Michael A. Webb

Position
Assistant Professor of Chemical and Biological Engineering
Office Phone
Assistant
Office
A325 Engineering Quad
Education

Ph.D., Chemical Engineering, California Institute of Technology, 2016

M.S., Chemical Engineering, California Institute of Technology, 2015

B.S., Chemical and Biomolecular Engineering, University of California – Berkeley, 2011

Advisee(s):
Bio/Description

Honors and Awards

  • ACS COMP OpenEye Cadence Molecular Sciences Outstanding Junior Faculty Award, 2025
  • CAREER Award, National Science Foundation, 2023
  • Howard B. Wentz, Jr. SEAS Junior Faculty Award, 2022
  • Herbert Newby McCoy Award, Division of Chemistry and Chemical Engineering, Caltech, 2016
  • Chemical Computing Group Excellence Award, American Chemical Society, 2016
  • Resnick Fellowship, Resnick Sustainability Institute, 2012-2014

Research Interests

The Webb Group utilizes theory and simulation to characterize, understand, and guide the design of novel soft materials for health and sustainability applications. Some of our current interests are motivated by the use of both natural and synthetic polymers in technologies like batteries, fuel cells, water treatment, tissue engineering, and drug-delivery. Thus, we aim to use predictive modeling frameworks to study aspects of charge-transport phenomena in polymeric media, stimuli-responsive behavior of biopolymer-based solutions/gels, and the interfacial physics/properties of polymer-composite materials.

We believe that polymer-based materials are exciting design platforms that offer the opportunity to achieve specific target functionality by tunably altering sub-unit chemistry, architecture, stimuli-response, and much more. These possibilities manifest as a complex, often unintuitive design space that is difficult to navigate using experiment alone, yet macromolecular systems can be challenging to describe using theory or simulation, particularly with any degree of chemical specificity. Consequently, we employ a range of computational approaches that are systematically linked to bridge the length- and timescales necessary to make chemically informed predictions on the behavior of soft and adaptive materials.

Our research balances a combination of fundamental mechanistic inquiry, methods development, and targeted design efforts. We are further interested in exploiting and adapting data-driven methodologies/machine learning techniques in these efforts.

Selected Publications
  1. M. A. Webb, Y. Jung, D. M. Pesko, U. Yamamoto, G. W. Coates, N. P. Balsara, Z.-G. Wang, T. F. Miller III. A Systematic Computational and Experimental Investigation of Lithium-ion Transport Mechanisms in Polyester-based Polymer Electrolytes. ACS Cent. Sci., 1, 198-205, 2015.
  2. M. A. Webb J.-Y. Delannoy, and J. J. de Pablo. Graph-based Approach to Molecular Coarse-graining. J. Chem. Theor. Comput., 15, 1199-1208, 2019.
  3. M. A. Webb, B. M. Savoie, Z.-G. Wang and T. F. Miller III. Chemically Specific Dynamic Bond Percolation Model for Ion Transport in Polymer Electrolytes. Macromolecules, 48, 7346-7358, 2015.
  4. M. A. Webb and T. F. Miller III. Position-Specific and Clumped Stable Isotope Studies: Comparison of the Urey and Path-Integral Approaches for Carbon Dioxide, Nitrous Oxide, Methane, and Propane. J. Phys. Chem. A, 118, 467-474, 2014.
  5. M. A. Webb, U. Yamamoto, B. M. Savoie, Z.-G. Wang, T. F. Miller III. Globally suppressed dynamics in ion-doped polymers. ACS Macro Lett., 7, 6, 734-738, 2018.