Understanding Formation Dynamics and Physical Properties of Nanocapsules Using Charge Detection Mass Spectrometry

Abstract

Characterizing the size, structure, and composition of nanoparticles is vital in predicting and understanding their macroscopic properties. In this work, charge detection mass spectrometry (CDMS) was used to analyze nanocapsules (~10-200 MDa) consisting of a liquid oleic acid core surrounded by a dense silica outer shell. CDMS is an emerging method for nanoparticle analysis that can rapidly measure the mass and charge of thousands of individual nanoparticles. We find that increasing the feed volume of the tetraethylorthosilicate (TEOS) precursor added to form the silica shell of the nanocapsules yielded both higher and broader nanocapsule mass distributions with differentiable densities. A two-dimensional mass versus charge analysis also revealed the formation of two distinct populations of nanocapsules. These two nanocapsule morphologies were also present in transmission electron microscopy (TEM) images and exhibited low-density spherical cores and crescent-shaped cores where the remainder of the core volume was “filled in” by more dense silica. Nanocapsule shell growth kinetics over a ~48-hour synthesis period were also monitored by sampling the reaction mixture at various times, quenching the sampled aliquots, and then characterizing these time-resolved samples by CDMS. The CDMS data reveal three distinct growth phases in nanocapsule formation; rapid initial nucleation, an “inverted” distribution of silica growth, and a final slow growth phase where the rate of mass increase and final nanocapsule masses are dictated by the initial TEOS feed volumes. CDMS-enabled understanding of the diverse nanocapsule sizes, morphologies, and growth dynamics will allow us to better predict nanocapsule properties while reducing the experimental burden in optimizing nanocapsules for real-world applications.

Graphical Abstract

Nanoparticle deployment for real-world applications has dramatically impacted numerous fields, such as display technologies and drug delivery.^1,2 While nanoparticles are extensively diverse in composition (material, structure, size), the overall distribution of nanoparticle species (e.g., size, mass) dictates bulk macroscopic performance properties. In some cases, such as inorganic nanocrystals, properties are dictated by nanoparticle size. Subsequent post-synthetic purification and characterization (e.g., spectroscopic, microscopy) makes it possible to produce nanoparticles with well-behaved and predictable ensemble properties. The ability to tightly control size distributions increases opportunities for applications that can have broad societal impacts. For example, quantum dot-based technologies represent a multi-billion USD industry, impacting display technologies, photovoltaics, and healthcare imaging.^3–6

In other contexts, understanding and controlling the distribution of nanoparticle species for predictable properties can be more challenging, such as for nanoparticles comprised of molecular or polymeric species. Nanoparticle heterogeneity can be a significant barrier to the commercialization of novel nanotechnologies due to quality control costs.^7–9 This heterogeneity typically originates from fabrication techniques (e.g., via emulsion without a polymeric template) or heterogeneous internal payload concentrations (e.g., a drug for dispersal upon nanoparticle decomposition). Quantifying this heterogeneity of nanoparticles can be challenging. Characterization techniques, such as absorption/emission, dynamic light scattering (DLS), and small-angle X-ray scattering (SAXS), typically provide average information about an ensemble of large nanoparticle populations, but are less informative for highly heterogeneous samples containing multiple subpopulations.^10,11 On the other hand, microscopy-based techniques, such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), scanning tunneling electron microscopy (STEM), and atomic force microscopy (AFM) provide excellent insights into structure and size independent of heterogeneity because individual particles are analyzed.^10,12,13 However, the relatively harsh sample preparation and measurement process for these microscopy-based methods, e.g., drying and affixing to a rigid surface and irradiation with a high energy electron beam, can alter the native colloidal properties of a nanoparticle sample.^14–16 Data acquisition and analysis can also be time-consuming and often limits sample sizes to a few hundred nanoparticles, which do not always provide a statistically significant landscape of species present in a sample.¹⁷ Taken together, the ability to rapidly screen thousands of individual nanoparticles from their native environment would lead to more accurate characterization which, in turn, will make it possible to improve material design principles to access desired nanoparticle properties.

