Structural Analysis of Water and Alcohol Solutions

Structural analysis of water and alcohol solutions

A thesis submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Master of Science

in the Department of Materials Science

of the College of Engineering and Applied Science

Kelly J. Cross

B.S. Purdue University

May 2007

Committee Chair: Dale W. Schaefer, Ph.D.

Abstract

Water-alcohol solutions have been extensively studied to correlate molecular structure to thermodynamic properties, which are known to deviate strongly from ideality. This project offers an analysis of cluster formation in ethanol-water binary solutions and an approach to identify distinctive structures within water and alcohol (W-A) solutions.

Thermodynamic properties (such as enthalpy) and hydrogen bond strength can provide physical evidence of clustering within the solution. The heat of mixing was observed as a function of concentration. The concentration dependence of hydrogen bonding strength was analyzed through Infrared spectroscopy. Molecular aggregation in solution was explored experimentally with light scattering.

Some of the results were consistent with published data and some results did not support data in the current literature. The calorimetry data were consistent with the published data showing a minimum at ~20 mol%. In the water rich region, we assume the hydrogen-bonded water clusters isolate individual ethanol molecules. The frequency shift observed with IR spectroscopy shows that the C-O bond strength increases with increasing ethanol concentration. Similar to the observations of D’Angelo, the frequency shift of the C-O and C-H stretching is concentration-dependent and is attributed to the transfer of electron density from the carbon of the methyl group. The observed minimum

(17 mol%) in the H-OH bending absorption band frequency indicates an increase in hydrogen bond strength between water molecules in the water-rich region.

The light scattering analysis was complex and required multiple systems to draw conclusions from the results. Two systems, ethanol in water and butoxy-ethanol in water, were studied with light scattering to observe the Rayleigh ratio (RR). The RR is proportional to the scattered light intensity. The ethanol-in-water system did not show a peak in the plot of RR as a function of concentration. However, for the butoxy-ethanol system a maximum in the RR vs. concentration occurs at ~2.5 mol%, close to the 3 mol% reported by Ito. The average scattering intensity, however, was four times less than reported by Ito and Schmitz. The major finding of the research is that the cluster nature, which is intimately related to solution properties, changes with concentration.

The calorimetry and IR data suggest enhanced hydrogen bond strength of water in the water rich region that transitions to increased self association of ethanol in the alcohol rich region.

iii

Blank Page

Acknowledgements

First, I would like to thank The Creator and sustainer of all life. To my ancestors who paved the way for me including my father, Pastor Israel L. Cross II.

Next I would like to thank my mother for being my hero and my role model.

I am grateful for the support of my partner, my family, and my extended family.

Thank you Drs. Marie Paretti and Holly Matusovich for teaching me technical writing.

Thank you to Dr. Schaefer, Dr. Danni Wu, Dr. Naiping Hu, Dr. Stephen G. Fenimon, Dr. Carlos Co, Dr. Douglas Kohls and the Schaefer research group for their collective efforts.

Lastly, thank you to OVAL for the financial support of this research.

Hotep

Table of Contents Abstract ...... ii

Blank Page ...... iv

Acknowledgements ...... v

Table of Contents ...... vi

List of Tables and Figures ...... viii

Chapter 1: Introduction ...... 1

Motivation for Study ...... 1

Chapter 2: Calorimetry and Thermodynamics ...... 3

Chapter 2.1: Introduction ...... 3

Chapter 2.2: Experiment ...... 6

Chapter 2.3: Results and Discussion ...... 8

Chapter 2.4: Conclusions ...... 12

Chapter 3: FT-IR ...... 13

Chapter 3.1: Introduction ...... 13

Chapter 3.2: Experiment ...... 17

Materials ...... 17

Measurements ...... 17

Chapter 3.3: Results and Discussion ...... 19

Chapter 3.4: Conclusions ...... 24

Chapter 4: Light Scattering ...... 26

Chapter 4.1- Introduction/Motivation for Study ...... 26

Chapter 4.2: Experiment ...... 29

Materials ...... 29

Measurements ...... 29

Chapter 4.3: Results and Discussion ...... 32

Water-Ethanol (W-E) ...... 32

2-Butoxy-ethanol in water (BE) ...... 33

Chapter 4.4: Conclusions ...... 36

Chapter 5: Summary and Future Work...... 37

References ...... 39

Appendices...... 41

Appendix A: Calorimetry ...... 41

Calorimetry Procedure ...... 41

IR Spectroscopy Chapter ...... 42

1.3.2 Spectrum ...... 42

IR Summary Tables ...... 44

Light Scattering Chapter ...... 46

Appendix C: Static Light Scattering Procedure ...... 46

Appendix D: Dynamic Light Scattering Procedure...... 51

vii

List of Tables and Figures Figure 1: Schematic of the ChemiSens CPA200 calorimeter [10] ...... 8

Figure 2: Multiple peak-fitting example of EtOH added to water...... 10

Figure 3: Excess enthalpy of mixing (∆H) vs. EtOH mol fraction ...... 11

Figure 4: Complete IR spectrum 500-4000 (cm-1) ...... 16

Figure 5: Schematic of standard FT-IR spectrometer [7] ...... 18

Figure 6: –CH stretch region from 2965-3000 cm-1 ± 9 cm-1 ...... 19

Figure 7: –CH stretch vs. mol fraction compared to Mizuno ...... 20

Figure 8: –CO stretch from 950-1150 cm-1 ± 17 cm-1 ...... 21

Figure 9: FT-IR data: C-O stretch compared to Mizuno data [18] ...... 22

Figure 10: Refractive Index Increment for aqueous ethanol solutions ...... 30

Figure 11: RII of 2-butoxyethanol in water solution compared to Ito[30] ...... 31

Figure 12: ACF of X=20mol% ethanol at various scattering angles in water...... 32

Figure 13: 45 wt% butoxy-ethanol separated from water at 60°C [34] ...... 34

Figure 14: Various concentrations of BE-water solutions: RR vs. Angle at room temperature...... 34

Figure 15: BE-water solution average RR vs. concentration at RT ...... 35

Figure 16: BE-water solution average RR vs. concentration at elevated temperature, 44°C ...... 36

Figure 17: Power vs. Time compare to R∆T vs. Time ...... 41

viii

Chapter 1: Introduction

Motivation for Study Microscopic structural ordering in binary liquid mixtures is a fundamental problem in liquid state physical chemistry that requires understanding microscopic heterogeneities. Water-alcohol binary mixtures have been studied extensively to correlate solution structure with thermodynamic properties that deviate from ideal behavior. [1] Regular solution theory does not accurately describe highly associated solutions such as alcohol and water. Despite spectroscopic investigations to observe the local concentration fluctuations within these non-ideal solutions, scientific consensus has not been reached on the molecular origin of non-ideality. If “clathrate like” structures are the predominate structure of water-alcohol solutions, as suggested in this thesis, a number of observations from non ideal thermodynamics to taste perception in alcoholic beverages fall in to place.

In order to better understand the solution mixing tendencies, recent studies focus on the statistical behavior of the transient conformations observed in aqueous alcohol by spectroscopic techniques. This approach implies that the bulk solution thermodynamic properties are intimately related to the local molecular behavior. The focus of the study is the fundamental causes of structural rearrangement in the water hydrogen bond network induced by alcohol. The transient nature of water is apparent and the tetrahedral network of hydrogen bonds in water is generally accepted.

Therefore, the research question is: does the behavior of water change in the presence of alcohol and if so how? The objective of this thesis is to investigate the local structure formation in binary alcohol and water solutions.

Motivated by Mendeleev’s approach–observing inflections in physical properties– we plotted the density and excess volume versus mole fraction and weight percent.

Both properties show strong deviations from ideal solution behavior. For this study, the thermodynamics were explored through heat of mixing calculations based on calorimetry data. Next, Fourier transform-infrared spectroscopy (FT-IR) was chosen as an analytical technique to provide evidence of hydrogen bonding changes as a function of the alcohol concentration. Finally, the solutions were evaluated via light scattering to measure the concentration and temperature dependences of the concentration fluctuations.

An emerging route toward the development, testing, and refinement of molecular models of the hydrophobic interaction, hydration, and the physics of aqueous macromolecules involves the use of small molecule systems (i.e. low molecular weight alcohols) as prototypes. [2] The development of predictive models of thermodynamic properties associated with hydrogen bonding, however, remains a challenge. This challenge is of interest to engineers because water-alcohol solutions have a variety of applications from the food and beverage industry to a solvent medium for complex reactions or medicinal functions. Ethanol and ethanol–water are also used as co- solvents in supercritical fluid technology, natural refrigerants, and, in the recent past, as heat carriers for solar collectors.

