Professor, Department of Computational and Data Sciences
My research focuses on the discovery, interpretation, prediction, modeling, simulation, and organization of the microscopic interactions between atoms and molecules in condensed phases of matter and beyond. My research emphasizes the development of the next generation of atomistic and quantum models for simulation of matter, including bio-materials, soft and hard materials. The ability to predict properties of matter is a fundamental requirement of technological advances and economic competitiveness.
■ Insights of the solvent effect on a variety of solvated polymers through explicit modeling of the solvent and atomistic modeling of the polymers.
■ Discovery of the thermodinacs-structure relations in binary metal alloys, their heat of transformation along phase transitions.
■ Development of a variety of force fields for macromolecular systems.
■ Structural fingerprints of biomolecules through Molecular Dynamics and Machine Learning.
■ Interfacial phenomena between different polymers.
■ R. Handler, E. Blaisten-Barojas, P. M. Ligrani, P. Dong, M. Paige, Vortex Generation in a Finitely Extensible Nonlinear Elastic Peterkin Fluid Initially at Rest. Engineering Reports e12135 (2020). doi.org/10.1002eng2.12135
■ J. Andrews and E. Blaisten-Barojas, Exploring with Molecular Dynamics the Structural Fate of PLGA Oligomers in Various Solvents. Journal of Physical Chemistry B, 123, 10233-10244 (2019).
■ D. Reitz and E. Blaisten-Barojas, Simulating the NaK eutectic alloy with Monte Carlo and Machine Learning, Scientific Reports 9, 704 (2019).
■ G. Gogovi, F. Almsned, N. Bracci, K. Kehn-Hall, A. Shehu and E. Blaisten-Barojas, Modeling the Tertiary Structure of the Rift Valley Fever Virus L protein. Molecules 24, 1768 (2018).