Bimodal Morphology Transition Pathway in the Synthesis of Ultrasmall

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C: Physical Processes in Nanomaterials and Nanostructures

Bimodal Morphology Transition Pathway in the Synthesis of Ultrasmall Fluorescent Mesoporous Silica Nanoparticles Melik Z. Turker, Kai Ma, and Ulrich B. Wiesner J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.9b00860 • Publication Date (Web): 19 Mar 2019 Downloaded from http://pubs.acs.org on March 21, 2019

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The Journal of Physical Chemistry

Bimodal Morphology Transition Pathway in the Synthesis of Ultrasmall Fluorescent Mesoporous Silica Nanoparticles

Melik Z. Turker†, Kai Ma†,¶, , and Ulrich Wiesner†,* †

Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853, USA

ABSTRACT

Morphological transitions during the surfactant directed synthesis of mesoporous silica nanoparticles (MSNs) are of great interest as these materials are highly desirable for applications in catalysis, separation, and drug delivery. We investigate the transition pathway in the formation of ultrasmall fluorescent MSNs of two different morphologies synthesized through micelle templating. Increasing the concentration of pore expander trimethylbenzene, [TMB], drives a transition from singlepore MSNs to silica rings. We show that in the transition region, while their relative composition varies, both particle structures maintain constant pore and particle sizes as a function of [TMB]. Beyond the transition region an increase in the size of the silica rings is observed. The bimodal nature of this transition is corroborated by a combination of gel permeation chromatography (GPC), fluorescence correlation spectroscopy (FCS), dynamic light scattering (DLS), and transmission electron microscopy (TEM) investigations and can be influenced by solution stirring rate. We expect that insights from the study of such transition pathways will be essential for the ability to synthesize advanced-generation nanomaterials for applications including nanomedicine.

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INTRODUCTION

Discovery of MCM-41 materials with varying pore sizes (15-100 Å) by Kresge et al. in 1992 was a breakthrough in nanomaterials research.1 From bulk-type materials to mesoporous silica nanoparticles (MSNs), these organic molecule self-assembly directed inorganic materials have offered new opportunities to materials scientists for a number of applications including drug delivery and biosensors.2– 8

It also has brought great attention to understanding the formation mechanisms of such materials

synthesized via self-assembled micelle/silica interactions in solution, vital for continuous improvements of mesoporous materials synthesis efforts.9

In 1998, Stucky et al. developed SBA-15 materials with larger pore sizes (46-300 Å) by introducing Pluronic-type block copolymer non-ionic surfactant micelle solution directed silica materials formation.10 Addition of an oil phase in the form of pore expander molecule trimethylbenzene (TMB) to the solution did not only result in pore size increases, but also caused a morphological transition from hexagonally ordered SBA-15 silica with pores around 4-12 nm into mesocellular foams (MCFs) with pores around 22-42 nm.11-13 While MCFs form through spherical micelle templates, SBA-15 silicas form through cylindrical rod-like templates, which start out as spheres and go through a morphological transition upon the addition of tetraethyl orthosilicate (TEOS). TEOS addition is known to screen the charge and repulsive interactions between micelle head groups thereby decreasing the effective area that micelle head groups occupy and inducing the morphological sphere to cylinder transition.13,14 With increasing concentration of TMB, [TMB], the inverse morphological transition has also been proposed, where hexagonally packed rod-like templates are first turned into a noded cylindrical shape maintaining the hexagonal packing, which upon further TMB addition break up into aggregated spheres producing the MCFs.13 As a result, the ordered hexagonal structure of SBA-15 silicas is only maintained for low [TMB],


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while morphological transformation to spherical micelles occurs with increasing [TMB] also leading to increasing pore sizes.15–20

In 2014, Kelley et al. reported on a detailed experimental morphology transition study on the distinct bimodal size distribution of gently agitated, kinetically trapped spherical block copolymer micelle assemblies perturbed far from their equilibrium size, but these micelles were not used to structure direct inorganic materials.21 There have been continued reports of bimodal pore size distributions in MSNs, but they often lack a detailed experimental study to elucidate the exact origin of this bimodal behavior that may stem from transitions between two different template structures as described above.22–24

