Polymer Informatics

A polymer property prediction platform (Polymer Genome), powered by machine learning, experimental data, and density functional theory computations





Polymer Complexity – Chemical & Morphological

Determination of the relationship between chemical/morphological complexity of polymers and their properties, using molecular dynamics, density functional theory and machine learning





Dielectric Aging & Breakdown

A multi-scale approach to model electric field-dependent defect formation and carrier transport in polymers leading to dielectric degradation and breakdown





Machine Learning Force Fields (AGNI)

A machine learning platform to predict atomic forces rapidly and accurately purely from atomic configurations and reference DFT data






Machine Learning Density Functional Theory (ML-DFT)

A machine learning platform to rapidly and accurately predict charge density, density of states, and other derived properties purely from atomic configurations and reference DFT data





Polymer Battery Electrolytes

Molecular mechanics, density functional theory, and machine learning to accelerate the rational design of polymer electrolytes for solid-state batteries





Khazana: The Group’s Materials Informatics Repository

User-friendly & searchable repository of downloadable published computational data and general purpose machine learning utilities from the Ramprasad Group




Recyclable Polymers

Identifying fundamental mechanisms that control chemical and photo-thermo-mechanical (in)stability of polymers to achieve goals of resilience and recyclability/reprocessability