Evolution of Ultrafast Vibrational Dynamics During Sol–Gel Aging

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Evolution of Ultrafast Vibrational Dynamics During Sol−Gel Aging Christopher J. Huber,‡ RiAnna L. Butler,† and Aaron M. Massari*,† †

Department of Chemistry, University of MinnesotaTwin Cities 207 Pleasant Street South East, Minneapolis, Minnesota 55455, United States ‡ Doane University, 1014 Boswell Avenue, Crete, Nebraska 68333, United States S Supporting Information *

ABSTRACT: A longitudinal 1D- and 2D-IR spectroscopy study is presented in which the homogeneous and inhomogeneous contributions to the line shape of a surface-bound SiH vibration are monitored in a silica sol−gel while it ages. The vibrational data are complemented by time-lapse 29Si NMR and rheological measurements leading up to the gel point. The silane stretching frequency evolves continuously over the equivalent of several days, tracking the increase in tertiary and quaternary functionalized silicon atoms. The 1D-IR peak shape of the mode is static up until gelation, but then broadens continuously as the gel ages. A frequency−frequency correlation function (FFCF) extracted from 2D-IR spectra reveals that the line shape changes stem from an increase in inhomogeneity while the homogeneous dynamics remain unaffected by changes in silica cross-linking.



INTRODUCTION Since their inception,1,2 silica sol−gels have enabled a multitude of fundamental and applied studies.3,4 Their relative ease of synthesis and pore size tunability have allowed scientists to answer important questions about the behavior of solvents5−10 and solutes11−14 in nanoscopic volumes, and to monitor the biological activity of proteins and enzymes as their solvation shells become vanishingly thin.15−20 Historically, the silica structure has been used as scaffolding upon (or within) which to confine solvents and/or solutes. In a departure from this passive role, our group recently showed that a silicon hydride vibration on the silica surface could be used to probe the structural dynamics of molecular guests within the pore volume.21,22 Rather than relying upon the spectroscopy of the infiltrating solvent or solute, or a chemically bound sensitizer, this approach transforms the silica matrix itself into a general sensing platform to monitor any infiltrating species. In this context, it is important to understand how a surface vibrational mode is influenced by changes in the supporting silica matrix. During sol−gel formation, hydrolysis and early condensation leading to a gel can be fast under catalytic conditions, but the condensed silica network retains many unreacted silanol groups that continue to react as the gel ages.23,24 This leads to a decrease in porosity and an overall densification over a period of 3−4 weeks.3,4,25−27 It is known that a silane vibration is sensitive to the nature of the substituents to which the silicon atom is bound.28−31 Spectral shifts in the SiH mode (νSi−H) are correlated with the electron withdrawing effects of nearest neighbor atoms to the silicon.28−31 The νSi−H can also be solvatochromic to varying degrees depending on silicon functionalization; solvatochromic shifts are enhanced when oxygen atoms are the nearest neighbor species, as in the case of silica.22 In addition, the © 2017 American Chemical Society

vibrational peak shape is affected by time dependent structural changes in the proximal solvation volume.21,22 The effects of sol−gel aging on a number of spectroscopic parameters have been studied,25,32−36 but its influence on the vibrational characteristics of surface vibrational modes remains unexplored. Here we present a nonequilibrium vibrational spectroscopy study monitoring the steady-state and time-resolved behavior of a surface-bound vibrational mode as a function of aging time. 2D-IR peak shape analysis provides dynamic information while the FTIR peak positions and shapes report on the chemical evolution within the silica matrix. Time-lapse 29Si NMR and rheological measurements complement the vibrational data to create a holistic view of the chemical changes that accompany sol−gel aging and their influences on νSi−H.