Chapter 2: Calorimetry and Thermodynamics

Chapter 2.1: Introduction The temperature and composition dependence of various thermodynamic properties (i.e. heat of mixing, partial molar volume, density) were investigated to explain the effect of alcohols on the structure or restructuring of water. Water-ethanol solutions have been extensively studied because the pure components are good reference materials, readily available, nontoxic, and relatively insensitive to impurities.

In addition, ethanol is the solvent choice for a wide variety of applications. In water- alcohol mixtures the composition range consists of three regions referred to as water rich, transition, and alcohol rich.

The anomalous thermodynamic properties are believed to originate from structural changes. Large heat effects that accompany liquid mixing indicate that thermodynamic properties deviate from ideal solution behavior. The purpose of this calorimetry study was to observe the heat of mixing of water-ethanol solutions over the entire concentration range. The heat of mixing is the difference between the enthalpy of a mixture and the sum of the enthalpies of its components at the same pressure and temperature. In this study, enthalpy data will be evaluated to find experimental evidence of “incomplete mixing” or micro-heterogeneities.

Many other researchers have studied ethanol and water solutions at ambient temperature and pressure but strikingly variable results have been reported. For example, Dixit and Sato concluded that the ethanol molecules in mixtures are in almost the same environment as in pure ethanol. ([3], [4]) Others subscribe to a microscopic mixing description where, due to hydrophobic hydration, water becomes more ordered in the vicinity of a hydrophobic entity (alcohol). The local structure in aqueous alcohol

3 solutions is complex but two phenomena, hydrophobic hydration and self-association, have been consistent themes.

This thesis explores hydrophobic hydration and the self-association in different composition regions. Based on calorimetry and light scattering experiments, isolated ethanol (alcohol) molecules are hydrated in the water-rich region, which is referred to as hydrophobic hydration. Self-association is explored by IR experiments, which show that hydrogen bonding strength of ethanol increases in the alcohol-rich region. Although the notion of enhanced water structure has persisted in the models of the hydrophobic effect in aqueous alcohol, the first step in the analysis was to assure that the instruments accurately measure thermodynamic properties.

Ott et al. for example described the design and construction of an isothermal-flow calorimeter and established water-ethanol (W-E) solutions as a reference system to essentially calibrate calorimeters.[5] Ott and coworkers measured the heat of mixing for water–ethanol (W-E) solutions over the entire composition range at constant temperature and various pressures.[5] The data were fit using a least-squares method to calculate the heat of mixing based on simple rule of mixing and also as a function of pressure. The equations were a test of the reliability and consistency of the data that allowed the authors to compare other published results. Therefore, W-E solutions were confirmed to be a good reference system to calibrate calorimeters and the isothermal- flow design was shown to measure the heat of mixing accurately for liquid solutions.[5]

With an established reference systems and a proposed instrument other researchers such as Wormald could expand the understanding of the relationship between heat of mixing and the solution local structure.

Wormald and Lloyd performed flow calorimetric measurements of the excess molar enthalpy, HE,M, of [xH2O+ (1−x)C2H5OH] at the pressure 15 MPa and over the temperature range 398 K to 548 K.[6] The authors also measured the heat of mixing for

W-E solutions over the entire composition range, with constant pressure, at elevated temperatures.[5, 6] The results suggest the variability of the analysis is greatest where heat of mixing values switch to positive to negative near values of x=0.5.[6] According to

Wormald and Lloyd, the success of the simple three-parameter equation to generate curves of the right shape at all temperatures in a mixture that is so strongly hydrogen bonded was better than expected. Therefore, the results confirm Ott’s heat of mixing data of W-E mixtures at room temperature but modify the least squares fit equation because at high temp a different shaped curve is generated. Also, both studies show that the shape of the enthalpy curve is composition dependent, which is consistent with other thermodynamic properties such excess volume.[6],5] Now that the calorimeter has been used to assess the heat of mixing, other thermodynamic properties such as excess entropy were explored by other researchers.

Soper et al. proposed a clustering model to explain anomalous negative excess entropy of mixing characteristic of aqueous lower alcohols that contain hydrophobic groups.[7] The model utilizes the molecular-scale segregation or clusters of the components across the entire concentration range. The experimental data are quantitatively consistent with model. The authors replicated Flory’s model of ideal polymer mixing to develop the idea that a boundary layer exists between water and ethanol.[7] Based on their analysis, the underlying cause of the hydrophobic effect or hydration is entropic in nature. Soper et al. and Flory also suggest that the distribution of

5 the two dissimilar species (i.e. water and ethanol) is not random. Therefore, water clustering in the presence of alcohol is a plausible explanation for entropic deviations from ideality, where mixing is completely random.

The above background research and results reported by Allison et al. [8] using classical molecular simulations to identify distribution of clusters lasting ~40 ps was the foundation for this experimental investigation. There have been several critiques of the

Franks and Evans concept, including simulation work that both support and refute

Franks and Evens “iceberg” concept. [7] The conclusions from this experiment suggest that the nature of clustering varies in the different concentration regions. This observation leads to an objective of the research, to relate the non-ideality of W-E solutions to the local solution structure by clarifying the hydrophobic nature of the alcohol molecules and the resultant architectural adjustments in water in the different concentration regions.

Chapter 2.2: Experiment 200 Proof ethanol was obtained from Pharmco Products Inc. and distilled MilliQ water was used without further purification. The heat of mixing was measured in the

ChemiSens CPA200 reaction calorimeter as shown in the schematic below. (See Figure

1) The computer controlled instrument recorded the time (s), the reference and solution temp (°C), and the power (W). TR and TJ are the measured reactor and jacket temperature, respectively. The jacket temperature was the reference temperature.

Constant pressure is assumed throughout the entire reaction process. The injection volume was small with minor heat flow. Thus the temperature deviation is negligible.

The reaction chamber was initially filled with 70 mL of water or 75 mL of ethanol.

After powering the system on and opening the software to run the reactor, the system was run in the “Low Power Mode”. The “Low Power Mode” is an isothermal process where the temperature was set to 30 °C. The assigned values for the reactor temperature control and the reference temperature control were set to 6 and 5, respectively. The reactor temperature was allowed to stabilize for at least one hour with argon purge gas at 20 psi. The stir speed was set to 200 rpm and each injection was

~1.2 ml through a 1/16” diameter tube. The flow through the loop was controlled to minimize thermal disturbance. A minimum of 20 minutes equilibration time was allotted between injections.

The heat of each injection was calculated by multiplying the power (J/s) times the time (s). The endpoints of the peak were taken as the average point of the baseline and may be a source of error in the heat calculation. The heat of mixing was calculated and plotted as function of ethanol mole fraction (Figure 3). The power was calculated from the heat flow as a function of the temperature difference and the heat capacity of the reaction fluid (i.e. water). The total power is the power that is generated in a defined calorimeter is estimated as the “True Heat Flow” corrected for heat accumulating due to temperatures deviating from the reference value. The “True Heat Flow” includes the agitation from the stirrer, which according the instructional manual is negligible for speeds less than 800 rpm.

The calibration data for each reactor are unique. The reactor chamber and torque transducer are calibrated during instillation by ChemiSens. The calibration data automatically load when the system is started. The torque transducer removed the

7 minimal heat generated by stirrer motion. The power (heat) delivered by the stirrer to the reactor solution is proportional to the torque multiplied by the stirring speed. The torque is proportional to the angle displacement of the torque element. The displacement is calculated relative from the “Zero” angle value, which should be close to

90 degrees. The “Zero” angle value is the correction factor applied to the baseline of the total power data generated by the instrument. The above calculations and the calibration information are available with the instrument instruction manual.

Special attention was directed to the concentration of the mixtures, especially at low ethanol mole fraction, where the major anomalies in volumetric properties occur. [9]

In Figure 1, TJ, out is the jacket medium outlet temperature (surrounding cooling water),

TR is the temperature inside the reactor, TJ is the jacket medium temperature (sensor on the reaction chamber jacket that maintains the set isothermal temperature), and TJ, in is the jacket medium inlet temperature.

Figure 1: Schematic of the ChemiSens CPA200 calorimeter [10]

Chapter 2.3: Results and Discussion The molecular interaction between two liquids when they are mixed was investigated through enthalpy of mixing. The enthalpy of mixing is exothermic for binary

8 mixtures with components that attract each other more strongly than they attract their own kind. [11] Hydrophobic hydration is the ordering of water around an alcohol head group to lower the surface tension (i.e. water isolating the methyl group of the ethanol molecule). This phenomenon leads to the release of heat that can be accurately quantified by a calibrated calorimeter. In this experiment, the peaks are a graphic representation of the power required to maintain the set temperature to accommodate the heat released by the solution mixing.

