X-Ray Topographic Characterization of Crystal Defects in High-Voltage 4H-SiC Wafers

Marie Lehmann

Articles

Vol. 1 No. 4 (2026)

X-Ray Topographic Characterization of Crystal Defects in High-Voltage 4H-SiC Wafers

Marie Lehmann^▸^▾

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Submitted: August 7, 2026
Published: August 7, 2026

Abstract

The rapid advancement of high-voltage power electronics has necessitated the development of semiconductor materials capable of withstanding extreme electrical and thermal conditions. Among the various wide bandgap materials, the 4H polytype of silicon carbide has emerged as the premier candidate for next-generation power devices, including those utilized in electric vehicles, renewable energy grid integration, and industrial motor drives. However, the commercial viability and operational reliability of high-voltage silicon carbide devices are fundamentally constrained by the presence of crystallographic defects inherent in the bulk material and epitaxial layers. This paper provides a comprehensive investigation into the characterization of crystal defects in high-voltage 4H-SiC wafers using X-ray topography. We systematically explore the morphological signatures of micropipes, threading screw dislocations, threading edge dislocations, basal plane dislocations, and stacking faults. Through non-destructive X-ray topographic imaging, the spatial distribution and density of these defects are analyzed in detail. The methodology encompasses both laboratory-based and synchrotron white-beam X-ray topography, highlighting the mechanisms of contrast formation based on kinematic and dynamical diffraction theories. Furthermore, the correlation between specific defect types and the degradation of high-voltage device performance is extensively discussed, providing critical insights for material scientists and process engineers aiming to optimize crystal growth and fabrication processes.

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26. Wan, H., Cheng, J., Deng, Y., Wu, D., Chen, Y., Lin, Z., ... & Ji, X. Towards Physics Aware Embodied Control with Graph based Object-centric Learning. ACM Transactions on Cyber-Physical Systems.
27. Chen, B., Hu, X., & Zhu, X. (2023). Essential Rule Derived from Thermodynamics and Kinetics Studies of Benzopyran Compounds.Molecules,28(24), 8039.
28. W. Zhang, "A 5-6 GHz PVT Robust Current Mode Passive Mixer for Direct Down-Conversion Receiver," in *2026 5th International Conference on Electronics, Integrated Circuits and Communication Technology (EICCT)*, 2026, pp. 420–424.
29. Li, X., Wang, P., Li, G., & Zhang, Y. (2023). Design of a novel self-test-on-chip interface ASIC for capacitive accelerometers. IEEE Transactions on Circuits and Systems I: Regular Papers, 70(7), 2834-2843.
30. Yao, Jingyu, et al. "Explainable AI Enhanced Traffic Forecasting for Proactive Autonomous Vehicle Routing." 2026 IEEE Conference on Technologies for Sustainability (SusTech). IEEE, 2026.
31. Li, Y. Z., Zhang, J. P., Chen, Z. Y., Wang, H. C., Zhang, K. X., Hu, S. S., ... & Dudley, M. (2026, August). Growth and Characterization of High-Quality Thick Epitaxial 4H-SiC Wafers for High Voltage Devices. In Defect and Diffusion Forum (Vol. 452, pp. 79-85). Trans Tech Publications Ltd.
32. Lu, J., Fang, Y., Yang, X., Hu, W., Tuo, J., & Zhang, F. (2025). Modal Metamodeling-Based Uncertainty Propagation for Frequency Response in Non-Proportional Damping Systems. International Journal of Structural Stability and Dynamics, 2650279.
33. Yang, Y., Wang, Q., Li, C., Hu, H., Wu, C., Jiang, Y., ... & Xu, B. (2025, May). Fewer may be better: Enhancing offline reinforcement learning with reduced dataset. In International Conference on Learning Representations (Vol. 2025, pp. 7076-7098).
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[1] 1. Chen, B. L., Zhang, J. Y., Xu, W. J., Yan, S. Y., & Zhu, X. Q. (2025). Thermodynamic and kinetic studies of mononuclear non-heme high-valent (FeO) 2+ complexes. ACS omega, 10 (4), 3718.

[2] 2. Luan, S., Wang, P., Zhang, L., He, Y., Huang, X., Jian, G.,... & Fu, Z. (2023). Atmospherically hydrothermal assisted solid-state reaction synthesis of ultrafine BaTiO3 powder with high tetragonality. Journal of Electroceramics, 50 (4), 97-111.

