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Mechanisms of Local Stress Sensing in Multifunctional Polymer Films Using Fluorescent Tetrapod Nanocrystals
Author(s) -
Shilpa N. Raja,
Danylo Zherebetskyy,
Siva Wu,
Peter Ercius,
Alexander S. Powers,
Andrew C. K. Olson,
Daniel X. Du,
Liwei Lin,
Sanjay Govindjee,
L.-W. Wang,
Ting Xu,
A. Paul Alivisatos,
Robert O. Ritchie
Publication year - 2016
Publication title -
nano letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.853
H-Index - 488
eISSN - 1530-6992
pISSN - 1530-6984
DOI - 10.1021/acs.nanolett.6b01907
Subject(s) - materials science , nanocomposite , stress (linguistics) , photoluminescence , ultimate tensile strength , core (optical fiber) , composite material , polymer , nanoscopic scale , nanocrystal , compressive strength , nanotechnology , composite number , optoelectronics , philosophy , linguistics
Nanoscale stress-sensing can be used across fields ranging from detection of incipient cracks in structural mechanics to monitoring forces in biological tissues. We demonstrate how tetrapod quantum dots (tQDs) embedded in block copolymers act as sensors of tensile/compressive stress. Remarkably, tQDs can detect their own composite dispersion and mechanical properties with a switch in optomechanical response when tQDs are in direct contact. Using experimental characterizations, atomistic simulations and finite-element analyses, we show that under tensile stress, densely packed tQDs exhibit a photoluminescence peak shifted to higher energies ("blue-shift") due to volumetric compressive stress in their core; loosely packed tQDs exhibit a peak shifted to lower energies ("red-shift") from tensile stress in the core. The stress shifts result from the tQD's unique branched morphology in which the CdS arms act as antennas that amplify the stress in the CdSe core. Our nanocomposites exhibit excellent cyclability and scalability with no degraded properties of the host polymer. Colloidal tQDs allow sensing in many materials to potentially enable autoresponsive, smart structural nanocomposites that self-predict impending fracture.

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