MDLab: AI frameworks for Carbon Capture and Battery Materials

Abstract

Practical applications of carbon capture by sorbents and membranes require broad knowledge of chemical and material properties. Appropriate sorbents must have high CO2 capacity and low regeneration energy to be cost effective, and high selectivity for CO2 over other molecules. Also for battery applications, the chemical and materials properties of electrolytes are important as the storage industry scales up. IBM’s MDLab is a software stack for Materials Discovery that uses AI to screen for carbon capture and battery materials based on measured and computed properties1. Examples of MDLab use are given here.