@article{167c5b403bb94d968de88c1f983cda01,
title = "MXene-Polymer Hybrid for High-Performance Gas Sensor Prepared by Microwave-Assisted In-Situ Intercalation",
abstract = "2D transition-metal carbides (Ti3C2Tx MXene) intercalated with organic molecules have been widely used in batteries and supercapacitors, but are quite rarely reported for gas sensing. Since Ti3C2Tx is sensitive to oxygen, most methods for preparing the intercalated Ti3C2Tx involve stirring the reactants with Ti3C2Tx for several hours under nitrogen protection. Herein, a method to prepare a hybrid of Ti3C2Tx and intercalated polysquaraine through microwave-assisted in situ polymerization that takes only a few minutes without the need of using a protective atmosphere is demonstrated. Owing to the increased interlayer space of the Ti3C2Tx after the polymerization, the gas sensors based on the hybrid exhibit a good sensing performance for NH3 detection, being able to detect at least 500 ppb NH3 with a 2.2% ppm−1 of sensitivity. This study provides a facile preparation method for developing intercalated MXenes, which are expected to be useful for a wide range of applications.",
keywords = "gas sensing, in situ polymerization, intercalation, microwave reaction, MXene",
author = "Jin Zhou and {Hosseini Shokouh}, {Seyed Hossein} and Komsa, {Hannu Pekka} and Lassi Rieppo and Linfan Cui and Lv, {Zhong Peng} and Krisztian Kordas",
note = "Funding Information: This manuscript has been co‐authored by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe‐public‐access‐plan ). Funding Information: This material is based upon work supported in part by: the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Applied Mathematics program under contracts and awards ERKJ314, ERKJ331, ERKJ345; the AEOLUS (Advances in Experimental Design, Optimization and Learning for Uncertain Complex Systems) Department of Energy Mathematical Multifaceted Capabilities Center; the Scientific Discovery through Advanced Computing (SciDAC) program through the FASTMath Institute under Contract No. DE‐AC02‐05CH11231; and by the Laboratory Directed Research and Development program at the Oak Ridge National Laboratory, which is operated by UT‐Battelle, LLC., for the U.S. Department of Energy under contract DE‐AC05‐00OR22725. Publisher Copyright: {\textcopyright} 2022 The Authors. Advanced Materials Technologies published by Wiley-VCH GmbH",
year = "2022",
month = sep,
doi = "10.1002/admt.202101565",
language = "English",
volume = "7",
journal = " Advanced Materials Technologies",
issn = "2365-709X",
publisher = "Wiley",
number = "9",
}