Environmental Solvent Effects and Temperature-Dependent Behavior of Molecular Rotors

Sarah Goodman Howell

(Under the direction of Mark A. Haidekker)

Abstract

Molecular rotors, a type of fluorescent molecule, are sensitive to their environment. These molecules form twisted intramolecular charge transfer (TICT) states, and once excited they return to ground state following one of two deexcitation pathways: nonradiative intramolecular rotation or fluorescence emission. Temperature and solvent viscosity effects on the quantum yields of six rotors have been observed. In consideration of the power-law relationship between viscosity and quantum yield, the purpose of this study is to investigate the intrinsic temperature-dependent behavior that governs the molecular rotor’s quantum yield. The TICT formation has been hypothesized to be temperature-dependent, and the power-law behavior has yet to be thoroughly examined. We have found that the temperature-dependent change in solvent viscosity accounts for the change in quantum yield, where temperature- dependent behavior of C and x have little influence.

Index words: Molecular Rotors, Viscosity, Viscosity Sensors, Twisted Intramolecular Charge Transfer States, Temperature-Dependency Environmental Solvent Effects and Temperature-Dependent Behavior of Molecular Rotors

Sarah Goodman Howell

B.S., Furman University, 2008

A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulﬁllment of the Requirements for the Degree

Master of Science

Athens, Georgia

Sarah Goodman Howell

Approved:

Major Professor: Mark A. Haidekker

Committee: William S. Kisaalita Peter A. Kner

Electronic Version Approved:

Maureen Grasso Dean of the Graduate School The University of Georgia August 2010 Acknowledgments

I would like to acknowledge Dr. Mark Haidekker for his direction and support throughout this project. I would also like to extend acknowledgments to Dr. William Kisaalita and Dr. Peter Kner, and to Darcy Lichlyter for her continuous help in the lab, along with this project.

iv Table of Contents

Page

Acknowledgments ...... iv

List of Figures ...... vii

List of Tables ...... xiii

List Of Abbreviations And Symbols ...... xiv

Chapter

1 Fluorescence Overview ...... 1

2 Introduction to Molecular Rotors ...... 5 2.1 Overview ...... 5 2.2 Photophysical Characteristics ...... 7 2.3 Applications of Molecular Rotors ...... 9

3 Environmental and Solvent Effects on Molecular Rotors . . . 11 3.1 Polarity of the Solvent ...... 11 3.2 Viscosity of the Solvent ...... 12 3.3 Effects of Temperature ...... 15

4 Materials and Methods ...... 19 4.1 Experimental Design ...... 19 4.2 Solvents and Molecular Rotors ...... 19 4.3 Measuring Viscosity ...... 20 4.4 Measuring Fluorescent Intensity Emission ...... 22 4.5 Finding C0 ...... 25

v 4.6 Determining Optimal x Values ...... 26

5 Results...... 28 5.1 Viscosity and Temperature ...... 28 5.2 Intensity and Temperature ...... 29 5.3 C0 Values ...... 29 5.4 X Values ...... 30

6 Discussion ...... 44 6.1 Solvent Properties ...... 44 6.2 Fluorescent Intensity Data ...... 45 6.3 Temperature Behavior of C and x ...... 45 6.4 Molecular Rotor Structure ...... 48

7 Conclusions and Future Research Considerations ...... 50 7.1 Future Research Considerations ...... 50

Bibliography ...... 51

Appendix

A Temperature/Viscosity Graphs ...... 54

vi List of Figures

1.1 In this ﬁgure, the processes occurring between absorption and emission are described by Jablonski. Vertical lines denote transition pathways between

states. S0 is referred to as the singlet ground state, S1 and S2 states as the

excited states, and T1 the triplet state. Adapted from [1] ...... 2 1.2 In this conceptual figure, the absorption and emission peaks can be seen. The distance between the two peaks is referred to as Stokes Shift...... 3 2.1 Chemical Structure of p-N,N-dimethylamino-benzonitrile (DMABN). . . . .6 2.2 This figure illustrates the rotating motion of the molecular rotor, 9-(2,2- Dicyanovinyl) julolidine (DCVJ). The planar state of this molecule is seen in Part 1, where the twisted state of DCVJ can be seen in Part 2 of the figure.7 2.3 This diagram illustrates a TICT molecule’s ground and excited-state ener-

gies, both in the TICT configuration ϕ2 and in the planar configuration ϕ1. Adapted from [2]...... 8 3.1 Structure of Crystal Violet, a triphenylmethane dye...... 12 4.1 Chemical structures of the molecular rotors, DCVJ (1), CCVJ (2), Rotor 3 (3), Rotor 4 (4), Rotor 5 (5), and Rotor 6 (6)...... 20 4.2 Brookfield DV III+ cone-and-plate Rheometer...... 21 4.3 In this photo the distinct components of the Rheometer are shown. The spindle is connected to the cone feature, which is the turning feature controlling the torque. The white cord, which is plugged into the sample cup, reports the precise temperature of the liquid in the cup. On the cup component, you can see the two hose attachments. These were used to circulate water from a water bath around the sample cup, controlling the temperature of the sample inside. 22

vii 4.4 In this figure you can see the scatter plots for α and β. As you will notice, the data points for both α and β are extremely close together, meaning that the ratio of slit settings for different rotor-dye combinations were similar. . . . . 24 4.5 In this figure is a photo of the Spex Fluoromax-3 Fluorophotometer that we used in this project. The section highlighted in yellow is the connection to the water bath where water acting as a coolant is circulated through. The area highlighted in green is the connection for the automated temperature control device, which maintained and altered the temperature of the sample solution. 25 5.1 Viscosity of Isopropanol with respect to change in temperature. The data was fitted using the V-F-T equation, Equation 3.20...... 28 5.2 Intensity time-course of Isopropanol mixed with DCVJ. This graph depicts the decrease in intensity with the increase in temperature...... 30 5.3 This graph shows the relationship between fluorescent intensity and change in temperature. As you can see, there is a decrease in intensity as temperature increases...... 31 5.4 This graph demonstrates the relationship between intensity and viscosity. As viscosity of the solvent decreases, intensity also decreases...... 32 5.5 These graphs depict the C0 values for each solvent-rotor combination. As you can see, C0 values varied with each solvent-rotor solution. The polar aprotic solvents (seen in red/orange colors) demonstrated more consistency than polar aprotic solvent (seen in blue/purple). However, this was not always the case. 33 5.6 To demonstrate the different trends of the C0 values, individual measurements of C0(T) are shown in this figure for DCVJ. From this figure it becomes evident that no uniform trend exists. As you can see, C0 increases with respect to temperature in the case of Isopropanol, remains almost constant in Pentanol, and decreases in the case of DMF...... 34

viii 5.7 Like Figure 5.6, the different shapes and tendencies of the C0 in CCVJ are seen in this figure. Interestingly, C0 in the case of Ethanol demonstrates a minimum at the apparent preferred temperature, 30◦C. This case cannot be justified with any known theory, all of which suggest either monotonically increasing or decreasing trends...... 35 5.8 This figure, showing all of the C0 values in 3, further demonstrates the changing shapes and tendencies with respect to temperature. Notably, Pen- tanol shows the same deviation as it did in CCVJ at 42◦. This could possibly be explained by experimental error; however, this deviation is not seen in DCVJ...... 36 5.9 Here, all C0 values are shown with 4. It is evident that no steady trend can be deciphered with respect to the change in temperature. In this molecular rotor, DMSO shows a definite increase, Isopropanol a slight increase, where in the other four dyes, a decrease in relation to temperature is observed. . . 37 5.10 5 C0 values are reported in this figure. Here, DMF exhibits an observed minimum at 30◦. As in the case of Ethanol in CCVJ, no explanation for this U-shape exists in current literature...... 38 5.11 Like in the figures mentioned above, no consistent trends can be deciphered from this figure. Isopropanol shows a slight increase in 6, where Pentanol moves more toward constant...... 39 5.12 This figure comprehensively depicts the coefficients of variation of C0(T) as a function of x. C0(T) becomes dependent on this optimal x value when x is assumed to be variable. A value of x was obtained for each solvent-rotor combination that minimizes the variability of C0, expressed as its coefficient of variation. The single and unique minima can clearly be seen in this figure. 40

ix 5.13 The figure shows the differences between the optimal x values of the polar protic solvents, and those of the polar aprotic solvents. As you can see, the polar aprotic solvents exhibited a higher optimal exponent x value on average. All of the dyes with the exception of two, CCVJ and Rotor 3, had a P-value (p<0.05), making them significantly different. CCVJ, with a P-value of 0.0572, was not significantly different due to the fact that there are two data points missing on the polar aprotic side. Rotor 3 was not significantly different due to the extreme outlier seen at x=0.43...... 42 5.14 These figures demonstrate the different optimal x values for each solvent-rotor combination. The green bar is set at x = 0.6. It is clear that the optimal x values depart from this value in varying degrees...... 43