The peak properties of the calorimetry experiment (Fig. 2) also indicate mixing behavior as the peak height is proportional to the amount of heat released during the mixing. For example, the decrease in peak height with increasing ethanol concentration corresponds to decrease in the heat released on mixing. The power data shown in

Figure 2 are an example of the IgorPro® multiple peak fitting analysis applied to all the runs plotted in Figure 3. The excess enthalpy was calculated as the sum of the heat for each injection and plotted as a function of ethanol mole fraction in Figure 3. The Igor code and instructions can be found in Appendix A.

The concentration dependence of excess enthalpy was evaluated to gain insight into structural rearrangement. The concentration dependence of the excess enthalpy is shown in Figure 3. The continuous change of entropy from the inside of a cluster to the mixing region between clusters is indicated by the change in slope of the excess enthalpy versus concentration curve.[7] There is general agreement that in the water rich region the hydrogen bonding strength of water is increased by presence of the hydrophobic head group of the alcohol. The enthalpy curve also had features that are consistent with other thermodynamic studies of W-E solutions.

Figure 2: Multiple peak-fitting example of EtOH added to water

0.2

0.0 Residuals, -0.2 current 1.0 peak

0.8

0.6

0.4

0.2 Total Power (J/s) Power Total

0.0

-0.2 3 5 10 15 20x10 Time (s)

The minimum is observed at ~ 17mol % is in good agreement with published value of 20 mol% for various thermodynamic properties including the excess volume.

The negative excess enthalpy of mixing results from the interplay of the relative strengths of the alcohol-alcohol, water-water and water-alcohol hydrogen-bond binding energies. Coccia et al. specified the three categories of water ethanol solutions; water rich, transitional or intermediate, and ethanol rich [12] The minimum is often attributed to restructuring of water around an isolated ethanol molecule. [13] The IR data (Chapter 3) show a corresponding change in hydrogen bond strength near the 20 mol% ethanol.

According to Pekar, anomalies occur in volumetric properties at low ethanol mol fraction where the water has a higher probability to surround an ethanol molecule. [9] Therefore, it is concluded that in the water-rich region, that transient clathrate-hydrate structures form as water molecules form a hydrogen bonded network around ethanol.

Figure 3 is a plot of the cumulative heat of mixing based on the heat output measured by the calorimeter reaction chamber. It is important to note that the error is cumulative. The curves that start on the left of the graph are experiments where the water was placed in the chamber and ethanol injections were added. The curves starting on the right of the graph are conditions where water was added to the initial ethanol volume. The reaction chamber volume was 200 mL and each run was started with an initial volume of ~75mL to ensure the stirrer was submerged in liquid.

Therefore, the break in Figure 3 below was an experimental constraint due to maximum volume of the liquid that could be held in the reaction chamber. The solid blue line is a plot of the Ott’s data generated from a continuous flow calorimeter [14].

Figure 3: Excess enthalpy of mixing (∆H) vs. EtOH mol fraction

The current results are similar to Ott’s data but are less pronounced because different experiment conditions (continuous flow process) and injection volume error.

The thermodynamic inflection point is interpreted as structural transition [15] where the heat of mixing shows anomalies at 25C. The inflection is attributed to structural

11 enhancement of the hydrogen bond network of water by ethanol; that is, hydrophobic hydration.[4] Also based on the slope of the enthalpy curve, the number of molecules in the cluster for the ethanol-rich clusters was different than that for the hydrated ethanol clusters. These results support the presence of microscopic clusters of ethanol in the water-rich region in the ethanol–water binary mixtures similar to alcohol clustering observed by Wakisaka.[16] Wakisaka et al. also noted that the enthalpy of the cluster formation for the ethanol-rich clusters was significantly smaller than that for the hydrated ethanol clusters. [16]

Chapter 2.4: Conclusions

The calibrated calorimeter was an appropriate instrument to measure the heat of mixing for multiple water-ethanol solutions. The concentration dependence of heat of mixing was observed, which supports the notion that the local solution structure directly impacts thermodynamics properties. Also, it is important to note the flow through the control loop was controlled to minimize thermal disturbance.

Although Ott and Wormald’s data where fit based on the rule of mixing, the current data is in good agreement. Based on the slope behavior in the enthalpy versus concentration curve, hydrophobic hydration is plausible explanation for the negative slope observed in the water-rich region of the. The curve minimum is also within reasonable agreement. Therefore, hydrophobic hydration is the dominant phenomena at low alcohol concentrations. However, there are limitations to these observations including alternative theories to explain the clustering that challenge the notion of

“iceberg” formation.

The current study has multiple limitations despite generating support for similar approaches to investigate the heat of mixing relationship to local solution structure.

One limitation was that the entropy was not measured or calculated, precluding free energy calculations. Another limitation was that the approach is an indirect method to investigate structure unlike the x-ray diffraction experiments. Along with these limitations, other researchers offer alternative theories to explain the non-ideal behavior of aqueous alcohol solutions.

One alternative explanation is offered by Dixit et al., who proposed incomplete mixing of dynamic fluid solutions based the variable hydrogen bond strength. [3]

Dixit et al. further went on conclude that the high alcohol concentrations behave similar to pure components of the mixture.[3] Nishikawa and Iijima [17], based on small angle x-ray scattering (SAXS) experiments, stated that clathrate-like clusters do not exist as a main component in aqueous alcohol solutions because the hydrogen bonding energy is nearly the same. Therefore, structures are only transient and unstable. The authors also asserted that the hydrophobic headgroup of ethanol was too small to form a stable cage. Nishikawa and Iijima further stipulated that the alkyl chain length of ethanol was too short to participate in stable interactions between chains such as linkage or stacking.[17]

Chapter 3: FT-IR Chapter 3.1: Introduction Recent studies of alcohol-water binary mixtures are leading to different insights into the behavior of water near molecules containing both hydrophobic and hydrophilic groups. [2] The absorbance band can lead to inferences regarding structural behavior in

13 water-alcohol solutions. [18] The frequency range where a given bond absorbs is influenced by the strength of the bond and the masses that take part in the bond. The frequency is proportional to the energy or bond strength by a factor of Planck’s constant

(E=hν). Therefore, a change in local solution structure will result in a change in the frequency. The objective of this IR study was to observe the concentration dependence of characteristics frequencies. From these data, changes in hydrogen bonding strength that leads to structural transitions in alcohol–water binary mixtures at room temperature can be inferred.

Previously researchers have utilized FT-IR and complementary spectroscopic techniques to investigate the solution behavior of aqueous alcohol. For example,

Mizuno et al. discussed hydrogen bonding interactions within water-ethanol mixtures based on FT-IR and NMR measurements at different temperatures.[18] The authors measured IR and NMR for the entire composition range and specifically analyzed the H-

OH vibrational band of water to evaluate hydrogen bonding. This particular band was selected to distinguish between the water and ethanol contributions because H-OH bending vibration is only due to hydrogen bonds found in water. These results were confirmed with NMR data where the protons are readily distinguished. The frequency shift was interpreted as the strengthening of the hydrogen bonds formed among water molecules in the presence of an alkyl group. The study supports the presence of clathrate-like structures in the water-rich region in W-E mixtures. Other researchers used IR in conjunction with other spectroscopic techniques to explore the hydrogen bonding in aqueous alcohol.

Nishi et al. used IR to study hydrogen bonding (HB) cluster formation of ethanol and water molecules in diluted aqueous solutions (XA ≤0.03) near ambient temperature.

Also, Nishi and coworkers performed cluster analysis with mass spectrometric analyses of the clusters and X-ray diffraction measurement.[19] The IR results indicate that even within the dilute solutions the solute-solute association is preferred. Nishi et al. described the observed results in terms of a clathrate structure with a hydrophobic core composed of coherent ethyl groups with a hydrogen-bonding water cage. These results articulated an important parallel between dilute aqueous ethanol and pressurized water and supports hydrophobic hydration that occurs in the water-rich region. [19] Other researchers used more advanced spectroscopic techniques to observe the strengthening of hydrogen bonding and concentration dependent structural transitions in alcohol–water binary mixtures at room temperature.

