560.6 (±31.3) 135.0 0.6029 0.05721 0.993723 563.6 (±29.0) Thym ¡dine 15.0 0.1267 0.08056 0.989037 433.3 (±1.1) 20.0 0.1267 0.08056 0.989343 449.1 (±1.2) 25.0 0.1267 0.08056 0.989624 463.6 (±1.2) 30.0 0.1267 0.08056 0.989860 475.9 (±1.0) 35.0 0.1267 0.08056 0.990065 486.7 (±1.0) 40.0 0.1267 0.08056 0.990252 496.5 (±0.9) 45.0 0.1267 0.08056 0.990426 505.8 (±1.0) 50.0 0.1267 0.08056 0.990585 514.3 (±1.0) 55.0 0.1267 0.08056 0.990741 522.8 (±1.0) 60.0 0.1267 0.08056 0.990876 530.2 (±1.0) 65.0 0.1267 0.08056 0.991002 537.3 (±1.1) 70.0 0.1267 0.08056 0.991114 543.6 (±1.0) 75.0 0.1267 0.08056 0.991226 550.0 (±1.1) 80.0 0.1267 0.08056 0.991321 555.6 (±1.1) 85.0 0.1267 0.08056 0.991427 561.8 (±1.1) 90.0 0.1267 0.08056 0.991512 563.7 (±1.1) 90.0 0.6029 0.07820 0.992675 617.1 (±24.2) 90.0 0.6029 0.08972 0.992521 643.6 (±26.2) 135.0 0.6029 0.07820 0.992980 660.3 (±21.1) 135.0 0.6029 0.08972 0.992885 688.2 (±23.3) 238 Table C.3: Apparent and standard partial molar heat capacities, Cp)(p and Cp,2°, of nucleic acid bases in excess hydrochloric acid measured from 15 to 90 0C. Apparent molar heat capacities of hydrochloric acid were taken from Patterson et. al (2001) with an error of 1.2 J K1 mol-1. t P ?-?f, expt -F3C3*-?f, 3 -?f, 2 ?,? 2 Cp,s/Cp,w 0C MPa J K"1 mol"1 J K"1 mol1 J K"1 mol"1 J K"1 mol"1 Aden¡neH+, m2 = 0.01072 mol kg"1 ITi3= 0.0003848 mol kg"1 15.0 0.127 0.997240 -225.9 (±1.3) -48.71 -258.3 (±1.3 -265.6 20.0 0.127 0.997159 -249.0 (±2.2) -46.12 -292.3 (±1.3 -299.9 25.0 0.127 0.997290 -211.3 (±2.9) -44.12 -243.1 (±1.3 -251.0 30.0 0.127 0.997567 -131.6 (±3.1) -42.62 -136.2 (±1.3 -144.5 35.0 0.127 0.997825 -57.35 (±2.66) -41.53 -36.41 (±1.3 -44.95 40.0 0.127 0.997976 -13.86 (±2.56) -40.80 21.97 (±1.3 13.13 45.0 0.127 0.998073 14.01 (±2.49) -40.36 59.40 (±1.3 50.28 50.0 0.127 0.998136 31.92 (±2.63) -40.16 83.54 (±1.3 74.12 55.0 0.127 0.998187 46.67 (±2.72) -40.18 103.6 (±1.3 93.86 60.0 0.127 0.998218 55.76 (±2.83) -40.36 116.1 (±1.3 106.1 65.0 0.127 0.998249 64.61 (±2.98) -40.69 128.5 (±1.3 118.1 70.0 0.127 0.998258 67.16 (±2.86) -41.15 132.4 (±1.3 121.6 75.0 0.127 0.998280 73.63 (±3.26) -41.72 141.8 (±1.3 130.6 80.0 0.127 0.998301 79.83 (±3.26) -42.40 150.9 (±1.3 139.2 85.0 0.127 0.998306 81.26 (±3.44) -43.18 153.6 (±1.3 141.4 90.0 0.127 0.998307 81.73 (±3.42) -44.05 155.1 (±1.3 142.4 Cytosinel-G, m2 = 0.03203 mol kg" 1ITi3= 0.01834 mol kg"1 15.0 0.127 0.993529 -91.87 (±1.90) -77.71 -66.78 (±3.00) -79.67 20.0 0.127 0.993584 -87.16 (±2.54) -73.57 -63.51 (±3.99) -77.00 25.0 0.127 0.993660 -80.73 (±2.80) -70.38 -56.60 (±4.40) -70.65 30.0 0.127 0.993767 -71.81 (±2.70) -67.97 -44.97 (±4.25) -59.55 35.0 0.127 0.993910 -59.84 (±2.28) -66.24 -27.87 (±3.58) -42.97 40.0 0.127 0.994049 -48.31 (±1.84) -65.07 -10.90 (±2.90) -26.52 45.0 0.127 0.994167 -38.42 (±1.63) -64.37 3.944 (±2.56) -12.19 50.0 0.127 0.994273 -29.59 (±1.33) -64.06 17.52 (±2.08) 0.854 55.0 0.127 0.994360 -22.32 (±1.17) -64.08 28.97 (±1.84) 11.75 60.0 0.127 0.994423 -17.08 (±0.96) -64.38 37.52 (±1.52) 19.70 65.0 0.127 0.994490 -11.53 (±0.82) -64.91 46.77 (±1.29) 28.31 70.0 0.127 0.994532 -8.03 (±0.82) -65.64 53.01 (±1.30) 33.86 75.0 0.127 0.994539 -7.463 (±0.787) -66.55 54.81 (±1.24) 34.93 80.0 0.127 0.994583 -3.801 (±0.743) -67.63 61.65 (±1.17) 40.97 85.0 0.127 0.994604 -1.969 (±0.727) -68.86 