ARTICLE pubs.acs.org/IECR
Systematic Investigation of Dispersions of Unmodified Inorganic Nanoparticles in Organic Solvents with Focus on the Hansen Solubility Parameters Jan U. Wieneke,†,‡ Bj€orn Kommoß,†,‡ Oxana Gaer,†,‡ Iana Prykhodko,§ and Mathias Ulbricht*,†,‡ †
Lehrstuhl f€ur Technische Chemie II, Universit€at Duisburg-Essen, 45141 Essen, Germany CeNIDE - Center for Nanointegration Duisburg-Essen, 47057 Duisburg, Germany § Physics of Solids Department, Physics Faculty, V.N. Karazin Kharkiv National University, 4 Svoboda Square, Kharkiv 61077, Ukraine ‡
bS Supporting Information ABSTRACT: Dispersions of unmodified nanoparticles (titanium dioxide, hydroxyapatite) were prepared by redispersion of nanoparticle powders in organic solvents using an ultrasound treatment. The dispersion quality was judged by dynamic light scattering (DLS) measurements and visual evaluation. Whereas “bad” solvents led to no or unstable dispersions with large particle diameters, dispersions made from the “good” solvents consisted of particles with relatively small diameters and were stable for several days or longer. For titanium dioxide, mixtures from four of the “good” solvents identified after first screening of a large set of solvents were prepared and tested as dispersion agent. Thus obtained dispersions showed superior properties compared to the previous dispersions, with small particles sizes and good long-time stability. Based on a rating of solvent quality and by calculation using the software HSPiP v3, the Hansen solubility parameters of the particles were then determined. Subsequently, entirely new solvent mixtures that could best fit these parameters were selected and found to also exhibit suitable properties as dispersion agent for the nanoparticles. The same iterative and quantitative approach worked also for the preparation of good and stable dispersions of hydroxyapatite. All results show that this is a promising methodology to disperse inorganic nanoparticles into suited organic solvents, for instance for the preparation of new polymeric nanocomposites. Furthermore, the method can be used to indirectly characterize the surface chemistry of nanoparticles.
1. INTRODUCTION For some processes the dispersion of inorganic nanoparticles in organic solvents is desirable, for instance for the preparation of inorganicorganic nanocomposites by different methods. Nanocomposites are of growing scientific and also industrial interest and the field is developing very quickly recently. There are different approaches toward inorganicorganic nanocomposites.1 Much research has been done on composites from organic polymers and silica nanoparticles.2 By utilization of organic dispersions it is also possible to incorporate inorganic nanoparticles in solution cast membranes which is a promising pathway to add stability or functionalities to these materials.3 Organic solvents have— compared to water—a wide range of properties with largely different structures, polarities, and interfacial energies. Most works dealing with dispersions of inorganic nanoparticles in organic solvents either use additives to improve solvent compatibility (e.g., fatty acid derivatives, functional polymers) or change the hydrophilicity of the particles by grafting of more hydrophobic moieties to their surface, e.g., by silanization,4 addition of organic phosphoric acid derivatives, or grafting of aminoalkanes. In our group another study was performed on the dispersion of SiO2 nanoparticles in different ionic liquids. By silane modification it was possible to change the surface properties of the particles from hydrophilic to hydrophobic and thus to compatibilize them also with hydrophobic ionic liquids.5 Ahn et al. used a barium oxide modification on the surface of 50-nm r 2011 American Chemical Society
TiO2 nanocrystals to obtain a BaOH surface. They achieved an enhanced dispersibility of the particles and obtained stable dispersions of 2 wt % in methanol and N,N-dimethyl formamide (DMF). They explained the improvement by higher solubility of Ba(OH)2 in the respective solvents and by the hindrance of TiOH condensation reactions (Ostwald ripening).6 Another practical approach is the replacement of water by mixing with a second (organic) solvent and subsequent complete removal of the water. Chopin et al. described the redispersion of 45-nm TiO2 nanoparticles that had been produced from titan oxychloride in a wet process in acidic water in presence of citric acid. The particles were redispersed into water with a pH of 1.5 and then ethylene glycol was added. After distillation of the water the remaining dispersion had 0.7 wt % residual water with a TiO2 mass fraction of 20% and particle size of 45 nm.7 Theoretical predictions on solvent/solute compatibility can be derived from the total cohesive energy density which can be measured by breaking up the cohesion between the molecules in evaporation experiments. The cohesion properties of a liquid can be described with the Hansen solubility parameters (HSP) established by Charles M. Hansen in 1967.8 The approach is Received: August 31, 2011 Accepted: December 12, 2011 Revised: December 9, 2011 Published: December 12, 2011 327
dx.doi.org/10.1021/ie201973u | Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
