Scott Auerbach

Photo of Prof. Scott Auerbach
Professor in Chemistry

222 Goessmann Laboratory
(413) 545-1240

Chemical Energy
Theoretical Computational
Computational Materials Science
NSF Postdoc. University of California at Santa Barbara; 1994-1995; Ph.D. University of California at Berkeley, 1993; B.S. Georgetown University, 1988 Summa cum Laude
Principal Research Interests: 

Modeling catalysts and materials for sustainability is the focus of my research group. We are developing and applying simulation methods to model self-assembly of nanoporous materials such as zeolites, and the dynamics of organic molecular transformations within zeolite nanopores. We are also developing data science approaches for understanding the fantastic complexity of crystal formation, and for ranking the synthesizability of hypothetical materials. Our ultimate goal is to shed light on the "atomic dance" underlying complex chemical transformations, and to assist in the design of new materials with advanced properties for a sustainable future.

SimulatiZeolite faujasiteng Self-Assembly of Nanoporous Materials

In collaboration with Wei Fan (UMass Amherst Chemical Engineering), we are unraveling the dynamics and thermodynamics of zeolite crystal formation using advanced DFT and Monte Carlo algorithms. We have recently revealed the structure-directing and charge-balancing roles of fluoride in zeolite formation, and have discovered how using multiple organic structure-directing agents can greatly accelerate zeolite crystal formation. Future work involves developing Monte Carlo methods to overcome crystallization barriers, and applying data science to shed light on complex crystallization pathways.

Data Science of Nanoporous Materials

Crystallization pathways, complex chemical transformations, ranking synthesizability of hypothetical materials -- what do they all have in common? Two things: great complexity and big data. In collaboration with Michele Ceriotti (EPFL, Materials) and Rocio Semino (Sorbonne, Chemistry), we are applying rigorous data science methods to tackle problems in this space, including developing a new visual atlas of zeolite structure types ("cloud atlas"), and sorting real and hypothetical zeolites to rank synthesizability of new materials ("sorting hat"). Our future work in data science will go wherever the complexity and big data take us!

SKinetic and Thermodynamic Control of Zeolite Catalysis

In collaboration with Friederike Jentoft (UMass Amherst, Chemical Engineering), we are combining DFT and experimental spectroscopy to observe how important organic transformations occur in zeolite catalyst nanopores. We are focusing on organic cations forming in acidic zeolites, and how they cyclize to form precursors of both biofuels (desired products) and coke (undesired byproducts that poison zeolite catalysts). Our most recent work simulates the interplay of kinetic vs. thermodynamic control of these reactions, finding strong kinetic control in more confining pore environments.