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In recent years, organic dye molecules as photosensitizers have played a significant role in the field of dye-sensitized solar cells. In this context, two primary dihydroindolocarbazole-based organic dyes (sk201 and sk202), which were synthesized recently by Song et al., and three further designed dyes (DMZ1-3) were theoretically investigated based on density functional theory and time-dependent density functional theory. Molecular geometries, absorption spectra, charge transfer, molecular electrostatic potential and nonlinear optical properties were quantificationally studied and visually presented to reveal the relationships between the molecular structures and performances of dyes. The effects of joining the isolated dyes and TiO2 on the molecular absorption spectra and energy levels were analyzed. Moreover, several parameters, such as efficiency of light-harvesting, driving forces of electron regeneration and injection, excited-state lifetime and vertical dipole moment, were calculated to give the multi-angle demonstrations of the photovoltaic performances for these dyes.
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Array‐Based Discrimination of Phenolic Acids in Water at Near‐Neutral pH with Chromogenic and Fluorescent Cyclodextrin‐Based Supramolecular Sensors
Abstract Phenolic acids are a class of poorly water‐soluble organic compounds with antioxidant properties that contain a carboxylic acid and a phenol group, common in plants. We used hydroxypropyl‐β‐cyclodextrin (HP‐β‐CD) as a supramolecular host to sense phenolic acids in water near physiological pH. The analytes’ complexation was monitored through changes in the optical absorption and emission properties of a series of six organic dyes, acting as indicators in a displacement assay, that were selected from screening a panel of 17 candidates. Binding constants between these dyes and the HP‐β‐CD were in the 102–104range. We showed that the nuanced differences in the dyes’ optical signatures associated with this displacement process, when analyzed and summarized using multivariate analysis algorithms such as principal component analysis (PCA), can be used to successfully discriminate among six phenolic acids, and to identify six unknown samples of such acids, down to a 0.02 mM concentration.
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- Award ID(s):
- 1919906
- PAR ID:
- 10391237
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Analysis & Sensing
- Volume:
- 3
- Issue:
- 1
- ISSN:
- 2629-2742
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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