Characterization of Morphology and Active Agent Mobility within

The porous properties of sol–gels make them attractive choices for developing functional materials requiring the controlled release of entrapped act...
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Characterization of Morphology and Active Agent Mobility within Hybrid Silica Sol−Gel Composites Hugh O’Neill,*,† Suresh Mavila Chathoth,‡ Mateus B. Cardoso,§ Gary A. Baker,∥ Eugene Mamontov,‡ and Volker S. Urban† †

Energy and the Environment Group, Biology and Soft Matter Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States ‡ Spectroscopy Group, Chemical and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States § LNLS - Laboratório Nacional de Luz Síncrotron, CEP 13083-970, Caixa Postal 6192, Campinas SP, Brazil ∥ Department of Chemistry, University of Missouri-Columbia, Columbia, Missouri 65211, United States ABSTRACT: The porous properties of sol−gels make them attractive choices for developing functional materials requiring the controlled release of entrapped active agents for a range of applications that include protective coatings, sensors, selfhealing films, and drug delivery. In this study, we investigate the properties of sodium benzoate as a model active agent entrapped within a mesoporous silica matrix formed from the biocompatible precursor diglycerylsilane (DGS). Quasi-elastic neutron scattering (QENS) is used to measure the mobility and diffusion of the mobile species in the gels, whereas smallangle neutron scattering (SANS) provides key information on the structural features of the gels. QENS measurements indicate that the diffusivity of the benzoate species decreases approximately 4-fold, from 14.3 × 10−10 m2 s−1 in bulk solution to 3.3 × 10−10 m2 s−1 following entrapment within DGS-derived sol−gels. A similar trend is exhibited by water entrapped within the porous network. However, subsequent detailed analysis reveals that the diffusivity of water is not solely influenced by simple confinement in the gels per se but rather by interaction(s) with benzoate species. It can be concluded that confinement in the mesoporous silica gels produces a pronounced suppression in the diffusivity of benzoate but, contrary to conventional wisdom, it appears that it is the composition of the mobile phase that most affects the diffusivity of D2O both within the mesoporous silica gels and in the bulk. Structural analysis of the gels using SANS confirms that the gels comprise highly branched structures with relatively large pore sizes in the mesoporous regime. There is no evidence for the formation of benzoate aggregates greater than 2 nm in size within the gels despite the fact that dynamics measurements reveal a decreased diffusivity for benzoate, which might reasonably be expected to occur as a result of aggregation and/or an increased interaction with the sol−gel matrix. The ability to characterize the distribution and diffusion of guests mobilized in porous host carriers remains a major scientific bottleneck in controlled-release research. In this fashion, this investigation nicely highlights the fact that neutron scattering techniques represent a set of powerful, complementary, and underutilized tools to characterize and unlock the complex structural and dynamic features of complex materials of interest in controlled release and elsewhere.

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INTRODUCTION Sol−gel chemistry is very versatile and has been demonstrated to be effective for a number of different applications.1 The properties of sol−gels can be modulated to promote attachment to different surfaces, such as metals and plastics, to control the pore size from the micro- (5 by addition of the BA, which is typically dissolved in a solution buffered at pH ∼7 after which gelation is allowed to continue. In addition, a significant quantity of alcohol is released as a byproduct of the reaction whose presence can be detrimental to some BAs. Lastly, TEOS or TMOS gels shrink extensively over time (up to 85% shrinkage), which results in cracking of the brittle matrix and changes in the pore characteristics of the composite material. These shortcomings have led to the development of new sol− gel precursors such as diglycerylsilane.6−9 Hydrolysis of this sol−gel precursor results in the release of glycerol, a biocompatible compound that can provide a stabilizing environment for the entrapped BA. Moreover, these gels have low shrinkage characteristics, which can allow greater control over morphology, including porosity and pore structure, in hybrid silica materials. In sol−gel systems, solute mobility is dependent on the morphology, interconnectivity, and surface chemistry of the pores.5 Electron microscopies and small-angle scattering techniques can be used to determine pore size and distribution in micro- and mesoporous materials.10 NMR, infrared, and Raman spectroscopies have been used to measure diffusion in sol−gel materials and microporous solids.11−13 These methods generally cannot provide detailed information about local conditions around relatively low-concentration guest molecules. Although fluorescence spectroscopy is a very sensitive technique, it requires inclusion of a fluorescent marker, a feature that can disrupt the very property being sought.14,15 Neutron scattering may offer distinct advantages for characterizing hybrid sol−gel materials over other techniques. Quasielastic neutron scattering (QENS) is a very appropriate tool for dynamic studies of complex macromolecular systems because it can be used to directly measure the mobility and diffusion of small molecules in micro- and mesoporous solids in the pico- to nanosecond time frame without requiring the attachment of an exogenous probe.16−18 Recently, QENS has been used to investigate the mobility of the anesthetic lidocaine in a transdermal drug delivery system19 and has also been used to characterize pharmaceutically relevant platforms such as lipidbased systems and colloidal emulsions and also the role of mono- and disaccharides as cryoprotectants.20−22 To fully understand solute mobility, it is necessary to have a priori knowledge of the structural properties of the material under investigation. Small-angle neutron scattering (SANS), in addition to providing information about pore size, can offer an additional advantage in that it can determine interconnectivity of pores due to the differential scattering of H2O and D2O. This technique has been applied for structural characterization of drug delivery systems (recently reviewed by ref 23). The information gained from neutron scattering characterization can be used to tune the molecular features of the

