<<

CORE Metadata, citation and similar papers at core.ac.uk

Provided by Digital Repository @ Iowa State University

Chemistry Publications Chemistry

5-6-2016 Probing surface bonding and dynamics by natural abundance, multidimensional, 17O DNP-NMR spectroscopy Frédéric A. Perras Iowa State University

Umesh Chaudhary Iowa State University

Igor I. Slowing Iowa State University, [email protected]

Marek Pruski Iowa State University

Follow this and additional works at: http://lib.dr.iastate.edu/chem_pubs Part of the Chemistry Commons The ompc lete bibliographic information for this item can be found at http://lib.dr.iastate.edu/ chem_pubs/998. For information on how to cite this item, please visit http://lib.dr.iastate.edu/ howtocite.html.

This Article is brought to you for free and open access by the Chemistry at Iowa State University Digital Repository. It has been accepted for inclusion in Chemistry Publications by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Probing surface hydrogen bonding and dynamics by natural abundance, multidimensional, 17O DNP-NMR spectroscopy

Abstract Dynamic nuclear polarization (DNP)-enhanced solid-state nuclear magnetic resonance (SSNMR) spectroscopy is increasingly being used as a tool for the atomic-level characterization of surface sites. DNP surface-enhanced SSNMR spectroscopy of materials has, however, been limited to studying relatively receptive nuclei, and the particularly rare 17O nuclide, which is of great interest for materials science, has not been utilized. We demonstrate that advanced 17O SSNMR experiments can be performed on surface species at natural isotopic abundance using DNP. We use 17O DNP surface-enhanced 2D SSNMR to measure 17O{1H} HETCOR spectra as well as dipolar oscillations on a series of thermally treated mesoporous silica nanoparticle samples having different pore diameters. These experiments allow for a nonintrusive and unambiguous characterization of hydrogen bonding and dynamics at the surface of the material; no other single experiment can give such details about the interactions at the surface. Our data show that, upon drying, strongly hydrogen-bonded surface silanols, whose motions are greatly restricted by the interaction when compared to lone silanols, are selectively dehydroxylated.

Disciplines Chemistry

Comments This is an article from Perras, Frédéric A., Umesh Chaudhary, Igor I. Slowing, and Marek Pruski. "Probing surface hydrogen bonding and dynamics by natural abundance, multidimensional, 17O DNP-NMR spectroscopy." (2016). doi: 10.1021/acs.jpcc.6b02579. Posted with permission.

This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/chem_pubs/998 Probing Surface Hydrogen Bonding and Dynamics by Natural Abundance, Multidimensional, 17O DNP­NMR Spectroscopy

Frédéric A. Perras,a Umesh Chaudhary,a,b Igor I. Slowing,a,b and Marek Pruskia,b a U.S. DOE Ames Laboratory, Ames, IA 50011­3020, USA b Department of Chemistry, Iowa State University, Ames, IA 50011­3020, USA

*Corresponding author. M. Pruski: Ames Laboratory, Iowa State University, 230 Spedding Hall, Ames, IA 50011­3020, USA. Phone: +1 515 294 2017 Fax: +1 515 294 4709. E­mail address: [email protected].

Abstract

Dynamic nuclear polarization (DNP)­enhanced solid­state nuclear magnetic resonance

(SSNMR) spectroscopy is increasingly being used as a tool for the atomic­level characterization of surface sites. DNP surface­enhanced SSNMR spectroscopy of materials has, however, been limited to studying relatively receptive nuclei and the particularly rare 17O nuclide, which is of great interest for materials science, has not been utilized. We demonstrate that advanced 17O

SSNMR experiments can be performed on surface species at natural isotopic abundance using

DNP. We use 17O DNP surface­enhanced 2D SSNMR to measure 17O{1H} HETCOR spectra as well as dipolar oscillations on a series of thermally treated mesoporous silica nanoparticle samples having different pore diameters. These experiments allow the non­intrusive and unambiguous characterization of hydrogen bonding and dynamics at the surface of the material, no other single experiment can give such details about the interactions at the surface. Our data show that, upon drying, strongly hydrogen­bonded surface silanols, whose motions are strongly restricted by the interaction when compared to lone silanols, are selectively dehydroxylated.

2 Introduction

Within the first half of this decade, advancements in dynamic nuclear polarization (DNP) equipment and methodology1 have allowed the routine measurement of solid­state nuclear magnetic resonance (SSNMR) spectra of surface sites.2 These developments have enabled, for the first time, the rapid atomic level characterization of surface species that were usually probed with lower precision using, for example, vibrational spectroscopy, EXAFS, XPS, and microscopy.3 One­ and two­dimensional (1D and 2D) 13C,2,4 29Si,5 27Al,6 and even 15N,7 89Y,8 and

119Sn9 SSNMR spectra of surface sites, which allow one to probe the intra­ and intermolecular connectivities, can now be measured on high­ and low­surface materials in a matter of minutes to a few hours. The surface of metal nanoparticles has also been directly characterized by this

DNP­surface­enhanced NMR spectroscopy (DNP­SENS) approach.10,11 Recent developments have shown that DNP­SENS is amenable to the studies of very low surface area materials (~1 m2/g) by NMR,12 which are beyond the detection limits of what can now be termed

‘conventional’ SSNMR spectroscopy.

DNP SSNMR methodology is also attractive for studying the extremely challenging 17O . Even though is the element of central importance in life sciences13 and materials chemistry,14 the applications of 17O SSNMR have been rather scarce in comparison to other ubiquitous elements: hydrogen, , , aluminum, and . This can be entirely attributed to the fact that the only NMR­active isotope of oxygen, 17O, has one of the lowest natural isotopic abundances among NMR­active (0.037 %, or 370 ppm). This

3 necessitates the use of 17O isotope enrichment, which is expensive and often difficult to achieve.

Aside from the low natural abundance, 17O is also a quadrupolar nucleus with a spin of 5/2. The quadrupolar interaction then further broadens and complicates the acquisition and interpretation of 17O NMR spectra of solids.

