Monodisperse Porous Silica/Polymer Nanocomposite Microspheres with Tunable Silica Loading, Morphology and Porosity

Abstract

Hybrid organic/inorganic nanocomposites combine the distinct properties of the organic polymer and the inorganic filler, resulting in overall improved system properties. Monodisperse porous hybrid beads consisting of tetraethylene pentamine functionalized poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) particles and silica nanoparticles (SNPs) were synthesized under Stoeber sol-gel process conditions. A wide range of hybrid organic/silica nanocomposite materials with different material properties was generated. The effects of n(H2O)/n(TEOS) and c(NH3) on the hybrid bead properties particle size, SiO2 content, median pore size, specific surface area, pore volume and size of the SNPs were studied. Quantitative models with a high robustness and predictive power were established using a statistical and systematic approach based on response surface methodology. It was shown that the material properties depend in a complex way on the process factor settings and exhibit non-linear behaviors as well as partly synergistic interactions between the process factors. Thus, the silica content, median pore size, specific surface area, pore volume and size of the SNPs are non-linearly dependent on the water-to-precursor ratio. This is attributed to the effect of the water-to-precursor ratio on the hydrolysis and condensation rates of TEOS. A possible mechanism of SNP incorporation into the porous polymer network is discussed.

Sol–Gel-Controlled Size and Morphology of Mesoporous Silica Microspheres Using Hard Templates

“…This is in contrast to the HBs, from which the MPSMs were derived. The size of the HBs remained constant when the sol–gel conditions were varied . Interestingly, for each factor level setting, a narrow size distribution with d 90 / d 10 values below 1.4 is observed (Figure , Table , and Figure S4, SI).…”

“…The larger SNPs require more time at the same temperature to reach a similar sintering degree as samples consisting of smaller SNPs. , Hence, the larger the SNPs in the HB are, the smaller is the effect of interparticle condensation and thus shrinkage. Moreover, in this polymer/silica system, the size of the SNPs and the amount of incorporated silica correlates linearly and in dependence on the sol–gel process conditions . The smaller the SNPs, the less silica is incorporated.…”

“…The introduction of meso-/macropores allows a good effective accessibility of the porous material for diffusion-controlled processes . Templating methods have been widely applied to prepare porous silica materials with tunable size and pore characteristics. − While soft templates are successfully used to prepare nanometer-sized silica particles, ,, hard templates are the choice to synthesize micrometer-sized mesoporous silica spheres (MPSMs). , This is because hard templates such as poly­(glycidyl methacrylate- co -ethylene glycol dimethacrylate) particles ( p (GMA- co -EDMA)) ,− are usually formative, i.e., determining the three-dimensional morphology. ,, Template-assisted methods for the preparation of MPSMs consist usually of three sequential steps: − (a) synthesis of the formative template, , (b) synthesis and/or incorporation of silica into the template, , and (c) subsequent removal of the template , (Figure ).…”

“…Our previous study determined how the sol–gel process factors the water-to-precursor ratio (here: tetraethyl ortho silicate, TEOS) and the ammonia concentration affects the silica deposition within the porous network of polymeric hard-templates . By systematically varying the sol–gel process conditions according to response surface methodology, three reaction regimes were identified .…”

Real-Time Quantification of Meat Paste Constituents Displaying Nonlinear Blending Behavior Including Salt Using an In-Line NIR MEMS Sensor

“…In this work, the complexity of differently composed meat pastes is modeled using model meat mixtures that were systematically varied according to an experimental design. Design of Experiments (DoE) in combination with Response Surface Methodology (RSM) is a powerful statistical tool, − which enables the identification and quantification of statistically significant recipe components as well as synergistic nonlinear blending behavior of mixture components, while requiring only a limited number of experiments making this approach much more effective and informative than conventional one-factor-at-a-time approaches. ,,, The methodology has thus been used in a wide variety of contexts including food technology. − Using a mixture design wherein salt was included as a component in the reference mixtures, the effect of compositional changes in the meat paste on the spectral characteristics in the NIR region was investigated. For this purpose, various meat pastes were produced based on a balanced mixture design with varying amounts of fat, protein, water, and salt and subsequently were analyzed with a novel process analyzer prototype using a MEMS-based NIR sensor.…”