Dr. Majid Shahbabaei | Oden Institute for Computational Engineering and Sciences | United States
Majid Shahbabaei is a computational materials theorist whose research focuses on advancing clean water, clean energy, and environmental sustainability through molecular-level investigation of transport phenomena in soft and nanostructured materials. He employs molecular dynamics simulations, density functional theory, and multi-physics modeling to uncover the mechanisms governing ion separation, water purification, nanopore transport, and electrochemical processes. His work spans membrane desalination, reverse electrodialysis energy harvesting, heavy-metal removal, lithium-ion recovery, gas separation, and protein sequencing using solid-state nanopores. Shahbabaei has made significant contributions to understanding transport in graphene-based membranes, polymer-derived carbon membranes, covalent- and metal–organic framework membranes, and zwitterion-functionalized nanopores. His research bridges materials science, nanofluidics, biophysics, and computational chemistry to provide design principles for next-generation membranes and electrochemical systems. He has published extensively on aquaporin-inspired channels, ion selectivity in functionalized membranes, and confined fluid behavior in low-dimensional systems. His studies also explore self-healing polymer electrodes, COF/MOF hybrid architectures, and hydration-driven ion transport in graphene oxide nanochannels. Shahbabaei’s work combines theoretical modeling with experimental frameworks to enhance water and energy technologies. He has collaborated internationally on projects in wastewater purification, thin-film nanocomposite membranes, and battery material recovery. Supported by competitive research grants, he leads in computational approaches for sustainable membrane and energy design. His contributions provide fundamental insights into fluid transport, interfacial interactions, and multi-physics behavior in nanostructured materials. By integrating theory and simulation, his research guides the development of efficient, high-performance filtration and separation systems. His interdisciplinary approach addresses urgent environmental and health challenges. Through innovative computational strategies, Shahbabaei continues to influence the design of advanced materials for energy, water, and environmental applications. His work demonstrates a vision for sustainable technologies grounded in molecular-level understanding and predictive modeling.
Profiles: Scopus | Google Scholar
Featured Publication
Saedodin, S., & Shahbabaei, M. (2013). Thermal analysis of natural convection in porous fins with homotopy perturbation method (HPM). Arabian Journal for Science and Engineering, 38(8), 2227–2231.
Shahbabaei, M., & Kim, D. (2017). Molecular dynamics simulation of water transport mechanisms through nanoporous boron nitride and graphene multilayers. The Journal of Physical Chemistry B, 121(16), 4137–4144.
Shahbabaei, M., Tang, D., & Kim, D. (2017). Simulation insight into water transport mechanisms through multilayer graphene-based membrane. Computational Materials Science, 128, 87–97.
Shahbabaei, M., & Kim, D. (2017). Transport of water molecules through noncylindrical pores in multilayer nanoporous graphene. Physical Chemistry Chemical Physics, 19(31), 20749–20759.
Shahbabaei, M., & Kim, D. (2021). Advances in nanofluidics for water purification and filtration: Molecular dynamics (MD) perspective. Environmental Science: Nano, 8(8), 2120–2151.