UMass Boston

Jason R. Green

Assistant Professor of Chemistry
University of Massachusetts Boston
jason dot green at umb dot edu

News | Publications | Funding | Open positions

Research in our group focusses on solving theoretical and computational problems related to the molecular scale transport of matter and energy. We are constructing new methods to characterize, understand, and control the dynamical processes of complex systems evolving far from thermodynamic equilibrium.

We have openings for graduate students and postdoctoral researchers.

Current graduate students

Helen Cuiyun Zhao - Chemistry
Lucas Newcomb - Chemistry

Current undergraduate students

Shane Flynn (Beacon fellow) - Chemistry/Biology
Jonathan Nichols - Chemistry
Will Fatherley - Biochemistry

Fluctuating and disordered rate processes
Kinetics provides predictions about how fast a particular process will happen - its rate. For example, predicting the rate of making and breaking hydrogen bonds in liquid water can give insight into the role of this process in the function of biomolecules. Many such processes present a theoretical challenge to kinetics because of the intrinsic fluctuations in the rate caused by the surrounding environment; the interaction between two water molecules sensitively depends on the proximity, geometry, and behavior of the water molecules surrounding them. We are designing a general theoretical framework that applies to this broad class of rate processes, including water. This framework is being implemented as a computational algorithm to analyze the results of both computer simulations and laboratory experiments.

Measuring disorder in irreversible decay processes
S.W. Flynn, H.C. Zhao, J.R. Green, J. Chem. Phys. 2014 in press

Statistical dynamics of mixing liquids
Natural phenomena mix matter, energy or both. The mixing of liquids is particular important; it is responsible for the molecular structure and function of biological cells, the production and processing of everyday products, and the yield of chemical reactions. For liquids that are sufficiently alike, thermodynamics makes predictions about whether the liquids will mix. However, the entropy associated with the interdiffusion of liquids is difficult to estimate, say, from molecular simulations, especially if the liquids are dissimilar or the mixing requires heat transfer. We have developed theory and computational strategies that enable the direct calculation of statistical entropy changes from the underlying molecular dynamics involved in mixing two liquids. These entropy changes are related to dynamical randomness and, yet, are consistent with the thermodynamic entropy of mixing.