journal article·2018-07-05Open access

A Universal Strategy To Prepare Sulfur-Containing Polymer Composites with Desired Morphologies for Lithium–Sulfur Batteries

Shao-Zhong Zeng, Xierong Zeng, Wenxuan Tu, Haitao Huang, Liang Yu, Yuechao Yao, Nengzhi Jin, Qi Zhang, Jizhao Zou

ACS Applied Materials & Interfaces· Volume 10· Issue 26

Abstract

Lithium–sulfur (Li–S) batteries are probably the most promising candidates for the next-generation batteries owing to their high energy density. However, Li–S batteries face severe technical problems where the dissolution of intermediate polysulfides is the biggest problem because it leads to the degradation of the cathode and the lithium anode, and finally the fast capacity decay. Compared with the composites of elemental sulfur and other matrices, sulfur-containing polymers (SCPs) have strong chemical bonds to sulfur and therefore show low dissolution of polysulfides. Unfortunately, most SCPs have very low electron conductivity and their morphologies can hardly be controlled, which undoubtedly depress the battery performances of SCPs. To overcome these two weaknesses of SCPs, a new strategy was developed for preparing SCP composites with enhanced conductivity and desired morphologies. With this strategy, macroporous SCP composites were successfully prepared from hierarchical porous carbon. The composites displayed discharge/charge capacities up to 1218/1139, 949/922, and 796/785 mA h g–1 at the current rates of 5, 10, and 15 C, respectively. Considering the universality of this strategy and the numerous morphologies of carbon materials, this strategy opens many opportunities for making carbon/SCP composites with novel morphologies.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Battery Materials and Technologies · Conducting polymers and applications · Synthesis and properties of polymers

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, P. R. China

Gansu Computing Center, Lanzhou 730030 Gansu, China

Department of Manufacturing and Materials, Cranfield University, Cranfield, Bedfordshire MK43 0AL, U.K.

Guangdong JANUS Intelligent Group Corporation Limited, Dongguan 523878, China

Funding

National Natural Science Foundation of China · Hong Kong Polytechnic University · Shenzhen Municipality · Dongguan Municipality · State Key Laboratory of Solidification Processing, Northwestern Polytechnical University

References (65)