EXPERIMENTAL SECTION Materials. Trimethoxysilane (TriMOS, 95% purity, SigmaAldrich), tetramethylorthosilicate (TMOS, 98% purity, Fluka), and hydrochloric acid (Macron) were used as-received. Sol−Gel Synthesis. A 6:0.6:3.2:0.1 mixture of TriMOS/ TMOS/HPLC grade H2O/0.04 M HCl was prepared, briefly shaken, and subsequently sonicated for 15 min. The reaction time was started once all the reactants were added, prior to the 15 min of sonication. An aliquot was sandwiched between two CaF2 windows with a spacer of an appropriate thickness, typically 50 μm. Most of the samples were characterized approximately 30−50 min after the solutions were mixed. The exact times were recorded and applied in the analysis below. FTIR Spectroscopy. Fourier transform infrared (FTIR) spectra were collected on a Nicolet 6700 FTIR spectrometer Received: December 18, 2016 Published: January 22, 2017 2933

DOI: 10.1021/acs.jpcc.6b12717 J. Phys. Chem. C 2017, 121, 2933−2939

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used to collect spectra at each of nine Tws, resulting in a total of 700 2D-IR spectra. Each spectrum was phase corrected using the pump−probe projection theorem.42,43 IR pump probe spectra were collected with the same laser system, as described in detail previously44 and in the SI. The resulting 2D-IR spectra were then analyzed using the peak ellipticity metric,45−48 which gives the normalized frequency−frequency correlation function (FFCF).43 The resulting ellipticities as a function of aging time were not synchronized for different samples and different Tws due to slightly different reaction starting times for each sample. To remedy this, all of the ellipticities at a single Tw were fit to an equation of the form y = −a1e−t/b1 + c1t + d1 allowing us to average the behavior at that Tw for multiple samples and to interpolate the ellipticity decays (as a function of Tw) at arbitrary aging times. We then selected 30 evenly spaced aging times at which to simultaneously fit the ellipticity decays and the closest-time FTIR spectra, and followed the procedure described by Kwak and co-workers to obtain the full FFCFs, including the homogeneous lineshapes.49

(Thermo Scientific) as an average of 16 scans with a resolution of 2 cm−1 under a constant flow of N2 gas. For reasons that will be explained below, time-lapse FTIR spectra were collected in two ways. Both methods used 50 to 250 μm path length cells constructed from two CaF2 windows sandwiched around a Teflon spacer gasket. In the first approach, the sol−gel reaction mixture was prepared as described above and then allowed to react in the sample cell. Spectra were collected every 8.57 min over a period of 1250 min (242 sequential spectra). In the second method, the sol−gel reaction mixture was prepared in a larger vial. Then, aliquots were drawn from the mixture while it reacted and were quickly assembled into a 50 μm path length sandwiched cell, as described above. FTIR spectra were acquired as frequently as the cell could be disassembled, reloaded, and reassembled. NMR Spectroscopy. 29Si NMR measurements were performed on a Bruker Avance 500 MHz NMR spectrometer. The probe was tuned to the 29Si signal at 99.4 MHz. Each experiment consisted of 23 scans with an acquisition time of 5.099 s. Rheology. Rheological measurements were performed on an AR-G2 Rheometer (TA Instruments) using a Couette concentric cylinders geometry. Once the reaction mixture was added to the cell, a loose cap carefully was placed over the well to hinder evaporation. Time sweeps were conducted at 25.0 °C with a constant angular frequency of 1.00 rad/s. The percent strain was allowed to float to apply a constant torque (7.690 μN·m). Experiments were stopped 5 min after the measured gel point to prevent the drying of silica on the aluminum surfaces of the bob and well. Container Size Effects on Gelation. A disparity was observed between the time scales of gelation of the FTIR and NMR samples. The FTIR samples sandwiched between two CaF2 windows with a 50 μm Teflon spacer observably gelled somewhere between 50 and 100 min, whereas the same solution took ∼7 h to gel in an NMR tube or a vial. Anglaret and co-workers found that base catalyzed sol−gel syntheses exhibited longer gel times as the size of the container increased, whereas gel times under neutral conditions were dimensionally independent.37−39 Monte Carlo simulations corroborated their experimental findings and pointed to bond flexibility as the major influence in the aggregation mechanism.37 The container size dependence of acid catalyzed silica sol−gel syntheses has not been reported, but we found this to be the case for our synthetic method. To resolve this issue, we compared FTIR spectra of sol−gel samples that reacted in a range of container sizes to rheological measurements performed in a Couette cell to define the characteristic gel time, tgel, in a large container. Details of this process are provided in the Supporting Information, SI. Throughout this work, we plot the time evolution of observables as t/tgel (using tgel for their respective container sizes) so that all of the measurements can be directly compared. 2D-IR Spectroscopy. The laser system used for 2D-IR and pump−probe spectroscopy has been described previously.40,41 Additional details are provided in the SI. Particular to this experiment, a sol−gel sample was prepared with careful attention to the reaction starting time, and successive scans were collected at a single Tw (time delay between pulses 2 and 3) for approximately 24 h or until scatter made the spectra unusable. Hence, each new identically prepared sample was used to collect multiple 2D-IR spectra, ∼ 25 min apart, at the same Tw while the sample aged. Two or three samples were