based on splitting the total cohesion energy E [J] of a liquid in three separate energies (eq 1): ED [J] for the nonpolar atomic dispersion interactions, EP [J] for the dipoledipole molecular interactions, and EH [J] as the energy of the hydrogen bonding molecular interactions. E ¼ ED þ EP þ EH
understand as they claimed that about 70% of the particle surface should have been covered with alkyl groups from the derivatization with fatty acids. Their conclusion was that the “far larger size” of the modified particles (compared to the solvent molecules) is responsible for this effect. In another part of their study they stated that “it is not necessary to include effects of hydrogen bonding between the SMNP [modified nanoparticles] and solvent molecules” because of the “dense surface modifier layer as the shell”. However, the result for dispersions in long chain aliphatic solvents does not imply that there is a dense alkyl shell on the surface that prohibits hydrogen bonding. Therefore, it could be questionable to ignore the hydrogen bonding parameter. Hence, irrespective the demonstration of a promising approach, some questions regarding the interpretation still remain.14 The use of the software HSPiP v3 is extending the scope for the calculation of HSP compared to older methods such as Tea’s plot as it can calculate the RED in a three-dimensional coordinate system and supports the user with data for more than 10 000 substances. More about the theoretical background of these calculations, their limitations and errors can be found in refs 911 and 15. Today HSP can not only be measured but also estimated, for example by a group contribution method16 so that there are HSP available even for nonvolatile substances like ionic liquids. As part of a larger research project, we investigated the transfer of dry powdered semiconductor nanoparticles that had been produced from gas-phase spray pyrolysis or in liquid-phase synthesis processes into dispersions made from different organic solvents. After a series of non-systematic experiments, we focused on the Hansen solubility parameters (HSP) which should also play a role in the deagglomeration and dispersion into smaller agglomerates or primary particles. The systematic screening was performed at constant parameters of the dispersion process and at low nanoparticle concentration (0.015 wt %) in order to show the influence of the different solvents. With small TiO2 nanoparticles from spray pyrolysis we started with “trial and error” experiments using pure solvents and then used intuitively mixed solvents. Based on a ranking of dispersion quality, HSP data were calculated and then used to prepare entirely novel solvent mixtures as dispersion agents. In a second part of this study, we investigated the dispersion of hydroxyapatite obtained from liquid-phase synthesis. Based on experiments with pure solvents in order to estimate HSP data, solvent mixtures fitting to the HSP of the particles were identified and found to work very well as dispersing agents. This approach provides an interesting route from testing of solvents in a laboratory toward technical applications—via this calculation it is possible to avoid solvents that have one or more of the following disadvantages: toxicity, too high or too low volatility, too high or low viscosity, or too high cost.
ð1Þ
Division of eq 1 with the molar volume Vm [m3] gives eqs 2a a nd 2b with the respective parameters δ [(MPa)1/2](eq 3ac). E ED EP EH ¼ þ þ Vm Vm Vm Vm
ð2aÞ
δ2 ¼ δ2D þ δ2P þ δ2H
ð2bÞ
δd ¼
ED Vm
1=2
δp ¼
EP Vm
1=2
δh ¼
EH Vm
1=2 ð3acÞ
The concept implies that liquids which have HSP values near to each other in a 3D coordinate system mix well. The closer the HSP values are, the higher is the affinity which can be expressed by the relative energy distance (RED). The values of the RED are calculated by division of the distance of two points in the system by the interaction radius. If the resulting RED is bigger than 1, there is a low compatibility; in the range of 1 partial mixing should occur; and for values below 1 a very good interaction is expected. The concept has been expanded from the mixing of different liquid hydrocarbons to a broad array of materials including all kinds of solvents and solvent mixtures, pharmaceuticals, biological molecules (DNA, proteins), and polymers. Recently the model has been used for different carbon based materials (i.e., carbon fiber/epoxy composite materials,9 single and multilayered graphene,10 and single-walled carbon nanotubes11). Most authors did not use mixtures but only pure solvents. There are few studies using this concept related to inorganic nanoparticles. In 1994, Suhara et al.,12 a group of researchers from the Japanese cosmetic company Shiseido, worked on the dispersibility of TiO2 which they modified by different hydroxylgroup bearing ethers to achieve varied surface properties. They investigated the changed properties and found deteriorated dispersibility in solvents such as acetonitrile, DMF, nitromethane, 2-ethyl-1-hexanol, butylmethylketone, and aniline, while the quality of dispersions made from i-butanol, ethylcellosolve, methylcellosolve, and ethanol improved very much. They calculated HSP via the older 2D Tea’s plot method, whereas Yamamoto13 used the HSPiP software (http://www.hansen-solubility.com) to recalculate data based on the older results. The HSP values estimated by Yamamoto differ largely from those presented by Suhara et al. but there were also several exceptions. The author proposed a non-uniformity of the surfaces of the investigated TiO2 particles resulting in different and nonuniform HSP values.12,13 Arita et al.14 described the dispersion of 56 nm CeO2 nanocrystals that had been modified with fatty acids by hydrothermal synthesis. Some of the 0.1 wt % dispersions were very stable (1 month) and the lowest particles sizes showed that dispersions of single nanoparticles could be achieved. They used also HSP to find correlations between the measured DLS size and the solvent properties. There were some uncertainties in their conclusions, i.e., they found that n-hexane and n-decane were bad solvents for their modified particles which is not easy to
2. MATERIALS AND METHODS 2.1. Materials. Titanium dioxide (TiO2) nanoparticles were received from IVG (Institute for Gas Dynamics and Combustion, University Duisburg-Essen, Germany) and had been produced by spray pyrolysis of titanium tetrapropoxide. The particles were crystalline, exhibited a specific surface area of 265 m2/g and had an average particle size of 5.3 nm (calculated from BET data; cf. 2.2). From X-ray diffraction (XRD) data (Supporting Information, Figure S1), the calculated crystallite size was 46 nm for anatase (95% fraction) and 4055 nm for rutile (5% fraction). 328
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
or 16 nm (fwhm size). The degree of crystallinity was about 76% (XRD). Solvents were purchased in “p.a.” grade and used as received. To exclude that effects are based on residual water in the organic solvents some of the best and the worst suitable solvents were investigated by Karl Fischer titration to determine the content of water. Water content was variable between 400 and 1000 ppm but without a trend related to the suitability for dispersion. Pure water was obtained from a Milli-Q purification system (Millipore). 2.2. Methods. SEM measurements of the powders were performed with an ESEM Quanta 400 FEG environmental scanning electron microscope. The samples were coated with a thin metal layer by use of an Emitech K550 Sputter Coater (50 mA, 60 s, Target: Au/Pd 80/20). Some of the dispersions were dried on TEM grids and then directly analyzed with a JEOL JSM 7500F in scanning mode. The particle sizes could be obtained from BET data measured on a NOVA-1000 BET surface area analyzer, Quantachrome Corp. By assuming nonporous spherical particles it is possible to calculate the diameter from the measured surface area [m3/g] and the density [g/m3]—this model yields a medium diameter. It was intended to create dispersions with a low particle concentration of 0.015% (m/m), with a small medium particle size and a narrow size distribution. The use of this low concentration allows detecting changes in the dispersions easily via visual changes caused by agglomeration and sedimentation. Crucial for later analytics is the use of syringe filters (PTFE 0.2 μm) to remove dust from all solvents before mixing them with the nanoparticles. The conditions were kept constant besides the use of different solvents because the quality of the dispersions is strongly dependent on the properties of the solvents, but also the used sonotrode probe, the power and duration of treatment, and the container used. The dispersions were obtained in a Bandelin RZ3 rosett cell by addition of 70 g of the organic solvent to 10.5 mg of the nanoparticles followed by the use of an ultrasound dispersion device (Bandelin Sonopuls HD 3200, 200 W, with extended probe VS70T). The sample then was treated at 10% of the maximum amplitude of the ultrasound device for 30 min while cooling the rosett cell from the outside in a waterice bath. The dispersions were characterized via dynamic light scattering (DLS) using a Malvern Nanosizer ZS with a square aperture glass cell. Average particle size distributions by number were recorded. The second analysis method was based on visual estimation of dispersion stability over 4 days, and digital photographs were periodically taken. TiO2 dispersions were prepared from several pure solvents and several mixtures (50:50/33:33:33/25:25:25:25) from four intuitively chosen solvents before the results were used for calculation of HSP. More solvent mixtures with matching HSP were then used. For the hydroxyapatite only pure solvents and then solvent mixtures calculated via HSP were used. For the calculation of the HSP values, the solvents were ranked “good” and “bad” with marks ranging from 1 (excellent) to 6 (insufficient). More details can be found in Section 3. We used the software HSPiP v3 to plot the solvent’s HSP values in a 3Dcoordinate system and to calculate a sphere that incorporates all the “good” and none of the “bad” solvents. The center of this sphere has also a set of Hansen solubility parameters and could be used in combination with the database: (a) to find for the
Figure 1. SEM image of the dry powdered TiO2 particles as received.
Figure 2. SEM image of the dry powdered hydroxyapatite after long time storage (approximately 5 years).
