The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
First-principles insight into Ni-doped InN monolayer as a noxious gases scavenger
Abstract
Abstract Using first-principles theory, we theoretically investigate the most stable doping site of Ni atom on pristine InN monolayer and adsorption behavior of Ni-doped InN (Ni-InN) monolayer upon four noxious gases (NO, CO2, H2S and NH3). Electron localization function (ELF), electron deformation density (EDD) as well as density of state (DOS) are considered to further understand the adsorption behavior of Ni-InN monolayer towards gas molecules. For possible application of our proposed material, work function and band structure of the isolated and gas adsorbed Ni-InN monolayer are analyzed as well. It is found that the Ni dopant prefers to be adsorbed on the pristine InN monolayer at the TN site with the lowest biding force (Eb) of −3.02 eV. Four gases could be stably adsorbed on the Ni-InN monolayer surface wherein the chemisorption is identified due to the large adsorption energy (Ead) and charge transfer (QT). ELF, EDD and DOS analyses corroborate the strong chemical interaction between Ni dopant and activated atoms in gas molecules. The band structure analysis provides the sensing mechanism of Ni-InN based resistance-type chemical sensor for detection of such four gaseous species. Our calculations can supply some guidance to explore promising novel gas sensors using group III-V nitrides in the gas-sensing field and environmental monitoring fields.
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From molecules to solids with the DMol3 approach
Delley, B. (2000) · The Journal of Chemical Physics · doi:10.1063/1.1316015 · Cited by 11,026
Recent Advances in Ultrathin Two-Dimensional Nanomaterials
Tan, C., Cao, X., Wu, X.-J., He, Q., Yang, J., Zhang, X., Chen, J., Zhao, W., Han, S., Nam, G.-H., et al. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00558 · Cited by 5,100
Self-citationRecent Advances in Two-Dimensional Materials beyond Graphene
Bhimanapati, G. R., Lin, Z., Meunier, V., Jung, Y., Cha, J., Das, S., Xiao, D., Son, Y., Strano, M. S., Cooper, V. R., et al. (2015) · ACS Nano · doi:10.1021/acsnano.5b05556 · Cited by 2,659
Doping Graphene with Metal Contacts
Giovannetti, G., Khomyakov, P. A., Brocks, G., Karpan, V. M., van den Brink, J., & Kelly, P. J. (2008) · Physical Review Letters · doi:10.1103/physrevlett.101.026803 · Cited by 2,605
Graphene‐Based Materials: Synthesis, Characterization, Properties, and Applications
Huang, X., Yin, Z., Wu, S., Qi, X., He, Q., Zhang, Q., Yan, Q., Boey, F., & Zhang, H. (2011) · Small · doi:10.1002/smll.201002009 · Cited by 2,569
Sun, P., Wang, K., & Zhu, H. (2016) · Advanced Materials · doi:10.1002/adma.201502595 · Cited by 668
2D Materials Beyond Graphene for High‐Performance Energy Storage Applications
Zhang, X., Hou, L., Ciesielski, A., & Samorì, P. (2016) · Advanced Energy Materials · doi:10.1002/aenm.201600671 · Cited by 611
Self-citationTang, H., Dou, K., Kaun, C.-C., Kuang, Q., & Yang, S. (2014) · J. Mater. Chem. A · doi:10.1039/c3ta13584e · Cited by 607
Graphene and Graphene-like Two-Dimensional Materials in Photodetection: Mechanisms and Methodology
Sun, Z., & Chang, H. (2014) · ACS Nano · doi:10.1021/nn500508c · Cited by 583
Enhancement of CO detection in Al doped graphene
Ao, Z. M., Yang, J., Li, S., & Jiang, Q. (2008) · Chemical Physics Letters · doi:10.1016/j.cplett.2008.07.039 · Cited by 451
Metadata
- Authors
- Cui, H., Zhang, X., Li, Y., Chen, D., & Zhang, Y.
- Venue
- Applied Surface Science
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 494
- Pages
- 859-866
- ISSN
- 0169-4332 (ISSN-L)
- OpenAlex
- W2964463888
- Cited by
- 325
- References
- 27
- FWCI
- 17.36
- Type
- journal article
- Language
- en
- Open access
- closed
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