Here, we demonstrate the application of an emerging mass spectrometry (MS) technique, charge detection mass spectrometry (CDMS)^18–25 to construct ensemble-level insights on nanocapsule formation. CDMS combines the ease of sample preparation and measurement speed of techniques like DLS with the ability to obtain information from numerous discrete particle measurements like TEM. CDMS enables rapid measurements of the mass and charge of thousands of individual nanocapsules at <15 minutes/sample. Conventional MS instruments typically measure only ion mass-to-charge ratios (m/z) based on aggregate signals from ensembles of ions, making it challenging or even impossible to infer the charge states of large ions when both the mass and charge-state distributions are heterogeneous.^18–27 CDMS circumvents these challenges by directly measuring both the m/z and charge of individual ions, enabling direct mass measurements of each analyte ion detected. CDMS has thus gained popularity in the analysis of relatively large (MDa-sized) analytes where inherent sample heterogeneity has precluded the use of conventional MS techniques (Figure 1A).^{18,20–25,28,27} Nanocapsules with core/shell motifs are a particularly interesting example of a challenging system with inherent heterogeneity.^29–33 Their potential for deployment for challenging applications, such as for volumetric 3D printing at low input powers, is enormous due to their durability against dissolution in a variety of chemical environments. ^29,34–36 These nanocapsules possess a liquid molecular core and a dense silica shell to ensure a molecular payload, such as a mixture of organic semiconductors, remains trapped in the particle’s interior (Figure 1B).³⁷ From this emulsion-based fabrication methodology, we obtain a heterogeneous population of nanocapsules (Figure S1). While we have substantially engineered the fabrication to maximize the desired optical properties and silica shell durability,^33,37 understanding of these nanocapsules and the variables controlling their formation is still limited. The capability of CDMS to measure simultaneously the distributions of mass and charge of heterogeneous populations is well-suited to further our understanding of nanocapsule properties and the fabrication process to ultimately enable rational materials design.

Figure 1:

(A) The wide mass range of CDMS enables its application to very large, heterogeneous analytes, such as nanocapsules, that cannot be weighed using conventional MS instrumentation. (B) A cartoon depiction of the nanocapsule fabrication process. Briefly, a solution of oleic acid containing a molecular payload (blue triangle) is emulsified in water. Nanodroplets of oleic acid are then trapped by (3-aminopropyl)triethoxysilane. The silica shell is produced by adding tetraethylorthosilicate and a PEG-silane polymer, which prevents nanocapsule aggregation. The emulsion is heated at 65 °C for 48 hours before purification by centrifugation and deployment for an end-use application.

In this investigation, we evaluate the impacts on nanocapsule mass and charge by varying the feed volume of tetraethylorthosilicate (TEOS), a precursor added to form the silica shell (Methods). Using both CDMS and TEM, we identify two distinct nanocapsule morphologies within the ensemble that have different available volumes for loading molecular payloads. We also can assign average nanocapsule silica densities to these morphologies and correlate them to other properties, such as relative gas permeation rates. CDMS measurements performed throughout the fabrication process are used to develop an understanding of nanocapsule growth kinetics. This study demonstrates that by rapidly characterizing the mass and charge distributions of nanocapsules generated under variable synthesis and purification conditions, we can improve our ability to design nanocapsules with predictable and homogeneous properties for use in applications such as 3D printing, bioimaging, and more.^29–32,34

Results and Discussion:

The effects of nanocapsule and silica shell formation as a function of TEOS and methoxy-terminated poly(ethylene glycol) silane (MPEG-silane) loadings have been previously reported.³⁷ The population of durable nanocapsules was optimized using spectroscopic methods, leading to a 3.0 mL TEOS feed volume on a 20 mL scale reaction. This engineering approach made it possible to successfully deploy nanocapsules containing organic semiconductor molecules for volumetric 3D printing.²⁹ Using DLS (Figure S2), we observe an increase in the average hydrodynamic diameter as the TEOS loading increases, as previously observed (~70-80 nm).³⁷ To move beyond a purely empirical approach to obtain desirable nanocapsule properties, we sought to establish CDMS as a valid methodology for understanding nanocapsule populations. We fabricated nanocapsules (without dispersing other organic molecular payloads in the oleic acid core) with varying TEOS loadings (1.0-4.0 mL, Methods) and purified them by centrifugation (Supporting Information).

