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Published January 11, 2022 | Supplemental Material
Journal Article Open

Quantifying Activation Rates of Scissile Mechanophores and the Influence of Dispersity


The ability to accurately and quantitatively characterize structure–mechanochemical activity relationships is important for informing the fundamental understanding of mechanochemical reactivity and, in turn, the successful advancement of the rapidly growing field of polymer mechanochemistry. Ultrasound-induced mechanical activation of polymers remains one of the most general methods for studying mechanophore reactivity; however, the activation rates of scissile mechanophores are still routinely deduced from changes in polymer size using gel permeation chromatography (GPC) that indirectly report on mechanophore activation with questionable accuracy. Here, the rates of ultrasound-induced mechanochemical activation of two distinct scissile and fluorogenic mechanophores are measured using photoluminescence spectroscopy and compared directly to rates determined using various methods for analyzing chain scission kinetics from GPC measurements. This systematic study confirms that the conventional method for analyzing chain scission kinetics is inaccurate and that it provides a misleading picture of mechanophore activity. Instead, time-dependent changes in the GPC refractive index response closely reproduce the rates of mechanophore activation determined spectroscopically. These results expand on prior work by providing a systematic evaluation of the methods used to characterize mechanophore activation kinetics and emphasize the need for a unified approach to kinetic analysis in the field of polymer mechanochemistry. Moreover, analysis of mechanophore activation efficiency reveals an important insight into the consequences of molecular weight dispersity on the characterization of mechanophore reactivity.

Additional Information

© 2021 American Chemical Society. Received 27 October 2021. Revised 10 December 2021. Published online 25 December 2021. Published in issue 11 January 2022. Financial support from Caltech is gratefully acknowledged. A.C.O. and M.E.M. were supported by NSF Graduate Research Fellowships (DGE-1745301). Support from an Institute Fellowship (A.C.O.) and a Barbara J. Burger Graduate Fellowship (M.E.M.) at Caltech is also gratefully acknowledged. The authors declare no competing financial interest.

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September 22, 2023
October 23, 2023