Contact InfoGeoChem 247Email[email protected] ProfileRubenstein Lab Webpage
For decades, quantum chemists have been forced to make an oftentimes humbling choice in their day-to-day work: to use highly accurate, many-body methods that are too slow to apply to realistic quantum systems, or, to use faster one-body methods that are significantly less accurate. This fundamental compromise has glaringly limited the impact of quantum chemistry. Indeed, while most of modern experimental chemistry is focused upon synthesizing complex molecules and designing novel nano- and bulk materials, most modern quantum chemistry techniques are hard-pressed to even approach the scales necessary to answer many of the most pivotal experimental questions about these systems. The Rubenstein group is focused on developing electronic structure methods that are at once highly accurate and scale well with system size to help bridge this divide and enable theory-driven materials design. The Rubenstein group also actively conducts research in the areas of molecular/quantum computing and computational biophysics.
Areas of Interest
- Theoretical quantum chemistry and physics
- Stochastic methods for electronic structure theory
- Strongly correlated and relativistic materials
- Quantum computing
- Actinide structure and transport
- Molecular computing
- Computational biophysics
- 2013 - Ph.D.: Columbia University
- 2008 - M.Phil.: University of Cambridge
- 2007 - Sc.B.: Brown University
Tang, W.-S., Monteiro da Silva, G., Kirveshlahti, H., Skeens, E., Feng, B., Sudijono, T., Yang, K., Mukherjee, S., Rubenstein, B.M., and L. Crawford (Dual Corresponding Authors). A Topological Data Analytic Approach for Discovering Biophysical Signatures in Protein Dynamics. PLoS Comput Biol. 18(5): e1010045 (2022). bioRXiv:10.1101/2021.07.28.454240
Staros, D., Hu, G., Nanguneri, R., Krogel, J., Bennett, M.C., Heinonen, O., Ganesh, P., and B.M. Rubenstein. A Combined First Principles Study of the Structural, Magnetic, and Phonon Properties of Monolayer CrI3. J. Chem. Phys. 156, 014707 (2022).
Arcadia, C., Dombroski, A., Oakley, K., Chen, S.-L., Tann, H., Rose, C., Kim, E., Reda, S., Rubenstein, B.M., and J. Rosenstein. Leveraging Autocatalytic Reactions for Chemical Domain Image Classification. Chem. Sci., 12, 5464 (2021). 2021 Chemical Science HOT Article.
Liu, Y., Zhu, G.-Z., Yuan, D.-F., Qian, C.-H., Zhang, Y.-R., Rubenstein, B.M., and L.-S. Wang. Observation of a Symmetry-Forbidden Excited Quadrupole-Bound State. J. Am. Chem. Soc., 142 (47), 20240 (2020).
Arcadia, C., Kennedy, E., Geiser, J., Dombroski, A., Oakley, K., Chen, S.L., Sprague, L., Sello, J., Weber, P., Reda, S., Rose, C., Kim, E., Rubenstein, B. M., and Rosenstein, J. K. Multicomponent Molecular Memory. Nature Communications, 11, 691 (2020).