From scanning electron microscopy (SEM; Figure 1) the size was visually estimated as 46 nm. Hydroxyapatite, Ca10(PO4)6(OH)2), was produced at Physics of Solids Department, V.N. Karazin Kharkiv National University, Kharkiv, Ukraine, in a wet process. The synthesis was performed by injecting a solution of ammonium hydrogen phosphate into a solution of calcium nitrate with a molar ratio Ca/P of 1.67 to form a slurry and mixing thoroughly for a minute. Precipitation of the product from the solution was performed by centrifugation. Then it was washed with distilled water three times. The samples were stored in air at room temperature for approximately 5 years. The samples were characterized by infrared spectroscopy and XRD (Supporting Information, Figure S2). The particle size was visually estimated by SEM to be 3060 nm (Figure 2), and by XRD the crystallite size was determined to be 11.5 nm (IB size) 329
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
Table 1. Solvents Used for TiO2 Dispersion Experiments— Marks for Dispersion Quality and Relative Energy Distance (RED) solvent
mark
RED
water
6
8.25
toluene
6
3.23
o-xylene
6
3.18
p-xylene
6
3.18
styrene 1,4-dioxane
6 5
3.12 2.65
2-propanol
5
2.58
anisole
5
2.08
ethyl acetate
5
2.03
acetonitrile
5
1.82
tetrahydropyran
4
1.80
diethylene glycol
3
4.21
1,2-dimethoxyethane ethylene glycol
3 2
2.16 4.21
tetrahydrofurane (THF)
2
1.75
γ-butyrolactone (GBL)
2
1.05
dimethyl sulfoxide (DMSO)
2
1.05
N,N-dimethyl acetamide (DMAc)
1
0.48
mixture (wt %)
mark
RED
THF/DMAc (50/50)
1
0.99
GBL/DMSO (50/50) THF/GBL (50/50)
1 1
0.99 0.61
THF/DMSO (50/50)
1
0.49
DMSO/DMAc (50/50)
1
0.44
GBL/DMAc (50/50)
1
0.30
THF/DMSO/DMAc (33/33/33)
1
0.54
GBL/DMSO/DMAc (33/33/33)
1
0.49
THF/GBL/DMAc (33/33/33)
1
0.45
THF/GBL/DMSO (33/33/33) THF/GBL/DMSO/DMAc (25/25/25/25)
1 1
0.15 0.16
Figure 3. TiO2 based dispersions from aromatic solvents: upper row directly after preparation, lower row after 4 days; from left to right: styrene, toluene, o-xylene, and anisole.
Figure 4. Some other TiO2 based dispersions: upper row directly after preparation, lower row after 4 days; from left to right: THF, 1,4-dioxane, ethyl acetate, GBL.
Using 1H NMR spectroscopy it was not possible to identify the formed products. The degradation behavior of the aromatic solvents is in good agreement with earlier reports where pyrolysis and radical oxidation processes were identified as the main reactions.17,18 During the sonification process different side processes occur: The collapse of the cavitation bubbles leads to high temperatures and pressures and thus can promote chemical conversions. There are two reactions that are known to have impact on degradation: (a) pyrolysis due to high temperature and pressure, and (b) radical formation with subsequent processes.17 The pyrolysis can occur in any solvent, the generation of radical species is dependent on the solvent and atmosphere. Aqueous solutions form hydroxyl radical species during sonification; the presence of oxygen leads to formation of oxygen radicals and ozone.17,18 Establishing an inert atmosphere during the sonification process could reduce this effect. We cannot explain the higher degradation tendency of the aromatic compounds over the other tested solvents but intermolecular interactions could play a role. The non-aromatic solvents were more stable and showed no visible signs of degradation; only the odor of DMSO changed to a slightly recognizable smell of garlic. If the dispersions contained remaining agglomerates in the micro scale, they had the appearance of opaque white slurries. For well dispersed systems with particles that had dimensions much below the wavelengths of visible light, the dispersions were translucent. These “good”
nanoparticles new suitable solvents, or (b) to calculate not intuitively predictable mixtures of solvents. By using the “solvent optimizer” function the program was used to calculate a set of fitting solvent mixtures to match the set of HSP of the nanoparticles. The output results of the program are given as vol% and were recalculated to wt%. Those solvent mixtures were tested and the resulting dispersions were analyzed as before.
