Dynamical Correlations for Statistical Copolymers from High-Throughput Broadband Dielectric Spectroscopy
Xiao Zhang, Jing Zhao, Changhuai Ye, Tzu Yu Lai, Chad R. Snyder, Alamgir Karim, Kevin A. Cavicchi
Broad-band dielectric spectroscopy (BDS) provides a powerful method of characterizing relaxation dynamics in diverse materials. Here we describe and employ a novel instrument for high-throughput broadband dielectric spectroscopy (HTBDS) that accelerates this capability, enabling simultaneous measurements of 48 samples. This capability is based around a coaxial switching system for rapid scanning between multiple samples on the same sample stage, coordinated with shared environmental control. We validate the instrument by measuring dielectric response in three polymers, distributed across 48 sample sites, and comparing results to measurements via a standard BDS instrument. Results are found to be reproducible and in agreement with relaxation times from traditional BDS. We then employ HTBDS to establish mixing rules for glass transition temperatures, kinetic fragility indices, and segmental stretching exponents in a series of acrylate copolymers, a matter of considerable technological interest in a variety of technological applications. Results are consistent with the empirical Fox rule for Tg averaging in polymer blends, while revealing a linear mixing rule for kinetic fragility indices. Finally, we test several proposed correlations between these distinct dynamical properties. These results demonstrate that HTBDS enables measurements of polymer relaxation at a throughput approximately 10 times higher than standard BDS approaches, opening the door to high-throughput materials design of dynamic response across a broad range of frequencies.
, Zhao, J.
, Ye, C.
, Lai, T.
, Snyder, C.
, Karim, A.
and Cavicchi, K.
Dynamical Correlations for Statistical Copolymers from High-Throughput Broadband Dielectric Spectroscopy, ACS Combinatorial Science, [online], https://doi.org/10.1021/acscombsci.8b00160, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926747
(Accessed December 6, 2023)