Publications, Activities, and Awards
- Bridging molecular properties to systems level indicators for adsorbent based post-combustion carbon capture using machine learning
- Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes
- Cost Limits of Pressure-Vacuum Swing Adsorption for Post-Combustion CO2 Capture
- How much can novel solid sorbents reduce the cost of post-combustion [formula omitted] capture? A techno-economic investigation on the cost limits of pressure–vacuum swing adsorption
- Hybrid-AI Based Modelling of Pressure Swing Adsorption
- Machine Learning and Models: How we find optimal materials for Solar and CCS technologies
- Machine learning-based design and techno-economic assessments of adsorption processes for CO2 capture
- Physics-Based Neural Networks for Simulation and Synthesis of Cyclic Adsorption Processes
- 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
- Reduced-order modelling of Pressure-swing adsorption processes for Pre-combustion CO2 capture
- Techno-economic assessment of optimised vacuum swing adsorption for post-combustion CO2 capture from steam-methane reformer flue gas
- Technoeconomic Assessment of Optimized Adsorption Processes for Post-Combustion CO2 Capture in Hydrogen Plants