Artificial 3D hierarchical and isotropic porous polymeric materials
Behzad, Ali Reza
Nunes, Suzana Pereira
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Environmental Science and Engineering Program
Imaging and Characterization Core Lab
Nanofabrication Core Lab
Water Desalination and Reuse Research Center (WDRC)
Permanent link to this recordhttp://hdl.handle.net/10754/627892
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AbstractHierarchical porous materials that replicate complex living structures are attractive for a wide variety of applications, ranging from storage and catalysis to biological and artificial systems. However, the preparation of structures with a high level of complexity and long-range order at the mesoscale and microscale is challenging. We report a simple, nonextractive, and nonreactive method used to prepare three-dimensional porous materials that mimic biological systems such as marine skeletons and honeycombs. This method exploits the concurrent occurrence of the self-assembly of block copolymers in solution and macrophase separation by nucleation and growth. We obtained a long-range order of micrometer-sized compartments. These compartments are interconnected by ordered cylindrical nanochannels. The new approach is demonstrated using polystyrene-b-poly(t-butyl acrylate), which can be further explored for a broad range of applications, such as air purification filters for viruses and pollution particle removal or growth of bioinspired materials for bone regeneration.
CitationChisca S, Musteata V-E, Sougrat R, Behzad AR, Nunes SP (2018) Artificial 3D hierarchical and isotropic porous polymeric materials. Science Advances 4: eaat0713. Available: http://dx.doi.org/10.1126/sciadv.aat0713.
SponsorsWe thank LNLS (Brazil) for access at the SAXS1 beamline, particularly F. Meneau and T. A. Kakile for their help during measurements, T. M. D’Alvise for helpful discussions on the procedure for growing CaCO3 crystals, P. N. Chitamb for the permeation measurement, and J. A. Palacio for help with the pore size statistics. Funding: This research was supported by the King Abdullah University of Science and Technology.
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