[3] 3. Li, H., Zheng, T., Peng, Y., & BouDagher-Fadel, M. K. (2023). The fusulinids in a middle-late Permian carbonate platform (from Maokou to Wuchiapingian stage) in eastern Sichuan Basin, China. In Stratigraphy & Timescales (Vol. 8, pp. 413-435). Academic Press.

[4] 4. Pabon, J. J. G., Wang, J., Chamanehpour, E., Salami, D., & Khosravi, A. (2025). Dynamic integration of solar-powered hydrogen systems with fuel cells and district heating for green data centers. International Journal of Hydrogen Energy, 196, 152557.

[5] 5. Zhang, K. X., Chen, Z. Y., Hu, S. S., Zhang, J. P., Li, Y. Z., Wu, D. L., ... & Soukhojak, A. (2026, August). Observation and Analysis of the “Galaxy” Defect in 4H-SiC through X-Ray Synchrotron Topography. In Defect and Diffusion Forum (Vol. 452, pp. 73-78). Trans Tech Publications Ltd.

[6] 6. Luan, S., Si, S., Zhang, L., Wang, P., Jian, G., Yang, J.,... & Cao, X. (2023). Fabrication of BaTiO3 nanopowders with high tetragonality via two-step assisted rotary furnace calcination for MLCC applications. Ceramics International, 49 (8), 12529-12539.

[7] 7. Yang, Y., Hu, H., Li, W., Li, S., Yang, J., Zhao, Q., & Zhang, C. (2023, June). Flow to control: Offline reinforcement learning with lossless primitive discovery. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 9, pp. 10843-10851).

[8] 8. Yang, Y., Ma, X., Li, C., Zheng, Z., Zhang, Q., Huang, G., ... & Zhao, Q. (2021). Believe what you see: Implicit constraint approach for offline multi-agent reinforcement learning. Advances in Neural Information Processing Systems, 34, 10299-10312.

[9] 9. Lv, X., Liu, S., Wang, P., Mohammad-Rezaei Bidgoli, E., & Arefi, M. (2023). On the dynamics and wave propagation of reinforced composite nanosystem. Engineering with Computers, 39(1), 151-171.

[10] 10. Wang, Y., Lou, M., Liang, W., & Zhang, C. (2023). Numerical and experimental investigation on tensile fatigue performance of reinforced thermoplastic pipes. Ocean Engineering, 287, 115814.

[11] 11. Chen, Z. Y., Zhang, J. P., Hu, S. S., Zhang, K. X., Li, Y. Z., Wang, H. C., ... & Dudley, M. (2026, June). Investigation of Spoke Pattern of Stacking Faults in 4H-SiC Wafers Grown by Physical Vapor Transport Method. In Materials Science Forum (Vol. 1190, pp. 55-62). Trans Tech Publications Ltd.

[12] 12. Chen, B. L., Jing, S., & Zhu, X. Q. (2023). Thermodynamics Evaluation of Selective Hydride Reduction for α, β-Unsaturated Carbonyl Compounds. Molecules, 28 (6), 2862.

[13] 13. Hu S, Chen Z, Zhang K, et al. Stacking fault analysis for the early-stages of PVT growth of 4H-SiC crystals[J]. Journal of Crystal Growth, 2026, 681: 128523.

[14] 14. Chen, B. L., Yan, S. Y., & Zhu, X. Q. (2023). A Mechanism study of redox reactions of the ruthenium-oxo-polypyridyl complex.Molecules,28(11), 4401.

[15] 15. Ma, Y., & Qu, D. (2026). Machine Learning Based Markov Decision Framework for Optimizing Circular Economy Systems.Engineering Proceedings,120(1), 44.

[16] 16. Wang, X., Wang, P., Jiang, W., Wu, F., Kiani, M., & Arefi, M. (2021). Mathematical and computer simulation for Electro-Magneto-Thermo-Elastic Buckling of the Porous Nano system. Structural Engineering and Mechanics, 80(2), 231-242.

[17] 17. Wang, Y. Y., Lou, M., Wang, Y., Wu, W. G., & Yang, F. (2022). Stochastic failure analysis of reinforced thermoplastic pipes under axial loading and internal pressure. China Ocean Engineering, 36(4), 614-628.

[18] 18. Luan, S., Tang, M., Mu, H., Yu, J., Wang, P., & Zhang, L. (2025). A co-precipitation route to produce BaTiO3 nanopowders with high tetragonality for ultra-thin MLCCs application. Journal of Materials Science: Materials in Electronics, 36 (9), 526.

[19] 19. Liu, J., & Huang, Y. (2026). GBMP-LCA: A Gradient Boosting–Based Framework for Performance Prediction and Life-Cycle Optimization of Green Building Materials. Fundamental Scientific Reports in Multidisciplinary Areas, 2 (02), 193-204.