3. RESULTS AND DISCUSSION 3.1. Titanium Dioxide Based Dispersions. Overall 20 solvents were tested as dispersion medium for TiO2 nanoparticles (Table 1). From this range of solvents several gave no dispersion at the given conditions: water, acetone, 2-propanol, 1,4-dioxane, DMF, THF, and ethyl acetate. All tested aromatic solvents (toluene, o- and p-xylene, styrene, and anisole) were not suitable as well due to the fact that the ultrasound treatment led to a change in color; some also formed a brown precipitate (Figure 3). Ultrasound energy input leads to a degradation which could also be observed when the aromatic solvents were treated without nanoparticles. 330
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
Table 2. Hydrodynamic Diameter from DLS (Number Average), Stability, and Mark for the Solvents and Intuitively Formed Solvent Mixtures Used for TiO2 Dispersion Experiments d [nm]
stability
mark
tetrahydrofurane
234 ( 43
++
2
1,2-dimethoxyethane
222 ( 12
O
3
diethylene glycol
200 ( 17
O
3
y-butyrolactone
177 ( 5
+
2
anisole
169 ( 35
--
5
ethylene glycol
161 ( 31
+
2
acetonitrile N,N’-dimethylacetamide
78 ( 6 34 ( 12
-++
5 1
dimethylsulfoxide
28 ( 2
+
2
solvent
mixture (wt %)
d [nm]
stability
mark
100 ( 36
++
1
THF/GBL (50/50)
29 ( 5
++
1
GBL/DMSO (50/50)
28 ( 6
++
1
GBL/DMAc (50/50)
24 ( 5
++
1
DMSO/DMAc (50/50) THF/DMAc (50/50)
21 ( 6 9(1
++ ++
1 1
THF/GBL/DMSO (33/33/33)
90 ( 15
++
1
THF/DMSO/DMAc (33/33/33)
40 ( 6
++
1
GBL/DMSO/DMAc (33/33/33)
30 ( 11
++
1
THF/DMSO (50/50)
THF/GBL/DMAc (33/33/33) THF/GBL/DMSO/DMAc (25/25/25/25)
17 ( 1
++
1
100 ( 28
++
1
Figure 5. SEM image of a dispersion of TiO2 dispersion from THF/ DMAc (50/50), dried on a carbon TEM grid.
dispersions had a blue tint which is caused by Rayleigh scattering (e.g., for THF, left in Figure 4). The rating of dispersion quality had two aspects: (1) the particle size in the dispersions, and (2) the stability over a given time. The stability was tested visually: No visual changes (++), slightly visible color changes to white (+), color change and some sedimentation (o), complete sedimentation and lack of blue color (--). After screening the first large set of solvents, from the entire range four solvents were chosen which were suitable to achieve dispersions with relative small particle sizes and stability over 4 days. Those were then used in mixtures to create dispersions as described before. The solvents were tetrahydrofurane, dimethylacetamide, γ-butyrolactone, and dimethylsulfoxide—each used in 50/50, 33/33/33, and one 25/25/25/25 wt % mixtures. In 8 of the 11 mixtures the particle size was below 50 nm, in the remaining three it was around 100120 nm, and all dispersions showed a very good long time stability with no visible sedimentation and stable blue tint for several weeks (Table 2). The different methods to estimate the medium size of the primary particles correlated well: from BET the estimated size was 5.3 nm, from XRD for anatase (95% fraction) the calculated crystallite size was 46 nm, and the smallest hydrodynamic diameter measured via DLS in the best dispersion was 9 nm (THF/DMAc 50/50). This dispersion was used to prepare samples for SEM. Due to the drying conditions larger soft agglomerates were found in which the smaller particles could be identified (Figure 5). On the basis of these experiments, a rating was given to each of the solvents and intuitively formed solvent mixtures in order to proceed with the computer-aided fitting. The critical point in this study was the marking of the different “good” dispersions. The
Figure 6. 3D plot of the data for TiO2 nanoparticles: Blue balls are the “good” solvents, and red cubes are the “bad” solvents. The green sphere includes all good solvents. The central point marks the data set used for the subsequent calculation of novel solvent mixtures. By inspection of all relevant 2D sections, it had been confirmed that all HSP points for “good” solvents were inside or on the surface of the sphere and that all HSP points for “bad” solvents were outside the sphere.
Table 3. Hydrodynamic Diameter from DLS (Number Average), Stability, and Mark for the Calculated Solvent Mixtures Used for TiO2 Dispersion Experiments Using Predicted Solvent Mixtures mixtures from calculations (wt %) DMSO/ethylacetate/NMP (58/26/16) NMP/dimethylformamide/benzyl-alcohol/
d [nm]
stability
mark
802 ( 14
--
6
31 ( 3
++
1
acetonitrile (54/18/17/11) NMP/methanol (91/9)
24 ( 2
++
1
n-amylacetate/DMSO (28/72)
23 ( 11
++
1
GBL/1,3-dioxolane/tert-butyl-alcohol/
16 ( 2
++
1
cyclohexanone (64/20/12/4) 331
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
Figure 7. Hydroxyapatite dispersions (510 days old). In comparison to the TiO2 dispersions there is no blue tint and the only visual difference between “good” and “bad” dispersions is the absence of sedimentation.
