journal article·2024-10-09

Modality-Tunable Exfoliated N-Doped Graphene as Effective Electrolyte Additive for High-Performance Lithium–Sulfur Batteries

Vaidik R. Shah, Ritwick Sinha, Walter J. Cesarski, Xiaosi Gao, Simuck F. Yuk, Yong Lak Joo

ACS Applied Materials & Interfaces· Volume 16· Issue 40
Publisher page

Abstract

While chemically doped graphene has shown great promise, the lack of cost-effective manufacturing has hindered its use. This study utilizes a facile fabrication approach for modality-tunable N-doped graphene via thermal annealing of aqueous-phase-exfoliated few-layered graphene from a Taylor–Couette reactor. This method demonstrates a high level of N-doping (27 atom % N) and offers modality tunability of the C–N bond without foregoing scalability and green chemistry principles. The resulting N-doped graphene, with varying N content and doping modality, is utilized in the lithium–sulfur battery electrolyte to address low ionic conductivity, lithium polysulfide (LiPS) shuttling, and Li anode instability. The study reveals that higher N content and pyridinic N modality graphene in the electrolyte positively influence battery performance. The results are 2-fold: higher overall N content improves capacity retention (73%) after 225 cycles at 0.2 C, and pyridinic-type nitrogen demonstrates the best performance at high C rates, exhibiting a 4-fold capacity increase relative to the reference cell at 2 C. Further, the computational study validates the adsorption affinity of LiPS to pyridinic nitrogen and improved Li + mobility on the graphene backbone observed experimentally. This first experimental study on the impact of N-dopant concentration and modality on electrochemical performance provokes insights into tailoring N functionalization to achieve superior electrochemical performance.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Battery Materials and Technologies · Advancements in Battery Materials · Thermal Expansion and Ionic Conductivity

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

Affiliations

Robert Fredrick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, United States

Department of Chemistry and Life Science, United States Military Academy, West Point, New York 10996, United States

Funding

Saudi Aramco · National Energy Research Scientific Computing Center · Division of Materials Research

References (70)

