Improved photoelectrochemical performance by forming a ZnO/ZnS core/shell nanorod array

Mei-rong Sui , Xiu-quan Gu , Mei-lin Shi , Yong Wang , Lin-lin Liu

Optoelectronics Letters ›› 2019, Vol. 15 ›› Issue (4) : 241 -244.

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Optoelectronics Letters ›› 2019, Vol. 15 ›› Issue (4) : 241 -244. DOI: 10.1007/s11801-019-8162-x
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Improved photoelectrochemical performance by forming a ZnO/ZnS core/shell nanorod array

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Abstract

ZnO nanorod arrays (NRAs) were prepared via a facile hydrothermal method for photoelectrochemical (PEC) applications. Then, ZnS thin shell layers were deposited onto them via a facile hydrothermal treatment process for constructing a ZnO/ZnS core/shell structure. It was demonstrated that the PEC activity of a ZnO NRA is enhanced significantly after the surface modification, although there weren’t any obvious changes in the visible-light harvesting efficiency. Both the Nyquist and Mott-Schottky (M-S) plots were employed to reveal the reason, which was attributed to higher electrocatalytic activity of ZnS than that of ZnO and the resulting higher charge transfer efficiency across the solid/liquid interfaces. Finally, a schematic band model was proposed for clarifying the charge carrier transfer mechanism occurred at the interfaces.

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Mei-rong Sui, Xiu-quan Gu, Mei-lin Shi, Yong Wang, Lin-lin Liu. Improved photoelectrochemical performance by forming a ZnO/ZnS core/shell nanorod array. Optoelectronics Letters, 2019, 15(4): 241-244 DOI:10.1007/s11801-019-8162-x

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References

[1]

LawM, GreeneLE, JohnsonJC, SaykallyR, YangP. Nat. Mater, 2005, 4: 455

[2]

GreeneL, LawM, TanDH, GoldbergerJ, YangP. Nano Lett., 2005, 5: 1231

[3]

WangL, GuX, ZhaoY, QiangY. J. Mater. Sci. Mater. Electron., 2017, 29: 4058

[4]

LeungY H, HeZ B, LuoL B, TsangC H A, WongN B, ZhangW J, LeeS T. Appl. Phys. Lett., 2010, 96: 053102

[5]

XuC, WuJ, DesaiU V, GaoD. Nano Lett, 2012, 12: 2420

[6]

XuC, WuJ, DesaiU V, GaoD. J. Am. Chem. Soc, 2011, 133: 8122

[7]

FujishimaA, HondaK. Nature, 1972, 238: 37

[8]

BhattM D, LeeJ S. J. Mater. Chem. A, 2015, 3: 10632

[9]

ZhangS, GuX, ZhaoY, QiangY. J. Electron. Mater, 2016, 45: 648

[10]

ZhongM, LiY, YamadaI, DelaunayJ-J. Nanoscale, 2012, 4: 1509

[11]

KuangY, JiaQ, NishiyamaH, YamadaT, KudoA, DomenK. Adv. Energy Mater, 2016, 6: 1501645

[12]

YangX, LiuR, DuC, DaiP, ZhengZ, WangD. ACS Appl. Mater. Interfaces, 2014, 6: 12005

[13]

SuJ, GuoL, BaoN, GrimesCA. Nano Lett, 2011, 11: 1928

[14]

WangL, WeiM, GuX, ZhaoY, QiangY. J. Electron. Mater, 2018, 47: 6540

[15]

YangX, WolcottA, WangG, SoboA, FitzmorrisR C, QianF, ZhangJ Z, LiY. Nano Lett, 2009, 9: 2331

[16]

BaiZ, YanX, LiY, KangZ, CaoS, ZhangY. Adv. Energy Mater, 2015, 6: 1501459

[17]

BaiZ, YanX, KangZ, HuY, ZhangX, ZhangY. Nano Energy, 2015, 14: 392

[18]

WangL, GuX, ZhaoY, QiangY, HuangC, SongJ. Vacuum, 2018, 148: 201

[19]

ChenW, RuanH, HuY, LiD, ChenZ, XianJ, ChenJ, FuX, ShaoY, ZhengY. Cryst. Eng. Comm., 2012, 14: 6295

[20]

ChelvanathanaP, YusoffaY, HaqueaF, AkhtaruzzamanaM, AlamcM M, AlothmancZ A, RashidM J, SopianK B, AminN. Appl. Surf. Sci., 2015, 334: 138

[21]

MaruskaH P, GhoshA K. Sol. Energy, 1978, 20: 443

[22]

BursteinE. Phys. Rev. Lett., 1954, 93: 632

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