Recently, however, advancements in gyrotron, low­temperature magic­angle spinning

(MAS),1 polarizing agent,15 and pulse sequence16,17 technologies have enabled the rapid detection of 17O signals in solids at natural isotopic abundance.17,18 For example, DNP enabled measurements of reliable 1D lineshapes, 2D 17O{1H} HETCOR experiments and 1H­17O distance measurements for natural abundance hydroxyl sites in a reasonable amount of time.17 A significant improvement to the application of DNP MAS NMR to 17O was the implementation of the PRESTO polarization transfer technique, which uses symmetry­based recoupling to transfer polarization from hyperpolarized 1H spins to the 17O spins, instead of conventional 1H­17O cross­polarization that suffers from unfavorable spin dynamics when applied to quadrupolar nuclei.19 PRESTO, combined with the quadrupolar Carr­Purcell­Meiboom­Gill (QCPMG) experiment,16c even enabled the detection of 17O sites on the surface of mesoporous silica nanoparticles (MSNs).17a

The prospect of using 17O SSNMR for characterizing the surface of silica materials, which are often used as supports for heterogeneous catalysts, is an exciting possibility. The first

1D 17O DNP­enhanced PRESTO­QCPMG NMR spectrum of a surface site that was recently reported on the MSN SBA­15,17 however, had a low signal to noise ratio and only featured a single broad resonance representing the disordered silanols on the surface. Much structural information is to be gained from spreading the overlapping the 17O resonances along the second

4 dimension using 2D 17O{1H} HETCOR spectroscopy.20 In this article we aim to demonstrate that, using DNP, it is indeed possible to perform various 17O 2D NMR experiments on surfaces at natural isotopic abundance. We apply 17O DNP SENS methodology to characterize the structure of surface hydroxyl sites and elucidate their hydrogen bonding interactions.

Results and Discussion

Sample Description

Two MCM­41­type MSN materials were chosen for this study, featuring regular and expanded pore diameters of 2.7 and 3.4 nm, surface areas of 1098 and 655 m2/g, and pore volumes of 0.985 and 0.486 cm3/g, respectively. The MSNs with 3.4 nm pores (MSN­3.4) were prepared by using mesitylene as a swelling agent;21 the synthetic procedure was otherwise identical to the MSNs having 2.7 nm pores (MSN­2.7), vide infra. It is expected that the change in the pore diameter will affect the interactions between the silanol groups at the surface. For example, if we assume a 1.5 Å Si­OH bond length, and a circular pore structure, the silanols would be on average 3% closer in the sample having a 2.7 nm pore diameter due to the increased pore curvature. We would then expect to observe more strongly interacting surface silanols in the MSN­2.7 sample. If the swelling procedure, however, increases the of surface silanols the opposite effect should be observed.

The high surface areas of these samples ensure that there is a relatively high content of radical­accessible hydroxyl sites per volume. The extent of surface hydrogen bonding may depend on the pore morphology, as was mentioned above, and may be further altered by drying the sample in vacuo at various temperatures. This process is known to to the dehydration and partial dehydroxylation of the sample, as seen, for example, by gravimetric and NMR

5 methods.22 Thermogravimetric analyses (TGA) were performed on both MSN samples under vacuum at a slow rate of 4°C/min, see Figure 1. As can be clearly seen in the derivative thermogravimetric data (DTG), there is a constant loss of mass as the samples are heated under vacuum up to 700°C. Notably, however, there is a distinct mass­loss event that occurs at 245°C and 275°C for the MSN­2.7 and MSN­3.4 samples, respectively. The dehydroxylation of vicinal silanol groups is the most likely origin of this sharp mass loss; the desorption of weakly bound water under vacuum is known to occur near room temperature.23 The lower dehydroxylation temperature in MSN­2.7 seems to suggest that the distance separating the vicinal silanols is indeed smaller in the sample with higher pore curvature. A greater insight into the interactions at the surface of MSN samples can only be obtained by a technique providing atomic resolution, such as 17O NMR.

6

Figure 1. Vacuum TGA (black) and DTG (red) curves are shown for both the regular (MSN­2.7, top) and expanded­pore (MSN­3.4, bottom) samples. It can be seen that a major mass­loss event, likely originating from the dehydroxylation of vicinal silanols, occurs at a higher temperature (275°C vs 245°C) in the MSN­3.4, although a greater overall mass loss occurs in this sample as well. This is marked by a dashed red line.

1D 17O DNP NMR Spectroscopy

The surface oxygen sites of MSNs have been studied in the past by 17O NMR; however, to label them, the samples are typically dehydroxylated at elevated temperatures and then treated with 17O­enriched water.24 Such treatment would break the strained siloxane bridges created at

7 the surface of the MSN during the dehydroxylation process; however, the silanols may not generally be reintroduced at the same locations.

Here, the natural abundance MSN­2.7 and MSN­3.4 samples were dried in vacuo for 2 hours at 25, 100, and 200°C. Due to the higher temperature that is needed for the dehydroxylation of vicinal silanols in the expanded­pore version (see Figure 1), an MSN­3.4 sample dried at 300°C was also prepared. The samples were then immediately impregnated with a 16mM of the TEKPol biradical15c in 1,1,2,2­tetrachloroethane for the DNP SSNMR measurements.

The DNP­enhanced 17O PRESTO­QCPMG NMR spectra of these samples are shown in

Figure 2. For clarity, the spikelet­free spectra were also reconstructed from the QCPMG echo trains by performing a weighed sum of the echoes.23 As can be seen from these spectra, the surface 17O signals correspond to a broad, featureless, peak, in agreement with the amorphous nature of the surface species. By comparing the spectra of MSN­2.7 and MSN­3.4 samples dried at higher temperatures to the room temperature samples, it can be noticed that in both cases the signal intensity is reduced by about 50%. Accurate quantification of the intensities is, however, impossible due to different sample sizes (note that new samples must be prepared for each DNP measurement), and possible variation in DNP enhancements due to different degassing levels and radical penetration. Note that the loss in intensity cannot be attributed to the removal of adsorbed water, because 17O NMR signals characteristic of water were not detected in any of the vacuum dried samples. It is also known that most of the absorbed water is removed by drying the sample in vacuo at room temperature.23 Instead, the loss of intensity likely occurs from the dehydroxylation of close silanols at the surface. This loss in intensity may be large, however, the

8 PRESTO technique is biased in favor of the detection of the 17O nuclei of vicinal silanols, vide infra. Although minute variations in the observed lineshapes are evident from the 17O SSNMR spectra, the complexity of the lineshapes precludes further interpretation of 1D spectra.

Figure 2. 17O PRESTO­QCPMG NMR spectra (spikelet and reconstructed) of MSN samples dried in vacuo at various temperatures. The spectra corresponding to the 2.7 nm pore MSN samples (MSN­2.7) are shown in (a) whereas those from the 3.4 nm pore MSN samples (MSN­3.4) are shown in (b). All the spectra were acquired in 16 hours of experiment time.

2D 17O{1H} HETCOR

Given that the acquisition of even 1D NMR spectra is highly time consuming, the additional signal enhancement offered by the QCPMG method is crucial to the success of 2D 17O

DNP SENS NMR. By altering the delay between the echoes in a QCPMG echo train, the spacings between the spikelets can be changed.16 Thus, if desired, the entire 17O signal can be

compressed into a single, sharp, spikelet whose width is dictated by the relevant T2 relaxation

9 time. This approach maximizes the signal to noise ratio, however a minimum of 2 spikelets are in principle needed to derive any NMR shift information from the 17O dimension.

Using this strategy we were able to acquire the first natural abundance 17O{1H} HETCOR spectra of surface sites (Figure 3). The 1H projections of these spectra are compared in Figure 4.

Note that the samples treated at temperatures of 100°C and above featured only one type of silanol proton and thus a single spikelet could be acquired to maximize the sensitivity by properly choosing the carrier frequency and echo delay. As can be seen from the 2D spectra of the 25°C samples, we observe a positive correlation between the 1H and 17O resonance frequencies, in agreement with prior literature reports.24 Given that the 1H chemical shifts of hydroxyls typically report on the strengths of hydrogen bonding interactions (higher chemical shift/frequency corresponding to stronger hydrogen bonding),25 these HETCOR spectra strongly suggest that the 17O resonance shifts of silanols share the same correlation with hydrogen bonding. In fact, prior 17O measurements on crystalline samples have shown that, like 1H shifts, the 17O chemical shift is lowered when hydrogen bonding is weakened.26

We also notice that the higher frequency 17O spikelet, and to some extent the lower frequency spikelet as well, in the HETCOR spectra of the 25°C samples, most notably in

MSN­3.4, show the resolution of two 1H resonances centered at chemical shifts of approximately

5.5 and 2 ppm. These resonances are clearly discerned in the 1H projections in Figure 4, and their respective chemical shifts agree very well with those of 5.5 and 1.8 ppm reported earlier for strongly hydrogen­bound and lone silanols.22c Prior to drying, there are then two strongly overlapping 17O signals corresponding to strongly hydrogen­bonded (vicinal) and weakly­ to non­interacting silanols. Further drying completely removes the correlation at 5.5 ppm from the

10 HETCOR spectrum indicating that those sites have been dehydroxylated. The other resonance at around 2 ppm, however, remains. Thus the 1D 17O SSNMR spectra measured on MSN samples dried at a temperature above 100°C represent solely the weakly­ to non­interacting sites, in agreement with the lower 1H resonance frequency of associated protons. Since the non­interacting (lone) silanol site is much less prominent in the HETCOR spectrum of the 25°C

MSN­2.7 sample, this suggests that a greater fraction of the surface silanols have close neighbors in this sample, most likely due to increased pore curvature.

Figure 3. 17O{1H} PRESTO­QCPMG HETCOR NMR spectra of (a) MSN­2.7 and (b) MSN­3.4 dried in vacuo at various temperatures. It is evident from the 25°C spectra that changes in the 1H and 17O resonance frequencies are correlated. Additionally, upon drying the 1H resonance with lower chemical shift progressively dominates the spectra. A second 1H resonance, at approximately the same 1H frequency as one observed in the sample dried at 100°C, is also apparent in the left spikelet of the spectrum of the 25°C MSN­3.4 sample. Dashed lines have been added to highlight the positions of those two shifts.

11 From the projections in Figure 4, it is also clear that there is a shift of the 1H resonance from 2.5 to 2.2 and finally 1.8 ppm upon drying the MSN­3.4 sample at 100°C, 200°C, and

300°C. This shows that the most strongly hydrogen­bonded silanols are gradually dehydroxylated at higher temperatures, further increasing the isolation of the remaining species, which at 300°C have the 1H chemical shift of lone silanols. The MSN­2.7 samples dried at

100°C and 200°C behave similarly to MSN­3.4, as evidenced by the same observed 1H chemical shifts.

Figure 4. Projections taken along the 1H dimension of the 17O{1H} PRESTO­QCPMG HETCOR NMR spectra, shown in Figure 3, of MSN­2.7 (a) and MSN­3.4 (b) samples dried in vacuo at various temperatures. A shift to lower frequency is observed upon drying, in agreement with the lessened hydrogen bonding. A comparison of the two spectra from the samples dried at room temperature also clearly shows the higher relative isolated silanol content in the MSN­3.4 sample.

12 Dynamics

We have previously demonstrated that 17O PRESTO­QCPMG NMR experiments may also be used to measure accurate H­O internuclear distances.17 Silanols are, however, known to possess a large degree of rotational freedom about the Si­O bond, specifically for non­hydrogen­bonded sites. This has notably been studied in detail using 2H NMR on silica gel.27 Librations of the Si­O­H moieties lead to partial averaging of the 1H­17O dipolar coupling tensor, and thus directly affect the 17O PRESTO­QCPMG H­O distance measurements. It should then, in principle, be possible to characterize the motions of the silanol groups at the surface of the MSN using natural abundance, DNP­enhanced, 17O SSNMR.

In order to quantify these motions we have designed the following simulation model.