Show source-provided references
1. 10.1021/ar300179v10.1021/ar300179v ↗
2. 10.7298/9BNZ-T45710.7298/9BNZ-T457 ↗
3. 10.1002/adfm.20190371210.1002/adfm.201903712 ↗
4. 10.1002/adma.20170059810.1002/adma.201700598 ↗
5. 10.1021/acsnano.9b0237410.1021/acsnano.9b02374 ↗
6. 10.1021/acsaem.0c0214110.1021/acsaem.0c02141 ↗
7. 10.1021/acs.nanolett.5b0416610.1021/acs.nanolett.5b04166 ↗
8. 10.1021/acsami.3c0151510.1021/acsami.3c01515 ↗
9. 10.1002/smll.20220403710.1002/smll.202204037 ↗
10. 10.1021/acsaem.9b0115210.1021/acsaem.9b01152 ↗
11. 10.1002/aenm.20190287210.1002/aenm.201902872 ↗
12. 10.1021/acsami.8b1419610.1021/acsami.8b14196 ↗
13. 10.1021/jz500691310.1021/jz5006913 ↗
14. 10.1002/adma.20140421010.1002/adma.201404210 ↗
15. 10.1038/nenergy.2016.9410.1038/nenergy.2016.94 ↗
16. 10.1039/C6TA07337A10.1039/C6TA07337A ↗
17. 10.1039/C9TA10301E10.1039/C9TA10301E ↗
18. 10.1149/MA2022-01182mtgabs10.1149/MA2022-01182mtgabs ↗
19. 10.1149/MA2022-028656mtgabs10.1149/MA2022-028656mtgabs ↗
20. 10.1021/nn101926g10.1021/nn101926g ↗
21. 10.1021/nl073187210.1021/nl0731872 ↗
22. 10.1016/j.cej.2018.04.16310.1016/j.cej.2018.04.163 ↗
23. 10.1021/nl203103710.1021/nl2031037 ↗
24. 10.1021/nn901850u10.1021/nn901850u ↗
25. 10.1103/PhysRevLett.85.521410.1103/PhysRevLett.85.5214 ↗
26. 10.1002/anie.20160592610.1002/anie.201605926 ↗
27. 10.1038/s41565-022-01185-210.1038/s41565-022-01185-2 ↗
28. 10.1039/C7CP04507G10.1039/C7CP04507G ↗
29. 10.1039/C6TA09030C10.1039/C6TA09030C ↗
30. 10.1021/acsnano.5b0734710.1021/acsnano.5b07347 ↗
31. 10.1002/anie.20170209910.1002/anie.201702099 ↗
32. 10.1039/C3TA14921H10.1039/C3TA14921H ↗
33. 10.1038/s41467-020-14686-210.1038/s41467-020-14686-2 ↗
34. 10.1021/cs200652y10.1021/cs200652y ↗
35. 10.1002/adma.20100411010.1002/adma.201004110 ↗
36. 10.1002/adfm.20190551110.1002/adfm.201905511 ↗
37. 10.1016/j.carbon.2015.09.05610.1016/j.carbon.2015.09.056 ↗
38. 10.1039/C4GC00049H10.1039/C4GC00049H ↗
39. 10.1039/C4RA05544F10.1039/C4RA05544F ↗
40. 10.1021/acs.jpcc.9b0255410.1021/acs.jpcc.9b02554 ↗
41. 10.1021/acsami.9b2282410.1021/acsami.9b22824 ↗
42. 10.1038/nmat394410.1038/nmat3944 ↗
43. 10.1002/slct.20190352310.1002/slct.201903523 ↗
44. 10.1039/D2NJ01662A10.1039/D2NJ01662A ↗
45. 10.1016/j.nanoen.2016.04.05310.1016/j.nanoen.2016.04.053 ↗
46. 10.1016/j.apsusc.2011.10.01910.1016/j.apsusc.2011.10.019 ↗
47. 10.1021/ja01539a01710.1021/ja01539a017 ↗
48. 10.1016/j.nanoen.2015.07.01410.1016/j.nanoen.2015.07.014 ↗
49. 10.1002/ente.20180100110.1002/ente.201801001 ↗
50. 10.1021/nn304037d10.1021/nn304037d ↗
51. 10.1016/j.est.2019.10115810.1016/j.est.2019.101158 ↗
52. 10.1149/1.222072910.1149/1.2220729 ↗
53. 10.1039/c1jm10845j10.1039/c1jm10845j ↗
54. 10.1039/c3cp51987b10.1039/c3cp51987b ↗
55. 10.1149/2.0181501jes10.1149/2.0181501jes ↗
56. 10.1021/ac203224410.1021/ac2032244 ↗
57. 10.1002/adma.20150155910.1002/adma.201501559 ↗
58. 10.1002/adfm.20220717210.1002/adfm.202207172 ↗
59. 10.1002/advs.20210600410.1002/advs.202106004 ↗
60. 10.1002/aenm.20200077910.1002/aenm.202000779 ↗
61. 10.1007/s41918-018-0021-010.1007/s41918-018-0021-0 ↗
62. 10.1016/j.cap.2020.11.00410.1016/j.cap.2020.11.004 ↗
63. 10.1038/s41524-020-0273-110.1038/s41524-020-0273-1 ↗
64. 10.1016/j.jpcs.2018.11.02710.1016/j.jpcs.2018.11.027 ↗
65. 10.1103/PhysRevLett.77.386510.1103/PhysRevLett.77.3865 ↗
66. 10.1016/j.cpc.2004.12.01410.1016/j.cpc.2004.12.014 ↗
67. 10.1103/PhysRevB.54.170310.1103/PhysRevB.54.1703 ↗
68. 10.1063/1.277070810.1063/1.2770708 ↗
69. 10.1002/jcc.2049510.1002/jcc.20495 ↗
70. 10.1002/jcc.2057510.1002/jcc.20575 ↗