software HSPiP supports school marks from “1” (excellent) to “6” (insufficient), but from “1” on the significance of the mark for the calculation reduces quickly. The scores were given based on two criteria, the particle sizes measured by DLS and the stability judged visually, both described before. For the TiO2 dispersions, a score “1” was only possible to achieve for dispersions with a medium hydrodynamic diameter of aggregates in dispersion lower than 125 nm, and a score “2” was given only for diameters below 250 nm. Only dispersions which were stable by visual evaluation (blue color, little deposition) could reach these marks. Dispersions which were less stable could not be ranked better than “3”, regardless of particle size. And unstable dispersions with pronounced sedimentation tendency were given a rating of “4”. In case of immediate flocculation the rating was “5” to “6”. For the evaluation, the “grading” algorithm of the software had been used: “1” corresponds to a “good” solvent, and “4” to “6” correspond to a “bad” solvent (giving a solvent a score of “4” or “6” did not change the results of the calculations), while “2” or “3” would be just above or below theta solvent quality. In the 3D plot the “bad” solvents are presented as red blocks while the “good” solvents appear as blue balls. The center of the calculated sphere, shown in green, has the Hansen parameters D = 17.5, P = 12.7, and H = 8.9 (corresponding to σD, σP, and σH; cf. eq 3ac) with a radius of 4.1 and a fit of 1.000 (Figure 6). Solvent mixtures with HSP values near the ones found by the fitting have then been calculated using the software and tested subsequently (Table 3). It can be seen that most calculated solvent mixtures were as good as the best two single solvents and about half of the mixtures that have been selected intuitively (cf. Table 2). The particles in these dispersions had small hydrodynamic diameters between 16 and 31 nm and the dispersions were stable. The mixtures consisted partly of various solvents not tested before. One of the mixtures exhibited “bad” properties for the dispersion of the nanoparticles. It can be noted that this DMSO-based mixture contained ethylacetate which was not suited as a single solvent (cf. Table 1); however, another DMSO-based mixture with n-amylacetate had excellent properties (cf. Table 3). This could indicate that the model is not perfect and the marks have to be optimized. A possible alternative explanation is that in these
real mixtures microphase segregation or particle shielding effects occur that lead to other local solvent properties than those predicted by the calculations. As test for an application of the dispersions as nanoparticle loaded polymerization medium, the THF/DMAc (50:50) dispersion with hydrodynamic particle diameter of 9 nm was heated for 2 h at boiling temperature. After this treatment the average hydrodynamic radius was unchanged. The best TiO2 dispersion consisted of THF/DMAc 50/50 and had an average hydrodynamic radius of 9 nm while the dry particle sizes were in the range of 5 nm. Pure THF is not the best suitable solvent (234 nm) while DMAc alone showed the best value (34 nm; similar to DMSO) of the tested pure solvents (cf. Table 2). By mixing these two substances a much better overall solvent for dispersion was created. The interaction between solvents and the surface of the nanoparticles can be of different kind and strength. The solvent molecules can be bound either by energetically weak physisorption or due to donor/acceptor coordination. For example, the amide group (in DMAc) could act as a donor and a titanium cation exposed on a TiO2 surface could act as the acceptor partner. To investigate such behavior in detail it is possible to wet, for instance, an epitaxially grown inorganic surface with the organic solvent and to use XPS analytics to detect chemical shifts in the donor atom spectra. Studies with XPS, STM, and other methods have been performed with pyridine and other molecules on TiO2 (110) surfaces.19 The excellent small particle size and the long time stability of the dispersions made from DMAc/THF 50:50 lead to the conclusion that the attractive interactions between solvent and particle are strong and prevent the agglomeration or sedimentation of the nanoparticles. 3.2. Hydroxyapatite Based Dispersions. In a separate case study we investigated hydroxyapatite particle dispersion and tested 11 solvents. The visual evaluation of the dispersion stability was not as easy as for the TiO2: all dispersions were clear without observable light scattering. For the “bad” solvents sedimentation could be observed. Therefore a second set of DLS measurements was performed after 45 days to evaluate dispersion stability. 332
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
4. CONCLUSIONS AND OUTLOOK Whereas the best dispersion for the titanium dioxide nanoparticles was found by intuitive mixing (THF/DMAc 50/50) most of the solvents identified by the systematic, computer-aided approach led to almost equally good dispersions. For the hydroxyapatite, some acceptable solvent mixtures but also one good solvent mixture and one suitable pure solvent that had not been tested before, could be identified. Several of the tested dispersions based on calculations were good but not excellent for both kinds of nanoparticles. This shows that the method is not yet perfect but it can indeed help narrow down the range of solvents to prepare good nanoparticle dispersions. It is another advantage of the HSP calculation approach that one has the tool to substitute solvents that are known to work for a system but have negative side effects (e.g., high toxicity, low or high volatility, too low or too high viscosity, color, too high cost, etc.) by solvent systems that do not have these drawbacks. Obviously, it was not possible to a priori “predict” good dispersants but experiments still have to be performed. The system of establishing the marks has to be refined as it is probably the biggest source of errors. It is also advisible to use a wider spectrum of solvents with a broader range of HSP values for the initial tests in order to obtain more data for ranking and calculation. In case particles show inhomogeneous surface chemistry it would also be possible to apply another calculation mode that uses a “double sphere” and describes the different kinds of surfaces in more detail. The HSP values found for the used titanium dioxide (D = 17.5, P = 12.7, H = 8.9) and hydroxyapatite (D = 17.6, P = 14.0, H = 9.4) particles are relatively similar. Nevertheless, there were still pronounced differences with respect to suited solvents. For instance, HSP for hydroxyapatite indicated DMF to be a good solvent. For TiO2, DMF was tested also (afterward) and it gave no dispersion of acceptable quality. It should also be noted that it has not yet been tested so far if the results can be transferred to dispersions with higher concentrations. However, the surface properties of the nanoparticles could be “mapped” by identifying the best fitting Hansen parameters, so that this methodology can be used as a kind of indirect surface analytical method. Future work will be devoted to improving the marking system and then focus onto dispersions in a higher concentration range.