Nanocapsule Measurements by CDMS.

With CDMS, we can rapidly access insights on nanocapsule populations as a function of TEOS loading that are not evident with DLS or other spectroscopic methods. Shown in Figure 2 are 2D mass vs. charge histograms for nanocapsule populations with TEOS loadings of 1.0-4.0 mL. The CDMS data show that the mode of the nanocapsule mass distribution shifts toward higher mass as the TEOS loading increases (Figure 2, Figure S3), a conclusion supported by the thousands of discrete nanocapsule measurements from each sample (summarized in Table S1).¹⁷ The CDMS results correlate well with the hydrodynamic diameters measured by DLS as a function of TEOS loadings (Figure S2, Figure S4). The large number of individual nanocapsules directly weighed by CDMS provides a superior understanding of the nanocapsule distributions relative to the single estimate of average sizes for the nanocapsule ensembles obtained using fitted light scattering data.³⁸ Repeated CDMS measurements show good reproducibility in both the average mass and the mass distribution among nanocapsule batches fabricated on the same day (Figure S5). The mass distributions at all TEOS loadings exhibit tailing toward higher mass, reaching ~200 MDa except at 1.0 mL TEOS, where tailing reaches ~100 MDa. The small distribution of ions observed at <25 MDa and between 100-200 charges (e) in each sample is consistent with “leftover” or “excess” low MW silica in the sample aggregating as the droplets formed by the electrospray ionization (ESI) process evaporate, a frequently observed phenomenon.^39–41 Taken together, these observations show that the nature of CDMS as an individual ion measurement technique allows for deeper insight into the range and distribution of nanocapsule sizes compared to bulk-averaged measurements like DLS.

Figure 2:

Normalized 2D mass vs. charge CDMS data for nanocapsules fabricated with increasing feed volumes of TEOS for 20 mL scale batches (A-D). The arrows in panel B emphasize the bimodal charge distribution for nanocapsules with similar masses. The accompanying 1D mass histograms are presented in Figure S3. Between ~6,700-17,500 ions were measured from each sample. A summary of the number of individual nanocapsule measurements and modes of the mass distributions for each sample are presented in Table S1. The blue dashed line denotes the Rayleigh charge limit of spherical water droplets as a function of mass.

In addition to enabling comparisons of the mass distributions, other useful insights can be gained from the charge-state distributions measured by CDMS for each sample. The extent of charging for large biological macromolecular ions produced by ESI is related to the solvent-accessible surface area of the analyte and, for approximately spherical analytes, generally follows the trend predicted by the Rayleigh charging limit.⁴² The Rayleigh charge limit equation (Eq. 1),

$$Z_R=8\pi {\left({\epsilon }_0\gamma R^3\right)}^{1/2}$$ (1)

$$Z_R={\left(\frac{48\pi {\epsilon }_0\gamma m}{\rho }\right)}^{1/2}$$ (2)

defines the relationship between the maximum charge (z_R) that can be supported by a spherical droplet of a given radius (R) and surface tension (γ) before Coulombic repulsion between charges results in droplet fission.^40,42 The radius in Eq. 1 can be rewritten in terms of a spherical analyte mass (m) via the analyte density (ρ) to yield Eq. 2. This relationship makes it possible to estimate nanocapsule densities based on CDMS mass and charge data. Eq. 2 is plotted using a density of 1.0 g cm⁻³ as a blue dashed line in Figure 2A–D, indicating the Rayleigh charging limit for water droplets.

Apart from nanocapsules formed with lowest TEOS loading (1.0 mL), nanocapsule charges are significantly below the Rayleigh limit for water. The lower charging observed for nanocapsules relative to this Rayleigh limit is consistent with densities that are greater than that of water. The final charge of a dried nanocapsule ionized in the ESI process is ultimately controlled by the Rayleigh limit of a droplet with the same surface area. Thus, denser spherical analytes will be more massive at a given extent of charging. With increasing TEOS loadings, the nanocapsule distributions in Figure 2 move progressively further away from the 1.0 g cm⁻³ Rayleigh limit (blue dashed lines Figure 2A–D), indicating a general increase in nanocapsule densities. This trend is consistent with the relatively high density of silica (2.20-2.65 g cm⁻³ depending on structure)^43,44 compared to the oleic acid core (0.895 g cm⁻³)⁴⁵ and an increasing proportion of nanocapsule mass attributable to the growth of the silica shell, which will be further discussed later in this report.

