4.6 Article

γ radiation induced self-assembly of fluorescent molecules into nanofibers: a stimuli-responsive sensing

期刊

JOURNAL OF MATERIALS CHEMISTRY C
卷 3, 期 17, 页码 4345-4351

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/c5tc00594a

关键词

-

资金

  1. Department of Homeland Security, Science and Technology Directorate [2009-ST-108-LR0005]
  2. NSF [CHE 0931466]
  3. SEED grant of the VP office of University of Utah [10029849]
  4. USTAR program

向作者/读者索取更多资源

Low dose detection of gamma radiation remains critical for radiology therapy and nuclear security. We report herein on a novel dual-band fluorescence sensor system based on a molecule, 4-(1H-phenanthro[9,10-d]-imidazol-2-yl)-N,N-diphenylaniline (PI-DPA), which can be dissolved into halogenated solvents to enable expedient detection of gamma radiation. The limit of detection was projected down to 0.006 Gy. Exposure to gamma radiation decomposes CHCl3 into small radicals, which then combine to produce HCl. Strong interaction of HCl with the imidazole group of PI-DPA converts it into a PI-DPA-HCl adduct, which self-assembles into nanofibers, quenching the fluorescence of the pristine PI-DPA molecule, while producing new fluorescent emission at longer wavelength. Such dual-band emission response provides improved sensing reliability compared to single band response. Systematic investigations based on acid titration, H-1 NMR spectral measurements and time-course SEM imaging suggest that the observed new fluorescence band is due to pi-pi stacking of the PI-DPA-HCl adduct, which is facilitated by the formation of hydrogen bonded cluster units. The nanofibers exhibited high and reversible photoconductivity. Combining with the sensitive fluorescence response, the photoconductive nanofibers will enable development of a multimode stimuli-responsive sensor system that is suited for small, low cost dosimetry of gamma radiation with improved sensitivity and detection reliability.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据