Operando Characterization of Volume Changes in Lithium-Ion Battery Electrodes during Cycling Using Isotope Multilayers
Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide This study reports on advancements in operando characterization of volume changes in lithium-ion battery (LIB) electrode materials during electrochemical cycling. Volume changes are crucial for LIB operation because they are related to the amount of stored energy as well as LIB integrity, performance, and safety. The study introduces a method based on isotope multilayers as active material to track the intrinsic modification of electrode volume in real time under operating conditions with operando neutron reflectometry. A nat Ge/ 73 Ge multilayer film is used as a model system to measure the volume change of amorphous germanium electrodes during charging and discharging. Isotope modulation produces a Bragg peak in the neutron reflectivity pattern, sensitive only to the modification of volume within the active material of the electrode. Battery side reactions, such as the growth and reduction of the solid-electrolyte interphase, are excluded. Using this method, the volume modification as a function of Li content x in Li x Ge can easily be derived from the scattering vector position of the Bragg peak without fitting numerous complex reflectivity patterns. The experiments show a reversible volume change of amorphous germanium of up to 250% for x ≈ 3, which appears to be largely independent of current density, cycle number, and the thickness of the individual Ge layers. Also, there are tentative indications that the crystallization and reamorphization of Li x Ge do not influence the volume change.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advancements in Battery Materials · Advanced Battery Materials and Technologies · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Clausthal University of Technology
Solid State Kinetics Group, Institute of Metallurgy
Clausthal Center for Materials Technology
Center for Neutron and Muon Sciences
Paul Scherer Institute
Funding
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
References (66)
Show source-provided references
1. 10.1063/5.027068810.1063/5.0270688 ↗
2. 10.1021/acsmaterialsau.4c0001110.1021/acsmaterialsau.4c00011 ↗
3. 10.1039/c3cp44438d10.1039/c3cp44438d ↗
4. 10.1021/jp502261t10.1021/jp502261t ↗
5. 10.1039/C4CP06017B10.1039/C4CP06017B ↗
6. 10.1021/acsnano.6b0203210.1021/acsnano.6b02032 ↗
7. 10.1021/acsami.6b0117010.1021/acsami.6b01170 ↗
8. 10.3139/146.11153610.3139/146.111536 ↗
9. 10.1016/B978-0-444-63739-0.00005-010.1016/B978-0-444-63739-0.00005-0 ↗
10. 10.1039/C8CP03540G10.1039/C8CP03540G ↗
11. 10.1021/acs.jpcc.9b0601110.1021/acs.jpcc.9b06011 ↗
12. 10.1016/j.elecom.2020.10673810.1016/j.elecom.2020.106738 ↗
13. 10.1149/1945-7111/ac076110.1149/1945-7111/ac0761 ↗
14. 10.1002/sstr.20240054210.1002/sstr.202400542 ↗
15. 10.1021/acsenergylett.5c0422110.1021/acsenergylett.5c04221 ↗
16. 10.1016/j.jpowsour.2017.05.09510.1016/j.jpowsour.2017.05.095 ↗
17. 10.1021/acsmaterialsau.4c0004610.1021/acsmaterialsau.4c00046 ↗
18. 10.1038/s41598-018-35915-110.1038/s41598-018-35915-1 ↗
19. 10.1080/21663831.2022.211481410.1080/21663831.2022.2114814 ↗
20. 10.1021/acsomega.3c0402910.1021/acsomega.3c04029 ↗
21. 10.1051/epjconf/20232860500210.1051/epjconf/202328605002 ↗
22. 10.1149/2.0131513jes10.1149/2.0131513jes ↗
23. 10.1103/PhysRevLett.116.02590110.1103/PhysRevLett.116.025901 ↗
24. 10.1016/j.nima.2016.03.00710.1016/j.nima.2016.03.007 ↗
25. 10.3390/batteries905024410.3390/batteries9050244 ↗
26. 10.1063/1.300229410.1063/1.3002294 ↗
27. 10.1103/PhysRevB.88.08520610.1103/PhysRevB.88.085206 ↗
28. 10.1007/s10800-022-01737-310.1007/s10800-022-01737-3 ↗
29. 10.1149/1945-7111/ac8a7910.1149/1945-7111/ac8a79 ↗
30. 10.1063/5.010961010.1063/5.0109610 ↗
31. 10.3390/batteries902010510.3390/batteries9020105 ↗
32. 10.1149/1.161366810.1149/1.1613668 ↗
33. 10.1021/nn403790910.1021/nn4037909 ↗
34. 10.1039/C6NR03575B10.1039/C6NR03575B ↗
35. 10.1002/cssc.20180196910.1002/cssc.201801969 ↗
36. 10.1016/j.jpowsour.2010.11.15510.1016/j.jpowsour.2010.11.155 ↗
37. 10.1088/1361-6528/abfa5410.1088/1361-6528/abfa54 ↗
38. 10.1002/aenm.20120002410.1002/aenm.201200024 ↗
39. 10.1039/d1cp05414g10.1039/d1cp05414g ↗
40. 10.3390/nano1321286810.3390/nano13212868 ↗
41. 10.1021/nn400330h10.1021/nn400330h ↗
42. 10.1021/nl202411810.1021/nl2024118 ↗
43. ;Braun, C. Parratt32 or the reflectometry tool ; Parratt32: HMI, Berlin, https://parratt32.software.informer.com/1.6/. 2005.
44. 10.1103/PhysRev.95.35910.1103/PhysRev.95.359 ↗
45. Munter A.
46. 10.3390/en1606274010.3390/en16062740 ↗
47. 10.1021/acs.chemmater.8b0018610.1021/acs.chemmater.8b00186 ↗
48. 10.1007/BF0288155210.1007/BF02881552 ↗
49. 10.1007/s11669-010-9840-310.1007/s11669-010-9840-3 ↗
50. 10.1016/j.calphad.2008.10.00610.1016/j.calphad.2008.10.006 ↗
51. 10.1002/advs.20200485510.1002/advs.202004855 ↗
52. 10.1149/1.283648110.1149/1.2836481 ↗
53. 10.1149/1.305598410.1149/1.3055984 ↗
54. 10.1002/aenm.20150059910.1002/aenm.201500599 ↗
55. 10.1016/j.ensm.2020.05.01010.1016/j.ensm.2020.05.010 ↗
56. 10.1002/celc.20130019510.1002/celc.201300195 ↗
57. 10.1149/1.173921710.1149/1.1739217 ↗
58. 10.1149/1.165242110.1149/1.1652421 ↗
59. 10.1021/ja108085d10.1021/ja108085d ↗
60. 10.1038/ncomms421710.1038/ncomms4217 ↗
61. 10.1016/j.xcrp.2021.10059710.1016/j.xcrp.2021.100597 ↗
62. 10.1103/PhysRev.154.75010.1103/PhysRev.154.750 ↗
63. 10.1016/j.tsf.2015.06.01710.1016/j.tsf.2015.06.017 ↗
64. 10.1149/1945-7111/ab75c010.1149/1945-7111/ab75c0 ↗
65. 10.1016/j.jpowsour.2014.04.01110.1016/j.jpowsour.2014.04.011 ↗
66. 10.1021/acsaem.6c0065310.1021/acsaem.6c00653 ↗