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METHODS AND MATERIALS Synthesis of Sol−Gels. Sodium benzoate was entrapped in aqueous silica gels synthesized using sol−gel chemistry. Deuterated diglycerylsilane (d-DGS), the sol−gel precursor reagent, was synthesized using the previously described procedure6 except that deuterated d8-glycerol was used in place of its hydrogenated counterpart. The sol−gels for QENS and SANS analysis were prepared using a two-step approach. First, the sol solution was formed by hydrolysis of d-DGS in D2O (pH 7) at a 1:3 mass ratio in an ultrasonication bath at 4 °C. In the second step, the gelation reaction was carried out by mixing 0.4 mL of the sol solution with the desired amount of sodium benzoate (2.5 M in D2O) or glycerol (Sample 5 only) to a final volume of 0.8 mL. The final compositions of the gels are listed in Table 1. The gels were aged for 48−72 h at room temperature (∼22 °C) before the neutron scattering measurements. For QENS measurements, the gelation reactions were carried out directly in the annular aluminum sample holders used for the measurements. For SANS analysis, the gelation reactions were carried out in quartz cuvettes with a 1 mm optical path length. Quasi-Elastic Neutron Scattering. Quasi-elastic neutron scattering (QENS) experiments were performed on the backscattering spectrometer (BASIS) at the Spallation Neutron Source, Oak Ridge National Laboratory.31 The polychromatic incident neutrons scattered by the samples are reflected back to 13973

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processes that involve the molecules in the sample. The coefficients y1 (y1 = 1 − y2 − y3), y2, and y3 are the relative fractions of scattering intensities from species that are mobile on the time scale of the experiment. The boundaries are defined by the spectrometer resolution and the accessible energy transfer range. Eq 2 becomes a one or two Lorentzian function when either both y2 and y3 or only y3 become zero, respectively. The Q2 dependence of the half-width and half-maximum (hwhm) can be fitted with the jump diffusion model shown in eq 3.33

Table 1. Molar Composition of Samples for QENS and SANS Measurements component silicic acid (Si(OD)4) d8-glycerol (C3D8O3) Na benzoate (C7H5O2Na) Water (D2O) h8-glycerol (C3H8O3)