We were intrigued by the presence of two partially overlapping mass/charge distributions are resolved at the 2.0 and 3.0 mL TEOS loadings (Figures 2B–C), which are not discernable by direct spectroscopic means. To extract physical properties of each subpopulation, nanocapsule densities for each TEOS loading were estimated directly from the CDMS data by choosing a density value for Eq. 2 that results in a Rayleigh limit function that follows the high charge edge of the 2D mass versus charge distributions shown in Figure 2. This analysis method is described in greater detail in the Supporting Information and representative best density-fit Rayleigh limit functions are shown in Figure S6. For the 2.0 and 3.0 mL data in Figures 2B–C, the well-resolved bimodal charge distributions observed indicate two distinct nanocapsule distributions with different densities are present. Each distribution was fit separately, yielding densities of 1.4 and 2.2 g cm⁻³ and 1.8 and 2.2 g cm⁻³ for the high and low charge distributions of the 2.0 and 3.0 mL TEOS loading data, respectively. While the uneven distribution shapes at lower charge for the 1.0 and 4.0 mL TEOS loading data (Figures 2A, 2D) suggest higher density nanocapsule distributions may exist, they are not well-resolved and only a single density fit was performed, yielding densities of 1.0 and 1.9 g cm⁻³ for the 1.0 and 4.0 mL TEOS loading data, respectively (Figure S7). It should be noted that these Rayleigh density fit values can only represent approximate averages of density due to variations in individual nanocapsule shapes, densities, and charging in ESI. However, all the estimated densities are within the range between the density of oleic acid and bulk silica materials that compose these nanocapsules and the densities follow the expected trend with increasing TEOS loading. Thus, from the present data, we estimate the uncertainty in these CDMS-based Rayleigh fit densities at ~±0.1 g cm⁻³. A multidimensional nanoparticle characterization technique that combines differential ion mobility and aerosol particle mass analysis has been applied to porous⁴⁶ and silane functionalized⁴⁷ silica nanoparticles to determine their densities with a similar level of uncertainty. Multidimensional analytical ultracentrifugation techniques can achieve even lower uncertainties in nanoparticle density measurements, but require longer (hours) acquisition times.^48,49

Insights from Combined CDMS and TEM Data.

We also acquired TEM images for each of the samples analyzed in Figure 2 to validate our CDMS findings, with representative images shown in Figure 3. While CDMS has been previously shown to resolve nanoparticle mixtures,²⁸ here we uncover insights into nanocapsules with heterogeneous compositions. The TEM diameters allow us to validate the charge distributions observed in the CDMS data. We find there is excellent agreement between the Rayleigh maximum charge based on the mean nanocapsule diameters determined by TEM (z_R,TEM) and nanocapsule mean charge measured by CDMS (z_avg), with a consistent, narrow range of the ratio z_avg/z_R,TEM (0.85-0.95) (Table S2). Similar values of z_avg/z_R,TEM have been commonly observed in ESI-MS spectra of large, roughly spherical biomolecular complexes^50,51 with known physical dimensions. CDMS measurements of 100% polystyrene nanoparticles have low values of z_avg/z_R,TEM, but this is thought to be a consequence of the low gas-phase basicity of the polystyrene surface that reduces the ability of the nanoparticle to retain charge.²⁸ The surface of the silica-shelled nanocapsules measured here, like large biomolecular complexes, include abundant heteroatoms amenable to protonation or cationization in the ESI process. This indicates that the average nanocapsule charging measured in the CDMS data as a function of TEM diameter (z_avg/z_R,TEM) is reasonable and that the extent of charging of CDMS can be used as a useful probe of nanoparticle size, density, and surface properties.

Figure 3:

Representative TEM images of nanocapsules fabricated with varying feed volumes of TEOS (A-D) after purification by centrifugation. Histograms of the extracted diameter distributions are presented in Figure S8. The yellow arrows and inset zoom-in frames indicate examples of nanocapsules with anisotropic oleic acid cores.