The dipolar coupling tensor, which is axially symmetric and traceless for a static spin pair, in the principle axis frame (PAF) is given by the following expression:

, (1) 1 0 0  D  0 1 0  PAF D   0 0 - 2

where ωD is the dipolar coupling constant defined as:

, (2)

 012   3 D   r1,2  4 

­3 with γi denoting the magnetogyric ratios of the coupled nuclei and ‹r1,2 › the motionally­averaged inverse cube of the internuclear distance between the coupled spins. As is evident from equation

2, the strength of the dipolar coupling is influenced by molecular motions, which can partially

13 average (weaken) the dipolar coupling. Stretching modes will induce an apparent lengthening on

the bond, and a reduction of ωD, due to the anharmoticity of these motions. Librations on the

other hand are more complex and can lead to increased asymmetry ηD of the dipolar coupling tensor,28 defined as:

, (3) D11  D22 D  D33

along with a reduction in ωD. In equation 3 the principle components of the motionally averaged

dipolar coupling tensor are ordered as: |D11| ≥ |D22| ≥ |D33|.

The value of the apparent dipolar coupling constant (ωD,app.), as well as ηD, depends intimately on the type of motion at play. Librations can be approximated as a rigid rotor, with hindered rotations. A reasonable, and simple, function describing the probability of finding the atoms at varying librational amplitudes would be a Gaussian distribution (equation 4),27 although simulations show that the end result is largely independent of the type of distribution used

. (4) 4ln(2) 1   4ln(2)2  P,  exp      

In equation 4, represents the deviation from the equilibrium internuclear vector  direction and is the width of the distribution of , which defines the amplitude of the   librational motions (Figure 5a). To determine the effect of  on the averaged dipolar coupling constant and asymmetry parameter, we need to average the dipolar coupling tensor (in the lab

14 frame) over all the orientations of the distribution. The dipolar coupling tensor in the laboratory frame is reoriented as follows:

(5)  1 DLAB(,) R (,)DPAF R(,) where is a rotational matrix; θ corresponds to the difference between 180° and the R(,)

Si­O­H bond angle, which is typically around 120°. Since the distribution (equation 4) is symmetric about the equilibrium bond orientation, a considerable simplification can be made by averaging the dipolar coupling tensors with orientations of ± . This would fix the orientation of  one tensor component perpendicular to the Si­O­H plane, which can then be simply averaged using equation 4:

.(6)  1  1 DLAB(,) 1/ 2(R (,)DPAF R(,)  R (, )DPAF R(, ))

If we then assume that the Si­O­H bond angle corresponds to 120° (i.e. θ = 60°), this simplifies to:

. (7)

 9 2 3 3  1 cos  0  cos  4 4  5 9 D (60,)   0 -  cos 2  0  LAB D  4 4   3 3 1   cos 0   4 4 

The motionally averaged eigenvalues can then be obtained by numerically using the following expression:

15 . (8)  Daveraged   P,D DLAB (60,)d

By assuming a Si­O­H angle of 120°, and a O­H bond length of 0.95 Å, the apparent dipolar coupling constant and asymmetry parameter of the dipolar coupling tensor are solely determined by the amplitude of the librations: . The predicted eigenvalues, relative dipolar  coupling constant, and asymmetry parameter of this averaged tensor are plotted as a function of the librational amplitude in Figure 5. As depicted in the plots, when the silanol is allowed to freely rotate (Δ = 360°), the dipolar coupling tensor is averaged to 1/8 of its static size, in  agreement with the 120° Si­O­H bond angle.29

16 Figure 5. (a) Model used to approximate the librational motions of a free silanol group. In principle a distribution of Δ values exists; we use a Gaussian distribution here. The resulting  averaging of the 17O­1H dipolar coupling tensor as a function of Δ is shown in (b)­(d). The  tensor components are plotted as a function of the librational amplitude in (b) and the resulting apparent dipolar coupling constant and dipolar asymmetry are shown in (c) and (d), respectively.

29 As expected, when Δ equals 360°, the tensor is scaled by |P2(cos(60°))| = 1/8. 

This model can then be used to predict the PRESTO heteronuclear dipolar oscillations for different librational amplitudes.19 In principle, these oscillations depend on both the size and asymmetry of the apparent dipolar coupling tensor. Plots showing these PRESTO heteronuclear dipolar oscillations as a function of the librational amplitude are shown in Figure 6. These curves can be used, for example, as basis functions in order to quantify the amount of motional silanol groups. The numerical simulations of the PRESTO dipolar oscillations were performed using the SIMPSON program.30

17 Figure 6. Examples of simulated PRESTO 17O­1H dipolar oscillations as a function of the librational amplitude, presented using the same intensity scale.

2D 17O{1H} Distance Measurements

The measurements of 17O­1H PRESTO­QCPMG dipolar oscillations were performed as previously described,17 on the MSN­2.7 and MSN­3.4 samples after drying 25°C and at 100°C.

These experiments required an even greater signal to noise ratio than HETCOR, and thus it was necessary to again condense the signal into a single spikelet. As previously done,17 the echo delay was fixed to one rotor period and the length of the first recoupling block, which precedes the 17O excitation pulse, was incremented.19,31 The plots showing the integrated intensity of the spikelet as a function of the recoupling time for the 25 and 100°C samples are shown in Figure

7a,b.

Figure 7. The PRESTO 17O­1H dipolar oscillations, measured on MSN­2.7 (a) and MSN­3.4 (b) samples dried in vacuo at 25°C (filled circles) and 100°C (empty squares). Fits using the dynamic model presented earlier are shown for the 25°C samples (solid red line) and are

18 decomposed in the histograms on the right, with the rapidly oscillating component shown by the dashed red line. As can be seen from the 100°C data, the population of the corresponding to hydrogen bonded silanols has been significantly diminished upon drying at elevated temperatures, whereas the slowly oscillating free silanols remained unaffected. There is also a greater fraction of the observed silanols that have hindered librations in MSN­2.7 than in MSN­3.4 (86% vs 73%).