x 6.1 This figure depicts three molecular rotors with similar structures. Rotor 4 has one carbon chain, Rotor 5 has two carbon chains, and Rotor 6 has four carbon chains. The top figure depicts the overall increase in exponent x value with the addition of carbon chains. The bottom figure is organized by solvent type and polarity. The group on the left are the polar protic solvents, beginning with the highest dielectric constant (EG) through the lowest (PENT). The second group on the right are the polar aprotic solvents, arranged the same with the highest dielectric constant (PC) at the beginning to the lowest of the polar aprotic solvents (NMP). It is evident that with the polar aprotic solvents decreased polarity leads to decreased x values. However, in the polar aprotic solvents, decreased polarity leads to increased x values. A point of interest is the fact that in the bottom figure, Pentanol seems not to follow the aforementioned decrease, as it is higher than Isopropanol. This can possibly be explained by the fact that Pentanol has a significantly smaller polar section than non-polar section in its molecular structure. This allows for increased van der Waals interaction, meaning more DSE. Isopropanol on the other hand, has somewhat of a compressed structure compared to Pentanol, meaning more hydrogen bonding...... 49 A.1 Viscosity of Ethylene Glycol with respect to change in temperature. The data was fitted using the V-F-T equation...... 54 A.2 Viscosity of Ethanol with respect to change in temperature. The data was fitted using the V-F-T equation...... 55 A.3 Viscosity of Pentanol with respect to change in temperature. The data was fitted using the V-F-T equation...... 55 A.4 Viscosity of DMSO with respect to change in temperature. The data was fitted using the V-F-T equation...... 56

xi A.5 Viscosity of DMF with respect to change in temperature. The data was fitted using the V-F-T equation...... 56 A.6 Viscosity of Propylene Carbonate with respect to change in temperature. The data was fitted using the V-F-T equation...... 57 A.7 Viscosity of NMP with respect to change in temperature. The data was fitted using the V-F-T equation...... 57

xii List of Tables

5.1 Values of A, B, and C for each solvent ﬁtted with V-F-T...... 29 5.2 Optimal x values for each solvent-dye combination...... 32 5.3 Average value of C0(T) using the optimal exponent x value...... 32 5.4 Coeﬃcient of variation values for each solvent-dye combination for x = 0.6. . 41

xiii List Of Abbreviations And Symbols

TICT- Twisted Intramolecular Charge Transfer

La,Lb-orbital conﬁgurations of local states DMABN-p-N,N-dimethylamino-benzonitrile CCVJ, Rotor 2-[9-(2-carboxy-2-cyanovinyl)-julolidine] DCVJ, Rotor 1-[9-(2,2-dicyano-vinyl)-julolidine] Rotor 3-phenyl (E)-1-cyano-2-[4-(dimethylamino)phenyl]ethenesulﬁnate Rotor 4-methyl (2Z)-2-cyano-3-[4-(dimethylamino)phenyl]prop-2-enoate Rotor 5-methyl (2E)-2-cyano-3-[4-(diethylamino)phenyl]prop-2-enoate Rotor 6-methyl (2E)-2-cyano-3-[4-(dibutylamino)phenyl]prop-2-enoate EG-Ethylene Glycol ICT-Intramolecular charge transfer LE-Locally excited LUMO-Lowest Unoccupied Molecular Orbital HOMO-Highest Occupied Molecular Orbital WLF-Model-Williams Landel Ferry Model DSE-Debye-Stokes-Einstein µ-Dynamic viscosity φ-Fluorescent Quantum Yield η-Solvent Viscosity λ-Wavelength - Dielectric constant τ-Lifetime

τn-Natural lifetime

xiv χ-Solvents microfriction ϕ-Angular deviation from the planar state θ-Rotational inertia of the phenyl group x-Dye Dependant Constant C-F¨orster-HoﬀmannProportionality Constant

kf , knf -radiative ﬂuorescence decay rate and non-radiative ﬂuorescence decay rates for LE excited state

0 0 kf , knf -radiative ﬂuorescence decay rate and non-radiative ﬂuorescence decay rates for TICT state ka-constant for forward reaction of TICT formation kd-constant for backward reaction from TICT to LE state kr-rate constant of a radiative event knr-rate constant of a non- radiative event φTICT -TICT state

φLE-Locally excited state

0 τCT barVa-Absorption wavenumber ¯ Vf -Peak ﬂuorescent emission wavenumber h-Plancks constant c-Speed of light n-Refractive index a-Radius of the void volume

µe, µe-Dyes excited and ground state dipole moments D-Diﬀusion constant

xv Chapter 1

Fluorescence Overview

When a molecule enters an excited state, photons are emitted. This photon emission is known as luminescence, and depending on which specific states become excited, luminescence can be separated into the distinct groups of fluorescence and phosphorescence. The process can be referred to as fluorescence when an electron returns from an excited singlet state to the energy level of the ground state, i.e., the lowest energy level. The first excited singlet

state is also known as S1, where the ground state is referred to as S0. As the electron moves

from the S1 state to the S0 state, photon emission can be observed. This pathway of photon emission is known as a radiative event. If a photon is not released en route to the ground

state, the term non-radiative event is appropriate for use. On occasion, the S1 state can

become a triplet state (T1) after excitation, though not favorable. The emission from T1 state is called phosphorescence and the transition from the S1 state to the T1 state is known as intersystem crossing [1]. The various pathways can be seen in the Figure 1.1. Though interesting, phosphorescence is not the focus of the study in this paper and has no relevant effect on the work to be mentioned. The light emitted during fluorescence has a longer wavelength than that of the source of excitation. This is due to the fact that energy is lost in vibrational energy levels during the excited lifetime. Sir G.G. Stokes is credited with the discovery of the difference in the peak absorption and emission wavelengths of the fluorescent sample. He observed that the energy from emission is less than that of absorption. Thus, the difference between the two is called the Stokes Shift seen in Figure 1.2 [1].

1 S2

Internal Conversion

Intersystem Crossing S1 Kisc

1 Fluorescence T

Phosphorescence

Kr Knr

Figure 1.1: In this ﬁgure, the processes occurring between absorption and emission are described by Jablonski. Vertical lines denote transition pathways between states. S0 is referred to as the singlet ground state, S1 and S2 states as the excited states, and T1 the triplet state. Adapted from [1] .

The emission eﬃciency of a ﬂuorophore is known as the quantum yield. That is, the ratio of the number of photons emitted to the number of photons absorbed. Quantum yield can be calculated with the use of Equation 1.1 [1],

k k φ = r ≈ r (1.1) kr + knr + kisc kr + knr where kr is the rate constant of a radiative event and knr is the rate constant of a non- radiative event from the S1 to S0 state. When selecting a fluorophore for a specific purpose, quantum yield is one of the important characteristics to be considered. In steady-state fluorescence, the peak emission intensity is directly proportional to the quantum yield, more specifically,

Iem = Iabs · g · c · φ (1.2)

2 Stokes Shift

Emission Intensity

Excitation

Wavelength of Light

Figure 1.2: In this conceptual ﬁgure, the absorption and emission peaks can be seen. The distance between the two peaks is referred to as Stokes Shift.

where Iabs is the absorbed excitation light, g is the instrument gain, and c is the dye concentration. Equation 1.2 is valid only for low concentrations where the inner-filter effect is negligible [1]. Lifetime is another important attribute, which can be defined as the average time a fluorophore spends in the excited state before its return to the ground state [1]. This characteristic is important due to the fact that it reveals the amount of time that a molecule will have to interact with its environment, and lifetime and quantum yield are closely related [1]. Lifetime is expressed in Equation 1.3 as,

1 τ = (1.3) kr + knr The maximum lifetime of the ﬂuorophore in the absence of non-radiative processes is referred to as the natural lifetime, and is deﬁned as:

3 1 τn = (1.4) kr Substituting Equation 1.3 and 1.4 yields the quantum yield:

τ φ = (1.5) τn

4 Chapter 2

Introduction to Molecular Rotors

2.1 Overview

Molecular rotors are categorized as fluorescent molecules that exhibit a twisting motion when they become excited. An illustration of this motion can be seen in Figure 2.1. These fluorophores are often referred to as twisted intramolecular charge transfer (TICT) molecules due to the fact that they possess the ability of rotational motion along their internal axis. Serving as an additional pathway for electrons which become excited, the observed rotation is considered a non-radiative decay mechanism. Some molecular rotors are simply derivatives of the p-(dialkylamino)-benzylidenemalonitrile group. Electron transfer from the julolidine to the nitrile group accounts for the intramolecular charge transfer mechanism. In the charged state, electrostatic forces cause the molecule to perform an intramolecular twisting motion. It is this rotation, which occurs along the julolidine-vinyl bond, that makes the molecule sensitive to surrounding viscosity: the local free volume is what governs steric hindrance of the molecular rotor. Therefore, as the environmental viscosity increases, intramolecular rotation is hindered and a higher frequency of radiative decay events occur. The first known report of these unique complexes came in 1962 when Ernst Lippert et al. observed that when mixed with polar solvents, dual fluorescence emission in p-N,N- dimethylamino-benzonitrile (DMABN), Figure 2.1, could be seen [3]. Both a regular fluorescence emission and a red-shifted fluorescence emission was observed. Regarding the differences in the two emissions, Lippert et al. offered the explanation that the variation was due to solvent polarity, which in turn could affect the orbital configuration La and Lb of

5 local states. A deexcitation from these two states was ﬁrst used to explain the dual emission, where the La state is mostly seen in polar solvents and Lb in non-polar solvents [3].

Figure 2.1: Chemical Structure of p-N,N-dimethylamino-benzonitrile (DMABN).