1

2

3

4

0.65

0.6

0.65

0.65

1.30

1.2

1.30

1.30

1.25

1.0

0.62

41.9

43.6

45.3

5

6

1.44 1.25

48.8

42.6

44.4 1.25

detectors by the analyzer Si(111) crystals; the reflected neutrons are monochromatic with a wavelength of λ = 6.267 Å (2082 μeV). The initial energy for each detected neutron can be calculated from its time-of-flight; because the final energy of 2082 μeV is known, the energy and the scattering momentum transfer can be determined. The samples were prepared in annular aluminum containers with an annular spacing of 0.5 mm. This ensured greater than 90% transmission of neutrons through the sample and minimized the possibility of multiple scattering in the samples. The sample containers were sealed with indium O-rings and mounted into a closed-cycled refrigerator in which the temperature could be controlled within ±0.5 K. The measurements of the diffusion dynamics were carried out at the physiologically relevant temperature of 310 K (37 °C), whereas the data collected from the same samples at 6 K was used as the sample-specific resolution function. The elastic intensity scans were recorded at 5 min intervals while decreasing the temperature from 310 K to at least 150 K at the rate of 2 K/min. QENS Data Analysis. The data analysis is restricted to the energy transfer range from −100 to +100 μeV (with a 0.4 μeV energy transfer bin) because outside this energy window the data was affected by spurious scattering. The energy resolution of the spectrometer, when averaged over all scattering momentum transfers, is approximately 3.4 μeV (full-width at half-maximum, fwhm). The raw data were converted from the time-of-flight bin to the energy transfer bin at selected Q values using standard BASIS data reduction software. The data analysis was carried out using the DAVE software.32 For quantitative analysis of spectral broadening as a function of Q and to understand the number of components that contributed to the quasi-elastic signal, the spectra at each Q value were fitted with eq 1. I(E) = [xδ(E) + (1 − x)S(E) + B(E)] ⊗ R(E)

(1)

⎡ Γ1 Γ2 1 1 + y2 S(E) = ⎢(1 − y2 − y3 ) 2 2 2 π E + Γ1 π E + Γ 22 ⎣ Γ3 ⎤ 1 ⎥ 2 π E + Γ 32 ⎦

(3)

where Γ1/2 (Q) is the Q dependent hwhm, D is the diffusivity, τ0 is the resident time between successive jumps, and ℏ is the reduced Plank’s constant. The jump length, l, of molecules is related to D and τ0 as, l = (6Dτ0)1/2. Table 2 shows, in addition to the diffusion parameters, the spectral weights of the Lorentzian components, both obtained from the fits with eq 1 and anticipated on the basis of the samples composition. The anticipated spectral weights were calculated under assumption that, in the low Q range utilized in the current study, the signal from each sample is dominated by incoherent scattering. Only the incoherent scattering cross section of H and D atoms is used for calculation of the spectral weights of each sample because the other atoms present do not have an incoherent neutron scattering cross section: (molar concentration (mmol/mL) × number of D or H atoms × incoherent cross section of D or H atoms)/(total incoherent scattering cross section due to D and H atoms in the sample). Small-Angle Neutron Scattering. SANS experiments were carried out using the CG3 Bio-SANS instrument34 at the High Flux Isotope Reactor of Oak Ridge National Laboratory. Scattering data were recorded for scattering vectors (q) 0.003 < Q < 0.14 Å−1 [q = (4π/λ) sin(θ/2), λ is the neutron wavelength and θ is the scattering angle] using 6 Å neutrons with a wavelength spread, Δλ/λ, of 0.15. Data were collected using a 1 × 1 m2, position sensitive He3-detector at sample-to-detector distances of 6.8 and 15.3 m. For SANS analysis, the sol−gels were formed in 1 mm path quartz cuvettes (Hellma USA, Plainview, NY). The relative amounts of D2O and H2O in the samples was varied to optimize the scattering power of the system (100% D2O) or to reach the contrast match of silica (60% D2O). D2O, the D2O/ H2O mixtures, and an empty cell were used to determine baseline scattering. Calibration measurements over the full Qrange were included as control measurements. SANS data analysis was carried out using the Irena evaluation routine implemented in commercially available Igor Pro Sof tware.35 A multilevel unified fit was used to describe the levels of structural organization evident in the scattering data.36,37 In this method, the scattering provided by each structural level is the sum of a Guinier exponential-form and a structurally limited power-law tail. A generalized equation representing any number of structural levels is written as:36,37

Here, δ(E) is a delta function centered at zero energy transfer, x represents the fraction of elastic scattering, B(E) is the background term, R(E) is the resolution, and S(E) is the model scattering function. The model scattering function is a two or a three Lorentzian function in the following general form:

+ y3

⎤ ℏ⎡ 1 ⎢1 − ⎥ τ0 ⎣ 1 + DQ 2τ0 ⎦

Γ1/2(Q ) =

n

I (Q ) =

⎛ −Q 2R 2 ⎞ ⎛ −Q 2R 2 ⎞ gi g(i + 1) ⎟ + Bi exp⎜ ⎟ ⎟ ⎜ ⎟ 3 ⎝ 3 ⎠ ⎝ ⎠

∑ Giexp⎜⎜ i=1

⎡ (erf(QR / 6 ))3 ⎤ Pi gi ⎢ ⎥ ⎢⎣ ⎥⎦ Q

(2)

where Γ1, Γ2, and Γ3 are the half-width at half-maximum (hwhm) of Lorentzian components due to various diffusion 13974

(4)

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where n is the number of structural levels observed, Gi is the Guinier prefactor, Rg is the radius of gyration, and Bi is a prefactor specific to the type of power-law scattering which is specified as the decay of the exponent Pi.