We were able to fit the data from the 25°C samples using a linear combination of functions corresponding to varying librational amplitudes, such as those in Figure 6. The sites having hindered motions have a larger apparent dipolar coupling and oscillate more strongly as a function of the recoupling time. As can be seen from the decompositions of these fits

(histograms in Figure 7), the vast majority of the observed surface silanols exhibit such hindered librations whereas others librate with amplitudes centered near 120°. The fact that the majority of the observed silanols have restricted mobility may of course be the result of the low temperatures used here as well as PRESTO’s bias towards polarizing strongly dipolar­coupled pairs. Notably, the MSN­2.7 sample has a higher proportion of hindered silanols (86% vs 73%). This can be observed from the visual inspection of the recoupling curves since the 17O SSNMR signal obtained a negative intensity after 250 μs of recoupling whereas the signal remained positive for the MSN­3.4 sample.

By comparing the dipolar oscillations in samples dried at 25°C and 100°C (Figure 7), it is also apparent that the strongly oscillating signal is greatly reduced in the samples dried at a higher temperature and that the more slowly oscillating components, appearing at longer recoupling times, are unaffected. For example, the dipolar recoupling curve in MSN­2.7 dried at

100°C (Figure 7a) never becomes negative after 200 μs of recoupling due to the slowly

19 oscillating component’s longer signal build­up time, unlike the sample dried at 25°C. The dipolar oscillations for both MSN samples that were dried at 100°C are very similar, suggesting that the same types of silanols remain after this thermal treatment regardless of the sample, in agreement with the HETCOR data.

In view of the HETCOR data, the correlation signal at a 1H chemical shift of 5 ppm, which quickly disappears when drying at 100°C, must correspond to the strongly dipolar coupled site. The relative populations of both types of sites observed from HETCOR and dipolar data are in fact in consistent with each other (compare, for example, Figures 4 and 7). Although this assignment has been proposed earlier based 1H SSNMR studies coupled with TGA analysis,22a,22c this is its first direct confirmation based on 1H­17O correlations and dynamic behavior. The origins of the hindered librations for this site must originate from the strong hydrogen bonding interaction, which restrains its bond vector in a preferential orientation.27 In agreement with the

TGA data, the 17O 2D SSNMR data then shows that there is a greater proportion of strongly interacting silanols in the MSN having the smaller pores. This may be statistical in origin since the higher pore curvature in the MSN­2.7 sample would favor the close interaction of silanols, as mentioned earlier. Thus, 17O DNP SENS provides unprecedented insight into the arrangement of silanol moieties at the surface, as well as their dynamics which is governed by the hydrogen bonding interactions. No other single technique can yield such detail.

29Si Double­Quantum Single­Quantum Correlation

2D 17O{1H} HETCOR data suggested that initial dehydroxylation at 100°C involved primarily the hydrogen­bound and immobile silanols. To further test this hypothesis we performed DNP­enhanced 29Si double­quantum­single­quantum (DQ­SQ) correlation

20 experiments,5e which correlate the chemical shifts of 29Si sites residing in close spatial proximity by using the post­C7 recoupling method (Figure 8).32 We note that the DQ­SQ spectra provide only a qualitative comparison: the initial excitation of 29Si nuclei occurs via 29Si{1H} cross polarization, which emphasizes the silanol sites (Q3) and leaves the Q4 sites suppressed in comparison. As can be seen from the spectra, acquired on MSN­3.4 and depicted in Figure 8, the drying process to a loss of intensity in the Q3­Q3 correlation peak corresponding to silanol groups that are close to each other in space. Importantly, also, after being dried at a temperature of 300°C in vacuo, a temperature higher than the major weight loss observed by TGA, the

Q3­Q4 peak is suppressed as well. The dominance of Q4­Q4 correlation is due to the significantly lower proportion of silanol groups at the surface in this sample, providing additional evidence that the weight loss observed between 100 and 300°C results from the dehydroxylation of neighboring silanols and not from dehydration. Note that it is known that a majority of the adsorbed water is removed in vacuo at room temperature.23 29Si­29Si DQ­SQ spectra acquired on the MSN­2.7 sample also show a loss in Q3­Q3 intensity.

Figure 8. 29Si­29Si post­C7 DQ­SQ spectra for the MSN­3.4 dried in vacuo at 25°C, 100°C, 200°C, and 300°C. The samples dried at elevated temperatures show a prominent decrease of the Q3­Q3 and Q3­Q4 correlation peaks, in agreement with the 17O­1H dipolar oscillations.

Conclusions

21 We have demonstrated that it is indeed possible to perform an array of DNP­enhanced

17O SSNMR experiments of surface sites at natural isotopic abundance in high surface area materials. High­resolution 2D 17O{1H} HETCOR spectra were measured in a reasonable amount of time enabling the separation between hydrogen­bound and isolated surface silanol groups in

1H and 17O dimensions. The measurements demonstrated that the 17O resonance frequency of the surface silanol sites, like the 1H resonance frequency, is correlated to the strength of the hydrogen bonding interactions. HETCOR data and dipolar coupling measurements enabled the observation of the progressive loss of strongly hydrogen­bonded silanol groups at the surface when drying at elevated temperatures. A dynamic analysis of the PRESTO data also enabled the quantification of the motions of these surface sites and showed that the strongly hydrogen­bonded sites have strongly hindered librations. By analyzing the 2D HETCOR data in the light of 29Si DQ­SQ correlation experiments, it became clear that the as synthesized samples contain a large number of vicinal silanol groups that participate in strong hydrogen bonding interactions, thus restricting their motions. These sites are dehydroxylated to form siloxane bridges upon drying the surface under vacuum at an elevated temperature. Notably as well, we observed from 17O DNP SENS measurements that there is a higher proportion of hydrogen­bonded silanols in the MSN sample having smaller pore diameters. We believe that these developments will inspire further uses of DNP­enhanced natural­abundance 17O 2D

SSNMR to non­intrusively probe the structure and dynamics at the surface of important materials and introduce oxygen to routine DNP SENS studies.

