Theoretical calculation study on enhancing the sensitivity and optical properties of graphene adsorption of nitrogen dioxide via doping

Zhu Hong-Qiang; Luo Lei; Wu Ze-Bang; Yin Kai-Hui; Yue Yuan-Xia; Yang Ying; Feng Qing; Jia Wei-Yao

doi:10.7498/aps.73.20240992

Abstract

In order to study the adsorption of NO₂ on pristine graphene and doped graphene (N-doped, Zn-doped, and N-Zn co-doped), we simulate the adsorption process by applying the first-principles plane-wave ultrasoft pseudopotentials of the density-functional theory in this work. The adsorption energy, Mulliken distribution, differential charge density, density of states, and optical properties of NO₂ molecules adsorbed on the graphene surface are calculated. The results show that the doped graphene surface exhibits higher sensitivity to the adsorption of NO₂ compared with the pristine graphene surface, and the order of adsorption energy is as follows: N-Zn co-doped surface > Zn-doped surface > N-doped surface > pristine surface. Pristine graphene surface and N-doped graphene surface have weak interactions with and physical adsorption of NO₂. Zn-doped graphene surfac and N-Zn co-doped graphene surface form chemical bonds with NO₂ and are chemisorbed. In the visible range, among the three doping modes, the N-Zn co-doped surface is the most effective for improving the optical properties of graphene, with the peak absorption and reflection coefficients improved by about 1.12 and 3.42 times, respectively, compared with pristine graphene. The N-Zn co-doped graphene not only enhances the interaction between the surface and NO₂, but also improves the optical properties of the material, which provides theoretical support and experimental guidance for NO₂ gas detection and sensing based on graphene substrate.

Keywords:

Authors and contacts

1.
College of Physics and Electronic Engineering, Chongqing Normal University, Chongqing 401331, China
2.
School of Physical Science and Technology, Southwest University, Chongqing 400715, China

Corresponding author: Zhu Hong-Qiang, 20132013@cqnu.edu.cn ; Jia Wei-Yao, wyjia@swu.edu.cn

Funds: Project supported by the Natural Science Foundation of Chongqing, China (Grant Nos. CSTB2023SCQ-MSX0207, CSTB2023SCQ-MSX0425), the Science and Technology Research Program of Chongqing Municipal Education Commission, China (Grant Nos. KJQN202200569, KJQN202200507, KJQN202300513, KJZD-K202300516), the Higher Education Teaching Reform Research Project of Chongqing, China (Grant No. 223145), and the “Curriculum Ideological and Political” Demonstration Project of Chongqing Municipal Education Commission, China (Grant No. YKCSZ23102).

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References

[1]	Cooper M J, Martin R V, Hammer M S, Levelt P F, Veefkind P, Lamsal L N, Krotkov N A, Brook J R, McLinden C A 2022 Nature 601 380 Google Scholar
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[12]	Yu W, Sisi L, Haiyan Y, Luo J 2020 Rsc Adv. 10 15328 Google Scholar
[13]	Dong Q C, Xiao M, Chu Z Y, Li G C, Zhang Y 2021 Sensors 21 3386 Google Scholar
[14]	Gui Y G, Peng X, Liu K Ding Z Y 2020 Physicas E 119 113959 Google Scholar
[15]	Zhu P C, Tang F, Wang S F, Cao W, Wang Q 2022 Mater. Today Commun. 33 104280 Google Scholar
[16]	Li Q F, Chen W L, Liu W H, Sun M L, Xu M H, Peng H L, Wu H Y, Song S X, Li T H, Tang X H 2022 Appl. Surf. Sci. 586 152689 Google Scholar
[17]	Hong H S, Ha N H, Thinh, D D, Nam N H, Huong N T, Hue N T, Hoang T V 2021 Nano Energy 87 106165 Google Scholar
[18]	Zhang T, Sun H, Wang F D, Zhang W D, Tang S W, Ma J M, Gong H W, Zhang J P 2017 Appl. Surf. Sci. 425 340 Google Scholar
[19]	Choudhuri I, Patra N, Mahata A, Ahuja R, Pathak B 2015 J. Phys. Chem. C 119 24827 Google Scholar
[20]	Shukri M S M, Saimin M N S, Yaakob M K, Yahya M Z A, Taib M F M 2019 Appl. Surf. Sci. 494 817 Google Scholar
[21]	Shamim S U D, Roy D, Alam S, Piya A A, Rahman M S, Hossain M K, Ahmed F 2022 Appl. Surf. Sci. 596 153603 Google Scholar
[22]	Zhang X X, Yu L, Gui Y G, Hu W H 2016 Appl. Surf. Sci. 367 259 Google Scholar
[23]	Jia X, An L 2019 Mod. Phys. Lett. B 33 1950044 Google Scholar
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[28]	Gao X, Zhou Q, Wang J X, Xu L N, Zeng W 2020 Appl. Surf. Sci. 517 146180 Google Scholar
[29]	Zheng T, Traian D, Thomas F 2021 Phys. Chem. Chem. Phys. 23 19627 Google Scholar
[30]	Ping L K, Mohamed M A, Mondal A K, Taib M F M, Samat M H, Berhanuddin D D, Menon P S, Bahru R 2021 Micromachines 12 348 Google Scholar

Cited By

图 1 石墨烯表面吸附NO₂分子结构的俯视图和侧视图　(a) 未掺杂石墨烯; (b) N掺杂石墨烯; (c) Zn掺杂石墨烯; (d) N-Zn双掺杂石墨烯

Figure 1. Structure of NO₂ adsorbed on graphene surface: (a) Pristine graphene; (b) N-doped graphene; (c) Zn-doped graphene; (d) N-Zn co-doped graphene.

