Publications, Activities, and Awards

  • Analysis of a Batch Adsorber Analogue for Rapid Screening of Adsorbents for Postcombustion CO2 Capture
  • Bridging molecular properties to systems level indicators for adsorbent based post-combustion carbon capture using machine learning
  • Evaluation of diamine-appended metal-organic frameworks for post-combustion CO2 capture by vacuum swing adsorption
  • Evaluation of diamine-appended metal-organic frameworks for postcombustion CO2 capture by vacuum swing adsorption
  • Experimental validation of multi-objective optimization techniques for design of vacuum swing adsorption processes
  • Experimentally validated machine learning frameworks for accelerated prediction of cyclic steady state and optimization of pressure swing adsorption processes
  • Improving the performance of vacuum swing adsorption based CO2 capture under reduced recovery requirements
  • Machine Learning and Models: How we find optimal materials for Solar and CCS technologies
  • Machine Learning-Based Multiobjective Optimization of Pressure Swing Adsorption
  • Measurement of competitive CO2 and H2O adsorption on zeolite 13X for post-combustion CO2 capture
  • Measurement of competitive CO2 and N2 adsorption on Zeolite 13X for postcombustion CO2 capture
  • Prediction of MOF performance in Vacuum-Swing Adsorption systems for post-combustion CO2 capture based on integrated molecular simulation, process optimizations, and machine learning models
  • Process Optimization-Based Screening of Zeolites for Post-Combustion CO2 Capture by Vacuum Swing Adsorption
  • Reduced-order modelling of Pressure-swing adsorption processes for Pre-combustion CO2 capture