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The Overview

Our research program marries physical organic chemistry techniques and data science to develop new reactions with broad applications; from enantioselective synthesis, to energy-related topics,  to biologically-inspired reactions.  Our unique approach to data chemistry not only enables reaction design in the areas described above but ultimately helps scientists understand the fundamental guiding principles by which the performance of these reactions is achieved by relating structure to function. 

Members of the Sigman group learn and develop mastery in multidisciplinary fields through a wide variety of internal and external collaborations. A culture of scientific diversity and creativity drives our innovative research, but this culture is only maintained by consistent efforts to promote diversity, equity, and inclusion. Members of the Sigman group are committed to these efforts and our continued growth as scientists and human beings. Everyone is welcome as we continue to create an inclusive culture where all forms of diversity are seen as an added value to the advancement of science and for society. 


Data Chemistry

At the heart of what we study are the driving forces behind reaction performance. To accomplish this, we integrate classical physical organic chemistry techniques with data science to interrogate complex relationships between structure and function.  

We often employ Multivariate Linear Regression (MLR) techniques, as well as threshold analysis, decision trees, and other machine learning, statistical analysis, and data science tools to relate computationally-measured properties of reaction components (catalysts, reagents, enzymes, etc.) to measured observables (e.g., %e.e., regioselectivity, rates). These techniques are utilized in nearly every project in the lab. 

In the Center for Computer-Assisted Synthesis (C-CAS) and the Center for Selective C-H Functionalization (CCHF), we deploy our workflows in collaborative efforts to understand catalysis and improve synthesis. Current research spans a wide variety of projects, including: 

  • Predicting and analyzing biocatalyst selectivity

  • New catalyst and ligand design in the CCHF

  • Understanding solubility of flow battery analytes

  • Development of high energy density materials for batteries

  • Probing reaction mechanism in metal-mediated reactions


Our lab is interested in utilizing electrochemical techniques to develop new reaction methodology. This strategy replaces chemical oxidants/reductants with an electrode to tune the reaction potential for a desired transformation. Developing a fundamental understanding of electrochemical processes can allow for the design of highly active catalytic materials.

In the Joint Center for Energy Storage Research (JCESR), we combine electrochemical techniques with multidimensional modeling strategies to design highly stable redox active species that can be used as anolyte/catholyte materials in redox flow batteries. Some specific current areas of study include:  

  • New materials for redox flow batteries

  • Applying multivariate modeling techniques to predict electrochemical outcomes


Enantioselective Catalysis

Using multivariate linear regression techniques, we can identify statistically significant correlations to validate, and more importantly, predict a reaction’s outcome. This type of approach can be critical to probe a reaction mechanism and inform the design of superior-performing catalysts. We have initiated a program that unites optimization with mechanistic interrogation by correlating reaction outputs (e.g., enantio, site, or chemoselectivity) with structural descriptors of the reagents, substrates and catalysts involved. Current projects in this area include:  

  • Physical Organic Chemistry in Catalyst Design using Multidimensional Optimization

  • Utilizing Classic and Modern Physical Organic Tools in Design of Experiments

  • Parameterization of Ligands for Asymmetric Catalysis (pyrox, box, chiral phosphoric acids, etc.)

  • Mechanistic Investigations to Elucidate Non-Covalent Interactions

  • Prediction of Reaction Outcome Through Ligand Library Virtual Screening

  • New catalyst and ligand design in the CCHF

  • Developing new optimization tools with the potential to interrogate reaction mechanism

  • Exploring the origins of reagent, substrate, and catalyst control in site selective reactions 

Active Collaborations

As an interdisciplinary lab that believes cultivating and maintaining a positive, highly collaborative environment is crucial to driving scientific innovation, we collaborate extensively with other academic groups, pharmaceutical companies, and organizations.

Active collaborations include: 

​Pharmaceutical Companies

  • Pfizer

  • Novartis Institute of Biomedical Research

  • GlaxoSmithKline

  • Merck

  • Genentech

  • Bayer


Academic Collaborations 

  • Song Lin, Cornell 

  • Scott Miller, Yale

  • Todd Hyster, Cornell, 

  • David Sherman, University of Michigan

  • Melanie Sanford, University of Michigan 

  • Robert Paton, Colorado State University

  • Alán Aspuru-Guzik, University of Toronto

  • Steve Buchwald, MIT 

  • Rashad Karimov, Auburn

  • Neil Garg, UCLA

  • Richmond Sarpong, UC Berkeley

  • Hosea Nelson, Caltech

  • Mike Rosen, UT Southwestern

  • Rob Knowles, Princeton

  • Shelley Minteer, University of Utah

  • Sarah Reisman, Caltech

  • Phil Baran, Scripps

  • Dean Toste, UC Berkeley

  • Lucas Souza, UC Davis

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