An alternative hypothesis came about in 1973 by Rotkiewicz et al. They formulated that a molecule could experience an intramolecular twisting motion, occurring around a single bond [4]. Resulting in variant energies, deexcitation of the fluorophore can arise from either the planar locally excited (LE) state or that of the twisted state. As for the case involving DMABN mentioned previously, the red-shifted emission band that was observed can be described as deexcitation occurring from the twisted state. Just as DMABN exhibited a definite energy change between the LE and the twisted state, this can also occur at a greater level in other molecules such as DCVJ, resulting in deexcitation from the twisted state without emission of a photon [5]. Though many things have the ability to affect a molecular rotor’s twisted-state formation, the strongest influence comes from the physical attributes of the surrounding media. Solvent polarity, along with prevention or obstruction of a chemical reaction caused by the organization of atoms in a certain molecule, or steric hindrance, can influence the twisted- state formation. Solvent polarity tends to enable a dipole orientation alteration, while steric hindrance has the ability to decrease the formation of twisted states in the molecules. The affectibility of these fluorophores in relation to the solvent of which they come into contact, makes them useful and unique molecules [2].

6 Figure 2.2: This ﬁgure illustrates the rotating motion of the molecular rotor, 9-(2,2- Dicyanovinyl) julolidine (DCVJ). The planar state of this molecule is seen in Part 1, where the twisted state of DCVJ can be seen in Part 2 of the ﬁgure.

2.2 Photophysical Characteristics

When considering the influences on twisted state formations of molecular rotors, there exists two notable levels: the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO). As a fluorophore is excited by moving an electron from HOMO to LUMO, an electron is generally promoted to what is referred to as an antibonding state ∗. Employing the π and σ orbitals, fluorescence typically emerges from a transition of π to π∗. Along with this transition, it is also possible for non-bonding n electrons to transition to the antibonding state of π∗ or σ∗. A donor and acceptor group make up the intermolecular charge transfer molecules, which are held together by a π-conjugation system. It is the donor group that is responsible for providing the n-electrons, which are transported to the acceptor’s unoccupied orbitals. Notably, negligible spatial overlap between the donor and acceptor orbitals results from the π-conjugation occurring between the donor and acceptor groups [2]. When the molecule undergoes a promotion to a higher energy level, it may relax to a number of vibrational states before reaching the ground state, emitting a photon. The energy loss can be accounted for in this relaxation, resulting in the wavelength shift referred

7 to previously as Stokes Shift. The twisted state formation can be characterized as the dominant vibrational state, resulting in loss of energy. It is an unbalanced dipole moment that is responsible for the twisting of the molecular rotor. This unbalance leads to a change in conﬁguration which requires the donor group nitrogen to translate from a pyramidal arrange- ment to that of the charge transfer state [6]. Figure 2.3 depicts the TICT molecule’s energy levels. In order to obtain the TICT excitation state, a small amount of energy must be over- come in the LE state, as the molecules are naturally inclined to return to the planar state. Furthermore, any actions delaying the formation of the twisted state, actually result in an overall increase in the energy barrier between the LE state and the TICT state. The solvent media has a great eﬀect on this energy barrier between the LE and TICT states. An example of this would be solvent polarity in the molecular rotor DMABN, which acts to decrease the energy barrier. Conversely, solvent viscosity generally increases the energy barrier for TICT formation in the rotor [7].

Figure 2.3: This diagram illustrates a TICT molecule’s ground and excited-state energies, both in the TICT conﬁguration ϕ2 and in the planar conﬁguration ϕ1. Adapted from [2].

8 As previously stated, return to the ground state through intermolecular rotation conse- quently results in a loss of energy, accounting for the second red-shifted, or solvatochromic shift emission band that is typically observed in aminobenzonitriles. The quantum yield ratio of the TICT and LE states can be determined by the use of both the forward and backward reaction rates. This ratio of the quantum yields can be calculated with the use of Equation 2.1 [8]:

0 φTICT kf ka = · 0 (2.1) φLE kf kd + 1/τCT 0 0 where TICT lifetime is denoted by τCT , kf is the rate of deexcitation from the twisted state, kf is the rate of deexcitation from the LE state, ka is the TICT formation rate from the

LE state, and kd is the rate of the return from the TICT state to the LE state. Relaxation from the TICT state is dominant due to the fact that ka kd the majority of the time. Furthermore, it is the molecular rotors which exhibit deexcitation without radiation that present a low quantum yield [2]. The unique photophysical properties of molecular rotors set them apart from other molecules. Fluorophores have been shown to be intensely sensitive to their local environment [1]. Among other properties, solvent polarity and viscosity can greatly eﬀect the TICT formation, quantum yield, and overall behavior of the molecules. Changes in these environments can alter the output of spectral data, making them useful in many diﬀerent applications.

2.3 Applications of Molecular Rotors

Fluorescent rotor molecules, because of their unique properties and sensitivity to solvent environment, have much to oﬀer the expanding arena of science, medicine and research. One such application is in the form of real time viscosity measurement. Today, measuring viscosity generally comes with a list of restrictions. Whether it be that the instrumentation is costly, that the process is slow and laborious, or that the sample is conﬁned to bulk sizes alone, the mechanism for measuring viscosity is in need of improvement [9]. As mentioned

9 previously, TICT formation in molecular rotors depends upon the viscosity of the environmental solvent. Thus, the emission intensity is viscosity-dependent, making these molecules an attractive avenue for viscosity measurement. Other applications such as polymerization dynamics probes, protein sensing and microviscosity probes are promising ﬁelds for molecular rotor application [2]. If these molecules are to be practically applied in the arenas of science and medicine, their behavior needs to be well-documented and understood.

10 Chapter 3

Environmental and Solvent Effects on Molecular Rotors

3.1 Polarity of the Solvent

As mentioned previously, polarity of the surrounding environment of the solvent can greatly influence the emission properties of molecular rotors. As the polarity of the solvent increases, the molecule’s emission occurs at a lower energy, or a longer wavelength. In most cases, the polarity of the molecule itself determines the sensitivity to the polarity of the solvent. Polar molecules tend to be affected more by polar solvents than do non-polar molecules. Spectral shifts are one consequence of the polarity of a solvent in which a molecular rotor is dissolved [1]. The polarity of a solvent leads to overall energy loss, and the magnitude of this effect is dependent upon the solvent’s dielectric constant . This loss of energy is characterized in Equation 3.1, known as the Lippert-Mantaga equation [1]:

2 − 1 n2 − 1 µ − µ V¯ − V¯ = · − · e 0 (3.1) a f hc 2 + 1 2n2 + 1 a3 ¯ ¯ where Va is the absorption wavenumber, Vf is the peak ﬂuorescent emission wavenumber, h is Planck’s constant, c is the speed of light, n is the refractive index, a is the radius of the void volume where the rotor is located, and µe and µ0 are the dye’s excited and ground state dipole moments respectively. Intramolecular charge transfer molecules are especially characterized by a major increase in the dipole moment in the excited state. DCVJ, for example, approximately triples in dipole moment after photoexcitation.

11 3.2 Viscosity of the Solvent

Emission intensity of the fluorophores can be vastly affected by solvent viscosity. An example of this effect was explored by Sumitani et al. in 1977 when they demonstrated that the intensity decays of stilbene were dependent on temperature [10]. Viscosity generally refers to the bulk property; however, molecular rotors are affected by solvent viscosity on a molecular scale. The Stokes-Einstein relationship connects the bulk viscosity to the diffu- sivity of the fluorophore. In terms of the Debye-Stokes-Einstein diffusion theory, the diffusion constant D is inversely proportional to the bulk viscosity η of the solvent [2]. This characteristic of molecular rotors was investigated by Försterand Hoffmann in 1971. Through examining various triphenylmethane dyes, they were able to recognize a power-law relationship between quantum yield and solvent viscosity. This was achieved both through experimentation and analytically, as they observed that triphenylmethane dyes in high viscosity solvents presented higher quantum yield, and those in solvents of lower viscosity expressed lower quantum yield values [11]. The mathematical equation relating quantum yield and solvent viscosity can be seen in the Förster-Hoffmannequation (Equation 3.12).

Figure 3.1: Structure of Crystal Violet, a triphenylmethane dye.

Försterand Hoffmann begin their derivation [11, 2] of the power-law relationship by introducing a definition of the solvent’s microfriction χ in terms of the Debye-Stokes-Einstein (DSE) equation (Equation 3.2),

12 χ = 8πr3η (3.2) where χ is the solvent’s microfriction, η is the bulk viscosity of the particular solvent, and r is the effective radius of thetriphenylamine dye’s phenyl group. The differential equation of rotation (Equation 3.3) interprets each of the three arms of the dye which are considered by Försterand Hoffmann as rotational masses, which obey the classical differential equation of motion,

d2ϕ dϕ Θ + χ + α(ϕ − ϕ ) = 0 (3.3) dt2 dt 0 where ϕ is the angular deviation from the planar state ϕ0, α is the spring constant of an imaginary spring that models the energy difference between the twisted and planar state, Θ is rotational inertia of the phenyl group, and χ is again the coefficient of microfriction. When this coefficient is large, χ24χΘ, the phenyl group comes back from its angle of deflection

ϕ to the planar state ϕ0. This process can be described with exponential dynamics related in Equation 3.4,

t ϕ(t) = δexp − + ϕ (3.4) T ∗ 0 where δ is known as the diﬀerence in the rotational angles assumed for the minimum S1 energy

∗ ∗ and S0 energy, and T is the relaxation time constant, T =χ/α. The time of relaxation is dependent on the solvent’s microviscosity and electrostatic forces. Försterand Hoffmann describe the rate of the deactivation processes by defining a function B(ϕ). This is done in order to relate the probability of the dye being in the excited state to the relaxation time,

∗ 2 T . The function is given as B(ϕ) = β(ϕ − ϕ0) where β acts as a proportionality constant. With this deﬁnition the probability %(t) that the molecule is in an excited state can be described by the diﬀerential equation (Equation 3.5),

d% 1 − = + B(ϕ) %(t) (3.5) dt τs 13 where τs is referred to as the dye lifetime without presence of rotational deexcitation. F¨orster

and Hoﬀmann gave a value of τs = 1 ns. The dye’s quantum yield φF is deﬁned in Equation 3.6.

