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Gokul Subraveti
Gokul Subraveti
SINTEF Energy Research
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Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)–a state-of-the-art review
Y Yan, TN Borhani, SG Subraveti, KN Pai, V Prasad, A Rajendran, ...
Energy & Environmental Science 14 (12), 6122-6157, 2021
1762021
Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Postcombustion CO2 Capture Based on Integrated Molecular Simulations, Process …
TD Burns, KN Pai, SG Subraveti, SP Collins, M Krykunov, A Rajendran, ...
Environmental science & technology 54 (7), 4536-4544, 2020
1732020
Techno-economic assessment of optimised vacuum swing adsorption for post-combustion CO2 capture from steam-methane reformer flue gas
SG Subraveti, S Roussanaly, R Anantharaman, L Riboldi, A Rajendran
Separation and Purification Technology 256, 117832, 2021
1252021
Machine learning-based multiobjective optimization of pressure swing adsorption
SG Subraveti, Z Li, V Prasad, A Rajendran
Industrial & Engineering Chemistry Research 58 (44), 20412-20422, 2019
1042019
Cycle design and optimization of pressure swing adsorption cycles for pre-combustion CO2 capture
SG Subraveti, KN Pai, AK Rajagopalan, NS Wilkins, A Rajendran, ...
Applied energy 254, 113624, 2019
932019
How much can novel solid sorbents reduce the cost of post-combustion CO2 capture? A techno-economic investigation on the cost limits of pressure–vacuum swing adsorption
SG Subraveti, S Roussanaly, R Anantharaman, L Riboldi, A Rajendran
Applied Energy 306, 117955, 2022
712022
Improving the performance of vacuum swing adsorption based CO2 capture under reduced recovery requirements
RT Maruyama, KN Pai, SG Subraveti, A Rajendran
International Journal of Greenhouse Gas Control 93, 102902, 2020
582020
Is Carbon Capture and Storage (CCS) Really So Expensive? An Analysis of Cascading Costs and CO2 Emissions Reduction of Industrial CCS Implementation on …
SG Subraveti, E Rodríguez Angel, A Ramírez, S Roussanaly
Environmental Science & Technology 57 (6), 2595-2601, 2023
462023
Physics-based neural networks for simulation and synthesis of cyclic adsorption processes
SG Subraveti, Z Li, V Prasad, A Rajendran
Industrial & Engineering Chemistry Research 61 (11), 4095-4113, 2022
342022
Can a computer “learn” nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes
SG Subraveti, Z Li, V Prasad, A Rajendran
Journal of Chromatography A 1672, 463037, 2022
192022
How Can (or Why Should) Process Engineering Aid the Screening and Discovery of Solid Sorbents for CO2 Capture?
A Rajendran, SG Subraveti, KN Pai, V Prasad, Z Li
Accounts of Chemical Research 56 (17), 2354-2365, 2023
142023
Can a computer “learn” nonlinear chromatography?: Experimental validation of physics-based deep neural networks for the simulation of chromatographic processes
SG Subraveti, Z Li, V Prasad, A Rajendran
Industrial & Engineering Chemistry Research 62 (14), 5929-5944, 2023
92023
Computational fluid dynamics study of viscous fingering in supercritical fluid chromatography
SG Subraveti, P Nikrityuk, A Rajendran
Journal of Chromatography A 1534, 150-160, 2018
82018
System optimization of hybrid processes for CO2 capture
L Riboldi, SG Subraveti, RM Montañés, D Kim, S Roussanaly, ...
Computer Aided Chemical Engineering 53, 1375-1380, 2024
32024
Machine learning-based design and techno-economic assessments of adsorption processes for CO2 capture
SG Subraveti
22021
Is CCS really so expensive? An analysis of cascading costs and CO2 emissions reduction of industrial CCS implementation applied to a bridge
SG Subraveti, E Rodriguez, A Ramirez, S Roussanaly
SSRN, 2022
12022
Adsorption and Chromatographic Processes: Modeling and Optimization
SG Subraveti
12017
Methane enrichment from dilute sources: Performance limits and implications for methane removal and abatement
SG Subraveti, R Anantharaman
2025
Process performance limits of three-step vacuum temperature swing adsorption for methane enrichment from dilute sources
SG Subraveti, R Anantharaman
2025
Hybrid Concepts as Enabling Options for CO2 Capture: an Extensive Mapping of Techno-Economic Potential
L Riboldi, R M Montañés, SG Subraveti, D Kim, S Roussanaly, ...
Sai Gokul and Kim, Donghoi and Roussanaly, Simon and Anantharaman, Rahul …, 2024
2024
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