65.77 (±1.14) 44.23 90.0 0.127 0.994619 -0.7375 (±0.388) -70.26 69.10 (±1.08) 46.64 239 Table F.3: Apparent and standard partial molar heat capacities, Cp^ and Cp/, of nucleosides in excess hydrochloric acid measured from 15 to 90 0C. Apparent molar heat capacities of hydrochloric acid were taken from Patterson et. al (2001) with an error of 1.2 J K1 mol1. T Cp 240 Appendix D: 1H NMR Spectra of Nucleoside Decomposition Products from Density Measurements Figure D.7.1: 1H NMR of cytidine (a) before injection (b] after injection at 175°C (c) after injection at 2000C. Minimal decomposition was observed at 1750C, and additional decomposition was observed at 2000C. fai ibi ::10 V-. S .:: :¦:?. *':':¦:':' : 8. '! : * ¦?¦ 2 W JO JL -—*~?~· :»-f..j.;,. ^T"" '¦i&i 8;:;::V.::: ::;-:*:· -"3?.G'- ppw» 241 Figure D.2: 1H NMR of thymidine (a) before injection (b) after injection at 1500C (c) after injection at 175°C. Minimal decomposition was observed at 15O0C, and substantial decomposition was observed at 175°C. J Ji JLW KL PP" .JuJ. *_„...? .,A....~? UIVl 10 9 ppm 242 Figure D.3: 1H NMR of uridine (a) before injection (b) after injection at 2000C (c] after injection at 225°C. Minimal decomposition was observed at 200°C, and substantial decomposition was observed at PF 225°C. _____M J 10 3 ppm 243 Appendix E: Regression methods for ionization constants Linear regression of UV-visible flow spectra of buffered adenosine solutions was conducted using Equation 4.10, as previously discussed: AW = AAH},ex Wk + AAHiex (X)Dl where AAH+ ex (X), AAHex(X) and A(X) are the absorbances at wavelength ? of the acid extreme, base extreme, and buffered solution, respectively, D is the ratio of the molality of adenosine in the acid extreme to its molality in the base extreme, m*AH+ ex /mAH,ex· and tne ratio of k/l Sives tne adenosine buffer ratio. Linear regression of Equation 4.10 solves for the parameters k and 1, and then the ratio of k/1 can be used to determine the ionization constant. Regressions were conducted in a range of 240 nm < ? < 290 nm. To determine the best range for analysis, two criteria were examined. First, the errors on k and 1 were minimized, and any systems with large errors on either parameter were excluded from any subsequent averages and models. Second, for any given range of wavelengths, the difference between the model fit and the experimental spectra was plotted, as in Figure E. If the equation represents the data well, the difference plot will show random scatter without any tremendous deviations from zero, as in Figure E.(a]. Poorly fitted models, such as that in Figure E. (b), will show non-random trends, such as sinusoidal-like fluctuations, or large deviations from zero. Figure E. (b) was also regressed with a range of wavelengths that is 10 nm narrower, which is not ideal because it is only fitting a small data set. A larger data range induced even more scatter, and a smaller range increased the errors on the 244 regression parameters to greater than one hundred percent. Any spectra which behaved analogously to Figure E.(b) were rejected from further analyses. 0.003 «¦= -0.001 0.006 0.004 ¦0.006 ?/nm Figure E.3: Difference in fitted and experimental absorbances of adenosine solutions at 175 0C and 95 bar with formate/formic acid buffer ratios of (a) 0.799 and (b) 4.86. 