1 Z ∞ φF = %(t)dt (3.6) τ0 0

In Equation 3.6, τ0 can be understood as the natural lifetime in the absence of non-radiative

relaxation events [2]. τ0 = 2 ns is a value that is normally given [11]. Equation 3.7 is a combination of Equations 3.4 and 3.5:

d%(t) 1 t 2 − = + β · δ · 1 − exp(− ∗ ) %(t) (3.7) dt τs T The solution of Equation 3.7 can be simpliﬁed by considering three special cases when the solvent viscosity is very low, of intermediate viscosities, and very high. The ﬁrst case to consider is when the solvent viscosity is very low. When the case of very low viscosity occurs, the quantum yield is minimized and becomes solvent-independent (Equation 3.8):

1 φF ≈ 2 (3.8) β · τ0 · δ In contrast, when the viscosity of the solvent is very high, minimization of nonradiative decay occurs. In this case, the quantum yield follows Equation 3.9:

2 τs 6σ φF ≈ 1 − 2 (3.9) τ0 η where σ represents a constant which is dye-dependent, containing all viscosity-independent

variables (α, β, δ, r, and τs) as deﬁned in Equation 3.10,

α2 β δ2 τ3 1/2 σ = s (3.10) 192π2 r6 The dye-dependent constant σ is measured in units of viscosity, with a typical value of σ = 100 Pa s. This value follows the assumption that the phenyl group size is r ≈ 2x10−10 m,

14 and the resulting energy from the potential diﬀerences α ≈ 10−9 J. It can be observed that

the maximum quantum yield in the case of Equation 3.9 for η σ is φF ≈ τs/τ0. For cases where η σ, Equation 3.11 results from the simpliﬁed version of Equation 3.6. This is the most important case because it deals with intermediate values of viscosity.

2/3 τs η φF ≈ 0.893 · (3.11) τ0 σ The dye-dependent constants found in Equation 3.11 can be ascertained by experimentation; therefore, they can be combined into one constant C observed in Equation 3.12,

x φF = C · η (3.12) which is commonly referred to as the Förster-Hoffmannequation, relating viscosity and quantum yield. For simplicity, all variables are considered to be unitless in Equation 3.12. The case of x ≡ 2/3 as a fixed value comes from the Equation 3.6 solution when η σ. It is possible for experimental results to yield x values which are either higher or lower [2].

3.3 Effects of Temperature

Regarding the interaction between quantum yield and viscosity, the assumption made by Loutfy et al. was that the rotational reorientation rate kor was proportional to D, which is the diffusion constant of the rotor in a solvent [12, 13, 14]. This diffusion constant D is defined in the Debye-Stokes-Einstein (DSE) model as,

1 kT D = · (3.13) 6V sg η where T is the absolute temperature, k is Boltzmann’s constant, η is the viscosity of the solvent, V is the ﬂuorescent dye volume, s represents the boundary condition, and g represents the shape factor. In the case where the rotational diﬀusion overcomes the reorientation rate, Equation 3.14 is true:

15 kT k ∝ D ∝ (3.14) or η Though some literature seems to validate Equation 3.14 [15], deviations from this model have been recognized. Through analysis of the behavior of the temperature-dependent emission of molecular rotors combined with various solvents, Loutfy and Arnold [14] discovered that the reorientation rate exhibited behavior corresponding to the Gierer-Wirtz model [16] shown in Equation 3.15,

η η 1−x k = a + b (3.15) or T T where a and b are constants. The treatment by Gierer and Wirtz deviates from the continuum model in the DSE theory by modeling the solvent and solute as layers of ﬁnite-sized spheres. Furthermore, Doolittle related free volume and viscosity empirically in Equation 3.16:

V η = A · exp B o (3.16) Vf where A and B are experimental constants, Vo is the van der Waals volume of the ﬂuid, and

Vf is the ﬂuid free volume. In assuming this diﬀerent interaction, the relationship between quantum yield and viscosity in terms of free volume was investigated by Loutfy and Arnold [14]. In their paper, they plotted the quantum yield (log scale) over the free volume (lin scale) and found straight lines. It was this observation which ultimately led Loutfy and Arnold to conclude that the quantum yield follows a power-law relationship with free volume, namely,

kr x φF = ◦ exp(Vo/Vf ) (3.17) knr ◦ where knr is the free-rotor reorientation rate, Vo is the van der Waals volume of the solvent and Vf is the solvent volume. Using Doolittle’s equation [17] (Equation 3.16) to replace the free-volume term by viscosity, they arrived at the power-law relationship:

16 x kr η φF = ◦ (3.18) knr A ◦ x where kr, knr, and A are solvent-independent constants and can be combined into a dye- dependent constant, displayed in Equation 3.12. Another related point of interest is that of thermal linear expansion. This well-known concept, deﬁned as the change in a molecule’s linear dimensions in relation to a change in temperature, is shown in Equation 3.19:

Vf = Vg + α(T − Tg) (3.19)

where Vf is the ﬁnal volume, Vg is the volume at the glass transition temperature, α is the

thermal expansion coeﬃcient, T is temperature, and Tg is the glass transition temperature. If substituted into the Doolittle equation (Equation 3.16), this leads immediately to the Vogel- Fulcher-Tammann (VFT) model [18, 19]. The original form of the VFT equation can be found in Equation 3.20,

Vg η(T ) = η0 · exp (3.20) Vg + α(T − Tg)

where η0 is an inherent viscosity, Vg is the volume at the glass-transition temperature, α is

the linear thermal expansion coeﬃcient, and Tg is the glass transition temperature. Thus, any change in the reorientation with temperature rate should be explained by the temperature- related change in viscosity. To validate the this assumption, Loutfy and Arnold created an auxiliary constant B, deﬁned as:

x kr T B = ◦ · (3.21) knr A This constant is used in their equation relating the dye ﬂuorescence quantum yield and the viscosity of the solvent seen in Equation 3.22.

η x φ = B (3.22) F T 17 This power-law relationship appears to have a temperature-dependent constant C. This ambiguity was carried further by Sava Lukac in 1984. As you can see in Equation 3.23, Lukac did not even account for viscosity.

E k = Aexp A (3.23) or kT

This absence leads to the assumption that there exists a temperature-driven rotation rate kor [20]. If this assumption is correct, the quantum yield becomes highly temperature-dependent, too:

k k E φ = r = r · − A (3.24) knr A kT This direct temperature-dependency would compete with the viscosity-driven change in quantum yield described in Equation 3.12. In the next chapter we will explore this incon- clusiveness further through investigating the temperature-dependent behavior of the components of the power-law relationship seen in Equation 3.12.

18 Chapter 4

Materials and Methods

4.1 Experimental Design

This project was designed to investigate the behavior of the constants C and x (Equation 3.12) with respect to change in temperature. Little work has been completed to explore the inﬂuence of these constants on ﬂuorescent quantum yield. In search of a better and more complete understanding of their behavior, this study aims to examine the standing hypothesis of a temperature-driven reorientation rate in molecular rotors. Furthermore, exponent x values have yet to be thoroughly considered. Hence, this project was further expanded to explore an optimal x value for each solvent-rotor combination. With the use of our own empirical values of C, we will investigate the intrinsic temperature-dependence of molecular rotors.

4.2 Solvents and Molecular Rotors

Eight solvents in all were used, both of polar protic and polar aprotic type. Polar protic solvents possess an acidic hydrogen and display hydrogen bonding. In general, these types of solvents demonstrate low dielectric constants and low polarity. On the other hand, polar aprotic solvents do not possess an acidic hydrogen, nor do they display hydrogen bonding, generally providing them with a high dielectric constant and high polarity. The polar protic solvents that were employed included Isopropanol, Ethylene Glycol, Ethanol, and Pentanol. The polar aprotic solvents included Dimethyl sulfoxide (DMSO), Dimethylfor- mamide (DMF), Propylene Carbonate, and N-Methyl-2-pyrrolidone (NMP). These solvents were chosen because of their Newtonian nature and their reasonable viscosity ranges.

19 Six molecular rotors, whose structures can be seen in Figure 4.1, 9-(2,2-Dicyanovinyl) julolidine (DCVJ, Molecule 1), 9-(2-Carboxy-2-cyanovinyl) julolidine (CCVJ, 2), phenyl (E)-1-cyano-2-[4-(dimethylamino)phenyl]ethenesulﬁnate (3), methyl (2Z)-2-cyano-3-[4- (dimethylamino)phenyl]prop-2-enoate (4), methyl (2E)-2-cyano-3-[4-(diethylamino)phenyl]prop- 2-enoate (5), and methyl (2E)-2-cyano-3-[4-(dibutylamino)phenyl]prop-2-enoate (6) were also used. These rotors were combined with each solvent independently, creating a solvent- dye mixture.

1 2 3

4 5 6

Figure 4.1: Chemical structures of the molecular rotors, DCVJ (1), CCVJ (2), Rotor 3 (3), Rotor 4 (4), Rotor 5 (5), and Rotor 6 (6).