TEM also provides insights into the origins of the two density distributions at constant mass (Figure 2B–2C, Figure 3B–3C). Nanocapsules in TEM appear with darker-shaded shells surrounding a more lightly shaded core, consistent with the synthesis scheme shown in Figure 1, where the denser silica surrounds a less dense oleic acid core.^14,15 The shape of the silica shell and oleic acid core display two distinct morphologies. Some nanocapsules exhibit isotropic spherical oleic acid cores (circular cores in TEM images). However, nanocapsules with anisotropic, non-spherical oleic acid cores are also observed (crescent-shaped cores in the TEM images, examples emphasized with yellow arrows in Figure 3). The darker shading of the anisotropic-cored nanocapsules indicates displacement of oleic acid by much denser silica, consistent with the lower charge, higher density distributions observed in the CDMS data with CDMS-estimated densities that near the value for bulk silica (Figure 2). It is unlikely that these anisotropic-cored nanocapsules are artifacts of exposure to ultra-high vacuum (UHV) used in both TEM and CDMS measurements. While TEM experiments require long UHV exposures (minutes) and include irradiation by a high-intensity electron beam for relatively long periods (minutes), the relatively fast ionization and measurement process of CDMS result in UHV exposures of only a few hundred milliseconds. The “gentle” nature of the ESI process used to ionize analytes in CDMS is well documented and is commonly used to investigate the structures and stoichiometries of non-covalently bound biological complexes.^52,53 Moreover, while the images in Figure 3 data are for samples purified by centrifugation, these two distinct populations are also observed before purification, albeit at significantly different proportions (Figure S8, Table S3). Before purification by centrifugation, the percentage of nanocapsules with anisotropic oleic acid cores is ~4-8x less than post-centrifugation. This observation suggests that the centrifugation-based purification process is selective for the higher density, anisotropic-cored nanocapsules. Interestingly, the percentage of nanocapsules with anisotropic oleic acid cores is higher in the samples prepared with 3.0 mL TEOS, the composition that produced nanocapsules with the best spectroscopic properties³⁷ compared to those prepared with 2.0 mL TEOS.

The combination of TEM dimensions and CDMS masses also allows us to directly extract other nanocapsule properties, such as density, composition, and shell thickness. We calculated the nanocapsule average densities as a function of TEOS feed volume (Figure S9, Table S1, and Table S4), which range from ~1.5-2.3 g cm⁻³. We note the diameters extracted by TEM reasonably match with those extracted by CDMS, but we will use the TEM-derived diameters for the following discussion (Figure S9). Even with varying morphologies, these densities are reasonable in the context of reported bulk silica and oleic acid densities^45,54 and are consistent with density values estimated directly from CDMS data using the Rayleigh charged-based approach presented above (Figure S6–S7). Additionally, they match estimates based on a core diameter of ~25 nm (similar in nanocapsules with spherical cores) and the TEOS volume-dependent shell thicknesses observed in the TEM images (Figure 3). With these densities, we can gain insight into nanocapsule compositions by estimating the percentage of silica integrated into the nanocapsules (Table S5), which has proven difficult to predict based on feed TEOS volumes. ³⁷ At low TEOS loadings (1.0 mL), nanocapsules are ~35-40% silica (a minimum boundary condition assuming the silica has 100% crystalline, quartz-like character⁵⁴). At moderate TEOS loadings (2.0-3.0 mL), nanocapsules are, on average, similar in composition (at least 70% silica). Finally, with a high TEOS loading (4.0 mL), nanocapsules are at least ~80% silica on average.

One practical implication of the densities determined by CDMS and TEM is correlating density with other observable physical properties. For example, density measurements give significant insight into the oxygen permeability of the nanocapsules’ silica shells, an important property when nanocapsule payloads are oxygen-sensitive. We assessed relative oxygen permeability by encapsulating triplet-triplet annihilation upconversion (TTA-UC) materials in the nanocapsules, as TTA-UC is inherently an oxygen-sensitive process.^30,55–58 By quantifying the relative upconverted light output of nanocapsules with and without oxygen exposure, we determined the silica shell’s relative effectiveness as an oxygen barrier (i.e., without the incorporation of any other oxygen-quenching additives). We fabricated TTA-UC nanocapsules with 2.0-4.0 mL of TEOS and empirically determined that oxygen exposure has minimal impact on the upconversion emission when at least 2.0 mL TEOS is utilized (Figure S10), indicating that a minimum average density of ~2 g cm⁻³ (and a corresponding silica shell thickness of ~10 nm) is required for oxygen protection (Table S4).