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RESULTS AND DISCUSSION The overall aim of this study was to investigate the structure and dynamics of a hybrid composite sol−gel material to gain insight into the effect of confinement on the distribution and dynamics of entrapped Na benzoate molecules. Neutron scattering techniques benefit from the difference in the scattering length densities of hydrogen (1H) and its isotope deuterium (2H). The incoherent scattering from 1H nuclei has a scattering signal approximately 40 times greater than that of 2 H. To maximize the scattering signal from the entrapped Na benzoate molecules, a deuterium labeled sol−gel precursor was synthesized to attenuate the scattering signal from the glycerol released during the hydrolysis of the sol−gel precursor. In addition, D2O was used as the solvent for synthesis of the sol− gels. The composite materials were formed by addition of the Na benzoate in a D2O-based solution to a partially hydrolyzed d-DGS precursor. The condensation reaction occurred relatively rapidly to yield homogeneous optically clear gels. The samples were prepared as described in Materials and Methods with the compositions shown in Table 1. Small-Angle Neutron Scattering. SANS was used to investigate the structural properties of the gels. The scattering curves of the gel samples with Na benzoate were all very similar, exhibiting power-law dependence (solid red line) over the entire Q-range measured (0.003−0.15 Å−1) (part A of Figure 1). The exponent of the power-law fits varied between 2.36−2.39, which is indicative of a branched-gel structure. There was no evidence of a shoulder-type Guinier region in the low Q region, which suggests that the sol−gel structures have pores that have larger dimensions (>∼100 nm) than the lengthscales accessible by the SANS performed measurements. However, the scattering profiles of the gels formed in the absence of Na benzoate, exhibited power-law dependence in the mid- and high-Q-range (part B of Figure 1). The exponent of the power-law fit was slightly larger than the sol−gelbenzoate composites at 2.58 but is also consistent with a branched-gel-structure. However, unlike the sol−gel−benzoate composites, the scattering profile deviated from power-law dependence in the low Q region, which could be attributed to the presence of a Guinier region. The Guinier model was used to fit the scattering profile in the low Q region (Q < 0.006 Å−1) generating a radius of gyration of 550 Å. This dimension may be interpreted as the average size of the silica clusters38 or the macropores in the gel. In parallel, measurements were carried out at the contrast match-point for the sol−gel (60% D2O) to highlight the scattering contribution of the Na benzoate in the gels. However, no scattering above the background was evident (data not shown). This is the expected behavior when the system has a solute dispersed into a continuous medium and provides clear evidence that there was no formation of Na benzoate aggregates large enough to be detected by SANS in the gels. Analysis of QENS Data. QENS measurements were carried out on Na benzoate confined in silica gels, Na benzoate in bulk liquid, and also the appropriate control samples (Table 1). At first, the elastic intensity scans were performed for temperatures below 320 K for the Q values between 0.2−1.7 Å−1 to evaluate qualitatively how confinement of Na benzoate in the pores of

Figure 1. SANS profiles of sol−gel samples. A, with 1.25 M Na benzoate (Sample 1 from Table 1); B. control sol−gel sample in the absence Na benzoate (Sample 4 from Table 1).