Experimental

Sample preparation

22 Cetyltrimethyl ammonium bromide (CTAB), tetraethyl orthosilicate (TEOS) and mesitylene were obtained from Aldrich and were used as received. To produce MCM-41 MSNs with 2.7 nm pores (MSN-2.7), CTAB (1.0 g), NaOH (2M, 3.5 mL) and deionized water (480 mL,

18 megohm) were mixed and placed in pre-heated oil bath (82 oC) under vigorous stirring. After the temperature stabilized at 82°C, the reaction was stirred for an additional hour. TEOS

(5.0 mL) was then added dropwise and the reaction was left to proceed for two more hours. The product was separated by hot filtration and washed with a copious amount of water and methanol. Finally, the surfactant was removed by acid washing and the resulting silica was dried at room temperature, and then at 100°C under vacuum. The synthesis of the MSNs with expanded pores (MSN-3.4) followed the same procedure of the MSN-27 sample, but mesitylene

(3.0 mL) was added to the reaction mixture prior to the introduction of TEOS. The surface area and pore size distribution were measured by nitrogen sorption isotherms at -196°C using a Micromeritics Tristar analyzer. The surface area was calculated by the

Brunauer-Emmett-Teller (BET) method and the pore volume was calculated by the

Barret-Joyner-Halenda (BJH) method. Small angle powder diffraction measurements were performed on a Bruker AXS D8 Discover powder diffractometer at 40 kV, 40 mA for Cu Kα (λ =

1.5406 Å) using a fast-mode continuous position sensitive detector (Linxeye Xe). The diffractograms were analyzed using the Bruker’s Diffract Eva program. TGA was performed under vacuum on NETZSCH STA 409 PC/PG instrument operating from 25oC to 700oC at

4°C/min.

DNP NMR Spectroscopy

All DNP measurements were performed at 9.4 T using a Bruker Avance III MAS­DNP

NMR system equipped with a 263 GHz gyrotron accessory. The samples were impregnated with a 16 mM 1,1,2,2­tetrachloroethane solution of the TEKPol biradical and then packed into

23 3.2­mm o.d. sapphire MAS rotors. The rotors were prespun at room temperature outside the probe and, subsequently, spun at 105 K for the NMR measurement.

17O PRESTO­QCPMG experiments were performed under MAS at 12.5 kHz using the previously published pulse sequence17a with 160 μs (2 rotor periods) of dipolar recoupling. The

17O central­transition selective 90° and 180° pulses lasted 5 and 10 μs, respectively. The spikelet separation was set to 1.25 kHz and 14k scans were acquired with a 4 s recycle delay for a total experimental time of 16 hours. In all cases 64 echoes were accumulated although only 12 were

used for the Fourier transformation due to the short T2 relaxation times of the samples.

The 17O{1H} PRESTO­QCPMG HETCOR experiments were acquired using the same conditions as the 1D spectra, except for the spikelet separation which was increased to 3.125 kHz for samples treated at 25°C and to 6.25 kHz for samples treated at 100°C, 200°C, and 300°C, in

order to improve the sensitivity. 1536 scans were accumulated per t1 increment of 130.7 μs and

frequency­switched Lee­Goldberg homonuclear decoupling was applied during t1 to improve the

1 33 resolution in the H dimension. Between 24 and 32 t1 increments were acquired and the

States­TPPI method was used for phase­sensitive detection.

The 17O­1H dipolar oscillations were measured with a series of PRESTO­QCPMG experiments under MAS at 10 kHz. The second PRESTO recoupling time was fixed, to maintain a consistent echo duration, and the length of the first recoupling block was incremented in steps

of 22.2 or 44.4 μs. Typically, 2k scans were accumulated per t1 increment. The curves were predicted numerically using SIMPSON30 (ver. 4.1) with the same experimental conditions,

17 assuming an axially­symmetric EFG tensor and a CQ( O) value of 4.4 MHz. Powder averaging was accomplished using 232 orientations generated by the ZCW scheme.34

24 29Si DQ­SQ spectra were acquired under 5 kHz MAS, using 2.8 ms (14 rotor periods) of

Post­C7 recoupling for DQ excitation and reconversion.32 29Si{1H} cross­polarization with 4 ms contact time was used to excite the 29Si nuclei. The 1H and 29Si 90° pulses both lasted 2.5 μs.

Between 14 and 20 t1 increments of 200 μs were acquired and the States method was applied for phase­sensitive detection.

Acknowledgements

This research is supported by the U.S. Department of Energy (DOE), Office of Science,

Division of Chemical Sciences, Geosciences, and Biosciences. Support for F.P. is through a

Spedding Fellowship from the Ames Laboratory, which is funded by the Ames Laboratory’s

LDRD program. Ames Laboratory is operated for the DOE by Iowa State University under

Contract No. DE­AC02­ 07CH11358.

References

25 1 (a) L. R. Becerra, G. J. Gerfen, R. J. Temkin, D. J. Singel, and R. G. Griffin, Phys. Rev. Lett., 1993, 71, 3561; (b) V. S. Bajaj, C. T. Farrar, M. K. Hornstein, I. Mastovsky, J. Vieregg, J. Bryant, B. Eléna, K. E. Kreischer, R. J. Temkin, and R. G. Griffin, J. Magn. Reson., 2003, 160, 85; (c) T. Maly, G. T. Debelouchina, V. S. Bajaj, K.­N. Hu, C.­G. Joo, M. L. Mak­Jurkauskas, J. R. Sirigiri, P. C. A. van der Wel, J. Herzfeld, R. J. Temkin, and R. G. Griffin, J. Chem. Phys., 2008, 128, 052211; (d) M. Rosay, L. Tometich, S. Pawsey, R. Bader, R. Schauwecker, M. Blank, P. M. Borchard, S. R. Cauffman, K. L. Felch, R. T. Weber, R. J. Temkin, R. G. Griffin, and W. E. Maas, Phys. Chem. Chem. Phys. 2010, 12, 5850; (e) V. K. Michaelis, T.­C. Ong, M. K. Kiesewetter, D. K. Frantz, J. J. Walish, E. Ravera, C. Luchinat, T. M. Swager, and R. G. Griffin, Isr. J. Chem. 2014, 54, 207.

2 (a) H. Lock, R. A. Wind, G. E. Maciel, and C. E. Johnson, J. Chem. Phys. 1993, 99, 3363; (b) A. Lesage, M. Lelli, D. Gajan, M. A. Caporini, V. Vitzthum, P. Miéville, J. Alauzun, A. Roussey, C. Thieuleux, A. Mehdi, G. Bodenhausen, C. Copéret, and L. Emsley, J. Am. Chem. Soc. 2010, 132, 15459; (c) R. G. Griffin, Nature, 2010, 468, 381.

