Professor Laura Gagliardi

Project Title: 
Modeling Catalysis and Gas Separation in Metal Organic Frameworks, Actinide Chemistry, and Development of Machine-Learning Algorithms and Efficient Multireference Methods for Quantum Chemistry

This group investigates chemical systems and materials containing transition metals and heavier atoms like lanthanides and actinides with quantum chemical methods and molecular simulation methods. Over the years, these researchers have acquired an expertise in developing and applying quantum chemical methods for the study of such systems. They are also using machine learning and data science tools to screen porous materials such as metal organic frameworks for water harvesting and catalysis. This work is strongly connected with experimental work in the sense that it both inspire possible future experiments, and it confirms and/or refines existing experimental results.

MSI resources are used to perform calculations on the following chemical- and material-related challenges:

  • Gas adsorption and separation in porous materials
  • Catalysis in metal organic frameworks
  • Actinide and lanthanide chemistry
  • Molecular photocatalysts
  • Modeling charge and exciton dynamics in solar cell material
  • Discovery of new magnetic materials for quantum computing
  • Development of novel multireference methods

The group employs various software packages available through MSI.

This group's work was featured on the MSI website in October 2016: A New Method for Creating a Catalyst on a Metal-Organic Framework.

Project Investigators

Saumil Chheda
Yogev Gluzman
Soumi Haldar
Bhavnesh Jangid
Daniel King
Abhishek Mitra
Hung Pham
Debmalya Ray
Jacob Schaffner
Thais Scott
Prachi Sharma
Matt Simons
Jenny G Vitillo
Benjamin Yeh
 
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