Srikanth Patala

Adjunct Assistant Professor

Research will be focused on developing computational and analytical techniques to quantify the structure-property relationships in complex heterogeneous materials. Specific areas of interest currently include the analysis of interfacial properties; the role of interfaces in influencing the mechanical and transport-related phenomena in structural materials; statistical analysis and characterization of complex microstructures. We utilize state-of-art experimental techniques to quantify 3D microstructural features and incorporate these aspects in a variety of computational methods to facilitate more accurate modeling of both processing-structure and structure-property relationships. These characterization and computational methods will provide essential tools, which are expected to be an integral part of the design process involved in microstructure optimization.

Dr. Patala’s research interests include structural characterization and quantification of structure-property relationships across multiple length scales; statistical analysis of defects and their interactions in polycrystalline materials; and in developing inverse design principles for optimizing performance in structural and functional materials.


Implications of gnomonic distortion on electron backscatter diffraction and transmission Kikuchi diffraction
Fancher, C. M., Burch, M. J., Patala, S., & Dickey, E. C. (2022, January 4), JOURNAL OF MICROSCOPY, Vol. 1.
A phase-field approach for modeling equilibrium solute segregation at the interphase boundary in binary alloys
Kadambi, S. B., Abdeljawad, F., & Patala, S. (2020), Computational Materials Science, 175, 109533.
Application of Monte Carlo techniques to grain boundary structure optimization in silicon and silicon-carbide
Guziewski, M., Banadaki, A. D., Patala, S., & Coleman, S. P. (2020), Computational Materials Science, 182, 109771.
Interphase boundary segregation and precipitate coarsening resistance in ternary alloys: An analytic phase-field model describing chemical effects
Kadambi, S. B., Abdeljawad, F., & Patala, S. (2020), Acta Materialia, 197, 283–299.
Quantum Materials for Energy-Efficient Computing
Chowdhury, S., Zhuang, H., Coleman, S., Patala, S., & Bair, J. (2020, September), JOM, Vol. 72, pp. 3147–3148.
Quantum Materials for Energy-Efficient Computing (vol 72, pg 3147, 2020)
Chowdhury, S., Zhuang, H., Coleman, S., Patala, S., & Bair, J. (2020, December), JOM, Vol. 72, pp. 4721–4721.
Vacancy diffusion in multi-principal element alloys: The role of chemical disorder in the ordered lattice
Thomas, S. L., & Patala, S. (2020), Acta Materialia, 196, 144–153.
Short-range order structure motifs learned from an atomistic model of a Zr50Cu45Al5 metallic glass
Maldonis, J. J., Banadaki, A. D., Patala, S., & Voyles, P. M. (2019), ACTA MATERIALIA, 175, 35–45.
Understanding grain boundaries - The role of crystallography, structural descriptors and machine learning
Patala, S. (2019), COMPUTATIONAL MATERIALS SCIENCE, 162, 281–294.
An efficient Monte Carlo algorithm for determining the minimum energy structures of metallic grain boundaries
Banadaki, A. D., Tschopp, M. A., & Patala, S. (2018), COMPUTATIONAL MATERIALS SCIENCE, 155, 466–475.

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Srikanth Patala