3 A. J. Rossini, A. Zagdoun, M. Lelli, A. Lesage, C. Copéret, and L. Emsley, Acc. Chem. Res. 2013, 46, 1942.

4 (a) T. Kobayashi, O. Lafon, A. S. L. Thankamony, I. I. Slowing, K. Kandel, D. Carnevale, V. Vitzthum, H. Vezin, J.­P. Amoureux, G. Bodenhausen, and M. Pruski, Phys. Chem. Chem. Phys., 2013, 15, 5553; (b) O. Lafon, A. S. L. Thankamony, T. Kobayashi, D. Carnevale, V. Vitzthum, I. I. Slowing. K. Kandel, H. Vezin, J.­P. Amoureux, G. Bodenhausen, and M. Pruski, J. Phys. Chem. C, 2013, 117, 1375.

5 (a) O. Lafon, M. Rosay, F. Aussenac, X. Lu, J. Trébosc, O. Cristini, C. Kinowski, N. Touati, H. Vezin, and J.­P. Amoureux, Angew. Chem. Int. Ed. 2011, 50, 8367; (b) M. Lelli, D. Gajan, A. Lesage, M. A. Caporini, V. Vitzthum, P. Miéville, F. Héroguel, F. Rascón, A. Roussey, C. Thieuleux, M. Boualleg, L. Veyre, G. Bodenhausen, C. Copéret, and L. Emsley, J. Am. Chem. Soc., 2011, 133, 2104; (c) A. J. Rossini, A. Zagdoun, M. Lelli, D. Gajan, F. Rascón, M. Rosay, W. E. Maas, C. Copéret, A. Lesage, and L. Emsley, Chem. Sci. 2012, 3, 108; (d) O. Lafon, A. S. L. Thankamony, M. Rosay, F. Aussenac, X. Lu, J. Trébosc, V. Bout­Roumazeilles, H. Vezin, and J.­P. Amoureux, Chem. Commun. 2013, 49, 2864; (e) D. Lee, G. Monin, N. T. Duong, I. Z. Lopez, M. Bardet, V. Mareau, L. Gonon, and G. De Paëpe, J. Am. Chem. Soc. 2014, 136, 13781.

6 (a) D. Lee, H. Takahashi, A. S. L. Thankamony, J.­P. Dacquin, M. Bardet, O. Lafon, and G. De Paëpe, J. Am. Chem. Soc., 2012, 134, 18491; (b) V. Vitzthum, P. Miéville, D. Carnevale, M. A. Caporini, D. Gajan, C. Copéret, M. Lelli, A. Zagdoun, A. J. Rossini, A. Lesage, L. Emsley, and G. Bodenhausen, Chem. Commun. 2012, 48, 1988; (c) D. Lee, N. T. Duong, O. Lafon, and G. De Paëpe, J. Phys. Chem. C, 2014, 118, 25065; (d) M. Valla, A. J. Rossini, M. Caillot, C. Chizallet, P. Raybaud, M. Digne, A. Chaumonnot, A. Lesage, L. Emsley, J. A. van Bokhoven, C. Copéret, J. Am. Chem. Soc. 2015, 137, 10710.

7 (a) A. J. Rossini, A. Zagdoun, M. Lelli, J. Canivet, S. Aguado, O. Ouari, P. Tordo, M. Rosay, W. E. Maas, C. Copéret, D. Farrusseng, L. Emsley, and A. Lesage, Angew. Chem. Int. Ed. 2012, 51, 123; (b) T. Kobayashi, S. Gupta, M. A. Caporini, V. K. Percharsky, and M. Pruski, J. Phys. Chem. C, 2014, 118, 19548; (c) T. Gutmann, J. Liu, N. Rothermel, Y. Xu, E. Jaumann, M. Werner, H. Breitzke, S. T. Sigurdsson, and G. Buntkowsky, Chem. Eur. J. 2015, 21, 3798.

8 F. Blanc, L. Sperrin, D. Lee, R. Dervisoğlu, Y. Yamazaki, S. M. Haile, G. De Paëpe, and C. P. Grey, J. Phys. Chem. Lett., 2014, 5, 2431.

9 (a) P. Wolf, M. Valla, A. J. Rossini, A. Comas­Vives, F. Núñez­Zarur, B. Malaman, A. Lesage, L. Emsley, C. Copéret, and I. Hermans, Angew. Chem. Int. Ed., 2014, 53, 10179; (b) W. R. Gunther, V. K. Michaelis, M. A. Caporini, R. G. Griffin, and Y. Román­Leshkov, J. Am. Chem. Soc., 2014, 136, 6219; M. P. Conley, A. J. Rossini, A. Comas­Vives, M. Valla, G. Casano, O. Ouari, P. Tordo, A. Lesage, L. Emsley, and C. Copéret, Phys. Chem. Chem. Phys. 2014, 16, 17822.

10 L. Protesescu, A. J. Rossini, D. Kriegner, M. Valla, A. de Kergommeaux, M. Walter, K. V. Kravchyk, M. Nachtegaal, J. Stangl, B. Malaman, P. Reiss, A. Lesage, L. Emsley, C. Copéret, and M. V. Kovalenko, ACS Nano, 2014, 8, 2639.

11 Johnson, R. L.; Perras, F. A.; Kobayashi, T.; Schwartz, T. J.; Dumesic, J. A.; Shanks, B. H.; Pruski, M. Chem. Commun. 2016, 52, 1859.

12 R. P. Sangodkar, B. J. Smith, D. Gajan, A. J. Rossini, L. R. Roberts, G. P. Funkhouser, A. Lesage, L. Emsley, and B. F. Chmelka, J. Am. Chem. Soc., 2015, 137, 8096.

13 (a) V. Lemaître, M. E. Smith, and A. Watts, Solid State Nucl. Magn. Reson. 2004, 26, 215; (b) J. Zhu, E. Ye, V. Terskikh, and G. Wu, Angew. Chem. Int. Ed. 2010, 49, 8399.