RESULTS AND DISCUSSION Figure 1a shows representative FTIR spectra of the SiH peak during the sol−gel reaction. The νSi−H blue-shifts significantly

Figure 1. (a) Selected (baselined and normalized) FTIR spectra of νSi−H as a function of reaction time measured at t/tgel = 0.7, 0.9, 1.4, 3.9, 13.5, and 20 (arrow indicates direction of change with increasing time); and (b) 29Si NMR spectra of the silica sol−gel reaction mixture at t/tgel = 0.11, 0.22, 0.33, and 0.44. Q0, Q1, Q2, and Q3 indicate uncondensed, 1°, 2°, and 3° condensed silicon regions.

(∼17 cm−1) due to progressive cross-linking in the silica matrix to which the mode is covalently bound. The νSi−H frequency indicates the average degree of condensation in the sol−gel and the continuous shift in Figure 1a shows that the reaction occurs both before (t/tgel < 1) and well after (t/tgel > 1) the gel point. Some of these changes can be further quantified by 29Si NMR spectroscopy.50−53 Less condensed silicon atoms (with more SiOCH3 or SiOH groups) are found downfield from their more condensed counterparts (with more SiOSi 2934

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The Journal of Physical Chemistry C bonds) due to decreased shielding by the more electronegative carbon atoms. Figure 1b shows selected 29Si NMR spectra at four different time points early in the reaction. The spectra are demarcated into four regions (Q0 −Q 3 ) by degree of condensation.51 There are multiple peaks in each segment of the spectrum signifying different degrees of hydrolysis within a specific degree of condensation. The completely uncondensed monomer (Q0) extends from −72 ppm to −76 ppm, primary condensed Si centers (Q1) extend from −81 ppm to −86 ppm, secondary condensed Si centers (Q2) extend from −90 ppm to −94 ppm, and tertiary condensed centers (Q3) extend from −100 ppm to −104 ppm. Quaternary condensed Si atoms did not show any resolvable peaks within the time window of the experiment (prior to gelation) but were characterized by solidstate 29Si NMR in a prior report.22 Figure 2 presents the time evolution of several measurements leading up to the gel point (t/tgel < 1). Figure 2a shows that

quantify the degree of condensation during the reaction. As expected, condensation of the hydrolyzed sol−gel precursors into siloxane polymers leads to loss of uncondensed and 1° silicon atoms in exchange for 2° and 3° atoms in the 29Si NMR spectra. For illustration purposes, we have also overlaid a longtime result at t/tgel ≫ 1 obtained previously by SS−29Si NMR showing the proportions of 1°, 2°, 3°, and 4° Si atoms after the sol−gel reaction was complete and the sample had aged for 3− 4 weeks.22 For our synthetic conditions, these are the values that we expect the data to approach after aging. This highlights that chemical reactivity persists beyond the gel point for sol− gels leading to morphological and structural changes as the gel ages.25,32−36 As the reaction progresses, the solution becomes more viscous, and the NMR peaks become unresolvable. Rheological measurements (SI) allow us to directly monitor the viscosity of the reaction mixture leading up to gelation. Figure 2d shows that the viscosity is below 100 cP for the entire range of the NMR measurements, but then rapidly changes by orders of magnitude as the gel point is reached. Interestingly, the νSi−H and peak widths in Figure 2a,b are insensitive to changes in the solution viscosity showing that they report local environmental effects rather than macroscopic flow parameters. Following the gel point, the vibrational spectrum of νSi−H in Figure 3a shows a progressive, albeit slower, blue-shift.

