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Excited State Processes in Linear π-System-Based Organogels

Babu, Sukumaran S., Kartha, Kalathil K., Ajayaghosh, Ayyappanpillai·2010·The Journal of Physical Chemistry Letters

Abstract

This article describes the recent progress made to the understanding of the excited state interactions in organogels derived from linear π-conjugated molecules. The soft organogel scaffolds of such systems create an excellent ambience for the self-organization of the molecules allowing the modulation of their excited state properties and thereby opening a new world of fascinating materials with interesting physical properties at nano- and macroscopic levels. Noncovalent interactions provide opportunity for the molecules to interact electronically within a space of defined size and shape. As a result, the photophysical properties of the molecules in solution and gel states are different from each other. In this perspective article we analyze the role of the self-assembled organogel scaffolds of π-gels derived from linear π-systems in modulating the excited state properties such as excited state energy transfer, exciplex emission, phosphorescence, and aggregation-induced enhanced emission (AIEE), when compared to the corresponding individual molecules.

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Metadata

Authors
Babu, S. S., Kartha, K. K., & Ajayaghosh, A.
Venue
The Journal of Physical Chemistry Letters
Published
2010-11-18
Volume
1
Issue
23
Pages
3413-3424
ISSN
1948-7185 (ISSN-L)
OpenAlex
W2043062607
Cited by
172
References
0
FWCI
8.91
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Excited State Processes in Linear π-System-Based Organogels. https://app.cochat.ai/papers/10.1021/jz101219y
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Babu, S. S., Kartha, K. K., & Ajayaghosh, A. (2010). Excited State Processes in Linear π-System-Based Organogels. The Journal of Physical Chemistry Letters. https://doi.org/10.1021/jz101219y

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.