In the last decade, MSN research has evolved into a much smaller size regime below 10 nm hydrodynamic particle diameter. This ultrasmall size regime is particularly relevant for applications in the field of nanomedicine, where silica particle sizes below 10 nm have resulted in efficient renal clearance in animal studies and first human clinical trials thereby substantially reducing the potential for adverse side effects.25-28 At the same time that MSN synthesis efforts in this size regime may open new types of applications, they help to elucidate early mesoporous silica material formation mechanisms, which in turn may accelerate improved materials synthesis. Ma et al. were the first to report a well-controlled synthesis route to single-pore fluorescent MSNs with hydrodynamic diameters < 10 nm, referred to as mesoporous Cornell dots, or simply mC dots.29,30 Key features enabling precise particle size and narrow size distribution control below 10 nm were rapid hydrolysis allowing only a narrow time window for particle nucleation as well as control over the particle growth period by rapid particle capping via the addition of poly(ethylene glycol)-silane (PEG-silane) at different time-points of the synthesis, similar to how size and size distribution are controlled in living polymerizations. More recently, Ma et al. reported on studies introducing TMB into the same surfactant/water/silica system, which resulted in the formation of ~10 nm sized silica rings (Cornell rings or simply C rings) as well as slightly larger silica cages, including ~12 nm ACS Paragon Plus Environment

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diameter

cages

with

dodecahedral

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structure.31,32

While a separate study revealed that the addition of TMB leads to a marked broadening of the surfactant micelle size distribution ultimately responsible for the formation of larger (~100-200 nm) sized quasicrystalline MSN structures,33 the exact [TMB] dependent pathway/mechanism of the morphological transition between ultrasmall single-pore MSNs and silica rings remains unclear. This is what the current study focuses on. Elucidation of such pathways will help in the improved synthesis of advanced ultrasmall nanomaterials for applications in fields including nanomedicine. For example, results reported here may lead to the synthesis of more homogeneous nanoparticle batches or smaller average nanoparticle sizes leading to less uptake in organs like liver and spleen.27,28

METHODS

Materials

All materials were used as received. Hexadecyltrimethyl ammonium bromide (CTAB, ≥99%), tetramethyl orthosilicate (TMOS, ≥99%), 2.0 M ammonium hydroxide in ethanol, and anhydrous dimethyl sulfoxide (DMSO, ≥99%) were purchased from Sigma Aldrich. 2-[methoxy(polyethyleneoxy)69propyl]trimethoxysilane (PEG-Silane, MW ~500 g/mol), and (3-mercaptopropyl) trimethoxysilane (MPTMS, 95%) were obtained from Gelest. Mesitylene (TMB, 99% extra pure) was purchased from Acros Organics. Tetramethylrhodamine-6 C2 maleimide (TMR) was purchased from Anaspec. Absolute anhydrous ethanol (200 proof) was obtained from Pharmco-Aaper. Glacial acetic acid was purchased from Macron Fine Chemicals. 0.9% sodium chloride irrigation USP solution was purchased from Braun. Syringe filters (0.2 µm, PTFE membrane) were purchased from VWR International. Vivaspin sample concentrators (MWCO 30K) and Superdex 200 prep grade were obtained from GE Health Care. Snakeskin dialysis membrane (MWCO 10K) was purchased from Life Technologies. Deionized (DI) water was


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generated using a Millipore Milli-Q system (18.2 MΩ.cm). Glass bottom microwell dishes for FCS were obtained from MatTek Corporation. Carbon film coated copper grids for TEM were purchased from Electron Microscopy Sciences.