Table 4. Hydrodynamic Diameter from DLS (Number Average) for the Hydroxyapatite Dispersions from Pure Solvents, Measured 45 Days after Preparation solvent
d [nm]
d [nm]
(as prepared)
(45 days)
mark
water
1570 ( 468
1171 ( 12
5
hexane
630 ( 63
234b
5
acetonitrile
592 ( 3
685 ( 4
5
ethyl acetate y-butyrolactone (GBL)
184 ( 99 179 ( 15
162 ( 5 96 ( 10
3 2
tetrahydrofurane (THF)
133 ( 42
192 ( 10
2
N-methyl-2-pyrrolidone (NMP)
80 ( 23
70 ( 7
1
ethanol
82 ( 4
60b,a
2
acetone
72 ( 14
155
3
dimethylsulfoxide (DMSO)
68 ( 3
86b,a
1
56 ( 3
48 ( 4
1
0
N,N -dimethylacetamide (DMAc) a
One measurement. b Measurement performed after 8 days.
Table 5. Hydrodynamic Diameter from DLS (Number Average) for the Hydroxyapatite Dispersions Prepared from the Calculated Solvent Mixtures mixtures from calculation (wt %)
d [nm]
d [nm]
(as prepared) (45 days) mark 182 ( 94
52a
2
DMF/acetonitrile/acetone (82/12/6)
107 ( 12
51a
2
DMSO/acetonitrile/benzyl alcohol/
69 ( 20
56a
1
N,N-dimethylformamide (DMF)
67a
73a
1
DMSO/acetone/cylcohexanone/ ethanol (65/20/10/5)
51 ( 11
46a
1
acetonitrile/benzyl alcohol/a cetone (55/40/5)
NMP (39/21/21/16)
a
One measurement.
From the range of tested pure solvents the best ones were again DMAc and DMSO (mark “1”). Ethanol and acetone gave also good but relatively unstable dispersions (marks “2” and “3”; the lower rank for acetone was due to partial sedimentation, along with a significant increase of particle size after 45 days). Acetonitrile, hexane, and water were “bad” dispersing agents (mark “5”). The dispersions (or supernatants) were all clear, with obvious sedimentation in case of the bad ones (Figure 7). The DLS data of the dispersions made from pure solvents are presented in Table 4. The center of the calculated sphere for this nanomaterial had the HSP parameter set of D = 17.6, P = 14.0, and H = 9.4 with a radius of 3.0 and a fit of 1.000. Four mixtures and one pure solvent fitting to these HSP values have then been tested. The results are presented in Table 5. From the hydroxyapatite dispersion results it can be seen that the particles in DMF show a hydrodynamic diameter very similar to those in the best solvents used for the initial tests (cf. Table 4). One of the solvent mixtures, a quaternary one, also fits very well in this range. It is also remarkable that, for instance, acetonitrile, which alone was not suited at all, could well be used in mixtures. Of the other three solvent mixtures, two gave dispersions with acceptable hydrodynamic diameters (e100 nm).
’ ASSOCIATED CONTENT
bS
Supporting Information. XRD data for the used TiO2 and hydroxyapatite nanomaterials. This material is available free of charge via the Internet at http://pubs.acs.org.
’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected].
