journal article·2025-07Open access

Harnessing Dynamic Electrostatic Fields for Energy Generation with Diode Cells

Renyun Zhang, Magnus Hummelgård, Ye Xu, Martin Olsen, Jonas Örtegren, Göran Thungström, Henrik Andersson, Zhong Lin Wang

Advanced Science· Volume 12· Issue 28

Abstract

Abstract Harvesting energy from distributed mechanical motions has garnered significance in future power sources for small electronics and sensors. Although technologies like triboelectric nanogenerators have shown promising results, their efficacy hinges on the alignment of motion vectors and device architectures. Here, an approach employing stationary diode cells (DiCes) to generate electricity is presented. This approach leverages dynamically changing electrostatic fields to induce potential differences across diode junctions via electrostatic induction, which is verified theoretically and experimentally. DiCes constructed with multiple diodes can directly output DC voltage and current. A 0.02 m2 sized DiCe contains 360 diodes can supply a DC voltage and current of maximum 490 V and 1.08 mA, respectively, which equals a DC power density of 26.5 W·m−2. Capable of functioning in both contact and non‐contact modes, DiCes offer versatile applications, from wirelessly powering implanted medical devices to harvesting energy from vehicles and roads.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Energy Harvesting in Wireless Networks · Advanced Sensor and Energy Harvesting Materials · Innovative Energy Harvesting Technologies

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

Affiliations

Department of Engineering, Mathematics, and Science Education Mid Sweden University Sundsvall SE 85170 Sweden

Department of Computer and Electrical Engineering Mid Sweden University Sundsvall SE 85170 Sweden

Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 100083 China

School of Nanoscience and Technology University of Chinese Academy of Sciences Beijing 100049 China

References (44)

Show source-provided references
1. 10.1002/aenm.20180290610.1002/aenm.201802906 ↗
2. 10.1109/JSAC.2015.239169010.1109/JSAC.2015.2391690 ↗
3. 10.1038/s41467-021-23944-w10.1038/s41467-021-23944-w ↗
4. 10.1038/s41467-022-31067-z10.1038/s41467-022-31067-z ↗
5. M. A.Weimer T. S.Paing R. A.Zane in2006 37th IEEE Power Electronics Specialists Conference IEEE 2006 pp.1–5.10.1109/pesc.2006.1712213 ↗
6. 10.1038/s41578-022-00460-x10.1038/s41578-022-00460-x ↗
7. 10.1002/adhm.20210019910.1002/adhm.202100199 ↗
8. 10.1038/s41569-020-0426-410.1038/s41569-020-0426-4 ↗
9. 10.1038/s41578-022-00441-010.1038/s41578-022-00441-0 ↗
10. 10.1002/adma.20160225110.1002/adma.201602251 ↗
11. 10.1016/j.apenergy.2019.11387110.1016/j.apenergy.2019.113871 ↗
12. 10.1016/j.nanoen.2012.01.00410.1016/j.nanoen.2012.01.004 ↗
13. 10.1016/j.nanoen.2017.12.05310.1016/j.nanoen.2017.12.053 ↗
14. 10.1016/j.nanoen.2022.10740910.1016/j.nanoen.2022.107409 ↗
15. 10.1126/sciadv.ads229110.1126/sciadv.ads2291 ↗
16. 10.1016/j.nanoen.2015.01.03810.1016/j.nanoen.2015.01.038 ↗
17. 10.1063/1.513410010.1063/1.5134100 ↗
18. 10.1016/j.mser.2025.10095310.1016/j.mser.2025.100953 ↗
19. 10.1002/smll.20240579210.1002/smll.202405792 ↗
20. Blender Online Community http://www.blender.org2018.
21. MB‐Lab Development Team MB‐Lab: Advanced 3D humanoid creation tool for Blender (Version 1.7.8) [Software]2024 https://github.com/animate1978/MB‐Lab.
22. 10.1103/PhysRevApplied.9.02403310.1103/PhysRevApplied.9.024033 ↗
23. 10.1109/RBME.2017.268352010.1109/RBME.2017.2683520 ↗
24. 10.1038/s41467-020-20803-y10.1038/s41467-020-20803-y ↗
25. 10.1109/MMM.2010.93857910.1109/MMM.2010.938579 ↗
26. 10.1002/ente.20200053310.1002/ente.202000533 ↗
27. 10.1186/1743-0003-8-2210.1186/1743-0003-8-22 ↗
28. 10.1016/j.nanoen.2021.10604110.1016/j.nanoen.2021.106041 ↗
29. 10.1021/acsaem.8b0066710.1021/acsaem.8b00667 ↗
30. 10.1007/s40684-019-00144-y10.1007/s40684-019-00144-y ↗
31. 10.1016/j.fmre.2021.05.00210.1016/j.fmre.2021.05.002 ↗
32. 10.1002/eom2.1205410.1002/eom2.12054 ↗
33. 10.1016/j.elstat.2012.12.01210.1016/j.elstat.2012.12.012 ↗
34. 10.1016/j.elstat.2005.04.00210.1016/j.elstat.2005.04.002 ↗
35. 10.1016/j.nanoen.2019.06.03810.1016/j.nanoen.2019.06.038 ↗
36. 10.1016/j.nanoen.2019.01.06310.1016/j.nanoen.2019.01.063 ↗
37. 10.1016/j.nanoen.2019.01.04210.1016/j.nanoen.2019.01.042 ↗
38. 10.1021/acsnano.8b0256210.1021/acsnano.8b02562 ↗
39. 10.1002/adma.20210126210.1002/adma.202101262 ↗
40. 10.1002/adma.20170407710.1002/adma.201704077 ↗
41. 10.1109/MAP.2020.301287210.1109/MAP.2020.3012872 ↗
42. 10.1109/TAP.2015.243171910.1109/TAP.2015.2431719 ↗
43. 10.1109/TMTT.2004.82358510.1109/TMTT.2004.823585 ↗
44. 10.1038/s41598-018-33388-w10.1038/s41598-018-33388-w ↗