Improved H2 detection performance of GaN sensor with Pt/Sulfide treatment of porous active layer prepared by metal electroless etching
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2021-12-01
Type
ArticleAuthors
Shafa, MuhammadAravindh, S. Assa
Hedhili, Mohamed N.

Mahmoud, Saleh T.
Pan, Yi
Ng, Tien Khee

Ooi, Boon S.

Najar, Adel
KAUST Department
Surface ScienceComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Date
2020-12Embargo End Date
2021-12-01Submitted Date
2020-05-15Permanent link to this record
http://hdl.handle.net/10754/666672
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High-performance chemiresistor gas sensor made of sulfide porous GaN decorated with Pt nanoparticles, which shows tunable sensor response and enhanced sensitivity. The fabricated gas sensors show detection of H2 down to 30 ppm at 23 °C after sulfide treatment and Pt decorated porous GaN. The response time and recovery time were equal to 47 s and 113 s, respectively. Density functional theory simulations were used to support the detection mechanism based on sulfide treatment. Adsorption energy calculations showed that H adsorption energy is lowered by the simultaneous presence of S and Pt on the GaN (0001) surface. The density of states (DOS) calculations revealed possibility of bond strengthening when Pt and S is adsorbed on GaN surface along with H, arising from the hybridization of d and p orbitals of Pt and S with that of H 1s orbitals.Citation
Shafa, M., Aravindh, S. A., Hedhili, M. N., Mahmoud, S. T., Pan, Y., Ng, T. K., … Najar, A. (2020). Improved H2 detection performance of GaN sensor with Pt/Sulfide treatment of porous active layer prepared by metal electroless etching. International Journal of Hydrogen Energy. doi:10.1016/j.ijhydene.2020.10.275Sponsors
This work was supported by Projects No. UPAR 31S443 & 31S214 from UAE University. M. Shafa and Y. Pan acknowledge the National Key R&D Program of China (2017YFA0206202), National Science Foundation of China (11704303) and China Postdoctoral Science Foundation Grant (2019M663691). S. Assa Aravindh gratefully acknowledges CSC – IT Center for Science, Finland for computational resources and Academy of Finland (#311934) for funding.Publisher
Elsevier BVAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S0360319920344736ae974a485f413a2113503eed53cd6c53
10.1016/j.ijhydene.2020.10.275