Pradhan et al. more recently investigated the structural transition in aqueous alcohol solutions using the absorption and emission characteristics of Coumarin 153

(C153), a fluorescence reference standard.[1] A minimum in the peak frequency of the absorption spectrum of C153 indicated the effect of hydrogen bonding network on the structural transition of alcohol. The time resolved anisotropy decay of C153 spectrum indicated two distinct rotational time constants as the curve was bi-exponential over the entire composition range. Pradhan et al. plotted the average rotational correlation time as a function of alcohol concentration. The authors interpreted the sharp change in slopes of average rotational correlation time with alcohol mole fraction as structural transition in the environment around the rotating solute. [1] The results from the

Pradhan et al. study showed the difference in dielectric constants leads to different

15 spectroscopic behavior and supports the self association of alcohol and pressurized water in water rich region (low alcohol concentration). [1]

Therefore, based on the previous research, the IR data in this study will be analyzed based on the concentration dependence of characteristics frequencies that suggest changes in hydrogen bonding leading to structural transitions in alcohol–water binary mixtures at room temperature. During this study three absorption bands were monitored in the water-alcohol mixtures: the H-OH bending vibration, the CO stretch, and the CH stretch. The OH group stretch is the largest band labeled in Figure 5 and can be found between 3000 and 3600 cm-1. This band was not used in the study because both water and alcohol contribute.

Figure 4 is a graphical display of the complete IR spectrum from 500-4000 cm-1.

Figure 4: Complete IR spectrum 500-4000 (cm-1)

0.5

Water 0.4 X=0.07 OH band X=0.17 CO band X=0.20 0.3 X=0.24 X=0.34 X=0.50 H-OH bend X=0.77

Abs orba nce 0.2 ETOH

CH band 0.1

0.0 1000 1500 2000 2500 3000 3500 4000 -1 Wavenumber (cm )

The C-O stretch can generate a strong band in the1000-1260 cm-1 range depending on the coupling with adjacent carbons. The transfer of electron density from the methyl

16 group to C-O bond can induce asymmetric stretching in primary alcohols. Finally, the absorption band at ~1640 has previously been identified as the bending of a water molecule. [18]

The water hydrogen bond network and random thermal motion determine the local structure reorganization in solutions [1]. Thus, structural rearrangement upon the addition of alcohol will impact the induced dipole moment (IR active). The band position indentifies the functional groups present in solution. The band characteristics can provide information on local solution structure, which shifts the frequency. The frequency will vary according to what is bonded to a functional group. Specifically, the change in the IR spectrum can be attributed to the change in hydrogen bonding strength caused by alcohol participation in the water hydrogen-bond network. The IR data will be qualitatively analyzed in terms of hydrogen bond strength and the onset of rearrangement to accommodate alcohol molecule within the water network [1].

Chapter 3.2: Experiment

Materials The 200 proof ethanol obtained from Pharmco Products Inc. was used without further purification. Distilled Milli-Q water was used for the preparation of all sample solutions.

The mass of each water and alcohol sample was measured on a Denver Instrument

APX-60 top loading balance with a readability of 0.1 mg. The solutions were prepared in triplicate and used for both the light scattering and FT-IR experiments.

Measurements The FT-IR data was measured at 22 ± 1°C in nitrogen gas atmosphere with a

Digilab FT-IR/FTS 3000 spectrometer. The energy resolution was 0.25 cm-1 and the

17 absorbance was measured from 500 - 4000 cm-1. The frequency, v, of the -CO stretch and H-OH bend and stretch are the characteristic bands observed in alcohol IR spectrum. Concurrent rotational energy changes with the vibrational energy cause the spectrum to be displayed as a continuous band rather than individual lines. [6] The relative mass, atomic geometry (i.e. tetrahedral configuration), and the force constants of the intermolecular bonds determine the frequency or absorption wavelength. [6]

Figure 5: Schematic of standard FT-IR spectrometer [7]

Mirror drive

Piston

Mirror B (movable)

Mirror A (fixed) Source Beam eeeee Splitter

Combined Beam

Sample Cell

Detector

Converter- Analog to Digital

Computer Recorder

Chapter 3.3: Results and Discussion

The characteristic band of the –CH stretch was used to analyze the strengthening of the hydrophobic methyl association of the ethanol molecules in the solution. [20] The C-H stretch, which is only present in alcohol molecules, shows a slight increase in frequency when plotted as a function of concentration. Figure 6 is the C-H stretch for W-E solutions that cover the entire composition range.

Figure 6: –CH stretch region from 2965-3000 cm-1 ± 9 cm-1

The C-H and methyl groups are hydrophobic and thermodynamic studies of excess entropy suggest that these groups cluster to lower the surface tension. [7]

Keeping that in mind, the shift to higher frequency is considered a consequence of stronger bond energy. Therefore, the results are interpreted as evidence of ethanol self-association with increasing alcohol concentration.

The –CH stretch data (2978 cm-1 ± 9 cm-1), which are comparable to Mizuno’s data (2975 cm-1 Mizuno’s), are shown in Figure 7. The frequency shift can be attributed to an aqueous local environment of the methyl groups. [18] The minimum in Figure 7 is consistent with the concentration dependence of excess enthalpy where the minimum was observed at ~20 mol%. The frequency shift minimum when plotted versus ethanol concentration indicates the C-H bond is weakest at that concentration. Conversely at the curve minimum, other groups that participate in hydrogen bonds are the strongest.

Also, the frequency shows a linear increase with concentration after the curve minimum.

The present results are similar to Onori and Santucci experiment that was interpreted as the self association of alcohol as ethanol concentration increases.[21]

Figure 7: –CH stretch vs. mol fraction compared to Mizuno

The concentration dependent C-H stretch frequency shift is concurrent with a

-1 -1 frequency shift of the –CO stretch (~1050 cm ± 17 cm , Fig. 8). Mizuno et al. attributed this concurrence to the electron density decreasing in carbon of the methyl

20 group and being transferred to the carbon of –CO that is only present in alcohol.[18]

Spectral properties such as IR frequency shift are anticipated to adjust when alcohol is added to water because it enhances hydrogen bond strength of all species and facilitates clusters formation. [1] These two structural modifications will become evident because they create local micro-heterogeneities that are detectable by most spectroscopic instruments.

Figure 9 demonstrates the concentration depepndent frquency shift of the CO stretch. The curves in Figure 9 are a single experiment that was repeated to ensure accuracy and determine standard devetion for frequency measurements. The current data are qualitatively similar to Mizuno’s data but displayed a negative slope in the plot of the frequency as a function of concentration (Figure 9). The figure is displayed with the standard error. Therefore, the increase in non-polar methyl groups (in ethanol) leads to the breakdown of the water hydrogen bond network, whereupon the methyl groups will increasingly self-associate in the alcohol rich region.

Figure 8: –CO stretch from 950-1150 cm-1 ± 17 cm-1

The final characteristic absorpotion band monitored during this analysis was the bending vibration of the water, H-OH, between 1600-1900 cm-1. Intramolecular hydrogen bonding of water persists in the water-rich phase. [22] The low alcohol concentration hydrogen bond network of water molecules is preserved in the same state found in pure water [16]

Figure 9: FT-IR data: C-O stretch compared to Mizuno data [18]

Parke et al concluded that when ethanol molecules are introduced to water, the water molecules around the hydrophobic end of the ethanol undergo a structural rearrangement in such a way that strengthens W-W bonds.[23] The current observation of the concentration dependent frequency of the H-OH bend is consistent with Parke et al. conclusion and the definition of hydrophobic hydration.

According to Mizuno the H-OH vibrational bend of water can be used to investigate the hydrogen bonds of water molecules because the frequency shift corresponds to the change in strength of hydrogen bonds formed among water molecules. [24] The frequency shift of the H-OH vibration is plotted as function of

22 concentration is shown in Figure 10. Mizuno et al. also performed an IR analysis on haloethanol solutions where the bending vibration (~1600 cm-1) of water had a concentration dependent shift to higher frequency.[24] Based on the analysis of NMR data, the shift in H-OH vibration in the current data is also interpreted as support of clustering and hydrophobic hydration occurring in the water-rich region.[18]

Figure 10: Concentration dependence of –OH stretch (1640 cm-1 ± 8.9 cm-1)

The results are confirming the previous IR results indicating that the hydrogen bond between water molecules is stronger in the water rich region. The H-OH is obviously concentration dependent and supports the clustering explanation of the enhanced hydrogen bond strength (hydrophobic hydration).[25] Hydrophobic hydration describes the restructuring of water around the non-polar ethanol molecules. Therefore, although qualitatively the experimental data are similar to the results of Mizuno, the current study shows a negative slope before 20 mol%. This increased sensitivity in the

IR data can be attributed to smaller incremental solution data points. Mizuno and

23 coworkers did not see the abrupt shift as they prepared aqueous ethanol samples in increments of 10 mol%.

Chapter 3.4: Conclusions

In conclusion, the IR data establish the concentration dependence of all three characteristic frequencies in W-E solutions at room temperature that are sensitive to the local environment. For example, the C-H and C-O stretches gain strength as the ethanol concentration increases. These phenomena also impact the H-OH bend as hydrophobic hydration concept suggests that the hydrogen bond strength in water will increase with the addition of ethanol. The observed shift in the H-OH was evidence of the hydrogen bond strength of water molecules getting stronger in the water rich region.