14 S. E. Ashbrook, and M. E. Smith, Chem. Soc. Rev. 2006, 35, 718.

15 (a) C. Song, K.­N. Hu, C.­G. Joo, T. M. Swager, and R. G. Griffin, J. Am. Chem. Soc. 2006, 128, 11385; (b) C. Sauvée, M. Rosay, G. Casano, F. Aussenac, R. T. Weber, O. Ouari, and P. Tordo, Angew. Chem. Int. Ed. 2013, 123, 11058; (c) A. Zagdoun, G. Casano, O. Ouari, M. Schwarzwälder, A. J. Rossini, F. Aussenac, M. Yulikov, G. Jeschke, C. Copéret, A. Lesage, P. Tordo, and L. Emsley, J. Am. Chem. Soc. 2013, 135, 12790.

16 (a) F. A. Perras, J. Viger­Gravel, K. M. N. Burgess, and D. L. Bryce, Solid State Nucl. Magn. Reson. 2013, 51­52, 1; (b) F. H. Larsen, H. J. Jakobsen, P. D. Ellis, and N. C. Nielsen, J. Magn. Reson. 1998, 131, 144; (c) F. H. Larsen, J. Skibsted, H. J. Jakobsen, and N. C. Nielsen, J. Am. Chem. Soc. 2000, 122, 7080.

17 (a) F. A. Perras, T. Kobayashi, M. Pruski, J. Am. Chem. Soc. 2015, 137, 8336; (b) F. A. Perras, T. Kobayashi, M. Pruski, Phys. Chem. Chem. Phys. 2015, 17, 22616.

18 F. Blanc, L. Sperrin, D. A. Jefferson, S. Pawsey, M. Rosay, and C. P. Grey, J. Am. Chem. Soc. 2013, 135, 2975.

19 (a) X. Zhao, W. Hoffbauer, J. Schmedt auf der Günne, and M. H. Levitt, Solid State Nucl. Magn. Reson. 2004, 26, 57; (b) J. D. van Beek, R. Dupree, and M. H. Levitt, J. Magn. Reson. 2006, 179, 38.

20 W. P. Aue, E. Bartholdi, and R. R. Ernst, J. Chem. Phys. 1976, 64, 2229.

21 I. I. Slowing, B. G. Trewyn, V. S.-Y. Lin, J. Am. Chem. Soc. 2007, 129, 8845.

22 (a) C. E. Bronnimann, R. C. Zeigler, and G. E. Maciel, J. Am. Chem. Soc. 1988, 110, 2023; (b) C. C. Liu and G. E. Maciel, J. Am. Chem. Soc. 1996, 118, 5103; (c) J. Trébosc, J. W. Wiench, S. Huh, V. S.­Y. Lin, and M. Pruski, J. Am. Chem. Soc. 2005, 127, 3057.

23 L. T. Zhuravlev, Surf., A, 2000, 173, 1.

24 N. Merle, J. Trébosc, A. Baudouin, I. Del Rosal, L. Maron, K. Szeto, M. Genelot, A. Mortreux, M. Taoufik, L. Delevoye, and R. M. Gauvin, J. Am. Chem. Soc. 2012, 134, 9263.

25 (a) B. Berglund and R. W. Vaughan, J. Chem. Phys. 1980, 73, 2037; (b) H. Eckert, J. P. Yesinowski, L. A. , and E. M. Stolper, J. Phys. Chem. 1988, 92, 2055; (c) R. Kaliaperumal, R. E. J. Sears, Q. W. Ni, and J. E. Furst, J. Chem. Phys. 1989, 91, 7387; (d) U. Sternberg and E. Brunner, J. Magn. Reson. Ser. A, 1994, 108, 142. 26 (a) A. Wong, K. J. Pike, R. Jenkins, G. J. Clarkson, T. Anupõld, A. P. Howes, D. H. G. Crout, A. Samoson, R. Dupree, and M. E. Smith, J. Phys. Chem. A, 2006, 110, 1824; (b) F. G. Vogt, H. Yin, R. G. Forcino, and L. Wu, Mol. Pharmaceutics, 2013, 10, 3433.

27 T. Kobayashi, J. A. DiVerdi, and G. E. Maciel, J. Phys. Chem. C, 2008, 112, 4315.

28 (a) B. H. Meier, F. Graf, R. R. Ernst, J. Chem. Phys., 1982, 76, 767; (b) J. Tritt­Goc, N. Piślewski, U. Haeberlen, Chem. Phys., 1986, 102, 133; (c) J. Tritt­Goc, J. Phys. Chem. Solids, 1995, 56, 935; (d)P. Schanda, M. Huber, J. Boisbouvier, B. H. Meier, and M. Ernst, Angew. Chem. Int. Ed., 2011, 50, 11005.

29 J. J. Kinnun, A. Leftin, and M. F. Brown, J. Chem. Educ., 2013, 90, 123.

30 (a) M. Bak, J. T. Rasmussen, and N. C. Nielsen, J. Magn. Reson., 2000, 147, 296; (b) Z. Tošner, R. Andersen, B. Stevensson, M. Edén, N. C. Nielsen, and T. Vosegaard, J. Magn. Reson., 2014, 246, 79.

31 M. Goswami and P. K. Madhu, J. Magn. Reson. 2012, 219, 4.

32 (a) Y. K. Lee, N. D. Kurur, M. Helmle, O. G. Johannessen, N. C. Nielsen, and M. H. Levitt, Chem. Phys. Lett. 1995, 242, 304; (b) M. Hohwy, H. J. Jakobsen, M. Edén, M. H. Levitt, and N. C. Nielsen, J. Chem. Phys. 1998, 108, 2686.

33 A. Bielecki, A. C. Kolbert, M. H. Levitt, Chem. Phys. Lett., 1989, 155, 341.

34 (a) S. K. Zaremba, Ann. Mat. Pura Appl., 1966, 73, 293; (b) H. Conroy, J. Chem. Phys. 1967, 47, 5307; (c) V. B. Cheng, H. H. Suzukawa Jr., M. Wolfsberg, J. Chem. Phys., 1973, 59, 3992.