the sol−gels influences its dynamics. The melting or freezing transition in a sample is associated with an onset or cessation of diffusion motions of molecules respectively, which manifests itself as an abrupt step in the elastic intensity scan. This step appears due to a redistribution of elastic scattering intensity, from the molecules in the solid state, to quasi-elastic scattering intensity, which is associated with the scattering of molecules in the liquid state. Likewise, on freezing, the quasi-elastic intensities due to scattering from the mobile molecules become converted into the elastic intensity, thereby resulting in abrupt increase of the latter. The effect of temperature on the elastic intensity of each sample is shown in Figure 2 at an arbitrarily selected Q value of 1.1 Å−1. The other Q values measured show the same trend. All of the samples display a large and abrupt change in the elastic intensity at approximately 265 K indicating the freezing point of the liquids in the samples. There was no difference in the freezing temperature for the sol−gel samples and the bulk liquids, which demonstrates that the liquids in the sol−gels did not experience a significant confinement effect by the silica matrix. This suggests that the pore sizes of the gels are large in comparison to the size of the entrapped molecules and are too large to induce any noticeable confinement effects on the diffusion dynamics of the entrapped liquids. Furthermore, one can conclude that the observed freezing point depression in comparison with bulk D2O (277 K) is entirely due to the presence of solutes in the D2O solvent and is not influenced by 13975

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number of components that contributed to the quasi-elastic signal, the spectra at each Q value were fitted using Lorentzian functions. The number of Lorentzian functions that are required to fit the scattering data can be related to the translational motions of the different species in the samples. A single Lorentzian function produced fits to the data that were of very poor quality for all the samples. However, two Lorentzian functions were required to describe the scattering data of the samples which contained glycerol and D2O. Furthermore, three Lorentzian functions were necessary to produce good fits to the samples that contained Na benzoate, glycerol, and D2O (sample compositions in Table 1). The Q dependence of Γ1, Γ2, and Γ3, the hwhm of the Lorentzian components obtained from the fits with eq 2, is shown in Figure 4. At low Q values,

Figure 2. Temperature dependence of the elastic neutron scattering intensities.

the confinement effects of the gels. This is consistent with the SANS analysis, which showed that the gel pores are relatively large so are not expected to influence the dynamics of the D2O solvent. Other studies that report reduced water mobility in silica glasses compared to bulk water have been carried out with microporous materials in which water diffusion resembles the properties of bulk water at low temperatures.39−43 Above a certain value of the pore size, microscopic diffusion of water is no longer suppressed by the effects of confinement. A representative semilogarithmic presentation of the scattering data collected for each sample at Q = 0.9 Å−1 is shown in Figure 3. The elastic intensity peak is centered at zero

Figure 4. Calculation of the diffusion coefficients of the solutes in the gels. The half-width at half-maximum of the Lorentzian components, Γ1/2(1), Γ1/2(2), and Γ1/2(3), obtained from the fits with eq 1 and eq 2 to the QENS spectra (Figure 2) are plotted as a function of square of momentum transfer. The solid lines are the fits with jump diffusion model (eq 3).

the Lorentzian components exhibit a Q2-proportional dependence, and at high Q values the broadening becomes almost saturated, which is a signature of so-called translational jump diffusion. It should be noted that rotational diffusion processes, which are too fast to be detected in our experiment, would yield a Q-independent hwhm of the quasi-elastic signal. The Qdependence of each Lorentzian component (Γ1, Γ2, and Γ3) can be fitted with a jump diffusion model (eq 3). In the jump diffusion model, a molecule is at rest (except for the vibrational motions) for a period of time, τ0, before performing a diffusion jump in an arbitrary direction at a distance l. A fit to the experimental data yielded parameters for diffusivity (D), jump length (l), and the residence time (τ0) for each Lorentzian component, which are listed in Table 2. As described above, the quasi-elastic broadening observed in the spectra is due to the motions of glycerol and Na-benzoate

Figure 3. Semilogarithmic representation of QENS data collected for each sample. Data are shown for Q = 0.9 Å−1. The solid black lines are either two or three component Lorentzian fits to the experimental data as described in the text.

energy transfer (0 μeV) and is dominated by the silica gel matrix. The observed spectral broadening is related to the quasi-elastic signal and originated from the translational motions of mobile species in the sol−gels. The faster rotational diffusion processes yield a quasi-elastic scattering signal that is much wider compared to the BASIS instrument’s dynamic range and thus cannot be probed. For quantitative analysis of spectral broadening as a function of Q and to determine the 13976

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Table 2. Parameters of the Translational Jumps Diffusion Processes Obtained from the QENS Data Fitsa sample

component

mol. ratios

D ± SD (10−10m2 s−1)

τ0 (ps)

1

D2O Na benzoate d8-glycerol D2O Na benzoate d8-glycerol D2O Na benzoate d8-glycerol D2O d8-glycerol D2O Na benzoate d8-glycerol D2O h8-glycerol