Synthesis of the Particles

Our fluorescent mC dots and C rings were synthesized as described previously. 29-31 To that end, 0.227 mmol of CTAB and 1 mL of 20 mM aqueous ammonium hydroxide solution were added into 9 mL DI water. Following this step, for the synthesis of pure mC-Dots there was no addition of TMB. The [TMB] was varied from 14.4 mM to 360.8 mM to drive the morphological transition from mC dots to C rings. Solutions were then stirred at 30°C for 40 mins to fully dissolve CTAB. Following this step, 0.45 mmol TMOS, and 0.0004 mmol TMR dye (conjugated with 0.01 mmol MPTMS in DMSO, 12-24 h prior to synthesis) were added into the reaction and stirring was continued at 30°C for 24 h. On the second day, 0.21 mmol PEG-silane was added into the solution and stirring continued for another 24 h at 30°C. Unless otherwise stated, stirring rate was kept at 600 rpm. The relative molar ratios of the reactants were 1 TMOS: 0.498 CTAB: 0.043 ammonium hydroxide: (0 – 7.89) TMB: 0.47 PEG-Silane: 0.00088 TMR: 0.022 MPTMS: 1090.9 DI water. On the third day of synthesis samples were heated at 80°C for 24 h without stirring to facilitate covalent PEG-silane attachment onto the SNP surface.34,35

The following day, the solution was cooled down to room temperature and subsequently transferred into a dialysis membrane. After that, the sample solution was dialyzed for 24 h to extract CTAB and TMB out of the pores in a 200 mL acid solution, mixed from ethanol, DI water, and acetic acid at volume ratios of 1:1:0.014. This extraction step was repeated three times. It was followed by dialysis in 2 L DI water for 24 h, which was also repeated 3 times. In the final step, sample solutions were syringe filtered (0.2 µm MWCO) to remove large aggregates and dust particles.


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GPC Purification of the Particles

Following dialysis and filtration steps, samples were transferred into spin filter sample concentrators and centrifugation (Eppendorf 5810 R) was performed at 4300 RPM for 30 min. After that, 400 µL of up-concentrated samples were injected into a GPC column packed by Superdex 200 prep grade resin. Buffer solution (0.9% sodium chloride) was pumped into the column using a Bio-Rad BioLogic LP system. Bio-Rad BioFrac fraction collector collected GPC fractions of samples. Following fractionation, which separated particles from small aggregates and precursors as described elsewhere,34 particle solutions were transferred back into spin filters for up-concentration. Following the centrifugation at 4300 RPM for 30 min for 3 times, particles transferred in DI water were finally syringe filtered for subsequent characterization experiments.

Quantitative analysis of GPC data

Bio-Rad LP software recorded ultraviolet (UV) absorption versus elution time graphs for each sample. GPC spectra of different samples were only compared in terms of their shapes (symmetry), but not in terms of their elution times of the peak positions, since absolute elution time is highly dependent on details of the manual use of the equipment and column preparation which may change from day to day. OriginLab software was employed to fit two Log-normal distributions under each curve by floating the peak centers for the two distributions. Areas below each Log-normal distribution curve were compared to calculate the ratios between mC dot and C ring populations.

For skewness calculations, small residual aggregation peaks were excluded by only selecting the main product peak highlighted in red in Figure S4. Skewness is the ratio of the third moment of the distribution function with the cube of its standard deviation (see equ.(5) below).36 Since probabilities for


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y

different data points are not equal to each other, each data point was weighted by ∑ yj , where y i is the UV

intensity at point i. The average time, 𝑋𝑋𝑎𝑎𝑎𝑎𝑎𝑎 , for each data point is defined as 𝑦𝑦𝑗𝑗

𝑋𝑋𝑎𝑎𝑎𝑎𝑎𝑎 = ∑𝑖𝑖𝑖𝑖 𝑋𝑋𝑗𝑗 × ∑

𝑖𝑖 𝑦𝑦𝑖𝑖

i i

(1)

where x i is the elution time for data point i. The second moment of the distribution is then:

2

𝑦𝑦𝑗𝑗

2𝑛𝑛𝑛𝑛 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 = ∑𝑖𝑖𝑖𝑖 ��𝑋𝑋𝑗𝑗 − 𝑋𝑋𝑎𝑎𝑎𝑎𝑎𝑎 � × ∑


� (2)

The corresponding standard deviation is defined as:

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 = √2𝑛𝑛𝑛𝑛 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

(3)

The third moment of the distribution function is expressed as:

3

𝑦𝑦𝑗𝑗

3𝑟𝑟𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 = ∑𝑖𝑖𝑖𝑖 ��𝑋𝑋𝑗𝑗 − 𝑋𝑋𝑎𝑎𝑎𝑎𝑎𝑎 � × ∑


� (4)

Finally, the skewness of the distribution can be derived from the following formula:36