4.3 Measuring Viscosity

The viscosity of the various solvents was measured using a Brookﬁeld DV III+ cone- and-plate Rheometer seen in Figure 4.2. With the use of a pipette, 800µL of each solvent was distributed into the device cone. With the machine connected to a water bath, the temperature was steadily increased in 3◦ increments from 15 to 45◦C. At each 3◦ increment, viscosity was measured and recorded using the Brookﬁeld Rheocalc v2.3 software, which controlled all aspects of testing. Nine data points were collected, four increasing to the highest torque, one at the highest torque, and then four decreasing to the lowest torque. Due

20 to machine limitations and to ensure the least amount of experimental error, the two lowest torque data outputs were excluded. The remaining seven points were then averaged. The viscosity data measured in mPa s, for each temperature was ﬁtted by nonlinear regression using a form of the Vogel-Fulcher-Tammann equation (Equation 4.1). The original V-F-T equation can be seen in Equation 3.20.

B η(T ) = exp A + (4.1) C + T where η(T) is temperature-dependent viscosity, T is temperature, and A, B, and C are constants.

Figure 4.2: Brookﬁeld DV III+ cone-and-plate Rheometer.

21 Figure 4.3: In this photo the distinct components of the Rheometer are shown. The spindle is connected to the cone feature, which is the turning feature controlling the torque. The white cord, which is plugged into the sample cup, reports the precise temperature of the liquid in the cup. On the cup component, you can see the two hose attachments. These were used to circulate water from a water bath around the sample cup, controlling the temperature of the sample inside.

4.4 Measuring Fluorescent Intensity Emission

Six molecular rotors, 9-(2,2-Dicyanovinyl) julolidine (DCVJ), 9-(2-Carboxy-2-cyanovinyl) julolidin (CCVJ), Phenyl (E)-1-cyano-2-[4-(dimethylamino)phenyl]ethenesulﬁnate (3), Methyl (2Z)-2-cyano-3-[4-(dimethylamino)phenyl]prop-2-enoate (4), Methyl (2E)-2-cyano-3- [4-(diethylamino)phenyl]prop-2-enoate (5), Methyl (2E)-2-cyano-3-[4-(dibutylamino)phenyl]prop- 2-enoate (6), all of lab stock dissolved in DMSO, were independently and thoroughly combined with each of the eight ﬂuorescence-grade solvents. With the use of a pipette, 20 µL of 5mM stock DCVJ was added to 10mL of each solvent, resulting in 10µM DCVJ in solvent

22 solution. The same method was employed to obtain a 10µM concentration of all other solvent-dye solutions. The mixtures were then measured into a screw-top glass cuvette. The cuvette was then placed into the fluorometer, where it was allowed 10 minutes to reach the desired starting temperature of 15◦C. After the desired temperature was reached, the intensities of each fluorescent-dye mixture was measured using a Spex Fluoromax-3 Fluo- rophotometer (Figure 4.5). The optimal excitation and emission output was found using the fluorometer, and following those acquisitions, a time-based acquisition scan was performed. With the use of a water bath, the temperature was increased in increments of 3◦ from 15◦ to 45◦C every 900 seconds under complete control. Over a time span of 9900 seconds, an intensity time-course for each solvent-rotor solution was obtained. With the resulting data, the intensity for each degree-increment platform was collected by taking the average of the intensity data of the last 200 seconds at each temperature. Taking the last 200 seconds of the data time-course helped to ensure that the solvent-rotor combination, as well as the fluorometer had time to stabilize fully at each selected temperature. The resulting averages were then plotted with the use of Graphpad Prism version 5.0. Due to solvent and dye properties and machine limitation, one constant setting for excitation and emission slits on the Fluorometer could not be used. The slit setting merely determines how much light can pass through the sample. As the number of the slit setting increases, the amount of light enabled to pass increases as well. Larger slit settings leads to a higher fluorescent output. Therefore, slit settings of 3/3, 4/4, and 5/5 were all utilized throughout the project. Though most of the solvent-dye solutions required the use of the slit setting 4/4 (excitation slit setting at four and emission slit setting at four), there were some that did not fit that regimen. To accommodate for the differences, normalizing values were determined by selecting a few rotor-solvent combinations and running an emission acquisition scan at optimal excitation values on the Fluorometer. Three scans were completed, one at slit setting 3/3, one at 4/4, and the last at 5/5. After compiling all of the data, ratios

23 were calculated. α represents the shift from 5/5 slits to 4/4 slits (Equation 4.2), where β represents the shift from 3/3 to 4/4 slits (Equation 4.3).

I α = 4/4 (4.2) I5/5

I β = 4/4 (4.3) I3/3

I4/4 is the intensity output at slit setting 4/4, I5/5 is the intensity output at slit setting 5/5, and lastly I3/3 is the intensity output at slit setting 3/3. After averaging the ratios that were calculated for α from all of the rotor-dye combinations, and then doing the same for β, normalizing values were found. When transitioning from 3/3 slit setting to 4/4 slit setting, a value of 2.94 was multiplied by the intensity output. When transitioning from a slit setting of 5/5 to a slit setting of 4/4, a value of 0.42 was multiplied by the intensity output. Thus, all intensity data was corrected to a 4/4 slit setting.

4.0 3.5 3.0 2.5 2.0 1.5 1.0

Normalization value Normalization 0.5 0.0 α β Parameter constant

Figure 4.4: In this ﬁgure you can see the scatter plots for α and β. As you will notice, the data points for both α and β are extremely close together, meaning that the ratio of slit settings for diﬀerent rotor-dye combinations were similar.

24 Figure 4.5: In this ﬁgure is a photo of the Spex Fluoromax-3 Fluorophotometer that we used in this project. The section highlighted in yellow is the connection to the water bath where water acting as a coolant is circulated through. The area highlighted in green is the connection for the automated temperature control device, which maintained and altered the temperature of the sample solution.

4.5 Finding C0

As previously mentioned, there exists a power-law relationship between the quantum yield of a molecular rotor and viscosity of a solvent [11]. This is shown in Equation 4.4, a form of the F¨orster-Hoﬀmannequation seen in Equation 3.12.

logφ = C + x · logη (4.4)

where φ represents quantum yield, C is a supposed temperature-dependent constant, x is a supposed dye-speciﬁc constant, and η is the viscosity [13]. Due to the fact that viscosity is temperature-dependent and φ is proportional to intensity (Equation 1.2), the equation becomes:

log(I) = logC0 + x · logη(T ) (4.5)

25 where C0 is a term which includes the proportionality constant between intensity and φ, and η(T ) represents temperature-dependent viscosity. It has been suggested that both the constant C and viscosity can inﬂuence intensity [14]. Therefore, after solving for C0 the equation becomes:

logC0 = log(I) − x · logη(T ) (4.6)

Using x = 0.6 for all solvent-dye calculations [11], the equation then becomes:

I C0 = (4.7) η0.6 With the viscosity-adjusted data, the inﬂuence of the solvents on the mobility of rotation can be seen. According to some literature [14], C0 should ﬁt an Arrhenius function such as:

E C0(T ) = a · exp − A (4.8) kT

where EA = activation energy, k = Boltzmann’s constant, and T = temperature.

4.6 Determining Optimal x Values

Determined in the derivation by Försterand Hoffmann given previously, the constant C is defined with the use of the physical properties of the molecular rotor. The value x ≡ 2/3 is reached by an integration step. Furthermore, empirical derivations reached by Loutfy et al. lead to the conclusion that the constant C is dependent on both the solvent and the molecular rotor. Here, the exponent x is experimentally determined [14]. In our search of an optimal x value for each solvent-dye mixture, the coefficient of variation (CV) of C0 was minimized. The ”optimal” value of x was defined as that value of x which minimized the temperature-dependent variation of C0. CV, defined as the ratio of the standard deviation to the mean of the sample, can be seen in Equation 4.9. A function of the CV for different values of x was found, determining the optimal x. Coefficients of variation were also found for each solvent-rotor combination when x = 0.6.

26 σ CV = · 100 (4.9) µ where σ is the standard deviation and µ is the mean of each set of C0(T).

27 Chapter 5

Results

5.1 Viscosity and Temperature

All eight of the solvents followed the expected decrease in viscosity with the increase of temperature, an example of which is shown in Figure 5.1. Each data set was ﬁtted with the Vogel-Fulcher-Tammann (VFT) equation mentioned previously in Equation 3.20 and its empirical form, Equation 3.20.

Isopropanol 3.0

2.5 R square=0.9935 A ~ -10.45 2.0 B ~ 3851 C ~ 319.9 1.5

Viscosity 1.0

0.5 Y=exp(A+B/(C+x)) 0.0 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure 5.1: Viscosity of Isopropanol with respect to change in temperature. The data was ﬁtted using the V-F-T equation, Equation 3.20.

28 Table 5.1: Values of A, B, and C for each solvent ﬁtted with V-F-T.

A B C ISO -10.45 3851.00 319.90 EG -3.53 926.60 120.80 ETH -20.57 20756.00 976.10 PENT -5.700 1600.00 204.00 DMSO -5.41 1800.00 266.10 DMF -2.683 540.20 183.70 PC -3.01 724.20 159.60 NMP -3.04 781.90 191.30

5.2 Intensity and Temperature

The DCVJ-, 3-, 4- 5-, and 6-solvent mixtures showed a decrease in ﬂuorescent intensity with the increase in temperature as predicted [9]. As an example, a graph of the intensity time-course for Isopropanol and DCVJ can be seen in Figure 5.2. As for the solvent-CCVJ mixtures, all with the exception of two solvent-dye solutions, followed the same decrease in intensity as the temperature was increased. DMF and NMP, not showing the expected decrease, instead showed an increase in intensity. The relationship between intensity and change in temperature can be seen in Figure 5.3, and the relationship between intensity and change in viscosity can be seen in Figure 5.4.