Looking forward, assigning a physical parameter directly attributed to the nanocapsules (e.g., density or shell thickness), to a specific desired property (e.g., oxygen-blocking effectiveness), is a powerful tool to efficiently ensure batch-to-batch quality assurance. This capability also enables us to make improved comparisons between differing nanocapsule compositions, reducing experimental burdens in engineering and optimization efforts. Beyond the correlation between oxygen blocking and density demonstrated here, we anticipate that similar studies could be applied to designing and characterizing nanomaterials for on-demand generation and delivery of therapeutic gases (e.g., NO) via nanocarriers. Correlating the rate of diffusion of therapeutic gases generated in the interior of nanocarriers to a physical property like shell density will prove useful in the design, synthesis, and quality assurance of such materials, which have traditionally been difficult to deploy for in vivo applications.^59,60

Nanocapsule Growth Kinetics.

While robust spectroscopic means have been utilized to monitor changes in the coordination environments of various silica species,^61–63 with complex systems like nanocapsules, it is difficult to correlate these changes with nanoscale morphologies. With CDMS, we can directly monitor the formation of nanocapsules over time. Aliquots from reactions were quenched by dilution in water and characterized by CDMS. We emphasize no significant changes in nanocapsule mass were observed over multiple days (Supporting Information), signifying effective quenching of the reaction at the time of each aliquot. Figures 4 and Figures S11–13 present CDMS results measuring nanocapsule growth as a function of time under our previously engineered optimized conditions for silica shell durability, with a 3.0 mL TEOS loading. Overall, we observe 3 significant events (“Growth Phases”) during the synthesis. First, we observe extensive nucleation from the stabilized micelle surface within minutes of TEOS addition resulting in a ~2x increase in mass (Figure 1, Figure 4A–B), with nanocapsules (and other silica species) growing from ~9 MDa to ~25 MDa at room temperature. The second phase occurs upon initial reaction heating (Figure 4C–D, Figures S11–S13). The lower charge, higher density distribution becomes noticeable at 9 hours (Figure 4E) and is distinct after 25 hours (Figure 4F–G). The same growth and differentiation behaviors are reproducible among separate batches with 3.0 mL TEOS loading (Figure S14–15). The same growth phases and differentiation were also observed for nanocapsules synthesized using 2.0 mL of TEOS, albeit at lower masses (Figure 5A, Figures S16–S17).

Figure 4:

(A-H) CDMS data collected to monitor nanocapsule growth over time (TEOS feed volume = 3.0 mL). The blue dashed line denotes the Rayleigh charge limit of spherical water droplets as a function of mass. Time points are defined relative to the addition of TEOS at t=0. The data in sample H was collected after two purifications by centrifugation. We emphasize that sample C (t=1 hour) likely represents an underestimate of the average mass. Sample C contained visible particulates, signifying high molecular weight species were present that are not detected by CDMS, resulting in relatively sparse signal compared to other samples. Additional timepoints and 1D projections are presented in Figures S11–S13 respectively.

Figure 5:

(A) A summary of CDMS data (mode of the distribution) collected to monitor nanocapsule growth, comparing TEOS feed volumes of 2.0 mL and 3.0 mL using data from Figure 4 and Figures S11–S13, S16–S17. Time points are defined relative to the addition of TEOS at t=0. The numbered regions refer to Growth Phases 1-3. We emphasize that samples at t=1-3 hours likely represent an underestimate of the average mass, as these samples contained visible particulates, resulting in a relatively sparse signal compared to other samples. (B) Sources of silica range from low molecular weight TEOS through high molecular weight species. We note that TEOS is unlikely to be present in large quantities, as hydrolysis and condensation occurs rapidly upon addition to water.⁶¹ (C) Cartoon depictions of the hypothesized nanoscopic processes occurring during Growth Phases 1-3, with silica sources in (B) omitted for clarity. Briefly, Growth Phase 1 represents initial silica condensation to the micelle shell. Then, silica condensation and hydrolysis lead to the formation of more high molecular weight silica, heterogeneous mass distributions, and oleic acid leakage (black) (C, Phase 2). Finally, in Phase 3, silica addition over days from various silica species in solution add to the nanocapsule shells, leading to two different nanocapsule morphologies (C, Phase 3).

