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    A Highly Selective Metal-Organic Framework Textile Humidity Sensor

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    Type
    Article
    Authors
    Rauf, Sakandar cc
    Vijjapu, Mani Teja
    Andres, Miguel Angel
    Gascón, Ignacio
    Roubeau, Olivier
    Eddaoudi, Mohamed cc
    Salama, Khaled N. cc
    KAUST Department
    Advanced Membranes and Porous Materials Research Center
    Chemical Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Functional Materials Design, Discovery and Development (FMD3)
    Physical Science and Engineering (PSE) Division
    Sensors Lab
    Date
    2020-06-19
    Embargo End Date
    2021-06-09
    Permanent link to this record
    http://hdl.handle.net/10754/663545
    
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    Abstract
    The increase in demand and popularity of smart textiles brings new and innovative ideas to develop a diverse range of textile-based devices for our daily life applications. Smart textile-based sensors (TEX sensors) become attractive due to the potential to replace current solid-state sensor devices with flexible and wearable devices. We have developed a smart textile sensor for humidity detection using a metal-organic framework (MOF) as an active thin-film layer. We show for the first time, the use of the Langmuir-Blodgett (LB) technique for the deposition of a MIL-96(Al) MOF thin film directly onto the fabrics containing interdigitated textile electrodes for the fabrication of a highly selective humidity sensor. The humidity sensors were made from two different types of textiles, namely, linen and cotton, with the linen based sensor giving the best response due to better coverage of MOF. The TEX sensor showed a reproducible response after multiple cycles of measurements. After three weeks of storage, the sensor showed a moderate decrease in response. Moreover, TEX sensors showed a high level of selectivity for the detection of water vapors in the presence of several volatile organic compounds (VOCs). Interestingly, the selectivity is superior to some of the previously reported MOF coated solid-state interdigitated electrode devices and textile sensors. The method herein described is generic and can be extended to other textiles and coating materials for the detection of toxic gases and vapors.
    Citation
    Rauf, S., Vijjapu, M. T., Andres, M. A., Gascón, I., Roubeau, O., Eddaoudi, M., & Salama, K. N. (2020). A Highly Selective Metal-Organic Framework Textile Humidity Sensor. ACS Applied Materials & Interfaces. doi:10.1021/acsami.0c07532
    Sponsors
    M.A. Andrés acknowledges the support of Ministerio de Educación from the Spanish Government under a FPU grant (Formación de Profesorado Universitario, FPU14/05367) and a short term mobility FPU grant (EST18/00291) and of King Abdullah University of Science and Technology and Advanced Membranes and Porous Materials Center under the Visiting Student Program. Authors also acknowledge Prof. Dr. Christian Serre for kindly providing MIL-96(Al) NPs used in this contribution.
    We acknowledge the financial support from King Abdullah University of Science and Technology (KAUST), Saudi Arabia. K.N. Salama would like to acknowledge the funding from AMPM center under the CCF grant. Also, the research leading to these results has received funding from Spanish MINECO and FEDER (projects MAT2016-78257-R and MAT2017-86826-R), and the Aragon Government (DGA) and FEDER (research group E31_17R).
    Publisher
    American Chemical Society (ACS)
    Journal
    ACS Applied Materials & Interfaces
    DOI
    10.1021/acsami.0c07532
    Additional Links
    https://pubs.acs.org/doi/10.1021/acsami.0c07532
    ae974a485f413a2113503eed53cd6c53
    10.1021/acsami.0c07532
    Scopus Count
    Collections
    Articles; Advanced Membranes and Porous Materials Research Center; Physical Science and Engineering (PSE) Division; Functional Materials Design, Discovery and Development (FMD3); Electrical and Computer Engineering Program; Chemical Science Program; Sensors Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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