5.3 C0 Values

C0 was carefully calculated for each solvent-ﬂuorescent dye solution. As hypothesized, no uniform trend was evident between the calculated C0 and temperature. There was, however, somewhat of a trend observed between polar protic and polar aprotic solvent-dye mixtures. This trend was more strongly represented in the polar aprotic solvents than in the polar

29 3.5×100 6

3.0×100 6

15°C 18°C 21°C 42°C 45°C 2.5×100 6

0 6

Intensity (cps) Intensity 2.0×10

1.5×100 6 0 900 1800 2700 3600 4500 5400 6300 7200 8100 9000 9900 Time (seconds)

Figure 5.2: Intensity time-course of Isopropanol mixed with DCVJ. This graph depicts the decrease in intensity with the increase in temperature.

protic solvents. The C0 values of the polar aprotic solvents were also higher on average than those of the polar protic type. In an eﬀort to simplify the data, all C0 values were divided by 106. With DCVJ, the C0 values ranged from 0.4 to 1.3, showing no consistent tendencies. The calculated values of CCVJ with respect to temperature were higher, ranging from 1.2 to 4.0, also showing no overwhelming consistency. Both 3 and 6 revealed values ranging from around 1.3 to 3.0. Furthermore, the 4-solvent mixtures showed C’ values from 0.7 to 2.0, and the 5-solvent mixtures reported values from 0.7 to 1.3. All of these values are represented in Figure 5.5.

5.4 X Values

Though x = 0.6 was used for our calculations to calculate C0 [11], we wanted to see if there was a value of x which minimized the variation of C0 in relation to temperature. Upon minimization of the coeﬃcient of variation for each solvent-dye solution, the optimal x value was determined for each sample. The optimal x values for DCVJ ranged from 0.5 to 1.1, with coeﬃcients of variation ranging from 0.22 to 0.96. The cumulative results of

30 3.3×100 6

3.0×100 6

2.8×100 6

2.5×100 6

2.3×100 6

2.0×100 6 Average Intensity (cps) Intensity Average 1.8×100 6 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C°)

Figure 5.3: This graph shows the relationship between ﬂuorescent intensity and change in temperature. As you can see, there is a decrease in intensity as temperature increases.

the optimal x-value for the remaining dyes were similar, ranging from 0.43 to 1.2, with coefficients of variation ranging from 0.18 to 1.7. One extreme outlier was observed in the DMF-3 mixture. All of the other solvent-3 solutions reported optimal x values close to 1.0; however, the DMF-3 combination reported an optimal x value of 0.43. Taking into account all of the solvent-dye solutions, the polar aprotic solvents exhibited higher optimal x values on average than did the polar protic solvents. Furthermore, the determined optimal x values varied distinctly with each solvent. Exact optimal x values for each sample can be seen in Table 5.2. The coefficients of variation, which were all extremely low for each optimal x, are reported in Figure 5.12. The coefficients of variation for x = 0.6 for each solvent-dye combination can be seen in Table 5.4.

31 1.8×100 6

1.6×100 6

1.4×100 6

1.2×100 6

Intensity (cps) Intensity 1000000

800000 3.0 2.5 2.0 1.5 1.0 Viscosity (mpa s)

Figure 5.4: This graph demonstrates the relationship between intensity and viscosity. As viscosity of the solvent decreases, intensity also decreases.

Table 5.2: Optimal x values for each solvent-dye combination.

ISO EG ETH PENT DMSO DMF PC NMP DCVJ 0.50 0.77 0.67 0.56 0.91 1.10 0.78 1.00 CCVJ 0.60 0.83 0.69 0.52 0.94 — 0.91 — 3 0.59 0.88 0.81 0.75 0.92 0.43 0.90 1.20 4 0.49 0.79 0.68 0.65 0.88 1.10 0.88 1.10 5 0.52 0.78 0.72 0.66 0.90 0.93 0.80 1.10 6 0.57 0.84 0.75 0.71 0.98 1.20 0.94 1.10

Table 5.3: Average value of C0(T) using the optimal exponent x value.

ISO EG ETH PENT DMSO DMF PC NMP DCVJ 0.38 0.29 0.66 0.57 0.39 0.93 1.02 0.83 CCVJ 1.22 1.86 1.42 2.18 1.43 — 1.55 — 3 1.79 0.98 1.77 1.41 1.31 1.57 1.48 1.95 4 0.76 0.46 0.93 0.67 1.05 1.81 1.00 1.39 5 0.83 0.74 0.94 0.56 0.81 1.26 0.85 0.67 6 1.99 1.31 1.62 1.08 1.51 2.79 1.52 1.94

32 DCVJ CCVJ ISOPROPANOL 4.0 ETHYLENE GLYCOL 4.0 ETHANOL 3.5 DMSO 3.5 3.0 PENTANOL DMF 3.0 2.5 PROPYLENE CARBONATE 2.5 NMP C’ 2.0 C’ 2.0 1.5 1.5 1.0 1.0 0.5 0.5 0.0 0.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

(a) DCVJ (b) CCVJ

4.0 4.0 3.5 3.5 3.0 3.0 2.5 2.5 2.0 C’ 2.0 C’ 1.5 1.5 1.0 1.0 0.5 0.5 0.0 0.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48

4.0 4.0 3.5 3.5 3.0 3.0 2.5 2.5

C’ 2.0 C’ 2.0 1.5 1.5 1.0 1.0 0.5 0.5 0.0 0.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature(°C) Temperature(°C)

(e) 5 (f) 6

Figure 5.5: These graphs depict the C0 values for each solvent-rotor combination. As you can see, C0 values varied with each solvent-rotor solution. The polar aprotic solvents (seen in red/orange colors) demonstrated more consistency than polar aprotic solvent (seen in blue/purple). However, this was not always the case.

33 DCVJ

Isopropanol Ethylene Glycol

1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8

C’ C’ 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C°) Temperature (C°)

Ethanol Pentanol

1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9

C’ 0.8 C’ 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C°) Temperature (C°)

DMSO DMF

1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9

C’ 0.8 C’ 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C°) Temperature (C°)

Propylene Carbonate NMP

1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9

C’ 0.8 C’ 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C°) Temperature (C°)

Figure 5.6: To demonstrate the different trends of the C0 values, individual measurements of C0(T) are shown in this figure for DCVJ. From this figure it becomes evident that no uniform trend exists. As you can see, C0 increases with respect to temperature in the case of Isopropanol, remains almost constant in Pentanol, and decreases in the case of DMF.

34 CCVJ

Isopropanol Ethylene Glycol

4.0 4.0

3.5 3.5

3.0 3.0

C’ 2.5 C’ 2.5

2.0 2.0

1.5 1.5

1.0 1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C ) Temperature (C )

Ethanol Pentanol

4.0 4.0

3.5 3.5

3.0 3.0 C’ C’ 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C ) Temperature (C )

DMSO Propylene Carbonate

4.0 4.0

3.5 3.5

3.0 3.0

C’ 2.5 C’ 2.5

2.0 2.0

1.5 1.5

1.0 1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C ) Temperature (C )

Figure 5.7: Like Figure 5.6, the different shapes and tendencies of the C0 in CCVJ are seen in this figure. Interestingly, C0 in the case of Ethanol demonstrates a minimum at the apparent preferred temperature, 30◦C. This case cannot be justified with any known theory, all of which suggest either monotonically increasing or decreasing trends.

35 Rotor 3 Isopropanol Ethylene Glycol

3.05 3.05 2.80 2.80 2.55 2.55 2.30 2.30 C’ C’ 2.05 2.05 1.80 1.80 1.55 1.55 1.30 1.30 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Ethanol Pentanol

3.00 3.05 2.75 2.80 2.50 2.55 2.25 2.30 C’ C’ 2.00 2.05 1.75 1.80 1.50 1.55 1.30 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

DMSO DMF

Propylene Carbonate NMP

Figure 5.8: This ﬁgure, showing all of the C0 values in 3, further demonstrates the changing shapes and tendencies with respect to temperature. Notably, Pentanol shows the same deviation as it did in CCVJ at 42◦. This could possibly be explained by experimental error; however, this deviation is not seen in DCVJ.

36 Rotor 4 Isopropanol Ethylene Glycol 2.10 2.10

1.85 1.85

1.60 1.60 C’ C’ 1.35 1.35

1.10 1.10

0.85 0.85

0.60 0.60 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Ethanol Pentanol 2.10 2.10

1.85 1.85

1.60 1.60

C’ 1.35 C’ 1.35

1.10 1.10

0.85 0.85

0.60 0.60 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

DMSO DMF 2.10 2.10

1.85 1.85

1.60 1.60

C’ 1.35 C’ 1.35

1.10 1.10

0.85 0.85

0.60 0.60 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Propylene Carbonate NMP 2.10 2.10

1.85 1.85

1.60 1.60

C’ 1.35 C’ 1.35

1.10 1.10

0.85 0.85

0.60 0.60 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Figure 5.9: Here, all C0 values are shown with 4. It is evident that no steady trend can be deciphered with respect to the change in temperature. In this molecular rotor, DMSO shows a deﬁnite increase, Isopropanol a slight increase, where in the other four dyes, a decrease in relation to temperature is observed.

