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Part-per-trillion trace selective gas detection using frequency locked whispering gallery mode microtoroids

Li, Cheng and Lohrey, Trevor D. and Nguyen, Phuong-Diem and Min, Zhouyang and Tang, Yisha and Ge, Chang and Sercel, Zachary P. and McLeod, Euan and Stoltz, Brian M. and Su, Judith (2022) Part-per-trillion trace selective gas detection using frequency locked whispering gallery mode microtoroids. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20220427-196780100

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Abstract

Rapid detection of toxic and hazardous gases at trace concentrations plays a vital role in industrial, battlefield, and laboratory scenarios. Of interest are both sensitive as well as highly selective sensors. Whispering gallery mode (WGM) microresonator-based biochemical sensors are among the most sensitive sensors in existence due to their long photon confinement times. One main concern with these devices, however, is their selectivity towards specific classes of target analytes. Here, we employ frequency locked whispering gallery mode microtoroid optical resonators covalently modified with various polymer coatings to selectively detect the chemical warfare agent surrogate diisopropyl methylphosphonate (DIMP) as well as the toxic industrial chemicals formaldehyde and ammonia at parts-per-trillion concentrations. This is 1-2 orders of magnitude better than previously reported, depending on the target, except for pristine graphene and pristine carbon nanotube sensors, which demonstrate similar detection levels but in vacuum and without selectivity. Selective polymer coatings include polyethylene glycol (PEG) for DIMP sensing, accessed by the modification of commercially available materials, and 3-(triethoxysilyl)propyl-terminated polyvinyl acetate (PVAc) for ammonia sensing. Notably, we developed an efficient one-pot procedure to access 3-(triethoxysilyl)propyl-terminated PVAc that utilizes cobalt-mediated living radical polymerization and a nitroxyl polymer-terminating agent. Alkaline hydrolysis of PVAc coatings to form polyvinyl alcohol (PVA) coatings directly bound to the microtoroid proved to be reliable and reproducible, leading to WGM sensors capable of the rapid and selective detection of formaldehyde vapors. The selectivity of these three polymer coatings as sensing media was predicted, in part, based on their functional group content and known reactivity patterns with the target analytes. Furthermore, we demonstrate that microtoroids coated with a mixture of polymers can serve as an all-in-one sensor that can detect multiple agents. We anticipate that our results will facilitate rapid early detection of chemical agents, as well as their surrogates and precursors.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.26434/chemrxiv-2022-606xvDOIArticle
https://resolver.caltech.edu/CaltechAUTHORS:20220421-197072600Related ItemConference Presentation
ORCID:
AuthorORCID
Lohrey, Trevor D.0000-0003-3568-7861
Stoltz, Brian M.0000-0001-9837-1528
Su, Judith0000-0002-1005-1755
Additional Information:The content is available under CC BY NC ND 4.0 License. This project was funded by the Defense Threat Reduction Agency (HDTRA11810044). J.S. owns a financial stake in Femtorays Technologies which develops label-free molecular sensors. The author(s) declare that they have sought and gained approval from the relevant ethics committee/IRB for this research and its publication.
Funders:
Funding AgencyGrant Number
Defense Threat Reduction Agency (DTRA)HDTRA11810044
Subject Keywords:gas sensor; toxic industrial chemical; chemical warfare agent surrogate; chemical warfare agent precursor; microtoroid; whispering gallery mode
DOI:10.26434/chemrxiv-2022-606xv
Record Number:CaltechAUTHORS:20220427-196780100
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220427-196780100
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114473
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:27 Apr 2022 19:30
Last Modified:27 Apr 2022 19:30

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