We hypothesize the mass “overshoot” observed within the first ~3 hours of nanocapsule growth (Growth Phases 1-2) is crucial for growing a dense silica shell. This overshoot is observed reproducibly with TEOS feed volumes of either 2.0 or 3.0 mL (Figure 5A, Figures S11–S17). The silica shell growth results from a complex equilibrium comprised of many condensation and hydrolysis reactions, with the degree of hydrolysis and condensation determining silica structure and density.⁶¹ In silica-generating reactions at high pH, highly branched structures are typically observed, and excess water promotes the reverse reactions and extensive depolymerization.⁶¹ This equilibrium process has been shown to produce an “inverted” molecular weight distribution under basic conditions similar to those used in this work, whereupon primarily high and low molecular weight species are observed.^61,64 This process is the likely origin of what is observed in Figure 4C and is depicted schematically in Figure 5B–C. Additionally, we hypothesize that the successive reorganization of silica species leads to the two different nanocapsule morphologies observed in Figures 2–3. Nanocapsules that undergo fewer silica losses/additions remain in the lower molecular weight regime of Figure 4C and keep isotropic, spherical morphologies. On the other hand, nanocapsules that are “crescent”-shaped (anisotropic) by TEM undergo significant silica loss/addition, resulting in the observed oleic acid leakage (Figure S18) and anisotropic morphologies. The initial feed volume of TEOS impacts the relative ratio of high and low molecular weight species, providing insight into the relative abundance of anisotropic nanocapsules obtained with 2.0 and 3.0 mL TEOS feed volumes (~20% vs ~60% respectively, Table S3). We infer the ability to generate “crescent”-shaped nanocapsules dramatically increases the population size of durable nanocapsules, which we have previously observed.^29,37 Beyond Growth Phases 1 and 2, the remaining silica that can be added to nanocapsule shells dictates the overall mass distribution and shell thicknesses that can be achieved, with 3.0 and 4.0 mL TEOS feed volumes providing sufficient silica for higher mass, thick-shelled species (Figure 2C–D, Figure 3C–D). Since the final silica densities are similar among nanocapsules with 2.0 – 4.0 mL TEOS feed volumes (Table S4), we hypothesize the density of nucleation sites for silica growth from nanocapsule shells are similar, whereas, with lower TEOS feed volumes (<2.0 mL), the density of nucleation sites is reduced. This indicates that the final nanocapsule density is largely dictated by the initial TEOS feed volume and not by a specific stage of nanocapsule growth.

Conclusions:

The rapid measurements of nanoparticle mass and charge enabled by CDMS yields significant new insights into nanocapsule assembly and physical properties throughout the synthesis and purification process. Post-synthesis measurements of the mass and extent of charging show the dependence of size and density of nanocapsules on increasing feed volumes of TEOS, a key silica-growing reagent. Distinct mass/charge distributions observed in CDMS data supports the solution-phase existence of two nanocapsule morphologies with different densities, corroborated by TEM. CDMS also enables direct monitoring of nanocapsule growth during the synthesis process and uncovers a mass overshoot early in the silica shell formation process that would be difficult to observe using indirect spectroscopic monitoring methods. This mass overshoot is correlated with a rapid silica condensation/hydrolysis equilibrium that likely leads to the formation of anisotropic, “crescent”-shaped nanocapsules which increases the total population of durable nanocapsules.