DownLoad: Full-Size Img PowerPoint

图 2 优化后石墨烯表面吸附NO₂分子结构的俯视图和侧视图　(a) 未掺杂石墨烯; (b) N掺杂石墨烯; (c) Zn掺杂石墨烯; (d) N-Zn双掺杂石墨烯

Figure 2. Top and side views of the molecular structure of NO₂ adsorbed on the optimized graphene surface: (a) Pristine graphene; (b) N-doped graphene; (c) Zn-doped graphene; (d) N-Zn co-doped graphene.

DownLoad: Full-Size Img PowerPoint

图 3 石墨烯表面吸附NO₂分子　(a) 总电子密度等面图(TCD)、(b) 电荷密度差图(CDD)和(c)电子密度差图(ECD). TCD图等面设为0.02 e/Å³; CDD图等面设为0.01 e/Å³, 蓝色代表电子积累, 黄色代表电子耗尽; ECD图红色代表电荷聚集, 蓝色代表电荷耗尽

Figure 3. (a) Charge density difference (CDD), (b) total charge density (TCD), and (c) electron density difference (EDD) plots of NO₂ molecules adsorbed on different graphene surfaces. The isosurfaces of TCD plots are set to 0.02 e/Å³; the isosurfaces of CDD plots are set to 0.01 e/Å³, blue represents electron accumulation and yellow represents electron depletion; in EDD plots, red represents charge accumulation and blue represents charge depletion.

DownLoad: Full-Size Img PowerPoint

图 4 石墨烯表面吸附NO₂分子的分态密度　(a) 未掺杂石墨烯; (b) N掺杂石墨烯; (c) Zn掺杂石墨烯; (d) N-Zn双掺杂石墨烯

Figure 4. Fractional density of adsorbed NO₂ molecules on graphene surfaces: (a) Pristine graphene; (b) N-doped graphene; (c) Zn-doped graphene; (d) N-Zn co-doped graphene.

DownLoad: Full-Size Img PowerPoint

图 5 石墨烯的介电函数虚部

Figure 5. The imaginary parts of the dielectric function of graphene.

DownLoad: Full-Size Img PowerPoint

图 6 石墨烯的(a)吸收谱和(b)反射谱

Figure 6. (a) Absorption spectrum and (b) reflection spectrum of graphene.

DownLoad: Full-Size Img PowerPoint

表 1 石墨烯表面吸附NO₂的距离和吸附能

Table 1. The distance and adsorption energy of NO₂ adsorption on graphene surface.

模型	初始距离/Å	优化后距离/Å	吸附能/eV
未掺杂石墨烯	3.00	2.96	–0.22
N掺杂	3.00	2.73	–0.69
Zn掺杂	3.00	1.94	–4.80
N-Zn双掺杂	3.00	1.93	–4.97

DownLoad: CSV

表 2 NO₂分子的Mulliken的电荷分布

Table 2. Mulliken charge distribution of NO₂.

模型	种类	s电子	p电子	总电子	电荷/e	分子带电荷/e	布居数	键长/Å
NO₂	N	1.39	3.18	4.57	0.44	0	0.68	1.23
	O	1.85	4.36	6.22	–0.22
	O	1.85	4.36	6.22	–0.22
未掺杂石墨烯	N	1.46	3.21	4.67	0.33	–0.25	0.63	1.24
	O	1.86	4.44	6.29	–0.29
	O	1.86	4.44	6.29	–0.29
N掺杂	N	1.51	3.23	4.74	0.26	–0.48	0.60	1.25
	O	1.86	4.53	6.39	–0.38
	O	1.86	4.51	6.36	–0.36
Zn掺杂	N	1.48	3.40	4.88	0.12	–0.59	0.67	1.26
	O	1.86	4.50	6.36	–0.36
	O	1.86	4.49	6.35	–0.35
N-Zn 双掺杂	N	1.49	3.40	4.88	0.11	–0.60	0.67	1.27
	O	1.86	4.51	6.37	–0.37
	O	1.86	4.48	6.34	–0.34

