Surfaces with the same chemical composition but different chemical patterns can have widely varying hydrophobicities.
The group in 2025. All group photos
Our research strives to achieve a molecular-level understanding of solvation and transport in aqueous and polymeric systems, with applications ranging from the prediction of protein interactions to the design of advanced materials for water purification and renewable energy.
To study these biological, nanoscopic, and polymeric systems, our group combines principles of statistical mechanics and liquid state theory with state-of-the-art molecular modeling and atomistic simulation techniques. We interface closely with experimentalists, both to realize our predictions and to refine our theoretical models.
Paper in PNAS
Interpretable machine learning models which incorporate chemical correlations between surface groups accurately predict the hydrophobicities of patterned surfaces.
Response of protein hydration waters to an unfavorable potential informs protein interaction interfaces.
Rationally-designed surface capable of spontaneously recovering its superhydrophobicity.
Characterizing surface wetting and interfacial properties using enhanced sampling.
Recent Publications
View allBall, R., Johnson, C. W., Zhang, L., Hopkins, R. N., Hwang, J., Winey, K. I., Patel, A. J., Osuji, C. O., & Anna, J. M. (2026). Correlating solvation shell dynamics and ion transport in highly ordered nanoporous polymers. Nature Communications. https://doi.org/10.1038/s41467-026-73642-8
Cai, Y., & Patel, A. J. (2026). Engineering Antifreeze Proteins to Optimally Resist Engulfment by Ice. The Journal of Physical Chemistry B, 130(19), 5106–5116. https://doi.org/10.1021/acs.jpcb.6c01236
Tu, W., Theisen, R. Q., Jin, P., Chenoweth, D. M., Patel, A. J., & Good, M. C. (2026). Delivery of peptide coacervates to form stable interaction hubs in cells. Nature Communications, 17(1), 2250. https://doi.org/10.1038/s41467-026-68793-7
Jiang, Z., Vicars, Z., Fialoke, S., Jamadagni, S. N., Koenig, P. H., & Patel, A. J. (2025). Thermodynamics of Self-Assembly and Supramolecular Transitions Using Enhanced Sampling. Langmuir, 41(23), 14656–14668. https://doi.org/10.1021/acs.langmuir.5c00114
Kim, B. Q., Vicars, Z., Füredi, M., Escobedo, L. F., Venkatesh, R. B., Guldin, S., Patel, A. J., & Lee, D. (2025). Amphiphilic nanopores that condense undersaturated water vapor and exude water droplets. Science Advances, 11(21), eadu8349. https://doi.org/10.1126/sciadv.adu8349
Johnson, C. W., Zhang, L., Culley, K. E., Oh, S. M., Gin, D. L., Geise, G. M., Patel, A. J., Winey, K. I., & Osuji, C. O. (2025). The Effects of Morphology and Hydration on Anion Transport in Self-Assembled Nanoporous Membranes. ACS Nano, 19(2), 2559–2569. https://doi.org/10.1021/acsnano.4c14234
Sudarshan, V., Seider, W. D., Patel, A. J., Oktem, U. G., & Arbogast, J. E. (2024). Path-Sampling and Machine Learning for Rare Abnormal Events: Application to Polymerization CSTRs. Chemical Engineering Science, 300, 120513. https://doi.org/10.1016/j.ces.2024.120513
Vicars, Z., Choi, J., Marks, S. M., Remsing, R. C., & Patel, A. J. (2024). Interfacial Ice Density Fluctuations Inform Surface Ice-Philicity. The Journal of Physical Chemistry B, 128(35), 8512–8521. https://doi.org/10.1021/acs.jpcb.4c03783
Thosar, A. U., Cai, Y., Marks, S. M., Vicars, Z., Choi, J., Pallath, A., & Patel, A. J. (2024). On the engulfment of antifreeze proteins by ice. Proceedings of the National Academy of Sciences, 121(24), e2320205121. https://doi.org/10.1073/pnas.2320205121
Sudarshan, V., Seider, W. D., Patel, A. J., Oktem, U. G., & Arbogast, J. E. (2024). Alarm rationalization and dynamic risk analyses for rare abnormal events. Computers & Chemical Engineering, 184, 108633. https://doi.org/10.1016/j.compchemeng.2024.108633