37 Rotor 5 Isopropanol Ethylene Glycol

1.45 1.45 1.35 1.35 1.25 1.25 1.15 1.15 1.05 1.05 C’ C’ 0.95 0.95 0.85 0.85 0.75 0.75 0.65 0.65 0.55 0.55 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Ethanol Pentanol

DMSO DMF

Propylene Carbonate NMP

Figure 5.10: 5 C0 values are reported in this ﬁgure. Here, DMF exhibits an observed minimum at 30◦. As in the case of Ethanol in CCVJ, no explanation for this U-shape exists in current literature.

38 Rotor 6 Isopropanol Ethylene Glycol

2.85 2.85 2.60 2.60 2.35 2.35 2.10 2.10 C’ C’ 1.85 1.85 1.60 1.60 1.35 1.35 1.10 1.10 12 15 18 21 24 27 30 33 36 39 42 45 48 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C) Temperature (°C)

Ethanol Pentanol

DMSO DMF

Propylene Carbonate NMP

Figure 5.11: Like in the ﬁgures mentioned above, no consistent trends can be deciphered from this ﬁgure. Isopropanol shows a slight increase in 6, where Pentanol moves more toward constant.

39 Isopropanol Ethylene Glycol 0.3 DCVJ 0.3 CCVJ Rotor 3 0.2 0.2 Rotor 4 Rotor 5 C.V. C.V. Rotor 6 0.1 0.1

0.0 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 x x

Ethanol Pentanol 0.3 0.3

0.2 0.2 C.V. C.V. 0.1 0.1

0.0 0.0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 X X

Dimethyl sulfoxide Dimethylformamide 0.3 0.3

0.2 0.2 C.V. C.V. 0.1 0.1

0.0 0.0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 0.0 0.5 1.0 1.5 2.0 X X

N-Methyl-2-pyrrolidone Propylene Carbonate 0.3 0.3

0.2 0.2 C.V. C.V. 0.1 0.1

0.0 0.0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 X X

Figure 5.12: This figure comprehensively depicts the coefficients of variation of C0(T) as a function of x. C0(T) becomes dependent on this optimal x value when x is assumed to be variable. A value of x was obtained for each solvent-rotor combination that minimizes the variability of C0, expressed as its coefficient of variation. The single and unique minima can clearly be seen in this figure. 40 Table 5.4: Coefficient of variation values for each solvent-dye combination for x = 0.6.

ISO EG ETH PENT DMSO DMF PC NMP DCVJ 3.27 7.01 1.55 1.27 6.41 5.37 3.56 7.15 CCVJ 0.82 9.74 4.26 2.69 7.16 —- 6.36 —- 3 6.71 11.57 4.64 1.75 6.42 5.55 6.08 9.69 4 3.55 7.96 1.85 1.95 5.85 5.54 5.62 8.62 5 2.66 7.32 2.87 2.18 6.24 4.63 4.11 8.37 6 1.01 9.92 3.24 3.53 7.88 7.92 6.91 8.76

41 DCVJ CCVJ

1.3 1.3 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 x 0.7 x 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 Polar Protic Polar Aprotic Polar Protic Polar Aprotic

Rotor 3 Rotor 4

1.3 1.3 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 x x 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 Polar Protic Polar Aprotic Polar Protic Polar Aprotic

Rotor 5 Rotor 6

1.3 1.3 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 x x 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 Polar Protic Polar Aprotic Polar Protic Polar Aprotic

Figure 5.13: The figure shows the differences between the optimal x values of the polar protic solvents, and those of the polar aprotic solvents. As you can see, the polar aprotic solvents exhibited a higher optimal exponent x value on average. All of the dyes with the exception of two, CCVJ and Rotor 3, had a P-value (p<0.05), making them significantly different. CCVJ, with a P-value of 0.0572, was not significantly different due to the fact that there are two data points missing on the polar aprotic side. Rotor 3 was not significantly different due to the extreme outlier seen at x=0.43.

42 Polar Protic CCVJ DCVJ Polar Aprotic 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 x 0.6 x = 0.6

x 0.6 x = 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0

DMF NMP DMSO DMSO ETHANOL ETHANOL PENTANOL PENTANOL ISOPROPANOL ISOPROPANOL

ETHYLENE GLYCOL ETHYLENE GLYCOL

PROPYLENE CARBONATE PROPYLENE CARBONATE

Rotor 3 Rotor 4 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7

x 0.6 x = 0.6 x 0.6 x = 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0

DMF NMP DMF NMP DMSO DMSO ETHANOL ETHANOL PENTANOL PENTANOL ISOPROPANOL ISOPROPANOL

ETHYLENE GLYCOL ETHYLENE GLYCOL

PROPYLENE CARBONATE PROPYLENE CARBONATE

Rotor 5 Rotor 6 1.2 1.2 1.1 1.1 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7

x 0.6 x = 0.6 x 0.6 x = 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0

DMF NMP DMF NMP DMSO DMSO ETHANOL ETHANOL PENTANOL PENTANOL ISOPROPANOL ISOPROPPANOL ETHYLENE GLYCOL ETHYLENE GLYCOL

PROPYLENE CARBONATE PROPYLENE CARBONATE

Figure 5.14: These ﬁgures demonstrate the diﬀerent optimal x values for each solvent-rotor combination. The green bar is set at x = 0.6. It is clear that the optimal x values depart from this value in varying degrees.

43 Chapter 6

Discussion

This study was designed to explore the intrinsic temperature dependency of molecular rotor molecules, namely the temperature-dependent behavior of the constants C and x in Equation 3.12. Without knowing the speciﬁcs of these constants, applications of molecular rotors, such as measuring microviscosity, cannot be completed with the desired accuracy.

6.1 Solvent Properties

A method was used to fit the viscosity data with respect to temperature. Viscosity is generally a function of temperature in Newtonian fluids, following the Arrhenius exponential law (Equation 4.8). Furthermore, the Vogel-Fulcher-Tammann (VFT) model is generally used for specific organic solvents, such as alcohols, that form glasses below a certain temperature. Statistical analysis of our data provides a significantly better fit with the V-F-T model seen in Equation 4.1. This fit served to decrease the experimental error caused by measuring the solvent viscosities because a function, assuming a good fit into the experimental data, reduces random deviations that may affect individual data points. Furthermore, we used a water bath with moderate accuracy and used the rheometer’s built-in temperature probe to accurately determine the temperature of each individual data point. In this fashion, the temperatures at which viscosity was measured did not need to match accurately, thus, the function fit eliminated multiple potential sources of inaccuracy. Two other solvents were tried besides the ones that were used in the project. Methanol and Sulfolane were thought to be good candidates for the polar protic and polar aprtoic types, respectively. However, due to Rheometer machine limitations, the viscosity of Methanol at

44 the higher temperatures was too low to extract reliable data. As for Sulfolane, the melting point of this solvent is 27.5◦C. Because our temperature range spanned 15◦ to 45◦C, Sulfolane turned into a solid at the lower temperatures, making it impossible to measure viscosity with the cone-and-plate Rheometer. The melting point of this solvent also impeded ﬂuorescent intensity measurements due to the small crystals that formed in the solvent-dye solution at the lower temperatures.

6.2 Fluorescent Intensity Data

As expected, the vast majority of the solvent-rotor combinations followed the predicted decrease in fluorescent intensity with the increase in temperature. In the cases of CCVJ-DMF and CCVJ-NMP, an unexpected increase in intensity as the temperature was increased was observed. In an effort to rule out experimental error, each of the two combinations was repeated a second time, returning the same result. As we are unsure of the reason behind this occurrence, we can only speculate that some sort of temperature-driven chemical reaction took place between the solvents and the molecular rotor CCVJ, causing the increase in the quantum yield output. This is perhaps due to the properties of the solvents, DMF and NMP, or the specific properties of CCVJ.

6.3 Temperature Behavior of C and x

As previously pointed out, the power-law relationships between viscosity and quantum yield arrived at by both Försterand Hoffmann [11] and Loutfy et al. [14], contain the constants C and x. It was Försterand Hoffmann that ended up at the power-law relationship by assuming that microfriction was experienced by the twisting molecular segments. They then associated the microfriction to the viscosity through the Debye-Stokes-Einstein model. Loutfy et al. on the other hand developed the same power-law relationship between quantum yield and viscosity in terms of molecular free volume. Along with these relationships, Förster and Hoffmann determined the constant C in their derivation, offering that it was dependent

45 upon physical properties of the molecular rotor in question. The value of x ≡ 2/3 resulted from an integration step in the derivation. Loutfy et al. took a more experimental approach. In their derivation, the constant C is both dye- and solvent-dependent, whereas the exponent x was also ascertained through experimentation [14, 2]. The values of x that Loutfyet al. found were 1/2, 3/4, and 1 [14]. Depending on the derivation, the constant C allows for different interpretations. Förster and Hoffmann found C, related to T in Equation 3.10, not to have any temperature- dependent terms. Loutfy and Law examined the temperature-dependent behavior of the

rotational relaxation rate kor, without speciﬁcally taking into account that viscosity changes with respect to temperature. Thus, Loutfy et al. allowed the possible interpretation of kor to be a temperature-dependent constant. Lukac took this idea further by stipulation, that the reorientation is temperature-driven and follows an Arrhenius function (Equation 3.23). If we assume the intrinsic reorientation rate to be temperature-driven, the constant C in Equation 3.12, which contains the intrinsic dye constants, must be temperature-dependent itself. In this case, a temperature-dependent change of intensity is caused by the intrinsic dye behavior and changed solvent viscosity, namely,