DownLoad: CSV

map

[1]	Cooper M J, Martin R V, Hammer M S, Levelt P F, Veefkind P, Lamsal L N, Krotkov N A, Brook J R, McLinden C A 2022 Nature 601 380 Google Scholar
[2]	Gholami F, Tomas M, Gholami Z, Vakili M 2020 Sci. Total. Environ. 714 136712 Google Scholar
[3]	Wang S, Liu J, Yi H, Tang X L, Yu Q J, Zhao S Z, Gao F Y, Zhou Y S, Zhong T T, Wang Y X 2022 Chemosphere 291 132917 Google Scholar
[4]	Lim H, Kwon H, Kang H, Jang J E, Kwon H J 2023 Nat. Commun. 14 3114 Google Scholar
[5]	Gao Z Y, Li L L, Huang H Y, Xu S P, Yan G, Zhao M L, Ding Z 2020 Appl. Surf. Sci. 527 146939 Google Scholar
[6]	Geng X, Li S W, Mawella-Vithanage L, Ma T, Kilani M, Wang B W, Ma L, Hewa-Rahinduwage C C, Shafikova A, Nikolla E, Mao G Z, Brock S L, Zhang L, Luo L 2021 Nat. Commun. 12 4895 Google Scholar
[7]	熊枫, 彭志敏, 丁艳军, 杜艳君 2022 71 203302 Google Scholar Xiong F, Peng Z M, Ding Y J, Du Y J 2022 Acta Phys. Sin. 71 203302 Google Scholar
[8]	Zhao S K, Shen Y B, Zhou P F, Zhong X X, Han C, Zhao Q, Wei D Z 2019 Sens. Actuat. B-Chem. 282 917 Google Scholar
[9]	Choi M S, Kim M Y, Mirzaei A, Kim S I, Baek S H, Chun D W, Jin C H, Lee K H 2021 Appl. Surf. Sci. 568 150910 Google Scholar
[10]	Brophy R E, Junker B, Fakhri E A, Arnason H Ö, Svavarsson H G, Weimar U, Bârsan N, Manolescu A 2024 Sens. Actuat. B-Chem. 410 135648 Google Scholar
[11]	Rani S, Kumar M, Garg P, Rani S, Kumar M, Garg P, Parmar R, Kumar A, Singh Y, Baloria V, Deshpande U, Singh V N 2022 ACS Appl. Mater. Interfaces 14 15381 Google Scholar
[12]	Yu W, Sisi L, Haiyan Y, Luo J 2020 Rsc Adv. 10 15328 Google Scholar
[13]	Dong Q C, Xiao M, Chu Z Y, Li G C, Zhang Y 2021 Sensors 21 3386 Google Scholar
[14]	Gui Y G, Peng X, Liu K Ding Z Y 2020 Physicas E 119 113959 Google Scholar
[15]	Zhu P C, Tang F, Wang S F, Cao W, Wang Q 2022 Mater. Today Commun. 33 104280 Google Scholar
[16]	Li Q F, Chen W L, Liu W H, Sun M L, Xu M H, Peng H L, Wu H Y, Song S X, Li T H, Tang X H 2022 Appl. Surf. Sci. 586 152689 Google Scholar
[17]	Hong H S, Ha N H, Thinh, D D, Nam N H, Huong N T, Hue N T, Hoang T V 2021 Nano Energy 87 106165 Google Scholar
[18]	Zhang T, Sun H, Wang F D, Zhang W D, Tang S W, Ma J M, Gong H W, Zhang J P 2017 Appl. Surf. Sci. 425 340 Google Scholar
[19]	Choudhuri I, Patra N, Mahata A, Ahuja R, Pathak B 2015 J. Phys. Chem. C 119 24827 Google Scholar
[20]	Shukri M S M, Saimin M N S, Yaakob M K, Yahya M Z A, Taib M F M 2019 Appl. Surf. Sci. 494 817 Google Scholar
[21]	Shamim S U D, Roy D, Alam S, Piya A A, Rahman M S, Hossain M K, Ahmed F 2022 Appl. Surf. Sci. 596 153603 Google Scholar
[22]	Zhang X X, Yu L, Gui Y G, Hu W H 2016 Appl. Surf. Sci. 367 259 Google Scholar
[23]	Jia X, An L 2019 Mod. Phys. Lett. B 33 1950044 Google Scholar
[24]	Segall M D, Lindan P J D, Probert M J, Pickard C J, Hasnip P J, Clark S J, Payne M C 2002 J. Phys. Condens. Mat. 14 2717 Google Scholar
[25]	Yang Z H, Wang Z Y, Su X P 2012 J. Cent. South Univ. 19 1796 Google Scholar
[26]	Basiuk V A, Henao-Holguin L V 2014 J. Comput. Theor. Nanosci. 11 1609 Google Scholar
[27]	朱洪强, 冯庆 2014 63 133101 Google Scholar Zhu H Q, Feng Q 2014 Acta Phys. Sin. 63 133101 Google Scholar
[28]	Gao X, Zhou Q, Wang J X, Xu L N, Zeng W 2020 Appl. Surf. Sci. 517 146180 Google Scholar
[29]	Zheng T, Traian D, Thomas F 2021 Phys. Chem. Chem. Phys. 23 19627 Google Scholar
[30]	Ping L K, Mohamed M A, Mondal A K, Taib M F M, Samat M H, Berhanuddin D D, Menon P S, Bahru R 2021 Micromachines 12 348 Google Scholar

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