3𝑟𝑟𝑟𝑟 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = (𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷)3

(5)

Characterization of mC dot and C ring Populations via Particle Morphology and Size


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For transmission electron microscopy (TEM) sample preparation, 1 µL of each sample was diluted into 100 µL ethanol, and 10 µL of this solution was dropped onto TEM grids and ethanol was evaporated at room temperature. TEM images were taken using a FEI Tecnai T12 Spirit model microscope operated with an acceleration voltage of 120 kV and manufacturer specified TEM resolution of 0.35 nm. In order to analyze particle morphology and size distribution from TEM images (details below), we manually drew blue filled circles around mC dots and red filled circles around C rings for hundreds of particles for each sample (Figure S6-S9). Images manually processed this way were exported to ImageJ software.

In TEM the mC dots and C rings were distinguished from each other using several unique features associated with electron density contrast (mC dots provide more contrast then C rings) and morphology (mC dots may be star-shaped, have single or multi-pore structure, and C rings have larger single pore morphologies). 25-27 Particles were excluded from analysis when they were touching, and when mC dot vs. C ring distinction was impossible. Even though this introduced a certain degree of uncertainty into the analysis, performing this analysis over multiple samples provided reproducible results. In an effort to reduce bias, we also labeled the particles in a way to cover the entire sample area homogeneously, without focusing on certain regions. After color coding, we split blue and red color channels of an image for processing. Each channel was then filtered by thresholding. After that, each processed image was split into 4 equal pieces for error calculations. In the last step, software calculated the particle numbers and average areas for each population. Particle diameters were calculated from the average areas using the exact particle numbers. Particle numbers for each population allowed to calculate number ratios between mC dots and C rings for a given synthesis condition.

Cryogenic electron microscopy (cryo-EM) was performed on C ring sample as described previously.31


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Dynamic Light Scattering (DLS) Characterization of mC dots and C rings

Average hydrodynamic particle sizes and size distributions by number were measured using dynamic light scattering (DLS) performed on a Malvern Zetasizer Nano-ZS operated at 20°C. Measurements were repeated 3 times in DI water for each sample to provide an average particle size.

Optical and Fluorescence Correlation Spectroscopy (FCS) Characterization of mC dots and C rings

All of the particle samples and free dye were absorption matched by dilution into DI water using a Varian Cary 5000 spectrophotometer (Varian, Inc., Palo Alto, CA). FCS measurements were performed on a home-built FCS setup using a HeNe 535 nm laser excitation source to obtain hydrodynamic size, brightness per particle, and concentration of samples from fits of the auto-correlation curves as described previously.34,37

RESULTS AND DISCUSSION

Fluorescent MSNs with two different structures (i.e. mC dots versus C rings; see Figure 1a and 1b, respectively) were synthesized in aqueous solution by using CTAB as the surfactant template, TMB as the pore expander at varying concentrations, TMOS as the silica source, and TMR as the fluorescent dye (see Figure 1c for chemical structures of all chemicals used for MSN formation). Detailed synthesis protocols and particle characterization together with a description of specific particle features can be found elsewhere (see Method section for a short summary of the synthesis process and exact molar reactant ratios employed).29-31 FCS and DLS hydrodynamic size measurements were performed as a function of different [TMB] in the synthesis batch. Using the regular reported mC dot synthesis protocol, i.e. a protocol not optimized for sub 10 nm sizes, the average particle size as measured by FCS obtained without


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any TMB addition was ~12.5 nm. Figure 1d shows the evolution in FCS determined hydrodynamic size upon the addition of TMB. Even for the smallest [TMB] tested (around 20 mM) the size immediately drops to values below 10 nm. Size values first hit a minimum of ~8 nm around 60 mM [TMB] and then increase again upon further TMB addition until reaching a plateau around ~9.5 nm of the average particle size (Figure S1) for values around 100-120 mM [TMB]. Separate DLS measurements corroborated this size evolution as a function of [TMB] (Figure S2).