Figure 2. Sample characteristics before the gel point: (a) νSi−H center frequency, (b) peak full width at half-maximum (fwhm), (c) integrated 29 Si NMR peak areas (Q0 = black, Q1 = red, Q2 = blue, and Q3 = green), and (d) solution viscosity, η, all as a function of the normalized sample gel time. In frame c, a red, blue, green, and orange marker are added at t/tgel = 1 indicating the long time integrated areas from solidstate 29Si NMR measurements for Q1, Q2, Q3, and Q4, respectively.22 These are marked at t/tgel = 1 as a point of reference but were actually collected from a sol−gel that had aged for several weeks.

Figure 3. (a) Center frequency and (b) fwhm from the FTIR spectra of the surface bound silane mode νSi−H in silica sol−gels before and after the gel point. The blue line at t/tgel = 1 marks the gel point as determined by rheological measurements.

Surprisingly, the fwhm of νSi−H behaves differently after the gel time than before it, increasing monotonically over the entire time range and ending at 51 cm−1. A likely interpretation is that the condensation and densification of the gel that occurs with aging leads to an increase in inhomogeneous broadening of νSi−H. 2D-IR measurements were performed on νSi−H to dissect the relative contributions to its spectral line shape in this aging period. Figure 4 shows representative 2D-IR spectra collected for the νSi−H in silica sol−gels at three different aging times and three different Tws. Conceptually, one can interpret the xcoordinate as the frequency at which a subensemble of SiH oscillators is excited by the first IR pulse, and the y-coordinate as the range of frequencies that this collection of oscillators exhibits after sampling its surroundings for a specified waiting time, Tw. The diagonal width in each plot shows the degree of inhomogeneity, whereas the antidiagonal represents the extent of frequency correlation: correlated frequencies give a diagonally elongated peak, uncorrelated frequencies give a

νSi−H shifts by nearly 10 cm−1 during this time period. Over the same range, the fwhm of the FTIR peak is effectively constant at 45 cm−1 (Figure 2b). This width reflects homogeneous and inhomogeneous broadening influences, but the relative contribution of each cannot be differentiated from the 1dimensional FTIR measurement. The fact that the peak fwhm is unchanging leading up to tgel implies that the extent of inhomogeneity in the chemical environments surrounding the SiH vibrational modes is either unchanged or is compensated by a change in the homogeneous line shape (this ambiguity will be rectified by 2D-IR measurements below). On the same x-coordinate, Figure 2c shows the integrated NMR peak areas within Q-regions defined in Figure 1b and normalized by the total peak area from all four regions to 2935

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Figure 5. Peak ellipticities from 2D-IR spectra of the v = 0−1 transition of νSi−H as a function of Tw and sol−gel aging time. The surface represents the averaged response of the data overlaid above and below it.

that the decays also experience a fast increase in ellipticity from the gel point up to about t/tgel = 4. Slices across this surface at 30 evenly spaced aging times were used to obtain a longitudinal view of how the ellipticity and FFCF evolve as silica sol−gels condense and age. Processing the ellipticity decays and FTIR spectra (see the Experimental Section) produced the FFCF at the selected aging times with a

Figure 4. Representative 2D-IR spectra of the νSi−H at 0.3, 4.5, and 10 ps Tws (rows) and three aging times (columns). The horizontal frequency axis (ω1) is obtained by Fourier transform of the time period between the first and second pulses in the 2D-IR sequence; the vertical axis (ω3) is the Fourier transform of the time period after the third pulse obtained by spectrally resolving the signal in a monochromator. The positive-going red peaks are the v = 0−1 fundamental transitions, and the negative-going blue peaks are the v = 1−2 transitions.

