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Morpho-Butterfly Inspired Lamella-based Optical Sensors for Measuring Percent Level Concentrations of H2 and CO with Au and CeO2

Published online by Cambridge University Press:  24 July 2020

Nora M. Houlihan  and
Michael A. Carpenter
Nora M. Houlihan
Affiliation:
SUNY Polytechnic Institute, 257 Fuller Road, AlbanyNY, 12203, U.S.A.
Michael A. Carpenter
Affiliation:
SUNY Polytechnic Institute, 257 Fuller Road, AlbanyNY, 12203, U.S.A.
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Abstract

Morpho-Butterfly inspired lamella structures were fabricated to make a multivariable optical sensor for measuring percent level concentrations of H2 and CO in a high temperature, zero-O2 environment. The SiO2 and Si3N4 3D structures were covered with gold nanoparticles (AuNPs) and cerium IV dioxide (CeO2) and exposed to varying concentrations of H2 and CO at 300°C. Experiments with AuNP sizes with an average diameter of 11 ± 3 nm and 3 ± 0.5 nm (larger and small AuNPs, respectively) showed that the larger AuNPs had a stronger response to the same concentrations of H2 and CO with less CO saturation and baseline drift. Further testing in the presence of 1% hydrocarbons (HCs) as an interfering gas showed excellent response to up to 17% H2 and CO in a zero-O2 environment with changes in reflected intensity of -13.1 ± 0.4% for H2 and -5.8 ± 0.3% for CO. The presence of HCs did not induce any baseline drift, with the total amount of drift being less than 0.5% over 13 hours of testing at 300°C.

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MRS Advances , Volume 5 , Issue 39: Electronics and Photonics , 2020 , pp. 2043 - 2053
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Copyright
Copyright © Materials Research Society 2020

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References

Mejdoubi, A., Andraud, C., Berthier, S., Lafait, J., Boulenguez, J., and Richalot, E., Phys. Rev. E 87, 022705 (2013).CrossRefGoogle Scholar
Giraldo, M.A., Yoshioka, S., Liu, C., and Stavenga, D.G., J. Exp. Biol. 219, 3936 (2016).CrossRefGoogle Scholar
Vukusic, P. and Sambles, J.R., Nature 424, 852 (2003).CrossRefGoogle Scholar
Potyrailo, R.A., Ghiradella, H., Vertiatchikh, A., Dovidenko, K., Cournoyer, J.R., and Olson, E., Nat. Photonics 1, 123 (2007).CrossRefGoogle Scholar
Potyrailo, R.A., Starkey, T.A., Vukusic, P., Ghiradella, H., Vasudev, M., Bunning, T., Naik, R.R., Tang, Z., Larsen, M., Deng, T., Zhong, S., Palacios, M., Grande, J.C., Zorn, G., Goddard, G., and Zalubovsky, S., Proc. Natl. Acad. Sci. 110, 15567 (2013).CrossRefGoogle Scholar
Kittle, J., Fisher, B., Kunselman, C., Morey, A., and Abel, A., Sensors (Switzerland) 20, (2020).Google Scholar
Zhu, Y., Zhang, W., and Zhang, D., Adv. Mater. Technol. 2, (2017).CrossRefGoogle Scholar
Potyrailo, R.A., Karker, N., Carpenter, M.A., and Minnick, A., J. Opt. (United Kingdom) 20, 024006 (2018).CrossRefGoogle Scholar
Poncelet, O., Tallier, G., Mouchet, S.R., Crahay, A., Rasson, J., Kotipalli, R., Deparis, O., and Francis, L.A., Bioinspir. Biomim 11, 36011 (2016).CrossRefGoogle Scholar
Janata, J., Principles of Chemical Sensors (Springer US, Boston, MA, 2009).CrossRefGoogle Scholar
Potyrailo, R.A., Surman, C., Nagraj, N., and Burns, A., Chem. Rev. 111, 7315 (2011).CrossRefGoogle Scholar
Potyrailo, R.A., Chem. Rev. 116, 11877 (2016).CrossRefGoogle Scholar
Potyrailo, R.A., Chem. Soc. Rev. 46, 5311 (2017).CrossRefGoogle Scholar
Houlihan, N.M., Karker, N., Potyrailo, R.A., and Carpenter, M.A., ACS Sensors 3, (2018).CrossRefGoogle Scholar
Seo, J., Lim, Y., and Shin, H., Sensors Actuators, B Chem. 247, 564 (2017).CrossRefGoogle Scholar
Ndaya, C.C., Javahiraly, N., and Brioude, A., Sensors (Switzerland) 19, (2019).CrossRefGoogle ScholarPubMed
Yamauchi, M., Ikeda, R., Kitagawa, H., and Takata, M., J. Phys. Chem. C 112, 3294 (2008).CrossRefGoogle Scholar
Wagner, J.B., Iandolo, B., Nugroho, F.A.A., Langhammer, C., Lidström, E., and Wadell, C., Nano Lett. 15, 3563 (2015).Google Scholar
Haruta, M., Catal. Today 36, 153 (1997).CrossRefGoogle Scholar
Carabineiro, S.A.C., Silva, A.M.T., Dražić, G., Tavares, P.B., and Figueiredo, J.L., Catal. Today 154, 21 (2010).CrossRefGoogle Scholar
Seguini, G., Llamoja Curi, J., Spiga, S., Tallarida, G., Wiemer, C., and Perego, M., Nanotechnology 25, 495603 (2014).CrossRefGoogle Scholar
Qin, S.J., Yue, H., and Dunia, R., Self-Validating Inferential Sensors with Application to Air Emission Monitoring (1997).Google Scholar
Bernstein, I.H., Garbin, C.P., and Teng, G.K., Applied Multivariate Analysis (Springer-Verlag New York Inc, New York, NY, 1988).CrossRefGoogle Scholar
Jollife, I.T. and Cadima, J., Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 374, 20150202 (2016).CrossRefGoogle Scholar