’ ACKNOWLEDGMENT This research was supported financially by the state of North Rhine-Westphalia and the European Union via the project “NanoEnergieTechnikZentrum” (NETZ) and, for the stay of I.P. in Essen, by the Leonhard-Euler-Program of the German Academic Exchange Service (DAAD). Additionally we thank Steven Abbott for technical support with the HSPiP software. 333
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
Industrial & Engineering Chemistry Research
ARTICLE
’ REFERENCES (1) Judeinstein, P.; Sanchez, C. Hybrid organicinorganic materials: A land of multidisciplinarity. J. Mater. Chem. 1996, 6, 511–525. (2) Zou, H.; Wu, S.; Shen, J. Polymer/Silica Nanocomposites: Preparation, Characterization, Properties, and Applications. Chem. Rev. 2008, 108, 3893–3957. (3) Ulbricht, M. Advanced functional polymer membranes. Polymer 2006, 47, 2217–2262. (4) Hong, R. Y.; Fu, H. P.; Zhang, Y. J.; Liu, L.; Wang, J.; Li, H. Z.; Zheng, Y. Surface-modified silica nanoparticles for reinforcement of PMMA. J. Appl. Polym. Sci. 2007, 105, 2176–2184. (5) Wittmar, A.; Ruiz-Abad, D.; Ulbricht, M. Dispersions of silica nanoparticles in ionic liquids investigated with advanced rheology. J. Nanopart. Res. 2011, in press. (6) Ahn, B. Y.; Seok, S. I; Pramanik, N. C.; Kim, H.; Hong, S. Redispersible rutile TiO2 nanocrystals in organic media by surface chemical modification with an inorganic barium hydroxide. J. Colloid Interface Sci. 2006, 297, 138–142. (7) Chopin, T.; Dupuis, D.; Lehaut, C.; Chartier, P.; Talpaert, X. Substrate with a photocatalytic coating based on titanium dioxide and organic dispersion based on titaniumdioxide. U.S. Patent 6362121, 2002 (8) Hansen, C. M. The Three Dimensional Solubility Parameter and Solvent Diffusion Coefficient, Their Importance in Surface Coating Formulation (Doctoral Dissertation); Danish Technical Press: Copenhagen, 1967. (9) Launay, H.; Hansen, C. M.; Almdal, K. Hansen Solubility Parameters for a Carbon Fiber/Epoxy Composite. Carbon 2007, 45, 2859–2865. (10) Hernandez, Y.; Lotya, M.; Rickard, D.; Bergin, S. D.; Coleman, J. N. Measurement of Multicomponent Solubility Parameters for Graphene Facilitates Solvent Discovery. Langmuir 2010, 26, 3208–3213. (11) Bergin, S. D.; Sun, Z.; Rickard, D.; Streich, P. V.; Hamilton, J. P.; Coleman, J. N. Multicomponent Solubility Parameters for Single-Walled Carbon NanotubeSolvent Mixtures. ACS Nano 2009, 3, 2340–2350. (12) Suhara, T.; Fukui, H.; Yamaguchi, M. Characterization of titanium dioxide modified with alcoholic hydroxyl groups. J. Jpn. Soc. Colour Mater. 1994, 67, 489–495. (13) Yamamoto, H. HSP Application note #21, Hansen Solubility Parameter (HSP) of TiO2; http://www.pirika.com/NewHP/PirikaE/ TiO2.html, version of March 3, 2010 (retrieved June 6, 2011). (14) Arita, T.; Ueda, Y.; Minami, K.; Naka, T.; Adschiri, T. Dispersion of Fatty Acid Surface Modified Ceria Nanocrystals in Various Organic Solvents. Ind. Eng. Chem. Res. 2010, 49, 1947–1952. (15) Abbott, S; Hansen, C. M.; Yamamoto, H. Hansen Solubility Parameters in Practice - Complete with software, data and examples (ebook), 3rd ed.; Hørsholm: Denmark, 2010; www.hansen-solubility.com, ISBN 9780955122026. (16) Stefanis, E.; Panayiotou, C. Prediction of Hansen Solubility Parameters with a New Group-Contribution Method. Int. J. Thermophys. 2008, 29, 568–585. (17) Shemer, H.; Narkis, N. Mechanisms and Inorganic Byproducts of Trihalomethane Compounds Sonodegradation. Environ. Sci. Technol. 2004, 38, 4856–4859. (18) Berlan, J.; Trabelsi, F.; Delmas, H.; Wilhelm, A. M.; Petrignani, J. F. Oxidative degradation of phenol in aqueous media using ultrasound. Ultrason. Sonochem. 1994, 1, 97–102. (19) Suzuki, S.; Yamaguchi, Y.; Onishi, H.; Sasaki, T.; Fukui, K.; Iwasawa, Y. Study of pyridine and its derivatives adsorbed on a TiO2(110)(1 1) surface by means of STM, TDS, XPS and MD calculation in relation to surface acid base interaction. J. Chem. Soc. Faraday Trans. 1998, 94, 161–166.
334
dx.doi.org/10.1021/ie201973u |Ind. Eng. Chem. Res. 2012, 51, 327–334