functional form of FFCF(t ) =

δ(t ) T2

( ) + Δ . In t

+ Δ12 exp − τ

2

1

this equation, T2 is the dephasing time that depends upon pure dephasing (T2*) and vibrational relaxation (T1) through 1 1 1 = T + 2T (here we neglect reorientational relaxation for T 2

2

1

a vibrational chromophore attached to a silica matrix). The dephasing time is then related to the homogeneous line width 1 (Γ) as Γ = πT . The Δ1 and τ1 terms represent the magnitude 2

and time scale of frequency fluctuations that result from a particular set of structural dynamics sensed by the νSi−H vibrational mode. Although we cannot determine the microscopic origins of these dynamics by 2D-IR alone, we nonetheless capture some characteristic dynamics that are present in the solvation volume of the νSi−H bound to silica. The best fit parameters are shown graphically in Figure 6. From the gel point up to about 6 times tgel, gradual increases in the inhomogeneous amplitudes (Δ1 and Δ2) of the FFCF (Figure 6a,c) are accompanied by a mild slowing of the time scale (τ1) of spectral diffusion (Figure 6b). This aging range translates into about 2 days, the time period during which the most dramatic morphological changes occur in sol−gel aging.3,4,25−27 Thereafter, τ1 stabilizes and Δ1 decreases while Δ2 exhibits a stronger linear increase. Throughout the aging period, the homogeneous line width (Γ, Figure 6d) and vibrational lifetime (T1, Figure 6e, measured in separate IR pump−probe experiments) are unchanged at about 2.5 cm−1 and 12 ps, respectively, indicating that the pure dephasing experienced by νSi−H is unaffected by the increased silica condensation. The frequency shift of νSi−H and population changes in 29Si NMR in Figures 2 and 3 already confirmed that the silica network continues to react, producing a high fraction of tertiary and quaternary Si centers, and the variations of the inhomogeneous parameters in the FFCF reflect this. Yet, the fast dephasing processes captured in Γ for νSi−H are insensitive to this chemical evolution. In contrast, previous work showed that Γ is in fact sensitive to the nature of the infiltrating solvent,22 which implies that the silica aging monitored here

round peak shape. The temporal evolution of the 2D-IR peak shapes from diagonally elongated to round is the result of frequency fluctuations cause by structural dynamics of the silica matrix and surrounding solvent. The plots in Figure 4 are organized vertically by increasing Tw and horizontally by increasing aging time. Going down any of the three columns shows that the peak shapes become more round (although still diagonally elongated) as a result of spectral diffusion. The νSi−H ultrafast vibrational dynamics persist even after gelation and aging. Looking across any of the three rows we see that the spectra become more diagonally elongated as the aging time increases indicating that the extent of inhomogeneity increases. The blue shift of the v = 0−1 peak due to increased silica condensation is also apparent across each row. These peak shape changes are quantified by the peak ellipticity,45−48 which will be the focus of the following analysis. We carried out a longitudinal study in which we monitored the 2D-IR peak ellipticities45−48 as a function of both Tw (up to 15 ps) and sample aging time (over 24 h). The v = 0−1 ellipticities from 700 spectra are overlaid onto a surface that maps the averaged behavior in terms of both time variables in Figure 5. The data describe the dynamic evolution of the proximal solvent around νSi−H during sol−gel aging. Qualitatively, the ellipticity decays (ellipticity versus Tw) in this figure have similar shapes and the primary difference as aging time increases is that there is a uniform shift to higher ellipticities. This would be expected for a sample that undergoes a monotonic increase in inhomogeneity, as suggested by the FTIR line width. A closer examination reveals 2936

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nanoscopic solvent studies that have shown an overall slowing of solvent dynamics as the solvent pool dimensions decrease.54,55 The pore sizes in the current work are in the 1−2 nm diameter regime,4 making it reasonable that the resolvable spectral diffusion time scale starts off even slower (∼6 ps). Aging then leads to even smaller pore sizes with slower inhomogeneous dynamics to the point that we can no longer resolve their time scale.



