Particle deposition onto charge-heterogeneous substrates
The deposition of model colloidal particles onto striped charge-heterogeneous surfaces was studied to determine the influence of surface chemical heterogeneity on the deposit morphology. The charge heterogeneity was created employing self-assembled monolayers of carboxyl- and amine-terminated alkane...
| Veröffentlicht in: | Langmuir : the ACS journal of surfaces and colloids. - 1992. - 25(2009), 9 vom: 05. Mai, Seite 4907-18 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2009
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| Zugriff auf das übergeordnete Werk: | Langmuir : the ACS journal of surfaces and colloids |
| Schlagworte: | Journal Article |
| Zusammenfassung: | The deposition of model colloidal particles onto striped charge-heterogeneous surfaces was studied to determine the influence of surface chemical heterogeneity on the deposit morphology. The charge heterogeneity was created employing self-assembled monolayers of carboxyl- and amine-terminated alkanethiols using a soft lithographic technique. Polystyrene sulfate microspheres and fluorescent polystyrene nanoparticles were sequentially deposited onto the patterned substrate under no flow (quiescent) condition. The deposited structures and the micropatterns were imaged using a combination of phase contrast and fluorescence microscopy. The experimental particle deposition behavior was compared to predictions based on random sequential adsorption (RSA) employing a Monte Carlo technique. Comparison of radial distribution obtained from experimental data was made with the theoretical results and found to be in good agreement despite the use of a simple binary probabilistic model in the simulations. The primary conclusion from the study is that particles tend to preferentially deposit at the edges of the favorable stripes. However, the extent of this bias can be controlled by the proximity of consecutive favorable stripes (or width of the intervening unfavorable stripes) as well as the particle size relative to the stripe width. Second, a simple binary probability distribution-based Monte Carlo RSA deposition model adequately predicts the deposit structure, particularly the periodicity of the underlying patterns on the substrate. These observations suggest that the patterns could be encrypted by the deposited particles, which can subsequently be decoded, given the proper "key" or information that is based on analyzing the deposit morphology |
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| Beschreibung: | Date Completed 02.06.2009 Date Revised 28.04.2009 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1520-5827 |
| DOI: | 10.1021/la804075g |