33.5 1.0 1.0 43.6 1.0 1.2 73.1 1.0 2.1 37.5 1.0 34.1 1.0 1.2 35.5 1.0

11.8 ± 0.2 3.3 ± 0.3 4.9 ± 2.9 16.2 ± 0.8 4.6 ± 0.3 4.6 ± 3.7 19.9 ± 1.7 7.5 ± 0.9 1.9 ± 1.1 21.1 ± 0.6 8.0 ± 5.2 12.8 ± 0.2 14.3 ± 3.0 20.8 ± 24.5 17.7 ± 0.3 3.3 ± 1.1

9.8 ± 0.9 19.3 ± 2.1 159 ± 20 5.7 ± 0.2 8.8 ± 0.8 104 ± 50 5.5 ± 0.3 8.8 ± 0.9 69 ± 38 4.3 ± 0.1 111 ± 17 9.5 ± 0.9 11.1 ± 1.4 117 ± 23 5.1 ± 0.1 39 ± 9

2

3

4 5

6

L (Å) 2.6 2.0 6.8 2.4 1.6 5.4 2.6 2.0 2.8 2.3 7.3 2.7 3.1 12.0 2.3 2.8

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.1 0.2 1.9 0.1 0.1 3.3 0.2 0.2 1.6 0.1 2.3 0.1 0.5 5.8 0.0 0.8

y1, y2, y3b

y1, y2, y3b

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.24 0.72 0.02 0.27 0.69 0.03 0.40 0.55 0.04 0.90 0.10 0.25 0.73 0.02 0.37 0.62

0.22 0.74 0.02 0.30 0.67 0.03 0.42 0.52 0.06 0.87 0.13 0.22 0.73 0.03 0.38 0.63

0.06 0.05 0.03 0.04 0.03 0.03 0.04 0.06 0.04 0.06 0.04 0.03 0.02 0.02 0.05 0.05

D, translational diffusion coefficient (SD, standard deviation); τ0, residence time between jumps; l, distance between jumps. bAlso shown are the measured (obtained from the fits) and expected spectral weights (y1, y2, y3) of the Lorentizian QENS components that originate from motions of different molecules.

a

large error bars; this is because the spectral weight of the signal due to the glycerol contribution is small except in the control sample that contained hydrogenated glycerol (sample 6). Most importantly, the diffusivity of Na benzoate was greatly decreased when entrapped in the sol−gel compared to in bulk solution, 3.3 × 10−10 and 14.3 × 10−10 m2 s−1, respectively. Thus, confinement in the pores has a pronounced suppression effect on the diffusivities of Na benzoate but not water. For the series of sol−gel samples studied, the diffusivity of Na benzoate monotonically decreases as the concentrations of the Na benzoate increases, which is similar to the trend exhibited by D2O. A plot of the diffusion coefficient of Na benzoate entrapped in sol−gels versus Na benzoate concentration is shown in Figure 5. The diffusion coefficient shows an

dissolved in D2O and confined in the porous sol−gel. The contribution to the spectral intensity from each of these species is expected to be proportional to its neutron scattering crosssection multiplied by its relative concentration in each sample studied. The parameters y1, y2, and y3 in eq 2 represent the experimentally determined spectral fractions of the intensities from molecules that contribute to the Lorentzian components with the hwhm of Γ1, Γ2 and Γ3. The fractions of intensity that could be expected from D2O, glycerol, and Na-benzoate, based on their concentration in each sample and their neutron scattering cross sections, were calculated for comparison with the experimentally determined Γ1, Γ2, and Γ3 components. As shown in Table 2, there was a remarkable agreement between the expected values and those determined from the experimental data fits, which makes possible to assign each Lorentzian fit component to the translational motions of D2O, d8-glycerol, and Na-benzoate molecules. The diffusivities of the D2O solvent molecules are not dramatically lower compared to the previously reported values for bulk D2O of 18.7 × 10−10 m2 s−1 and 29.8 × 10−10 m2 s−1 at 298 and 318 K, respectively (Table 2).44 For the series of silicagel samples studied, the diffusivity of D2O monotonically decreases from 21.1× 10−10 to 11.8 × 10−10 m2 s−1 as the concentration of the Na benzoate is increased. The diffusivity of D2O is very similar in the sol−gel and bulk sample with the highest concentration of Na benzoate (samples 1 and 5). Likewise, comparison of the sol−gel and control sample that are free of Na benzoate (samples 4 and 6) shows that the confined D2O do not slow down. In fact, the diffusivity of D2O in confinement in sample 4 is somewhat faster, which is likely due a difference in the influence of d8- and h8-glycerols on the water dynamics. These observations are in good agreement with the elastic intensity scans that were discussed above. As the major component of the sol−gel and bulk solutions, D2O largely determines the freezing temperature depression, which is not influenced by either the confinement in the gels, nor by the Na benzoate concentration. However, unlike the confinement, the compositional variations gently and systematically affect the diffusivity of D2O. Little can be said about the diffusivity of d8-glycerol in the different samples, which exhibit

