Self-Assembled Surfactant-Templated Synthesis of Porous Hollow Silica Nanoparticles: Mechanism of Formation and Feasibility of Post-Synthesis Nanoencapsulation
Bibliographic record
Abstract
SiO2 is bioinert and highly functionalizable, thus making it a very attractive material for nanotechnology applications such as drug delivery and nanoencapsulation of pesticides. Herein, we synthesized porous hollow SiO2 nanoparticles (PHSNs) by using cetyltrimethylammonium bromide (CTAB) and Pluronic P123 as the structure-directing agents. The porosity and hollowness of the SiO2 structure allow for the protective and high-density loading of molecules of interest inside the nanoshell. We demonstrate here that loading can be achieved post-synthesis through the pores of the PHSNs. The PHSNs are monodisperse with a mean diameter of 258 nm and a specific surface area of 287 m2 g–1. The mechanism of formation of the PHSNs was investigated using 1-D and 2-D solid-state nuclear magnetic resonance (SS-NMR) and Fourier-transform infrared spectroscopy (FTIR). The data suggest that CTAB and Pluronic P123 interact, forming a hydrophobic spherical hollow cage that serves as a template for the porous hollow structure. After synthesis, the surfactants were removed by calcination at 550 °C and the PHSNs were added to an Fe3+ solution followed by addition of the reductant NaBH4 to the suspension, which led to the formation of Fe(0) NPs both on the PHSNs and inside the hollow shell, as confirmed by transmission electron microscopy imaging. The imaging of the formation of Fe(0) NPs inside the hollow shell provides direct evidence of transport of solute molecules across the shell and their reactions within the PHSNs, making it a versatile nanocarrier and nanoreactor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".