At first glance, the overall shape of the curve describing the [TMB] dependent MSN size in Figure 1d may suggest two processes: one that first leads to a decrease in average size and a second one that leads to a subsequent increase. We know, however, that the measured average MSN size is the result of the evolution of two particle morphologies, mC dots and C rings. Therefore, an alternative scenario could be that these two particles have sizes independent of the [TMB] but their relative numbers vary as a function of [TMB] leading to the observed variation in average particle size. Finally, the observed behavior could be the result of a combination of these two scenarios involving both [TMB] dependent sizes and populations. In order to obtain insights into which of these scenarios accurately describes the observed behavior we carefully analyzed this system using a number of complementary characterization techniques. First, to get real space visualization of particle morphology, TEM images of the samples were carefully analyzed. Figure 2 shows a collection of representative images of batches obtained from a range of [TMB] between 0 and 144 mM. Particles synthesized without TMB (mC dots, Figure 2a) exhibit morphologies mostly with a single pore, some that are star-shaped, all with relatively small pores and thick walls, which give them high contrast in TEM (e.g. compare to substantially lower contrast for pure C rings in Figure 2f). Upon addition of small amounts of TMB, more ring-like particles emerge with larger pores and thinner walls resulting in relatively low TEM contrast (Figure 2b/c from 14.4/36 mM and S3 from 43.3 mM [TMB]). Increasing [TMB] above about 60 mM [TMB] resulted essentially in the extinction of mC-Dots


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on the TEM grids, while C rings became the dominant and finally exclusive particles (compare images in the upper (a-c) and lower rows (d-f) of Figure 2).

GPC elution profiles obtained for MSNs synthesized from different [TMB] were carefully analyzed next. Figure 3 shows five representative profiles for [TMB] between 0 and 61.3 mM. As described in the Methods section, absolute elution times should not be compared as these profiles were produced on different days with different GPC columns. There is an apparent trend when looking at the shapes of these curves, however. While GPC curves for the lowest (0 mM) and highest (61.3 mM) [TMB] are relatively symmetric, the three profiles in-between are skewed, suggesting more than one particle population. Following our TEM results suggesting two distinct particle populations for the intermediate [TMB] studied here, we fitted the corresponding GPC profiles with two Log-normal distributions (indicated in blue and red in Figure 3b-d), which provided reasonably good fits. Since the red distribution becomes increasingly dominant with increasing [TMB], and the profile for the highest [TMB] of ~61 mM was very well fitted with a single Log-normal distribution (shown in red in Figure 3e), we identified blue and red distributions as representing mC dots and C rings, respectively. This is consistent with the foregoing FCS and DLS data analyses, which had the average size minimum around 60 mM [TMB], as well as the TEM image analysis, which showed almost no mC dots at ~55 mM and no mC dots at ~70 mM [TMB] and above.

The results of the four different characterization techniques, i.e. FCS, DLS, TEM, and GPC together suggest, that there is a transition region between 0 and ~60 mM [TMB], where the particle synthesis batch composition evolves from a pure mC dot population at 0 mM [TMB] to a pure C ring population above ~60 mM [TMB], with mixed mC dot and C ring populations in-between. Analyzing TEM and GPC data in more detail subsequently allowed to extract more quantitative information about


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the nature of this morphology transition. Using the relative areas below the fitted blue and red distributions of GPC data in Figure 3 and an expanded GPC data set in Figure S4, Figure 4a shows quantitatively how mC dot and C ring populations change in the transition region (Figure S4 shows a set of GPC profiles between 0 and ~360 mM [TMB] further visualizing the skewness of the GPC profiles in the transition region). Based on the expanded data set and using equation (5) in the Methods section to calculate the skewness for each of these GPC elution profiles, Figure 4b shows quantitatively how skewness evolves as a function of [TMB], exhibiting first an increase and then a decrease of skewness in the transition region. A more rigorous TEM image analysis enabled quantification of particle numbers for mC dot and C ring populations as a function of [TMB]. This analysis is summarized in Figure 4c and reveals remarkably similar trends when compared to the data set displayed in Figure 4a derived from GPC. In addition to relative numbers, TEM image analysis also allowed particle size determinations. The results of this analysis for both particle populations as a function of [TMB] are shown in Figure 4d. Surprisingly, they suggest that the average sizes of mC dot and C ring populations stay constant in the transition region, while at [TMB] beyond ~60 mM C ring population size starts to increase until it reaches a plateau around 11 nm at 100 mM [TMB]. It is interesting to note, that comparing numbers in Figure 4d with those in Figure 1d, the TEM analysis derived particles sizes are larger than those determined by FCS (e.g. compare sizes for [TMB] above 75mM). This is at first puzzling as FCS measures a hydrodynamic particle size which includes the PEG corona chains with water molecules dragged along, while TEM only measures the size of the silica core, which should therefore be smaller. In order to rationalize this result, it is important to emphasize, however, that in our FCS analysis we assumed a spherical object by using the Stokes-Einstein relation to determine the hydrodynamic diameter/size, d, according to:

