- Mannodi-Kanakkithodi, A.*, Xiang, X.*, Jacoby, L*., Biegaj, R., Dunham, S. T., Gamelin, and D. R., Chan, M. K. 2022. Universal machine learning framework for defect predictions in zinc blende semiconductors. Patterns. 3(3), 100450. (* Equal contribution) [pdf]
- Xiang, X., Sommer, D. E., Gehrke, A., and Dunham, S. T. 2021. Coupled process and device modeling of Cu(In,Ga)Se2 solar cells. IEEE 48th Photovoltaic Specialists Conference (PVSC). pp. 1707-1711. [pdf]
- Mannodi Kanakkithodi, A. K., Xiang, X., Yang, J., Jacoby, L., & Chan, M. 2022. Machine Learning Defect Properties of Semiconductors. Bulletin of the American Physical Society. [link]
- Su, J., Xiang, X., Lv, R., Li, H., Fu, X., Yang, B., and Liu, X. 2018. Rapid and high-selectivity detection of rifampicin based on upconversion luminescence core-shell structure composites. Journal of Solid State Chemistry, 266, 9-15. [pdf]
- Xiang, X., Sommer, D. E., Gehrke, A., and Dunham, S. T. Coupled process/device modeling and point defect engineering of Cu(In,Ga)Se2 solar cells. (In Preperation)
- Gehrke, A., Sommer, D. E., Xiang, X. and Dunham, S. T. Atomistic models of In and Ga Diffusion in Cu(In,Ga)Se2. (In Preperation)
