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https://scholarbank.nus.edu.sg/handle/10635/239055
DC Field | Value | |
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dc.title | MACHINE LEARNING AIDED INTERPRETATION OF FACTORS AFFECTING NI-CATALYZED DRY REFORMING OF METHANE | |
dc.contributor.author | KEERTHANA VELLAYAPPAN | |
dc.date.accessioned | 2023-04-30T18:00:40Z | |
dc.date.available | 2023-04-30T18:00:40Z | |
dc.date.issued | 2022-12-05 | |
dc.identifier.citation | KEERTHANA VELLAYAPPAN (2022-12-05). MACHINE LEARNING AIDED INTERPRETATION OF FACTORS AFFECTING NI-CATALYZED DRY REFORMING OF METHANE. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/239055 | |
dc.description.abstract | Design principles for active and stable catalysts are well-established for Dry Reforming of Methane reaction &40;DRM&41;&44; however&44; predicting selectivity of DRM over competing side reactions that alter the product H₂&47;CO ratio remains challenging&46; Screening catalysts through experiments is an empirical method&46; It is also time and resource intensive&46; Therefore&44; in this work&44; we devise a Machine learning &40;ML&41; model to predict the catalyst performance while interpreting the model using various techniques&46; We curate a set of 1638 data points from published literature and train tree regressor models to predict the H₂&47;CO ratio as a function of 11 process parameters and catalyst properties&46; The trained CatBoost regressors achieved the best prediction performance with R&178; &61; 0&46;91&46; Our exploratory study highlights ability of data&45;driven ML models to unearth structure&45;property relationships in heterogeneous catalysis by isolating effects of individual design parameters in a manner that would be difficult to achieve experimentally&46; | |
dc.language.iso | en | |
dc.subject | Machine Learning,Heterogenous Catalysis,Dry Reforming of Methane,Ni Catalyst,Syngas,Catalyst Design | |
dc.type | Thesis | |
dc.contributor.department | CHEMICAL & BIOMOLECULAR ENGINEERING | |
dc.contributor.supervisor | Iftekhar A Karimi | |
dc.contributor.supervisor | Kawi Sibudjing | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF ENGINEERING (CDE) | |
dc.identifier.orcid | 0000-0002-1180-1247 | |
Appears in Collections: | Master's Theses (Open) |
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VellayappanK.pdf | 8.09 MB | Adobe PDF | OPEN | None | View/Download |
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