Figure 5. Diffusivity of Na benzoate in the sol−gels as a function of concentration.

exponential dependence on concentration. A similar dependence of diffusion coefficient on concentration has been shown for benzoate and other organic solutes in detergent micelles.45 The diffusion coefficients of the benzoate in the sol−gels were fitted to an exponential concentration dependence (D = D0 e(−K/M)) to yield D0 = 2.83 ± 0.2 × 10−10 m2 s−1, which represents the diffusion coefficient at infinite dilution, and K = 1.32 ± 0.01 M−1, an equilibrium constant which describes effect of confinement on benzoate. 13977

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CONCLUSIONS The ability to characterize the distribution and diffusion of guest molecules in host carriers remains a major scientific bottleneck in controlled-release research. To optimize the controlled release of active agents, it is crucial to gain an understanding of the factors that influence the dynamic properties of active agents entrapped in porous hosts. In this study, we have investigated the properties of sodium benzoate as a model active agent entrapped in a biocompatible sol−gel matrix formed using DGS as a precursor. Using quasi-elastic neutron scattering, it was possible to extract the diffusion coefficients for three solutes in the composite material which could be assigned to D2O, Na benzoate, and glycerol. Even at the lowest concentration, Na benzoate contributed ∼50% of the elastic signal, indicating that it is possible to measure bioactive agents at lower concentrations than those used in this study. The diffusivity of the Na benzoate decreased ∼4-fold when entrapped in sol−gels compared to in bulk solution and a similar trend was exhibited by the D2O solvent. However, further analysis showed that the diffusivity of D2O is not influenced by the confinement in the gels but rather by its interactions with Na benzoate. It can be concluded that confinement in the silica gels has a pronounced suppression effect on the diffusivities of Na benzoate, but it is the compositional variations in the samples that affect the diffusivity of D2O in silica gels and in bulk solution. Structural analysis of the gels using SANS showed that the gels are highly branched structures with relatively large pore sizes (>∼100 nm). There was no evidence for the formation of benzoate aggregates (>2 nm) in the gels even though the dynamics measurements showed a decrease in its diffusivity at the highest concentration, which could be a result of aggregation of benzoate molecules or increased interactions with the sol−gel matrix. An important advantage of neutron scattering techniques is that they are nondestructive and do not require modification of the molecule of interest for analysis. It is clear that these techniques could be used as powerful tools to characterize the dynamic and structural properties of a wide range of materials for the controlled release of active substances.

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authored by a contractor of the U.S. Government under Contract DE-AC05−00OR22725.

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AUTHOR INFORMATION

Corresponding Author

*Phone: 865-574-5004. Fax: 865-574-6268. E-mail: oneillhm@ ornl.gov. Notes

The authors declare no competing financial interest.

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REFERENCES

ACKNOWLEDGMENTS

Funding for this work was provided by the Laboratory Directed Research and Development SEED Money program at Oak Ridge National Laboratory (ORNL). Experiments at the Center for Structural Molecular Biology (ERKP291) using Bio-SANS were supported by the Office of Biological and Environmental Research. Experiments using BASIS were supported by the Office of Basic Energy Sciences (BES), U.S. Department of Energy (DOE). Research at ORNL’s High Flux Isotope Reactor and Spallation Neutron Source was sponsored by the Scientific User Facilities Division, BES, U.S. DOE. UTBattelle, LLC manages ORNL under U.S. DOE contract No. DE-AC05-00OR22725. The submitted manuscript has been 13978

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