Control of nanoparticle formation using the constrained dewetting of polymer brushes
Source abstract
Abstract
We have used coarse-grained molecular dynamics simulations to investigate the use of pinned micelles formed by the constrained dewetting of polymer brushes to act as a template for nanoparticle formation. The evaporation of a thin film containing a dissolved solute from a polymer brush was modeled to study the effect of solubility, concentration, grafting density, and evaporation rate on the nucleation and growth of nanoparticles. Control over particle nucleation could be imposed when the solution was dilute enough such that particle nucleation occurred following the onset of constrained dewetting. We predict that nanoparticles with sizes on the order of 1 nm to 10 nm could be produced from a range of organic molecules under experimentally accessible conditions. This method could allow the functionality of organic materials to potentially be imparted onto surfaces without the need for synthetic modification of the functional molecule, and with control over particle size and aggregation, for application in the preparation of surfaces with useful optical, pharmaceutical, or electronic properties.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Polymer Surface Interaction Studies · Pickering emulsions and particle stabilization · Surfactants and Colloidal Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Chemistry
The University of Sydney
Sydney, Australia
Te Pūnaha Matatini
University of Auckland
Auckland 1142, New Zealand
MacDiarmid Institute for Advanced Materials and Nanotechnology
Department of Physics
Funding
Australian Research Council
References (32)
Show source-provided references
1. Rhe · J. Macromol. Sci. C · 2002 · 42 · 9110.1081/MC-120003096 ↗
2. Zhou · Phys. Chem. Chem. Phys. · 2006 · 8 · 381510.1039/B606415A ↗
3. Motornov · Langmuir · 2003 · 19 · 807710.1021/la0343573 ↗
4. Sidorenko · Langmuir · 1999 · 15 · 834910.1021/la990869z ↗
5. Limpoco · Langmuir · 2007 · 23 · 1219610.1021/la701272a ↗
6. Welch · Soft Matter · 2011 · 7 · 29710.1039/C0SM00035C ↗
7. Huh · Macromolecules · 2005 · 38 · 297410.1021/ma047781z ↗
8. Pattanayek · J. Chem. Phys. · 2005 · 122 · 21490810.1063/1.1917772 ↗
9. Soga · EPL · 1995 · 29 · 53110.1209/0295-5075/29/7/004 ↗
10. Williams · J. Phys. II · 1993 · 3 · 1313
11. Lee · Macromolecules · 2013 · 46 · 632610.1021/ma400593z ↗
12. Koutsos · Macromolecules · 1997 · 30 · 471910.1021/ma961625d ↗
13. Zhao · Chem. Commun. · 2010 · 46 · 68610.1039/B915271G ↗
14. Maltsev · Appl. Phys. Lett. · 2002 · 81 · 308810.1063/1.1515880 ↗
15. Rath · Nano Lett. · 2007 · 7 · 384510.1021/nl072598f ↗
16. Muller · J. Biotechnol. · 2004 · 113 · 15110.1016/j.jbiotec.2004.06.007 ↗
17. Patra · Nanoscale · 2012 · 4 · 34310.1039/C1NR11313E ↗
18. Wang · Microchim. Acta · 2005 · 149 · 26710.1007/s00604-004-0303-6 ↗
19. Wang · Spectrochim. Acta, Part A · 2005 · 61 · 12910.1016/j.saa.2004.03.031 ↗
20. Wang · Anal. Sci. · 2004 · 20 · 101310.2116/analsci.20.1013 ↗
21. Li · J. Phys. Chem. C · 2009 · 113 · 752610.1021/jp810622a ↗
22. Plimpton · J. Comput. Phys. · 1995 · 117 · 110.1006/jcph.1995.1039 ↗
23. Kremer · J. Chem. Phys. · 1990 · 92 · 505710.1063/1.458541 ↗
24. Binder · Soft Matter · 2011 · 7 · 715910.1039/c1sm05212h ↗
25. Müller · Comput. Phys. Commun. · 2009 · 180 · 60010.1016/j.cpc.2008.12.002 ↗
26. Pastorino · Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys. · 2007 · 76 · 02670610.1103/PhysRevE.76.026706 ↗
27. van Gunsteren · Mol. Phys. · 1982 · 45 · 63710.1080/00268978200100491 ↗
28. CRC Handbook of Chemistry and Physics, ed. W. M. Haynes, CRC press, 94th edn, 2013
29. Hagen · J. Pharm. Sci. · 1983 · 72 · 40910.1002/jps.2600720422 ↗
30. Craft · J. Agric. Food Chem. · 1992 · 40 · 43110.1021/jf00015a013 ↗
31. Semenov · J. Chem. Eng. Data · 2010 · 55 · 1310.1021/je900296s ↗
32. Krátschmer · Nature · 1990 · 347 · 35410.1038/347354a0 ↗