[20] 20. Lu, W., & Wang, J. (2025). Accumulated Performance Comparison of Solar PV and Solar Thermal Water Heating in New Zealand. Engineering Reports, 7(12), e70526.

[21] 21. Peng, Y., Li, H., BouDagher-Fadel, M., Wang, L., Zhang, D., Zheng, T., & Yang, K. (2022). Benthic foraminifera distribution and sedimentary environmental evolution of a carbonate platform: A case study of the Guadalupian (middle Permian) in eastern Sichuan Basin. Marine Micropaleontology, 170, 102079.

[22] 22. Zhu, Q., & Chen, H. (2025, August). Bias correction of wind forecasts from the noaa global ensemble forecast system (gefs) using machine learning. In IGARSS 2025-2025 IEEE International Geoscience and Remote Sensing Symposium (pp. 4637-4640). IEEE.

[23] 23. Wang, J. (2026). A comparative conceptual analysis of CO2 heat pump dryers with closed-loop and open-loop air cycles. Energy Conversion and Management, 352, 121093.

[24] 24. Zhou, X., Wang, P., Al-Dhaifallah, M., Rawa, M., & Khadimallah, M. A. (2022). A machine learning-based model for the estimation of the critical thermo-electrical responses of the sandwich structure with magneto-electro-elastic face sheet. Advances in nano research, 12(1), 81-99.

[25] 25. Yang, Z., Hu, D., Guo, Q., Zuo, L., & Ji, W. (2023). Visual E 2 C: AI-driven visual end-edge-cloud architecture for 6G in low-carbon smart cities. IEEE Wireless Communications, 30(3), 204-210.

[26] 26. Wan, H., Cheng, J., Deng, Y., Wu, D., Chen, Y., Lin, Z., ... & Ji, X. Towards Physics Aware Embodied Control with Graph based Object-centric Learning. ACM Transactions on Cyber-Physical Systems.

[27] 27. Chen, B., Hu, X., & Zhu, X. (2023). Essential Rule Derived from Thermodynamics and Kinetics Studies of Benzopyran Compounds.Molecules,28(24), 8039.

[28] 28. W. Zhang, "A 5-6 GHz PVT Robust Current Mode Passive Mixer for Direct Down-Conversion Receiver," in *2026 5th International Conference on Electronics, Integrated Circuits and Communication Technology (EICCT)*, 2026, pp. 420–424.

[29] 29. Li, X., Wang, P., Li, G., & Zhang, Y. (2023). Design of a novel self-test-on-chip interface ASIC for capacitive accelerometers. IEEE Transactions on Circuits and Systems I: Regular Papers, 70(7), 2834-2843.

[30] 30. Yao, Jingyu, et al. "Explainable AI Enhanced Traffic Forecasting for Proactive Autonomous Vehicle Routing." 2026 IEEE Conference on Technologies for Sustainability (SusTech). IEEE, 2026.

[31] 31. Li, Y. Z., Zhang, J. P., Chen, Z. Y., Wang, H. C., Zhang, K. X., Hu, S. S., ... & Dudley, M. (2026, August). Growth and Characterization of High-Quality Thick Epitaxial 4H-SiC Wafers for High Voltage Devices. In Defect and Diffusion Forum (Vol. 452, pp. 79-85). Trans Tech Publications Ltd.

[32] 32. Lu, J., Fang, Y., Yang, X., Hu, W., Tuo, J., & Zhang, F. (2025). Modal Metamodeling-Based Uncertainty Propagation for Frequency Response in Non-Proportional Damping Systems. International Journal of Structural Stability and Dynamics, 2650279.

[33] 33. Yang, Y., Wang, Q., Li, C., Hu, H., Wu, C., Jiang, Y., ... & Xu, B. (2025, May). Fewer may be better: Enhancing offline reinforcement learning with reduced dataset. In International Conference on Learning Representations (Vol. 2025, pp. 7076-7098).

[34] 34. Xiong, S., Chen, T., Rupendra, A., Clement, C., Gasparri, E., & Lucchi, E. (2026). Embodied Carbon of Progressive Timber Integration in a 47-Storey Tropical High-Rise: A Singapore Public Housing Case Study. Building and Environment, 114910.

[35] 35. Li, Y., Zhou, Y., Zhang, Y., Wang, P., Zhang, Y., Li, X., & Zhang, X. (2025). Nonvolatile Optical Switch With a Programmable pn Heterojunction.IEEE Transactions on Electron Devices,72(8), 4030-4035.