𝑘𝑘 𝑇𝑇

𝐵𝐵 𝑑𝑑 = 2 6𝜋𝜋𝜋𝜋𝜋𝜋

(6)

where k B stands for the Boltzmann’s constant, T is the absolute temperature, 𝜂𝜂 is the dynamic viscosity, ACS Paragon Plus Environment

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and D is the diffusion constant determined by FCS.37 In contrast, both mC dots and C rings are not spherical but rather flat and hollow objects, in particular in the case of C rings, whose diffusion through water is therefore expected to be faster as compared to, e.g. a same diameter sphere, thereby resulting in smaller effective values of hydrodynamic diameter, d.

Considering the TEM particle size analysis at varying [TMB] (Figure 4d), it is reasonable to assume that the average FCS particle sizes measured for each batch in the transition region are the averages of the sizes of the two particle sub-populations, weighted by their relative population sizes. Since from TEM the average sizes of mC dot and C ring populations are constant in the transition region (see Figure 4d), using their respective FCS sizes one can back-calculate the relative contribution of each population to the FCS data. Results are shown in Figure S5 and are consistent with GPC and TEM derived results in Figure 4a and c, respectively.

We revealed the bimodal transition between two different MSN morphologies by using the combination of four complimentary characterization techniques: FCS, DLS, TEM and GPC. The data and its analysis suggested that mC dots and C rings preserve their individual morphologies and average sizes in a transition region in which increases in [TMB] primarily leads to variations in relative population numbers. Having revealed this type of behavior it is interesting to ask about its origin. As indicated before, C rings have larger pores compared to mC dots, but since they have smaller wall thickness and may be less elongated perpendicular to the ring radius direction, their hydrodynamic size is smaller than that of mC dots. Furthermore, at high [TMB] beyond the transition region, where all particles are pure rings, as one would expect ring size increases with [TMB]. This ring diameter increase is small, however, and amounts to only ~2 nm in hydrodynamic size. Both of these phenomena, i.e. preferential formation of larger pore C rings than mC dots and size increase of C rings beyond the transition region with increasing [TMB] are consistent with the expected increase in surfactant micelle size as pore expander concentration ACS Paragon Plus Environment

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increases. As discussed in the introduction, however, recent studies have revealed nontrivial organic molecule self-assembly based micellar size evolutions as a function of pore expander concentration as well as agitation (or both) that can lead, e.g. to bimodal as well as highly skewed micelle size distributions.21,33 The observed bimodal MSN size distribution in the [TMB] based morphological transition region, as well as the limited ring size control window at high [TMB] may be related to energetically favorable micellar configurations in stirred surfactant micelle solutions. Increased agitation of the oil/surfactant system may help to alter these micelle configurations.21,33 To be able to test this hypothesis, we chose a [TMB] of 36 mM, i.e. right in the middle of the transition region found for the 600 rpm stirring rate conditions tested, and doubled the stirring rate to 1200 rpm while keeping all other synthesis conditions the same. Figure 5 shows a representative TEM image of the resulting particles of this sample after purification, revealing only the C ring morphology, while the typical particle signatures of mC dots including star-shaped morphology and thicker walls providing increased image contrast relative to C rings were entirely absent. This proof-of-concept experiment suggests that similar to other recent cases, 21,33 pore expander concentration together with stirring rate control surfactant micelle size distributions which in turn govern MSN structure formation.

