Mohammed Zikry

Zan Prevost Smith Professor

Mohammed A. Zikry is the Zan Prevost Smith Professor at North Carolina State University in the Department of Mechanical and Aerospace Engineering. He received his Ph.D. from the University of California, San Diego, his M.S. from the Johns Hopkins University, and his B.S. from the University of Kansas.

Amongst his recent awards, he has received the Jefferson Science Award as a senior science advisor to the U.S. State Department, Senior Research Fulbright Award to Egypt and France, the ALCOA Distinguished Research Award, the Research Excellence Award (NCSU) and the Ralph Teetor Research Award from the Society of Automotive Engineering.

He has been awarded a Professeur, Premiere Classe, Strasbourg University, and he is also a Fellow of the American Society of Mechanical Engineering (ASME), the Regional Editor for Mechanics of Materials, and is co-chair of the Executive Committee of ASME’s National Materials Division. He has been a senior research advisor to the Army Research Office and the Department of Defense, and a consultant to numerous industries and organizations.

Click here to view details about Dr. Zikry’s Grants

Publications

A fundamental understanding of how dislocation densities affect strain hardening behavior in copper single crystalline micropillars
Xie, D., Chen, M.-J., Gigax, J., Luscher, D., Wang, J., Hunter, A., … Li, N. (2023), MECHANICS OF MATERIALS, 184. https://doi.org/10.1016/j.mechmat.2023.104731
A machine learning microstructurally predictive framework for the failure of hydrided zirconium alloys
Hasan, T., Capolungo, L., & Zikry, M. (2023), NPJ MATERIALS DEGRADATION, 7(1). https://doi.org/10.1038/s41529-023-00344-7
Dislocation-density evolution and pileups in bicrystalline systems
Chen, M.-J., Xie, D., Li, N., & Zikry, M. A. (2023), MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 870. https://doi.org/10.1016/j.msea.2023.144812
How can machine learning be used for accurate representations and predictions of fracture nucleation in zirconium alloys with hydride populations?
Hasan, T., Capolungo, L., & Zikry, M. A. (2023), APL MATERIALS, 11(7). https://doi.org/10.1063/5.0155679
Precipitate and dislocation-density interactions affecting strength and ductility in inconel alloys
Arcari, A., Horton, D., Chen, M.-J., & Zikry, M. A. (2023, August 16), JOURNAL OF MATERIALS SCIENCE, Vol. 8. https://doi.org/10.1007/s10853-023-08822-8
Predicting and Controlling Ribbing Instabilities of Carbon Nanotube-PDMS Thin-Film Systems for Multifunctional Applications
Phillips, M., Chen, M.-J., Islam, M. D., Ryu, J., & Zikry, M. (2023, July 19), ADVANCED ENGINEERING MATERIALS, Vol. 7. https://doi.org/10.1002/adem.202300582
Predicting and Controlling Ribbing Instabilities of Carbon Nanotube–PDMS Thin‐Film Systems for Multifunctional Applications
Phillips, M., Chen, M.-J., Islam, M. D., Ryu, J., & Zikry, M. (2023), Advanced Engineering Materials. https://doi.org/10.1002/adem.202370077
Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys
Hasan, T., Capolungo, L., & Zikry, M. A. A. (2023), SCIENTIFIC REPORTS, 13(1). https://doi.org/10.1038/s41598-023-32582-9
The Fiftieth Anniversary of the Founding of the ASME Journal of Engineering Materials and Technology
Zikry, M. A. (2023, July 1), JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY-TRANSACTIONS OF THE ASME, Vol. 145. https://doi.org/10.1115/1.4062506
Coupled electromagnetic and mechanical modeling and detection of buried objects
Elbadry, M., Wetherington, J., & Zikry, M. A. (2022), Applications in Engineering Science, 10. https://doi.org/10.1016/j.apples.2022.100106

View all publications via NC State Libraries

Mohammed Zikry