I(T ) = C(T ) · (η(T ))x (6.1)

and the temperature-dependency of C(T ) can be found by solving Equation 6.1 for C,

I(T ) C(T ) = (6.2) (η(T ))x and plotting C(T) over T. However, in investigating our C0 term (Equation 4.7), we could see no consistent trend in the C0 values with respect to temperature. In fact, as you can see in Figures 5.6, some plots increased, some decreased, and some even exhibited a U-shape. There were, however, minimal trends that could be observed with respect to the polar protic and polar aprotic solvents. In our graphs, you can see the slight diﬀerence between the polar protic and polar

46 aprotic, polar aprotic exhibiting higher C0 values on average. This is perhaps accounted for by the differences in solvent properties, and/or solvent-rotor interaction. Overall, the temperature-dependence of C0 seemed to have little influence on the quantum yield. Because no consistent trends could be observed, this led us to believe that both the assumption x = 0.6 for all solvent-dye combinations and the assumption of a temperature-driven intrinsic reorientation rate is incorrect or incomplete. Under the assumption that x = 0.6 is not entirely correct for all solvent-dye mixtures, we sought to explore the idea of an optimal x value that suits each combination. As reported in the results section, optimal x values were found, varying distinctly with each rotor-solvent solution. It is worthy to point out that the coefficients of variation that were observed were extremely low (Table 5.2), especially when compared to the coefficients of variation found when using x = 0.6 (Table 5.4). The low CV indicates that there exists a value of x where the constant C becomes temperature-independent within experimental error. Because there is an obvious trend in the solvents with respect to the optimal x, we predict that the solvent properties strongly affect the value of the x with minimal coefficient of variation. As you will notice in Table 5.2, the polar aprotic solvents (DMSO, DMF, Propylene Carbonate, and NMP) exhibit consistently higher x values than those of the polar protic type (Isopropanol, Ethylene Glycol, Ethanol, and Pentanol). This leads us to the assumption that perhaps all the exponent x values are attempting to approach x = 1 [12]. Exponent x = 1 corresponds to the Debye-Stokes-Einstein model [12]:

f krot · η = (6.3) 3Vrot

where krot is the rotational relaxation rate, f is the harmonic twist potential force constant,

and Vrot is the rotational volume. Equation 6.3 stipulates that the result of the rate of diﬀusion multiplied by the (macroscopic) viscosity is not a function of temperature and viscosity [12].

47 Due to the diﬀerences in optimal x values, which showed high dependence on the environmental solvent, it is our conjecture that any exponent x value that departs from the value of x = 1 is being aﬀected by competing processes. An example of a competing process would be that of hydrogen bonding. When hydrogen bonding takes place, the local excited state (LE) is stabilized, which should increase quantum yield. The hypothesis of competing processes holds true when considering the fact that the polar aprotic solvents are closer to x = 1 than those of the polar protic type. Because polar aprotic solvents do not display any hydrogen bonding, our theory is reinforced. Other competing processes could include excimer formation, quenching, or other solvent properties. Though we did not include any non-polar solvents in our study, we speculate that the optimal x values for those solvents would be close to x = 1.

6.4 Molecular Rotor Structure

Structure of the molecular rotor itself is another interesting point. In our study three of the molecular rotors that we used (Rotor 4, Rotor 5, and Rotor 6) are very similar in structure. The diﬀerences between them lies in the length of their respective carbon chains (Figure 4.1). Molecular rotor Rotor 4 has two methyl carbon chain, Rotor 5 has two ethyl carbon chains, and Rotor 6 has two propyl carbon chains. As you can see in Table 5.2, the longer the carbon chains, the higher the optimal x value on average. We propose that this is due to the fact that carbon chains lead to increased resistance, i.e. higher steric hindrance which then dominates more strongly over polar interaction. In our study, this would account for the slightly higher x values for the longer carbon chain molecules (Figure 6.1).

48 1.2 ISO 1.1 EG 1.0 ETH 0.9 PENT 0.8 DMSO 0.7 DMF 0.6 PC Exponent x Value Exponent 0.5 NMP 0.4

NW004 NW003 WC0106 1

1.2 WC0106 1.1 NW004 1.0 NW003 0.9 0.8 0.7 0.6 Exponent x Value Exponent 0.5 0.4

EG ISO PC ETH DMF NMP PENT DMSO

Figure 6.1: This figure depicts three molecular rotors with similar structures. Rotor 4 has one carbon chain, Rotor 5 has two carbon chains, and Rotor 6 has four carbon chains. The top figure depicts the overall increase in exponent x value with the addition of carbon chains. The bottom figure is organized by solvent type and polarity. The group on the left are the polar protic solvents, beginning with the highest dielectric constant (EG) through the lowest (PENT). The second group on the right are the polar aprotic solvents, arranged the same with the highest dielectric constant (PC) at the beginning to the lowest of the polar aprotic solvents (NMP). It is evident that with the polar aprotic solvents decreased polarity leads to decreased x values. However, in the polar aprotic solvents, decreased polarity leads to increased x values. A point of interest is the fact that in the bottom figure, Pentanol seems not to follow the aforementioned decrease, as it is higher than Isopropanol. This can possibly be explained by the fact that Pentanol has a significantly smaller polar section than non- polar section in its molecular structure. This allows for increased van der Waals interaction, meaning more DSE. Isopropanol on the other hand, has somewhat of a compressed structure compared to Pentanol, meaning more hydrogen bonding.

49 Chapter 7

Conclusions and Future Research Considerations

In conclusion, molecular rotors are fluorescent molecules that exhibit high sensitivity to their local environment, such as solvent polarity and/or viscosity. In this study, we investigated the temperature-dependency of two constants, C and x, which are included in the power-law equation relating viscosity and fluorescent quantum yield. After determining specific values for C, and exploring optimal values for x for each solvent-rotor combination, we have come to the conclusion that the change in quantum yield is justified by the temperature- dependent change in the viscosity of the environmental solvent. Furthermore, changes in the constants C and x as functions of temperature have little effect on the fluorescent quantum yield of the molecular rotor molecule.

7.1 Future Research Considerations

The use of more molecular rotors of diﬀerent types would be an excellent additional research avenue. Moreover, exploring more solvents of diﬀerent types and various properties would bring a greater spectrum of understanding with respect to the solvent-rotor interactions. The addition of non-polar solvents would serve to explore our hypothesis concerning optimal x values. Further investigation into the solvent-rotor interactions with respect to CCVJ-DMF, CCVJ-NMP, and 3-DMF would also be an interesting area of future research. Understanding these interactions would play a key role in the forward movement of this project.

50 Bibliography

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51 [8] Il’ichev YV; Kuhnle W.; Zachariasse KA. Intramolecular charge transfer in dual ﬂu- orescent 4-(dialkylamino)benzonitriles. reaction eﬃciency enhancement by increasing the size of the amino and benzonitrile subunits by alkyl substituents. The Journal of Physical Chemistry A, 102(28):5670–5680, 05 1998.

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53 Appendix A

Temperature/Viscosity Graphs

Ethylene Glycol 30

25 R square=0.9999 20 A ~ -3.531 B ~ 926.6 15 C ~ 120.8

Viscosity 10

5 Y=exp(A+B/(C+x))

12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure A.1: Viscosity of Ethylene Glycol with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

54 Ethanol 1.5 1.4 1.3 R square=0.9983 1.2 A -20.57 B 20756 1.1 C 976.1 1.0 Viscosity 0.9 0.8 Y=exp(A+B/(C+x)) 0.7 12 15 18 21 24 27 30 33 36 39 42 45 Temperature (°C)

Figure A.2: Viscosity of Ethanol with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

Pentanol

4.8

4.3 R square=0.9998 3.8 A ~ -5.700 B ~ 1600 3.3 C ~ 204.0

Viscosity 2.8

2.3 Y=exp(A+B/(C+x)) 1.8 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure A.3: Viscosity of Pentanol with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

55 DMSO

2.8 2.6 R square=0.9982 2.4 A ~ -5.409 B ~ 1800 2.2 C ~ 266.1 2.0 1.8 Viscosity 1.6 1.4 1.2 Y=exp(A+B/(C+x)) 1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (C )

Figure A.4: Viscosity of DMSO with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

DMF

1.05 R square=0.9983 0.95 A ~ -2.683 B ~ 540.2 C ~ 183.7 0.85

Viscosity 0.75

0.65 Y=exp(A+B/(C+x))

12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure A.5: Viscosity of DMF with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

56 Propylene Carbonate 3.5

3.0 R square=0.9999 A ~ -3.014 2.5 B ~ 724.2 C ~ 159.6

2.0 Viscosity 1.5 Y=exp(A+B/(C+x))

1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure A.6: Viscosity of Propylene Carbonate with respect to change in temperature. The data was ﬁtted using the V-F-T equation.

NMP

2.2

2.0 R square=0.9985 1.8 A ~ -3.038 B ~ 781.9 1.6 C ~ 191.3

Viscosity 1.4 1.2 Y=exp(A+B/(C+x)) 1.0 12 15 18 21 24 27 30 33 36 39 42 45 48 Temperature (°C)

Figure A.7: Viscosity of NMP with respect to change in temperature. The data was ﬁtted using the V-F-T equation.