The negative slope in both the heat of mixing and frequency of the H-OH vibration suggest clustering of water in the water-rich region. This conclusion is also supported by other researchers who observed enhanced hydrogen bond strength between water molecules when introduced to alcohol.

The change in slope in the -CO stretch versus concentration curve (Figure 9) also indicates a change in the local solution environment. The transition range precedes the alcohol-rich region where the frequency shift of the C-O and C-H stretch vibration is an indication of the self-association of the alcohol. The frequency shift of the hydroxyl band (in FT-IR appendix) indicates a definite transition region between the water-rich region and the alcohol-rich region. Other researchers suggest that the transition region is similar to the micellization process for some properties. Therefore the size of the hydrophobic headgroup effects the range of the transition region.[21]

The final conclusion is that the current IR data suggest a change in environment or structural modifications. The double band observed in the H-OH frequency as a function of concentration can be interpreted as the ability of proton from water to act as both a donor and acceptor. Pradhan et al. also results support this conclusion as the study described the bi-exponential nature of anisotropy decay as evidence of multiple rates of molecular aggregation or clustering. [1]. The final conclusion leads to the question of how stable are the clusters and what is the relaxation time or time constant of the local solution structure. (Chapter 4)

The above results are positive but there are limitations to the current study. For example, IR data is an indirect measure of structural changes just as calorimetry results provided inferences regarding local solution structure. Therefore, using complimentary spectroscopic techniques such as NMR measurements could strengthen the conclusions found here. Also some researchers do not support the notion that water clusters and alcohol clusters coexist in water-alcohol solutions. Nishi et al. postulate microscopic phase separation or Dixit’s incomplete mixing.[3, 19] Also Falk challenges the coupling of water proton as proton acceptor and donor.[26] A final limitation of the study is that, although the data suggest clustering in the water-rich region, some authors consider small molecule cluster unstable and transient. Koga et al. stated that small molecules move faster and have small time constants. Light scattering is a possible technique to calculate the time constant of the local solution structure relaxation.

Chapter 4: Light Scattering

Chapter 4.1- Introduction/Motivation for Study

The correlation time of concentration fluctuations, which depends on the mutual diffusion coefficient, affords information about the time scale of local structure fluctuations in binary solutions. [27] It is the aim of this section to measure the temperature dependence of the mutual diffusion coefficient obtained from dynamic light scattering. Another objective was to observe concentration fluctuations in butoxyethanol/water (BE) and water-EtOH mixtures in the noncritical temperature range using static light scatting. If the origin of non-ideal thermodynamics of mixing is molecular clustering, an increase in Rayleigh ratio should be observable. [28]

With the development of optical detection instruments and the ability to resolve individual frequencies, Raymond Mountain was one of the first researchers to systematically study liquid properties with scattered light. Mountain and Deutsch calculated the scattered light spectrum from thermodynamic fluctuation theory and equations appropriate to a two-component fluid model.[29]. The authors used linearized hydrodynamic equations to describe time dependence of fluctuations and correlated the fluctuations in the local thermodynamic properties to variation in the local dielectric constant (DC). The variations in DC cause light to scatter and the intensity of that light is recorded to link the DC variation directly to a measureable quantity. Based on the

Boltzmann principle, the light scattering data indicate changes in local solution structure such as change in entropy (or enthalpy observed with calorimetry).[29] This work was key in establishing the theoretical framework to interpret solution behavior and

26 demonstrating light scattering as a credible technique to measure local concentration fluctuations in binary solutions. After Mountain and Deutsch laid the theoretical background other researchers expanded the scope of the method to explore other solution properties such as phase separation.

Ito et al. used Rayleigh and Raman scattering to study local solution structure in

2-butoxy-ethanol(BE) aqueous solutions.[30] The authors explored the relationship between the local structure formation and phase separation by measuring concentration fluctuations at various temperatures that were below the lower critical solution temperature (LCST). The concentration dependence of the concentration fluctuations was observed from Rayleigh scattering at 21, 32, and 42 °C of binary BE-water solutions. Ito et al. concluded that two kinds of local structure exist in the solutions; clathrate hydrates and aggregates.[30] Also, Ito et al. proposed a model to understand local mixing in BE-water mixtures and supported the three distinct regions suggested by the calorimetry and IR data in this study.[31] Schmitz et al. expanded the study of Ito to consider how diffusion can lead to phase separation

Schmitz et al. also studied the BE-water system and reported the dynamic light scattering (DLS) results on noncritical solutions.[32] Schmitz and coworkers measured the temperature dependence of the mutual diffusion coefficient of BE-water mixtures in the noncritical temperature range. The mutual diffusion coefficients were calculated from the correlation function based on Fick’s second law of diffusion. The author’s results demonstrated a composition and temperature dependence of the mutual diffusion coefficient of 2-butoxyethanol/water mixtures of noncritical composition.[32]

Therefore, the study was an example of combining the DLS data used to measure the

27 diffusion rate and the static light scattering (SLS) used to measure the structure to explain the solution environment. The study utilized regular solution theory and provided evidence that the behavior of diffusion coefficients is primarily caused by the temperature and composition dependence of the chemical potential. With binary solutions covered by multiple researchers Ivanov and Winkelmann attempted to expand the method to a ternary liquid system.

Ivanov and Winkelmann performed DLS measurements in the ternary mixture of glycerol-acetone-water (GAW) and applied the theoretical model for binary liquid mixtures to explain the physical meaning of the two observed decay modes.[33] The authors present a theoretical description of the multiexponential autocorrelation function and compared it to mathematical models.[33] The time dependent intensity of the autocorrelation function (ACF) was used to calculate the diffusion coefficients. The correlation time is the time scale on which fluctuations evolve. Therefore, the study provides a reference for the time scale of the multiple relaxation modes of the system and provides a physical explanation of the nature of transport modes.

Motivated by the previous research, DLS measurements were performed on two binary systems; water-ethanol and 2-butoxyethanol solutions. The current study was conducted with the assumption the DLS is an appropriate technique to measure concentration fluctuations in small molecule alcohol mixtures. The hydrophobic hydration is assumed to affect concentration fluctuations.[23] Therefore, the local fluctuations of concentration in alcohol–water binary mixtures based on Rayleigh intensity are analyzed to provide information about the molecular mixing trends and physical evidence of clustering. The purpose of the light scattering experiment is to

28 observe the concentration fluctuations and calculate the mutual diffusion coefficients for water-ethanol and 2-butoxyethanol-water (BE-water) solutions. The data will be analyzed to determine the temperature and composition dependence of the concentration fluctuations and the mutual diffusion coefficients in the two systems.

Chapter 4.2: Experiment

Materials The 200 proof ethanol obtained from Pharmco Products Inc. was used without further purification. The Butoxy-ethanol was purchased from Fischer Scientific and used as received. Distilled Milli-Q water was used for the preparation of all sample solutions. The mass of each water and alcohol sample was measured on a Denver

Instrument APX-60 top loading balance with a readability of 0.1mg. The mass fractions can be found in Table 1(Appendix). Solutions were prepared in triplicate and used for both the light scattering and FT-IR experiments.

Measurements The light scattering data were collected using the Malvern Instruments CGS-3 multi-angle light scattering spectrometer located in the Advanced Materials

Characterization Center (AMCC). The experiments were performed in quartz cell, per the manual instructions, at room temperature and 44°C ± 0.05°C for ethanol and BE- water solutions, respectively. The BE-water samples were maintained at an elevated temperature by the Neslab EX-111 pumping heated water around the sample holder vat. The samples were placed in the vat and maintained at the elevated temperature for a minimum of 8 hours. The dynamic and static light scattering measurements were collected simultaneously.

Each sample was measured in the scattering range 50°< θ <120° and normalized by the toluene standard at wavelength of 632 nm. The samples were filtered with

Millipore® 0.2 micron (µm) polyethylene filter. The refractive index increment (RII) was measured by the WYA Abbe refractometer to be 0.0559 and 0.8852 for ethanol and BE, respectively (see Figure 11). This value was comparable with International Critical data on ethanol-water solutions. Ito found a much higher value for the refractive index increment as shown below in Figure 12. The Rayleigh ratio of the toluene standard as function of angle is within the 3% error indicated in the instrument manual. The intensity, temperature, and Rayleigh Ratio were measured by the instrument. A more detailed experimental procedure can be found in App C.

