journal article·2025-01-01Open access

Joint intelligent optimization design of the active region and electron blocking layer for AlGaN-based deep ultraviolet LEDs

Jinglei Wang, Huimin Lu, Jianhua Ma, Yifan Zhu, Zihua Zhang, Tongjun Yu, Xuecheng Wei, Hua Yang, Jianping Wang

AIP Advances· Volume 15· Issue 1

Abstract

Aiming to enhance the internal quantum efficiency (IQE) of AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs), the active region based on the V-shaped quantum well (QW) and the electron-blocking layer (EBL) structure are jointly optimized using intelligent algorithms in this work. This method focuses on maximizing the IQE of the DUV LEDs by optimizing the geometric and material parameters of multiple QWs (MQWs) and EBL. It is demonstrated that the DUV LED with an optimized structure exhibits smaller band edge tilt for improved wave function overlap in QWs and more effective carrier blocking for reduced electron overflow compared to that with a conventional structure. The results show that, by optimizing the active region and EBL structure using the proposed method, the IQE and maximum radiation intensity of the AlGaN-based DUV LED are enhanced by 38% and 41% at 200 A/cm2 injection current density, respectively.
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Research context

OpenAlex topics: GaN-based semiconductor devices and materials · Ga2O3 and related materials · ZnO doping and properties

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

Affiliations

The School of Computer and Communication Engineering, University of Science and Technology Beijing 1 , Beijing 100089,

The State Key Laboratory for Mesoscopic Physics, School of Physics, Peking University 2 , Beijing 100089,

Research and Development Center for Wide Bandgap Semiconductors, Institute of Semiconductors, Chinese Academy of Sciences 3 , Beijing 100083,

Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences 4 , Beijing 100049,

Funding

National Nature Science Foundation of China · Key Laboratory Foundation of Metrology and Calibration Technology

References (28)

Show source-provided references
1. Nat. Photonics · 2019 · 13 · 23310.1038/s41566-019-0359-9 ↗
2. Electron. Commun. Jpn. · 2015 · 98 · 110.1002/ecj.11667 ↗
3. Fundam. Res. · 2021 · 1 · 71710.1016/j.fmre.2021.11.005 ↗
4. Phys. Status Solidi A · 2006 · 203 · 176410.1002/pssa.200565427 ↗
5. Luminescence · 2021 · 36 · 29410.1002/bio.3965 ↗
6. J. Phys. D: Appl. Phys. · 2020 · 53 · 07300210.1088/1361-6463/ab4d7b ↗
7. Mater. Lett. · 2023 · 351 · 13509710.1016/j.matlet.2023.135097 ↗
8. Appl. Phys. Lett. · 2019 · 114 · 04210110.1063/1.5074177 ↗
9. Appl. Surf. Sci. · 2020 · 518 · 14621810.1016/j.apsusc.2020.146218 ↗
10. Micro Nanostruct. · 2023 · 175 · 20748910.1016/j.micrna.2022.207489 ↗
11. Opt. Express · 2019 · 27 · A145810.1364/oe.27.0a1458 ↗
12. Micro Nanostruct. · 2022 · 163 · 10715010.1016/j.spmi.2022.107150 ↗
13. IEEE J. Quantum Electron. · 2020 · 56 · 330010610.1109/jqe.2019.2956344 ↗
14. Mater. Sci. Eng.: B · 2023 · 296 · 11662410.1016/j.mseb.2023.116624 ↗
15. Optica · 2019 · 6 · 136710.1364/optica.6.001367 ↗
16. J. Appl. Phys. · 2022 · 132 · 22570410.1063/5.0128213 ↗
17. Acta Phys. Sin. · 2023 · 72 · 04850210.7498/aps.72.20222004 ↗
18. Int. J. Ind. Eng. Comp. · 2016 · 7 · 1910.5267/j.ijiec.2015.8.004 ↗
19. Appl. Soft Comput. · 2018 · 70 · 90310.1016/j.asoc.2017.10.001 ↗
20. Arch. Comput. Methods Eng. · 2022 · 29 · 76310.1007/s11831-021-09585-8 ↗
21. IEEE Trans. Cybern. · 2019 · 49 · 194410.1109/tcyb.2018.2817240 ↗
22. Appl. Soft Comput. · 2021 · 106 · 10732510.1016/j.asoc.2021.107325 ↗
23. Chin. J. Mech. Eng. · 2024 · 37 · 510.1186/s10033-023-00985-4 ↗
24. Phys. Status Solidi A · 2014 · 211 · 65610.1002/pssa.201330258 ↗
25. Appl. Phys. Express · 2015 · 8 · 02210410.7567/apex.8.022104 ↗
26. IEEE J. Quantum Electron. · 2016 · 52 · 110.1109/jqe.2016.2535252 ↗
27. IEEE Photonics J. · 2018 · 10 · 110.1109/jphot.2018.2852660 ↗
28. J. Appl. Phys. · 2001 · 89 · 581510.1063/1.1368156 ↗