245 Appendix F: Fitting parameters 'k' and T determined from Equation 4.14. t CHCOO" niAH2+/mAH error in k error in I °c /CHCOOH 10.80 0.1380 0.1489 0.0189 1.0785 0.0187 2.685 0.4692 0.3426 0.0106 0.7301 0.0104 1.103 1.153 0.4882 0.0069 0.4235 0.0068 25 0.8332 1.596 0.6713 0.0079 0.4205 0.0076 0.4977 2.308 0.7280 0.0086 0.3154 0.0084 0.2817 4.397 0.7429 0.0042 0.1689 0.0041 1.000 0.5546 0.3651 0.0028 0.6583 0.0027 0.7994 0.7205 0.4378 0.0039 0.6077 0.0039 50 0.5043 1.165 0.5670 0.0034 0.4869 0.0033 0.2508 2.460 0.7776 0.0055 0.3161 0.0054 0.1019 5.323 0.8863 0.0042 0.1665 0.0042 1.103 0.1697 0.1345 0.0061 0.7927 0.0063 0.8332 0.2250 0.2030 0.0082 0.9021 0.0084 100 0.4977 0.3931 0.2995 0.0027 0.7619 0.0028 0.2817 0.6668 0.3667 0.0026 0.5499 0.0027 0.1023 1.550 0.5909 0.0050 0.3811 0.0051 0.4977 0.0914 0.0870 0.0099 0.9520 0.0096 150 0.2817 0.1555 0.1211 0.0053 0.7788 0.0051 0.1023 0.3724 0.2631 0.0089 0.7066 0.0086 175 0.1019 0.1820 0.1613 0.0080 0.8864 0.0077 246 Appendix G: Effect of Degassing on Decomposition and Reaction Studies The importance of removing dissolved gasses from reaction solutions was assessed by comparing the 30 minute reaction spectra of the adenosine-phosphate reaction in a 10:1 buffer solution of H2PO4VH3PO4 at 200 0C. 310 330 ?/nm Figure G.l: Time evolved reaction spectra for adenosine in a 10 to 1 buffer solution of H2PO4VH3PO4 with a total ionic strength of 0.2 mol kg1 at 200 0C and 95 bar without the removal of dissolved gasses. The initial (---) and final (—) spectra are noted in black, and the final spectra from the same reaction solution with degassing [ ] is shown for comparison. The differences between the spectra at t=30 minutes for solutions with and without dissolved gasses is substantial. The value of Àmax and the absorption of at this wavelength are distinctly different, and there are fewer absorbing reaction products and a faster rate of decomposition of adenosine in the solution containing dissolved gases. 247 Appendix H: Analysis of Light-Related Decomposition Figure H.l: Spectra after 30 minute reactions of adenosine in a 10 to 1 buffer solution of H2PO4-/H3PO4 with a total ionic strength of 0.2 mol kg1 at 200 0C and 95 bar. One trial was measured by UV-visible spectroscopy for 40 seconds of every minute, and the final spectrum is shown [—), and the other was allowed to react for 30 minutes, and only one spectrum at the end of the reaction was taken ( ). 248 Appendix I: 31P NMR Spectra of Decomposition Products from UV-Visible Kinetic Measurements and Stopped Flow Experiments Figure 1.1: 31P NMR of Phosphoric Acid in D2O g o O ______JL T ¦ ——?—'— ! '—¦—'— I T——T~^-.—~-.—?—.— ——r——i——· G'' ' ¦·,··¦ 20 15 10 5 0 -5 -10 -15 -20 ppm 249 Figure 1.2: 31P NMR for adenosine in a 1 to 10 buffer OfH2PO4VH3PO4 at (a) 25°C and (b) 2000C Ca) —?———'——t—————ì——-"— r-"-· r~T~ 20 15 10 S 0 -5 -10 -15 -20 ppm (D) 1 ? *~ ——?—r 20 15 10 -10 -15 -20 ppm 250 Figure 1.3: 31P NMR for adenosine in a 1 to 1 buffer of H2PO4" /H3PO4 at [a] 25°C and (b) 2000C Ca) .....? 20 15 10 -10 -15 -20 ppm Cb) -^L. 20 15 10 -10 -15 -20 ppm 251 Figure 1.4: 31P NMR for adenosine in a 10 to 1 buffer of H2PO4" /H3PO4 at (a) 25°C and (b] 2000C (a) 20 15 10 -10 -15 -20 ppm Cb) 20 15 10 -10 -IS -20 ppm 252