Figure 10: Refractive Index Increment for aqueous ethanol solutions

Figure 11: RII of 2-butoxyethanol in water solution compared to Ito[30]

The Rayleigh ratio (RR) is the time-averaged or “total” or reduced intensity of the scattered light measured by the photon counting correlator. The correlator directly calculates the intensity and correlation function. The intensity correlation is used to calculate the auto correlation function (ACF) of the intensity. Next, the ACF at an angle

θ is analyzed to generate the relaxation time distribution. The initial slope of the exponential decay is proportional to the translational diffusion coefficient. Therefore,

DLS experiments can provide detailed solution properties such as the local relaxation time and translational diffusion. (The detailed proof out this analysis can be found in several polymer physics text such as Strobl “The Physics of Polymers and Doi,

"Introduction to Polymer Physics")

Chapter 4.3: Results and Discussion

Water-Ethanol (W-E) The auto correlation function displayed in Figure 12 is representative of all the water-ethanol samples and showed no distinct exponential decay. Therefore, the mutual diffusion coefficient and the time averaged relaxation time could not be calculated from the DLS results. No concentration fluctuation was observed in the static light scattering experiment either. However, the stable signal suggests that the samples are clean with minimal exposure to dust (or air bubbles) to distort signal intensity.

Rayleigh intensity is strongly influenced by the presence of dust particles. [28] The first data point on the graph is an instrument artifact (after pulsing in the detector) and has no physical meaning. With no exponential decay and the signal fluctuating near zero, only a sub-picosecond fluctuation can be inferred by the data. Therefore, no further analysis was performed on the water-ethanol solutions as no measureable correlation was observed.

Figure 12: ACF of X=20mol% ethanol at various scattering angles in water.

0.8 RETOH_X_0_20_A50 0.6 RETOH_X_0_20_A60 RETOH_X_0_20_A70 RETOH_X_0_20_A80 0.4 RETOH_X_0_20_A90

RETOH_X_0_20_A100

 (

2 RETOH_X_0_20_A110 g 0.2 RETOH_X_0_20_A120 RETOH_X_0_20_A130 RETOH_X_0_20_A140 0.0

-0.2 0.001 0.01 0.1 1 10 100 1000  (ms)

The lack of scattering intensity from the W-E solutions does not disprove the notion of clustering and is consistent with SAXS results.[17, 34] Nishikawa and Iijima observed diffraction results from stable water-ethanol clusters that were similar to the surrounding solvent.[17, 34] Scattering form clathrate-like cluster of sizes less than 10 angstroms would not be observable because the light scattering instrument is not sensitive to small scale concentration fluctuations. Therefore, these results are consistent with other experiments that conclude that the size of observable fluctuations is greater than 100 angstroms.

2-Butoxy-ethanol in water (BE) The phase diagram of binary solutions provides information to understand local solution behavior. The lower critical solution temperature of 2- butoxyethanol in water was established by Ellis in 1967. [35] Ellis mapped out the entire 2-phase envelope and evaluated the entire concentration range. The deviation from ideal behavior observed in excess thermodynamic properties of 2-butoxyethanol water mixtures is similar to deviations in aqueous ethanol. The phase separation that occurs at the lower critical solution temperature (LCST) is confirmed in the 45 wt% solution at 60°C observed below in Figure 14. The meniscus between the water and the butoxy-ethanol is indicated by a red arrow. The light scattering experiments were performed in the single- phase region at temperatures below the LCST. These experiments were performed to establish whether light scattering could measure concentration fluctuations near the phase-separation temperature where the size scale of the fluctuations should be much larger than expected in alcohol solutions and the time constant should be much larger.

Figure 13: 45 wt% butoxy-ethanol separated from water at 60°C [34]

Contrary to Ito and Schmitz results, no significant changes in the measured

Rayleigh ratio of 2-butoxyethanol solutions were observed in the water rich region. [30,

32] Figure 15 shows that the lower angles should be ignored and not included in calculations. In Figure 15, K= optical constant which is the ratio of the solvent refractive index times the refractive index increment to the laser wavelength and c = solution concentration in g/mL. Stray light compromises the smaller angles, especially for weakly scattering systems (per the instrument manual). No angle dependence was observed.

The current RR values are compared the Ito data in Figures 16. The data are qualitatively and quantitatively dissimilar. The inconclusive results led to an experiment where the BE-water solutions were heated to near the critical temperature in an attempt to observe larger scale fluctuations and critical slowing of the relaxation process.

Figure 14: Various concentrations of BE-water solutions: RR vs. Angle at room temperature.

Schmitz et al. and others report 42-46°C to be the critical temperature range for

BE-water solutions.[32] So samples were run at an elevated temperature of 44°C which is between the Ito data, 42°C, and the Schmitz data at 49°C. Figure 17 shows the RR trends of the BE-water solutions observed in the water rich region near the critical temperature. Intuitively, it is reasonable to expect large concentration fluctuations to be observed as BE has a larger polar headgroup than ethanol and thus would require more hydration water molecules. Therefore the BE is more dissimilar to water molecules than ethanol which should lead to greater (observable) concentration fluctuations. However, experimental results do not support this perception.

Figure 15: BE-water solution average RR vs. concentration at RT

Figure 16: BE-water solution average RR vs. concentration at elevated temperature, 44°C

Chapter 4.4: Conclusions

No significant change in the Rayleigh scattering was observed as a function of concentration, contradicting the Ito and Schmitz data on the butoxy-ethanol solutions.

The lack of scattering from the solutions generated a null autocorrelation function, making it impossible to calculate the mutual diffusion coefficients for either water- ethanol or water-2-butoxyethanol.

The discrepancy does require additional scrutiny as molecular dynamics simulations also support the results of Ito and Schmitz. However, the current results are consistent with small angle x-ray scattering experiments from our group that find no evidence of large-scale clustering in water-ethanol solutions. It is concluded that phase separation that occurs at the critical point does not have a broad transition region making it difficult to observe enhanced scattering except very close to the bimodal line.

A final conclusion is that the clathrate-like hydrate description should be confined to a range of molecules as the headgroup has to be a size that can support a hydrogen bond network of water.[36]

Despite effort to ensure the accuracy of the light scattering experiments, this study had limitations. One limitation of the study is that standard DLS is insensitive to fluctuations with time constants less 100 picoseconds. Another limitation for the experiment was the instrument software specified fitting equations. Researchers have suggested using multiple types of fitting equations to precisely evaluate the light scattering data where the thermal diffusion can be distinguished from the mass diffusion.[33]

Chapter 5: Summary and Future Work

In summary, alcohol-water binary solutions have been studied by multiple characterization methods to understand the structural basis for molecular association.

The purpose of this thesis was to investigate the relationship between the local solution structure and the anomalous thermodynamic properties. The main hypothesis was that the clusters and clathrate- like structures dominate the measures of water-alcohol solution properties. The calorimetry results were in reasonable agreement with published data although the calorimetry curve minimum was less dramatic than the Ott data. The minimum of the calorimetry data and the IR data as a function of alcohol mol fraction occurred at same location as currently published data. The IR data support the explanation of clustering because enhanced hydrogen bond strength was observed.

Finally, the light scattering intensity observed here is four times less than the value

37 reported by Ito and Schmitz. The concentration dependence of the RR was not comparable the Ito data, which limited the data analysis possibilities. Therefore, the current study provides evidence that the clusters exist in water-alcohol solutions, but the time scale of the clusters is too fast and the size scale too small to be observed by light scattering, even within a few degrees of the LCST.

Future work for the project can be summarized by the following statements:

• Repeat calorimetry experiment with larger reaction chamber and use continuous

flow process.