Elucidating nanocapsule populations by CDMS and TEM has important implications when considering deployment for various applications, such as previous work where we loaded optically active materials inside nanocapsules for volumetric 3D printing.²⁹ When molecular species are loaded into nanoparticles utilizing an emulsion-based fabrication process, molecules are not distributed equally within each nanoparticle: rather, they are assumed to be distributed according to a Poisson distribution.⁶⁵ The loading and distribution of species within a nanoparticle have a significant impact on the ensemble nanoparticle properties. ^66–69 Predicting optical properties from bulk properties has been difficult because of this phenomenon and we have so far relied on engineering methods to optimize desired optical properties.^29,33,37 The improved understanding of the highly diverse nanocapsule sizes and morphologies enabled by CDMS analysis will be key in developing models for predicting nanocapsule properties. In turn, this will greatly reduce the experimental burden in optimizing nanocapsules as well as other nanomaterials, like metal or core-shell alloyed nanoparticles for practical applications.

Methods:

Charge Detection Mass Spectrometry.

The CDMS instrument and data analysis methods have been previously described in detail.²³ Briefly, samples were loaded into borosilicate emitters with tip diameters of 2-10 μm and ionized by electrospray with potentials of 1.0-1.5 kV. Ions transit a heated capillary and RF ion funnel region where ions are desolvated before entering a region containing three quadrupole ion guides equipped with asymptotic guide rods. Ions are briefly stored in the third ion guide and then pulsed through an ion acceleration region into an electrostatic ion trap containing a detector electrode where they were trapped for 100 ms. Ion signals were digitized at 1 MHz and analyzed using software based on short-time Fourier transform analysis. ⁷⁰ Only data from ions that remained trapped for the entire 100 ms period were counted and included in the mass and charge histograms.

Nanocapsule Fabrication.

This fabrication method is adapted from previous reports.^29,33,37 Milli-Q water (20 mL, titrated to pH ~10 with KOH) was sparged under nitrogen for 30 minutes in a 40 mL clear vial before sealing and bringing into a nitrogen filled glovebox (<0.5 ppm O2). The water was transferred to a 50 mL centrifuge tube. Oleic acid (145 μL) was carefully dispensed into the water in one portion, and the centrifuge tube was sealed with electrical tape to prevent leaks. An emulsion was generated by vortexing the solution at the maximum speed for 5 minutes (VWR Analog Vortex Mixer, VWR; Fisherbrand Vortex Mixers Tube Holders, Fisher Scientific). Then, the emulsion was transferred back to the 40 mL clear vial and was immediately stirred at 1200 rpm. To each reaction, (3-aminopropyl)triethoxysilane (APTES) (75 μL) was added until the mixture became transparent. Then, 0.4 g 10K MPEG-silane was immediately added and stirred vigorously/shaken to disperse evenly. Within 5 minutes of the MPEG-silane addition, the chosen volume of TEOS was added in one portion. The vial was sealed, and the solution stirred vigorously at room temperature. After approximately 10 mins, the flask was removed from the glovebox and was stirred vigorously at 1400 rpm at a temperature of 65 °C for 42-48 hours. Additional details about nanocapsule purification and aliquoting are included in the Supporting Information.

Supplementary Material

Additional details about materials, measurement methods (Rayleigh limit density fitting, TEM, and DLS), and nanoparticle purification; supplementary figures including cartoon depictions of different nanocapsule morphologies, representative DLS data for nanocapsules fabricated with 1.0-4.0 mL TEOS loading volumes, 1D CDMS mass data for nanocapsules fabricated variable TEOS loading volumes, comparisons of DLS and CDMS results, 2D mass vs. charge CDMS data fit with different density Rayleigh fit lines, additional TEM images of nanocapsules fabricated with variable TEOS loading volumes, comparison of diameter distributions determined by TEM with those derived from CDMS mass measurements, Upconversion emission data for TTA-UC nanocapsules fabricated with variable TEOS loading volumes, 2D mass vs. charge CDMS datasets for additional time points in nanocapsule growth experiments, 1D CDMS mass data for all time points in nanocapsule growth experiments, summarized data for additional nanocapsule growth replicate experiments, photograph of nanocapsule solution showing oleic acid leakage during fabrication; supplementary tables including nanocapsule masses, counts, average charges, expected Rayleigh charging, TEM-determined percentages of nanocapsules with non-spherical cores, TEM diameters, calculated nanocapsule densities, and estimated percentages for silica and oleic acid compositions of nanocapsules; supplementary references.