CONCLUSIONS 1D- and 2D-IR spectra were monitored for a silane vibration integrated into a silica sol−gel matrix before and after gelation. Leading up to the gel point, the νSi−H mode frequency and 29Si NMR spectra reported an increase in the extent of condensation in the silica material, while the νSi−H peak width was insensitive to chemical changes occurring in the surrounding silica structure. The νSi−H mode frequency and 29 Si NMR spectra are local chemical indicators of the reactivity of silicon atoms in the mixture, and show no correlation with such macroscopic flow parameters as solution viscosity. After gelation, spectral diffusion slowed, as captured in the FFCF and the FTIR peak width, while the fast homogeneous dynamics were unaffected by the extent of cross-linking. This work demonstrates that the morphological densification that occurs during sol−gel aging leads to a slowing of some of the ultrafast dynamics that affect vibrational lineshapes. Conversely, homogeneous dynamics that were previously shown to be sensitive to the nature of the infiltrating solvent were found here to be independent of these structural changes. We assert that this is evidence that the very fast dynamics in the proximal solvent pool are unaffected the morphological changes that occur during aging. A missing element of this work is the ultrafast dynamic analysis of the silica system before gelation. Although there are only a few data points at t/tgel < 1, some of the parameters show that there is a clear change in dynamic behavior at the onset of the gel point. A faster measurement apparatus and possibly a specialized mixing cell would enable these dynamics to be monitored in real time, which is a direction of future efforts.

Figure 6. FFCF parameters calculated from the ellipticity decays and FTIR spectra for νSi−H over the course of aging beyond tgel, as described in the text. The blue line at t/tgel = 1 marks the gel point, as determined by rheological measurements. Error bars for frames a−d represent iteratively determined parameter limits that allow 99% of the best-fit χ2 value to be recovered while floating all other parameters; error bars on frame e are the standard error of the fit to a single exponential decay. The error bars on Γ are present but are smaller than the data markers.

does not significantly affect some of the dynamics in the proximal solvent volume around the surface-bound silane groups. We conclude that the increase in FTIR line width (Figure 3b) is a direct result of an increase in chemical inhomogeneity, as captured by the exponential and pseudostatic inhomogeneous terms in the FFCF. Cross-linking and branching lead to a more diverse range of chemical environments in which the silane group is bound, but do not measurably change the very fast dynamics of the solvent pool in which it is bathed. In reality, the dynamics that are sampled in a 2D-IR experiment occur on a continuum of time scales. The FFCF captures the events that are most strongly coupled to the vibrational mode studied and then attempts to categorize them with some functional form. These are the dynamics as viewed through the lens of the νSi−H mode; there are likely to be faster and slower processes that are unresolvable or too weakly coupled to the mode to produce frequency fluctuations on this time scale. If there are changes in the vibrational dynamics, then the motions that start out in one term in the FFCF may transition into another. In fact, the data in Figure 6 show this exchange. Initially, the increase in the fwhm of νSi−H is reflected in an increase in the amplitudes of spectral diffusion and pseudostatic terms as the characteristic time scale of spectral diffusion gets longer. Further aging shows a decrease in Δ1 with a concurrent rise in Δ2 indicating transfer of these dynamics into a time regime that is too slow for our measurements to resolve. We recently reported a systematic study of spectral diffusion dynamics in templated silica nanoparticles with 3 to 12 nm pores and found a similar loss of faster dynamics in the FFCF as the pore sizes decreased.21 This is also consistent with



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcc.6b12717. Details on container size effects on gelation and connecting gel times in different containers, 2D-IR spectroscopy, and IR pump−probe spectroscopy details, and rheological measurements with a Couette cell (PDF)



AUTHOR INFORMATION

Corresponding Author

*Phone: 612-626-8416. E-mail: [email protected] (A.M.M.). Notes

The authors declare no competing financial interest.

■ ■

ACKNOWLEDGMENTS The authors gratefully acknowledge funding from the National Science Foundation under CHE-0847356 and CHE-1464416. REFERENCES

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DOI: 10.1021/acs.jpcc.6b12717 J. Phys. Chem. C 2017, 121, 2933−2939