• Use a linear fitting model to analyze the FT-IR data and compare to published

models

• Evaluate single relaxation times with separate least squares fitting models

• Apply the Ornstein-Zernike equation which applies fluid theory to measure the

influence one molecule will have on another by quantifying the direct and indirect

contributions. (Radial distribution function)

References

1. Pradhan, T., P. Ghoshal, and R. Biswas, Structural transition in alcohol-water binary mixtures: A spectroscopic study. Journal of Chemical Sciences, 2008. 120(2): p. 275-287. 2. L. Dougan, S.P.B., R. Hargreaves, and J. P. Fox, Methanol-water solutions: A bi-percolating liquid mixture. JOURNAL OF CHEMICAL PHYSICS 2004. 121(NUMBER 13 ). 3. Dixit, S., et al., Molecular segregation observed in a concentrated alcohol-water solution. Nature, 2002. 416(6883): p. 829-832. 4. Sato, T., A. Chiba, and R. Nozaki, Dynamical aspects of mixing schemes in ethanol--water mixtures in terms of the excess partial molar activation free energy, enthalpy, and entropy of the dielectric relaxation process. The Journal of Chemical Physics, 1999. 110(5): p. 2508-2521. 5. Ott, J.B., et al., Excess enthalpies for (ethanol + water) at 298.15 K and pressures of 0.4, 5, 10, and 15 MPa. The Journal of Chemical Thermodynamics, 1986. 18(1): p. 1-12. 6. Wormald, C.J. and M.J. Lloyd, Excess enthalpies for (water + ethanol) atT= 398 K toT= 548 K andp= 15 MPa. The Journal of Chemical Thermodynamics, 1996. 28(6): p. 615-626. 7. Soper, A.K., et al., Excess Entropy in Alcohol−Water Solutions: A Simple Clustering Explanation. The Journal of Physical Chemistry B, 2005. 110(8): p. 3472-3476. 8. Allison, S.K., et al., Clustering and microimmiscibility in alcohol-water mixtures: Evidence from molecular-dynamics simulations. Physical Review B, 2005. 71(2): p. 024201. 9. Pecar, D. and V. Dolecek, Volumetric properties of ethanol-water mixtures under high temperatures and pressures. Fluid Phase Equilibria, 2005. 230(1-2): p. 36-44. 10. Ola, J.K., H. Helen, and W. Bengt, Influence of seed polymer molecular weight on polymerization kinetics and particle morphology of structured styrene-butadiene latexes. 2000. p. 297-311. 11. Ding, M.S., Excess Gibbs Energy of Mixing for Organic Carbonates from Fitting of Their Binary Phase Diagrams with Nonideal Solution Models. Journal of Solution Chemistry, 2005. 34(3): p. 343-359. 12. Coccia, A., et al., PMR studies on the structures of water-ethyl alcohol mixtures. Chemical Physics, 1975. 7(1): p. 30-40. 13. Hu, N., et al., Structural Basis of the Proton-Nuclear Magnetic Resonance Spectra of Ethanol–Water Solutions Based on Multivariate Curve Resolution Analysis of Mid-Infrared Spectra. Applied Spectroscopy, 2010. 64(3): p. 337-342. 14. V., O.J.B.S.C.E.C.G., Excess enthalpies for (ethanol+water) at 298.15 K and pressures of 0.4, 5, 10 and 15 MPa. Journal of chemical thermodynamics 1986. 18(1): p. 1-12. 15. Takamuku, T., et al., X-ray diffraction studies on methanol-water, ethanol-water, and 2- propanol-water mixtures at low temperatures. Journal of Molecular Liquids, 2005. 119(1-3): p. 133-146. 16. Wakisaka, A. and K. Matsuura, Microheterogeneity of ethanol-water binary mixtures observed at the cluster level. Journal of Molecular Liquids, 2006. 129(1-2): p. 25-32. 17. Nishikawa, K. and T. Iijima, Small-angle x-ray scattering study of fluctuations in ethanol and water mixtures. The Journal of Physical Chemistry, 1993. 97(41): p. 10824-10828. 18. Mizuno, K., et al., NMR and FT-IR Studies of Hydrogen Bonds in Ethanol-Water Mixtures. The Journal of Physical Chemistry, 1995. 99(10): p. 3225-3228.

19. Nishi, N., et al., Hydrogen-Bonded Cluster Formation and Hydrophobic Solute Association in Aqueous Solutions of Ethanol. The Journal of Physical Chemistry, 1995. 99(1): p. 462-468. 20. Yaacobi, M. and A. Ben-Naim, Hydrophobic interaction in water-ethanol mixtures. Journal of Solution Chemistry, 1973. 2(5): p. 425-443. 21. Onori, G. and A. Santucci, Dynamical and structural properties of water/alcohol mixtures. Journal of Molecular Liquids, 1996. 69: p. 161-181. 22. Robert M. Silverstein, F.X.W., David Kiemle, Spectrometric Identification of Organic Compounds, 7th Edition. 2005, New York, NY: John Wiley & Sons, Inc. 512. 23. Parke, S.A. and G.G. Birch, Solution properties of ethanol in water. Food Chemistry, 1999. 67(3): p. 241-246. 24. Mizuno, K., et al., IR Study of Hydrogen Bonds in Halogenoalcoholâˆ’Water Mixtures. The Journal of Physical Chemistry A, 1997. 101(7): p. 1366-1369. 25. Czarnecki, M.A. and D. Wojtków, Effect of varying water content on the structure of butyl alcohol/water mixtures: FT-NIR two-dimensional correlation and chemometric studies. Journal of Molecular Structure, 2008. 883-884: p. 203-208. 26. Falk, M., The frequency of the H---O---H bending fundamental in solids and liquids. Spectrochimica Acta Part A: Molecular Spectroscopy, 1984. 40(1): p. 43-48. 27. Kato, T. and T. Fujiyama, Light scattering study of local structures in solutions: chloroform- ethanol system. The Journal of Physical Chemistry, 1976. 80(25): p. 2771-2777. 28. Iwasaki, K. and T. Fujiyama, Light-scattering study of clathrate hydrate formation in binary mixtures of tert-butyl alcohol and water. The Journal of Physical Chemistry, 1977. 81(20): p. 1908-1912. 29. Mountain, R.D. and J.M. Deutch, Light Scattering from Binary Solutions. The Journal of Chemical Physics, 1969. 50(3): p. 1103-1108. 30. Nobuyuki Ito, T.F., and Yasuo Udagawa, A Study of Local Structure Formation in Binary Solutions of 2-Butoxyethanol and Water by Rayleigh Scatterring and Raman Spectra. Bulletin of the Chemical Society of Japan, 1983. 56(2): p. 379-385. 31. Nobuyuki Ito, K.S., Tadashi Kato, and Tsunetake Fujiyama, Observation of Mutual Diffusion Coefficients and Cooperative Motions in Binary Solutions of t-Butyl Alcohol–Water and 2- Butoxyethanol–Water. Bulletin of the Chemical Society of Japan, 1981. 54: p. 991. 32. Schmitz, J., L. Belkoura, and D. Woermann, Diffusivity in 2-butoxyethanol/water mixtures of noncritical composition approaching the liquid/liquid coexistence curve. The Journal of Chemical Physics, 1994. 101(1): p. 476-479. 33. Ivanov, D.A. and J. Winkelmann, Multiexponential decay autocorrelation function in dynamic light scattering in near-critical ternary liquid mixture. The Journal of Chemical Physics, 2006. 125(10): p. 104507-9. 34. Nishikawa, K., Small-angle x-ray scattering study of fluctuations in ethanol and water mixtures. Journal of physical chemistry (1952), 1993. 97(41): p. 10824-10828. 35. Ellis, C.M., The 2-butoxyethanol-water system: Critical solution temperatures and salting-out effects. Journal of Chemical Education, 1967. 44(7): p. 405-null. 36. Koga, Y., K. Nishikawa, and P. Westh, “Icebergs” or No “Icebergs” in Aqueous Alcohols?: Composition-Dependent Mixing Schemes. The Journal of Physical Chemistry A, 2004. 108(17): p. 3873-3877. 37. Masanao, I., et al., A convenient method to determine the Rayleigh ratio with uniform polystyrene oligomers. Journal of Applied Polymer Science, 2006. 99(4): p. 1953-1959.

Appendices

Appendix A: Calorimetry Figure 17: Power vs. Time compare to R∆T vs. Time

Calorimetry Procedure 1. Power on computer; Password=CPA200

2. Open all software. Ignore errors and hit ok. (System Check) Once system is Ok then hit continue.

3. In the Thermal Mode menu select “isothermal”. Set the reference temperature (i.e. 30°C)

4. Assign Values

-Reactor Temperature Control___6

-Reference Temperature Control___5

Then Quit

5. Now =current run. Start with ~75 mL of solvent in reaction chamber

6. Set-up reactor and attach the temperature sensor and the stirring rod.

7. Set stir speed (i.e. 200, <800 to ensure no thermal disturbance per the instructional manual)

8. Set-up injector with appropriate 1/16 in tubing. Requires ~20 psi argon gas and 22 gauge flat needle, open green valve. The gas does affect the speed of the injection.

9. Allow system to equilibrate for approximately one hour

10. After equilibration time, switch system to “Low Mode” and then OK

11. Record each injection volume if not automatic pump and allow ~20 minutes between injections.

12. Save data in F:\Filename. Data is saved as ASCII file. Will need data transporter to extract data files. Total Power (W) and Time (sec).