Show source-provided references
1. 10.1002/adma.20160175910.1002/adma.201601759 ↗
2. 10.1002/adma.20140511510.1002/adma.201405115 ↗
3. 10.1002/aenm.20130176110.1002/aenm.201301761 ↗
4. 10.1002/adma.20130316610.1002/adma.201303166 ↗
5. 10.1016/j.carbon.2015.03.00810.1016/j.carbon.2015.03.008 ↗
6. 10.1039/c002639e10.1039/c002639e ↗
7. 10.1021/acs.nanolett.5b0410510.1021/acs.nanolett.5b04105 ↗
8. 10.1038/ncomms441010.1038/ncomms4410 ↗
9. 10.1038/ncomms575910.1038/ncomms5759 ↗
10. 10.1038/nmat246010.1038/nmat2460 ↗
11. 10.1021/acsnano.5b0348810.1021/acsnano.5b03488 ↗
12. 10.1039/c4ta03877k10.1039/c4ta03877k ↗
13. 10.1039/c7ta08520f10.1039/c7ta08520f ↗
14. 10.1002/aenm.20170108210.1002/aenm.201701082 ↗
15. 10.1016/j.nanoen.2015.01.03310.1016/j.nanoen.2015.01.033 ↗
16. 10.1039/c4ta06511e10.1039/c4ta06511e ↗
17. 10.1002/chem.20170521110.1002/chem.201705211 ↗
18. 10.1016/j.jpowsour.2010.12.05210.1016/j.jpowsour.2010.12.052 ↗
19. 10.1021/acsami.6b0760710.1021/acsami.6b07607 ↗
20. 10.1021/mz400649w10.1021/mz400649w ↗
21. 10.1002/adma.20160383510.1002/adma.201603835 ↗
22. 10.1002/1521-4095(20020705)14:13/14<963::aid-adma963>3.0.co;2-p10.1002/1521-4095(20020705)14:13/14<963::aid-adma963>3.0.co;2-p ↗
23. 10.1002/adma.20110339210.1002/adma.201103392 ↗
24. 10.1002/anie.20151155310.1002/anie.201511553 ↗
25. 10.1039/c6ee01019a10.1039/c6ee01019a ↗
26. 10.1039/c3ta12634j10.1039/c3ta12634j ↗
27. 10.1021/acs.nanolett.6b0461010.1021/acs.nanolett.6b04610 ↗
28. 10.1038/nchem.162410.1038/nchem.1624 ↗
29. 10.1038/ncomms827810.1038/ncomms8278 ↗
30. 10.1039/c6ee02770a10.1039/c6ee02770a ↗
31. 10.1016/j.jpowsour.2017.04.09210.1016/j.jpowsour.2017.04.092 ↗
32. 10.1039/c2ee03495f10.1039/c2ee03495f ↗
33. 10.1021/acsami.7b1099110.1021/acsami.7b10991 ↗
34. 10.1038/ncomms216310.1038/ncomms2163 ↗
35. 10.1002/aenm.20150245910.1002/aenm.201502459 ↗
36. 10.1002/aenm.20150073810.1002/aenm.201500738 ↗
37. 10.1021/am508528p10.1021/am508528p ↗
38. 10.1021/nn203436j10.1021/nn203436j ↗
39. 10.1016/j.electacta.2016.08.01510.1016/j.electacta.2016.08.015 ↗
40. 10.1002/adma.20160516010.1002/adma.201605160 ↗
41. 10.1002/adma.20160166510.1002/adma.201601665 ↗
42. 10.1021/acs.nanolett.7b0022110.1021/acs.nanolett.7b00221 ↗
43. 10.1016/j.nanoen.2016.02.00810.1016/j.nanoen.2016.02.008 ↗
44. 10.1016/j.nanoen.2015.05.03610.1016/j.nanoen.2015.05.036 ↗
45. 10.1021/acsami.5b0853710.1021/acsami.5b08537 ↗
46. 10.1039/c7ta00799j10.1039/c7ta00799j ↗
47. 10.1021/am501627f10.1021/am501627f ↗
48. 10.1021/am505080r10.1021/am505080r ↗
49. 10.1002/adma.20150246710.1002/adma.201502467 ↗
50. 10.1002/aenm.20150253910.1002/aenm.201502539 ↗
51. 10.1002/aenm.20140175210.1002/aenm.201401752 ↗
52. 10.1002/aenm.20120108010.1002/aenm.201201080 ↗
53. 10.1021/nl504963e10.1021/nl504963e ↗
54. 10.1002/app.4399310.1002/app.43993 ↗
55. 10.1002/adma.20140256910.1002/adma.201402569 ↗
56. 10.1039/c4ra01313a10.1039/c4ra01313a ↗
57. 10.1021/jp501546610.1021/jp5015466 ↗
58. 10.1002/(sici)1097-4628(20000425)76:4<439::aid-app1>3.0.co;2-n10.1002/(sici)1097-4628(20000425)76:4<439::aid-app1>3.0.co;2-n ↗
59. 10.1021/nn507178a10.1021/nn507178a ↗
60. 10.1149/2.0861503jes10.1149/2.0861503jes ↗
61. 10.1016/j.nanoen.2017.03.01810.1016/j.nanoen.2017.03.018 ↗
62. 10.1149/1.208589610.1149/1.2085896 ↗
63. 10.1039/c7se00350a10.1039/c7se00350a ↗
64. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucc, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Keith, T.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, O.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, Revision B.01; Gaussian, Inc.: Wallingford CT, 2010.
65. 10.1021/acsnano.5b0734710.1021/acsnano.5b07347 ↗