CONCLUSION

Understanding the formation mechanisms of ultrasmall MSNs with different morphologies promises the design and controlled synthesis of advanced generation materials for a number of applications, in particular in biological and medical fields. To that end we have studied the morphological transformation between two representatives of these particles, so called mC dots and C rings with hydrodynamic diameters below 10 nm that occurs in an oil/surfactant/silica source system in water as a function of a pore expander molecule, TMB. Post-synthesis characterization of the particles using a combination of characterization techniques revealed that in a transition region the two particles coexist, ACS Paragon Plus Environment

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essentially with constant particle sizes for each sub-population, but changing relative abundance as the pore expander concentration is increased. In addition to pore expander concentration, a proof-of-principle experiment demonstrated that stirring rate is a second important control parameter suggesting that micelle size distribution is the critical factor that governs particle morphology in the synthesis. We hope these results will help further emphasize the importance of often neglected control parameters like stirring rate in the synthesis of solution self-assembly directed inorganic nanomaterials synthesis.

ASSOCIATED CONTENT Supporting Information is available online, and it contains Supplemental Figures. Figure S1 to S9.

AUTHOR INFORMATION *Corresponding Author. E-mail: [email protected] ORCID: Melik Z. Turker: 0000-0001-7801-4275 Kai Ma: 0000-0003-4415-6894 Ulrich Wiesner: 0000-0001-6934-3755

Present Adress: ¶Elucida Oncology Inc., New York, New York 10016

Competing Interests: U.W. and K.M have a financial interest in Elucida Oncology Inc. M.Z.T. declares no competing interests.

ACKNOWLEDGEMENTS


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This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number U54CA199081. We thank the Cornell Center for Materials Research (CCMR) for use of the electron microscopy facilities, which are supported by the National Science Foundation under Award Number DMR-1120296. M.Z.T. acknowledges the Ministry of National Education of the Republic of Turkey for his student scholarship support. The authors gratefully thank K. A. Spoth, and L. F. Kourkoutis for the help with cryo-EM images.

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Figure 1: TEM images of mC dots (a) and C rings (b) synthesized at 0 mM and 200 mM [TMB], respectively, at two different magnifications with their respective molecular renderings (see insets on the right), and cryo-EM image of an individual C ring edge on (left inset in (b)). (c) Molecular structures of chemicals used. (d) Hydrodynamic MSN size measured by FCS as a function of TMB concentration in the synthesis (error bars calculated from the FCS measurements of different batches).

Figure 2: TEM images of particle batches synthesized from varying [TMB]: (a) 0 mM, (b) 14.4 mM, (c) ACS Paragon Plus Environment

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36 mM, (d) 54.1 mM, (e) 72.17 mM, and (f) 144.35 mM. Representative particle morphologies for mC dots and C rings are indicated with blue and red arrows, respectively.

Figure 3: Representative GPC elution profiles at varying [TMB] (for larger set see Figure S4): (a) 0 mM, (b) 21.6 mM, (c) 36 mM, (d) 43.3 mM, and (e) 61.3 mM. Black curves represent the original GPC data sets for all conditions studied. Two Log-normal distributions were fitted to the data sets for (b), (c), and (d), where blue and red curves represent mC dots and C ring populations, respectively, and the green distributions represent the sum of blue + red distributions, which also provide reasonably good fits with the original GPC profiles. Only one Log-normal distribution was used to fit the GPC profiles in (a) and (e) representing essentially pure mC dot and C ring populations, respectively.


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Figure 4: Results of quantitative analysis of GPC and TEM particle characterization results, (a) and (c) Relative population ratio evolution as a function of [TMB] calculated from quantitative analysis of GPC elution profiles (a) and TEM image derived particle populations (c). (b) Skewness as a function of [TMB] as derived from analysis of GPC elution profiles. (d) Average particle size evolution as a function of [TMB] for each population of mC dots and C rings as derived from quantitative TEM image analysis. Error bars shown in (c) and (d) are calculated from the averaging of TEM images split into four subimages as described in the Methods section, whereas the data shown in (a) and (b) are from GPC runs of single batches.

Figure 5: TEM images at two different magnifications (see inset) of particles synthesized from 36 mM [TMB] with a 1200 rpm stirring rate, i.e. twice as high as in all other experiments reported.


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Bimodal Morphology Transition Pathway in the Synthesis of Ultrasmall

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