13. Use Windows M to get to the desktop

14. Additional online information: http://www.chemisens.se/CMS/?page_id=377

IR Spectroscopy Chapter

1.3.2 Spectrum

Run 1 Spectrum Figure 8: Example Spectrum 1-Water (Run 1)

Figure 9: Spectrum 9- Pure Ethanol (Run 1)

IR Summary Tables Table 1: Run 1 Peak Table

H-O-H bend O-H str C-O str X PEAK1 AREA PEAK4 AREA PEAK7 WATER 0.00 1642.336 28.378 3327.25 136.679 0.07 1643.680 29.608 3309.815 135.144 0.17 1645.440 31.075 3304.874 131.884 0.20 1645.855 31.048 3304.118 128.123 0.24 1646.619 32.158 3301.026 125.14 0.34 1647.714 6.427 3299.907 120.159 0.50 1648.886 5.916 3304.43 111.972 1045.022 0.77 1651.340 8.890 3352.774 57.88 1045.843 1 1694.599 6.480 3319.293 23.574 1047.929 OVAL 24 0.39 1648.062 6.800 3302.693 121.612 1045.281 OVAL 42 0.59 1649.928 8.800 3341.441 106.28 1045.346 OVAL 56 0.72 1650.893 9.040 3350.737 94.419 1045.739 Avg 1651.279 3318.197 1045.860 Std Dev 13.91643 19.96158 1.058052

Table 2: Run 2 Peak Table H-O-H bend O-H str C-O STR X PEAK1 AREA PEAK4 AREA PEAK7 WATER 0.00 1640.785 25.081 3325.458 154.183 0.07 1641.873 25.204 3309.549 153.961 0.17 1644.017 26.065 3309.536 133.923 0.20 1644.359 26.313 3303.965 132.354 0.24 1645.318 27.433 3302.345 129.812 0.34 1646.226 25.927 3300.428 125.811 0.50 1648.121 10.477 3326.682 116.544 1044.809 0.80 1651.427 6.700 3348.576 55.444 1045.964 1 1694.970 4.359 3117.074 24.231 1047.929 OVAL 24 0.39 1647.220 25.919 3301.77 123.229 1044.872 OVAL 42 0.59 1649.392 7.807 3335.322 107.326 1045.145 OVAL 56 0.72 1650.350 6.718 3345.041 94.835 1045.575 Avg 1650.338 3302.146 1045.716 Std Dev 14.42681 60.75984 1.169596

Table 3: Run 3 Peak Table H-O-H bend O-H str C-O str PEAK1 AREA PEAK4 AREA PEAK7 AREA WATER 0.00 1637.561 14.266 3300.804 141.805 X 0.07 1638.252 17.951 3295.794 141.103 0.17 1639.636 17.810 3287.736 138.666 0.20 1640.270 17.873 3284.96 136.888 0.24 1640.682 17.146 3286.885 135.672 0.34 1642.408 10.049 3283.699 130.915 0.50 1645.263 7.798 3288.156 111.288 1044.424 4.072 0.80 1650.225 3.781 3337.809 51.722 1045.825 10.635 1 0.000 0.000 3312.976 23.070 1047.829 18.012 OVAL 24 0.39 1643.075 8.879 3285.075 127.580 1044.357 2.591 OVAL 42 0.59 1646.922 6.874 3306.395 107.566 1044.842 6.067 OVAL 56 0.72 1648.514 5.601 3333.508 61.864 1045.369 7.998 Avg 1642.983 3300.316 8.229 Std Dev 4.24 18.96 5.57

Figure #: –OH region from 3000-3600 cm-1 ± 18 cm-1

0.5 Water X_0_07_ X_0_17_ OH stretch X_0_20_ 0.4 X_0_24_ X_0_34_ X_0_50_ 0.3 X_0_77_ ETOH

Absorbance Absorbance 0.2

0.1

0.0 3600 3500 3400 3300 3200 3100 3000

-1 Wavenumber (cm )

Figure #: Nishi’s data Concentration dependence of the –OH band frequency [19]

Light Scattering Chapter

Appendix C: Static Light Scattering Procedure

User Procedure: Static light scattering measurement Malvern Instruments CGS-3 ALV3000

I. Before Measurement

1. Verify Rayleigh ratio (RR) of standard. (i.e. Toluene = 1.350 X 10-5) [37]

2. Measure dn/dc (mL/g) for solution (i.e. TBA/H2O = 0.0901 mL/g)

3. Prepare a minimum of five (5) different concentrations (g/mL). Concentration will be measurement parameters. Concentration guidelines in instrument manual, but general rule of thumb can be that high molecular weight (MW) compounds can be dilute.

4. Choose cell for experiment per the Malvern instrument manual. (i.e. water- alcohol requires the quartz cell)

5. Select appropriate filter (i.e. 20 µm PT-FE)

6. A minimum of 1 hour for the laser to warm up.

II. Measurement

1. Open software by clicking on the ALV icon on the computer desktop

2. Select the standard radial. Start with the filtered toluene standard and place solution in the sample holder. Enter file name (i.e. Std) in the appropriate box.

3. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range). Be sure to accept the setup and hit “start measurement” as shown below.

Figure B1: Quick Set Menu

4. If polymer solution continue to step five (5). If water-alcohol solution skip steps 5-6.

5. Select the solvent radial. Filter solvent into cell and place solution in the sample holder. Enter file name (i.e. Solvent or water) in the solvent file box.

6. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range). Be sure to accept the setup and hit “start measurement” as shown above.

7. From the file drop down menu, select the Set Auto-save. Insert the name of the sample (i.e. 8_Ethanol_ for the 8% Ethanol). This stores the individual correlation function as an ASCII file for further data analysis that can be directly inserted into ALV DWS light scattering Igor code.

8. Enter sample identification and description in the sample description dialogue

9. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range, refractive index increment, and sample concentration).

10. Select the solution radial. Filter solution into cell and place solution in the sample holder. Enter file name (i.e. 8_Ethanol_ for the 8% Ethanol) in the solution file box. Be sure to accept the setup and hit “start measurement”.

Figure B2: Measurement Type radials

III. After Measurement

11. Open the ALV-Stat Software

12. Load data file as shown below in Figure B3

Figure B3: File loading for further analysis

13. Once the file is loaded select “continue without any change” indicated by the red arrow in Figure B3. The data will be displayed as shown below in Figure B4. A default Zimm plot will be shown in a separate window. The “k” value in the red circle can be changed to increase/decrease the space between data points

Figure B4: Data display

14. Right click on a point to “select” a data set. The scattering (Rayleigh) ratio values can be pasted to a notepad document by selecting “copy scattering ratios to clipboard” from the File drop down menu. The data will appear as shown below in Figure B5.

Figure B5: Scattering ratio data display

15. The individual ASCII files can be directly entered into the ALV_DWS_light_scattereing Igor code

Appendix D: Dynamic Light Scattering Procedure User Procedure: Dynamic light scattering measurement Malvern Instruments CGS-3 ALV3000.

I. Before Measurement

1. Verify Rayleigh ratio (RR) of standard. (i.e. Toluene = 1.350 X 10-5)

2. Choose cell for experiment per the Malvern instrument manual. (i.e. water- alcohol requires the quartz cell)

3. Select appropriate filter (i.e. 20 µm PT-FE)

4. A minimum of 1 hour for the laser to warm up.

5. Solution concentration recommendation (per the manual)

II. Measurement

1. Open software by clicking on the ALV icon on the computer desktop

2. Select the standard radial. Start with the filtered toluene standard and place solution in the sample holder. Enter file name (i.e. Std) in the appropriate box.

3. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range). Min Angle =Max Angle= 90°. Be sure to accept the setup and hit “start measurement” as shown below.

Figure C1: Quick Set Menu

4. Select the solvent radial. Filter solvent into cell and place solution in the sample holder. Enter file name (i.e. Solvent or water) in the solvent file box.

5. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range). Min Angle =Max Angle= 90°. Be sure to accept the setup and hit “start measurement” as shown above.

6. Enter sample identification and description in the sample description dialogue

7. Enter measurement parameters in the Quick set as described in the manual (i.e. angle range, refractive index increment, and sample concentration). Min Angle =Max Angle= 90°.

8. Select the solution radial. Filter solution into cell and place solution in the sample holder. Enter file name (i.e. 8_Ethanol_ for the 8% Ethanol) in the solution file box. Be sure to accept the setup and hit “start measurement”.

Figure C2: Measurement Type radials

III. After Measurement

11. Open notepad document

12. Apply fit to interpret data by selecting Simple fit from the Fit drop down menu

13. The Cumulant Fit will apply fitting program when fit button selected.

Figure B3: Cumulant Fit of Correlation Function

14. Apply a “Simple Fit” followed by a “Regularised fit”. Leave the default values for the regularized fit and hit OK to apply algorithm.

Figure B4: Regularised Fit

15. Right click on distribution curve to select unweighted radius and apply to data set. The data can now be displayed and copied to a notepad document. The screen will appear as shown below in Figure C6. The distribution function results are shown below in Figure C5.

Figure C5: Distribution function data display

Figure C6: Distribution function window