Simultaneous Photoreduction and Nitrogen Doping of Graphene Oxide for Supercapacitors by Direct Laser Writing

Xiuyan Fu , Shuai Xu , Yang Luo , Aiwu Li , Han Yang

Chemical Research in Chinese Universities ›› 2019, Vol. 35 ›› Issue (5) : 879 -883.

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Chemical Research in Chinese Universities ›› 2019, Vol. 35 ›› Issue (5) : 879 -883. DOI: 10.1007/s40242-019-9060-2
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Simultaneous Photoreduction and Nitrogen Doping of Graphene Oxide for Supercapacitors by Direct Laser Writing

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Abstract

Graphene-based supercapacitors have attracted tremendous attention owing to their outstanding electro-chemical performance. In terms of material, nitrogen(N)-doped graphene(NDG) displays enhanced specific capaci- tance and rate performance compared with bare graphene used as a supercapacitor electrode. However, it still remains a challenge to develop a facile and simple method of NDG in cost-effective manner. Here, we used a simple direct laser writing technique to accomplish the simultaneous photoreduction and N-doping of graphene oxide(GO) using urea as a N source. The N content of the resultant reduced N-doped graphene oxide(NGO) reached a maximum value of 6.37%. All reduced NGO(NRGO)-based supercapacitors exhibited a higher specific capacitance than those based on pure reduced GO(RGO). Interestingly, the electrochemical performance of NRGO-based supercapacitors varied with different contents of N species. Therefore, we can control the properties of the obtained NRGOs by adjusting the doping ratios, an important step in developing effective graphene-based energy storage devices.

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Simultaneous photoreduction and nitrogen-doping / Graphene based supercapacitor / Direct laser writing

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Xiuyan Fu, Shuai Xu, Yang Luo, Aiwu Li, Han Yang. Simultaneous Photoreduction and Nitrogen Doping of Graphene Oxide for Supercapacitors by Direct Laser Writing. Chemical Research in Chinese Universities, 2019, 35(5): 879-883 DOI:10.1007/s40242-019-9060-2

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References

[1]

Bi Y G, Feng J, Li Y F, Zhang X L, Liu Y F, Jin Y, Sun H B. Adv. Mater., 2013, 25(48): 6969.

[2]

Yin D, Feng J, Ma R, Liu Y F, Zhang Y L, Zhang X L, Bi Y G, Chen Q D, Sun H B. Nat. Commun., 2016, 7: 11573.

[3]

Wu D, Chen Q D, Niu L G, Wang J N, Wang J, Wang R, Xia H, Sun H B. Lab on a Chip, 2009, 9(16): 2391.

[4]

Xu B B, Zhang Y L, Xia H, Dong W F, Ding H, Sun H B. Lab on a Chip, 2013, 13(9): 1677.

[5]

Wu D, Wu S Z, Chen Q D, Zhao S, Zhang H, Jiao J, Piersol J A, Wang J N, Sun H B, Jiang L. Lab on a Chip, 2011, 11(22): 3873.

[6]

Wei H H, Zhang Q, Wang Y, Li Y J, Fan J C, Xu Q J, Min Y L. Adv. Funct. Mater., 2018, 28(3): 1704440.

[7]

Zhang X L, Song J F, Li X B, Feng J, Sun H B. Appl. Phys. Lett., 2012, 101(24): 243901.

[8]

Guo R, Chen J, Yang B, Liu L, Su L, Shen B, Yan X. Adv. Funct. Mater., 2017, 27(43): 1702394.

[9]

Yang C, Tang Y, Tian Y, Luo Y, Muhammad F U D, Yin X, Que W X. Adv. Energy Mater., 2018, 8(31): 1802087.

[10]

Ramesh S, Karuppasamy K, Kim H S, Kim H S, Kim J H. Scientific Reports, 2018, 8: 16543.

[11]

Feng D, Lei T, Lukatskaya M R, Park J, Huang Z, Lee M, Shaw L, Chen S, Yakovenko A A, Kulkarni A, Xiao J, Fredrickson K, Tok J B, Zou X, Cui Y, Bao Z. Nature Energy, 2018, 31: 30.

[12]

Qi D, Liu Y, Liu Z, Zhang L, Chen X. Adv. Mater., 2017, 29(5): 1602802.

[13]

Feng L, Wang K, Zhang X, Sun X, Li C, Ge X, Ma Y. Adv. Funct. Mater., 2018, 28(4): 1704463.

[14]

Guo L, Jiang H B, Shao R Q, Zhang Y L, Xie S Y, Wang J N, Li X B, Jiang F, Chen Q D, Zhang T, Sun H B. Carbon, 2012, 50(4): 1667.

[15]

Liu Y Z, Li Y F, Su F Y, Xie L J, Kong Q Q, Li X M, Gao J G, Chen C M. Energy Storage Materials, 2016, 2: 69.

[16]

Sun H J, Liu B, Peng T J, Zhao X L. J. Mater. Sci., 2018, 53(18): 13100.

[17]

Wen Z, Wang X, Mao S, Bo Z, Kim H, Cui S, Lu G, Feng X, Chen J. Adv. Mater., 2012, 24(41): 5610.

[18]

Han D D, Zhang Y L, Jiang H B, Xia H, Feng J, Chen Q D, Xu H L, Sun H B. Adv. Mater., 2015, 27(2): 332.

[19]

Wen Y, Huang C, Wang L, Hulicova-Jurcakova D. Chinese Science Bulletin, 2014, 59(18): 2102.

[20]

Han J, Zhang L L, Lee S, Oh J, Lee K S, Potts J R, Ji J, Zhao X, Ruoff R S, Park S. ACS Nano, 2013, 7(1): 19.

[21]

Kumar N A, Baek J B. Nanotechnology, 2015, 26: 492001.

[22]

Jeong H M, Lee J W, Shin W H, Choi Y J, Shin H J, Kang J K, Choi J W. Nano Lett., 2011, 11(6): 2472.

[23]

Singh S K, Dhavale V M, Boukherroub R, Kurungot S, Szunerits S. Applied Materials Today, 2017, 8: 141.

[24]

Zou Y, Kinloch I A, Dryfe R A W. J. Mater. Chem. A, 2014, 2(45): 19495.

[25]

Li X J, Yu X X, Liu J Y, Fan X D, Zhang K, Cai H B, Pan N, Wang X P. Chinese J. Chem. Phys., 2012, 25(3): 325.

[26]

Yang J, Jo M R, Kang M, Huh Y S, Jung H, Kang Y M. Carbon, 2014, 73: 106.

[27]

Zhang X Y, Sun S H, Sun X J, Zhao Y R, Chen L, Yang Y, Lu W, Li D B. Light: Science & Applications, 2016, 5: E16130.

[28]

Selvakumar D, Alsalme A, Alswieleh A, Jayavel R. J. Alloys Compounds, 2017, 723: 995.

[29]

Zhang Y, Wen G, Gao P, Bi S, Tang X, Wang D. Electrochimica Acta, 2016, 221: 167.

[30]

Gao W, Singh N, Song L. Nat. Nanotechnol., 2011, 6(8): 496.

[31]

El-Kady M F, Kaner R B. Nat. Commun., 2013, 4: 1475.

[32]

Wu Z S, Parvez K, Feng X L. Nat. Commun., 2013, 4: 8.

[33]

Liu S, Xie J, Li H. J. Mater. Chem. A, 2014, 2(42): 18125.

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