Dataset Information

Design of Highly Photofunctional Porous Polymer Films with Controlled Thickness and Prominent Microporosity.

ABSTRACT: Porous organic polymers allow the integration of various ?-units into robust porous ?-networks, but they are usually synthesized as unprocessable solids with poor light-emitting performance as a result of aggregation-related excitation dissipation. Herein, we report a general strategy for the synthesis of highly emissive photofunctional porous polymer films on the basis of a complementary scheme for the structural design of aggregation-induced-emissive ?-systems. We developed a high-throughput and facile method for the direct synthesis of large-area porous thin films at the liquid-electrode interface. The approach enables the preparation of microporous films within only a few seconds or minutes and allows precise control over their thickness with sub-nanometer precision. By virtue of rapid photoinduced electron transfer, the thin films can detect explosives with enhanced sensitivity to low parts-per-million levels in a selective manner.

SUBMITTER: Gu C

PROVIDER: S-EPMC4600238 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Design of Highly Photofunctional Porous Polymer Films with Controlled Thickness and Prominent Microporosity.

Gu Cheng C Huang Ning N Wu Yang Y Xu Hong H Jiang Donglin D

Angewandte Chemie (International ed. in English) 20150731 39

Porous organic polymers allow the integration of various π-units into robust porous π-networks, but they are usually synthesized as unprocessable solids with poor light-emitting performance as a result of aggregation-related excitation dissipation. Herein, we report a general strategy for the synthesis of highly emissive photofunctional porous polymer films on the basis of a complementary scheme for the structural design of aggregation-induced-emissive π-systems. We developed a high-throughput a ...[more]

PMID: 26234636

Similar Datasets

Project description:Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography is a well-established technique for high resolution imaging and reconstruction of the microstructure of a wide range of materials. Segmentation of FIB-SEM data is complicated due to a number of factors; the most prominent is that for porous materials, the scanning electron microscope image slices contain information not only from the planar cross-section of the material but also from underlying, exposed subsurface pores. In this work, we develop a segmentation method for FIB-SEM data from ethyl cellulose porous films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. These materials are used for coating pharmaceutical oral dosage forms (tablets or pellets) to control drug release. We study three samples of ethyl cellulose and hydroxypropyl cellulose with different volume fractions where the hydroxypropyl cellulose phase has been leached out, resulting in a porous material. The data are segmented using scale-space features and a random forest classifier. We demonstrate good agreement with manual segmentations. The method enables quantitative characterization and subsequent optimization of material structure for controlled release applications. Although the methodology is demonstrated on porous polymer films, it is applicable to other soft porous materials imaged by FIB-SEM. We make the data and software used publicly available to facilitate further development of FIB-SEM segmentation methods. LAY DESCRIPTION: For imaging of very fine structures in materials, the resolution limits of, e.g. X-ray computed tomography quickly become a bottleneck. Scanning electron microscopy (SEM) provides a way out, but it is essentially a two-dimensional imaging technique. One manner in which to extend it to three dimensions is to use a focused ion beam (FIB) combined with a scanning electron microscopy and acquire tomography data. In FIB-SEM tomography, ions are used to perform serial sectioning and the electron beam is used to image the cross section surface. This is a well-established method for a wide range of materials. However, image analysis of FIB-SEM data is complicated for a variety of reasons, in particular for porous media. In this work, we analyse FIB-SEM data from ethyl cellulose porous films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. These films are used as coatings for controlled drug release. The aim is to perform image segmentation, i.e. to identify which parts of the image data constitute the pores and the solid, respectively. Manual segmentation, i.e. when a trained operator manually identifies areas constituting pores and solid, is too time-consuming to do in full for our very large data sets. However, by performing manual segmentation on a set of small, random regions of the data, we can train a machine learning algorithm to perform automatic segmentation on the entire data sets. The method yields good agreement with the manual segmentations and yields porosities of the entire data sets in very good agreement with expected values. The method facilitates understanding and quantitative characterization of the geometrical structure of the materials, and ultimately understanding of how to tailor the drug release.

Dataset Information

Design of Highly Photofunctional Porous Polymer Films with Controlled Thickness and Prominent Microporosity.

Publications

Design of Highly Photofunctional Porous Polymer Films with Controlled Thickness and Prominent Microporosity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets