FES Funded ProjectsOutputs
| Title |
Category |
Date |
Authors |
| Predicting noncentrosymmetric quaternary tellurides using machine learningT12-P01 University of Alberta, Manhattan College, University of Ghana | Activity | 2021-07-28 | | | Revealing hidden patterns through chemical intuition and interpretable machine learning: A case study of binary rare-earth intermetallics RXT12-P01 Nanode Battery Technologies, Manhattan College, University of Alberta | Publication | 2023-01-30 | | | Explainable machine learning in materials chemistry: Decision trees as scoring functionT12-P01 University of Alberta | Activity | 2022-06-16 | | | Machine-learning prediction of new Laves phases with experimental validationT12-P01 University of Alberta | Activity | 2022-06-16 | | | Predicting thermoelectric figures-of-merit for half-Heusler compounds using machine learningT12-P01 University of Alberta | Activity | 2022-06-16 | | | Searching for new spinels using machine learningT12-P01 University of Alberta | Activity | 2022-06-17 | | | Revealing hidden patterns through chemical intuition and interpretable machine learning: A case study of binary rare-earth intermetallics RXT12-P01 University of Alberta, Manhattan College | Activity | 2022-07-27 | | | Searching for new spinels using machine learningT12-P01 University of Alberta | Activity | 2022-07-27 | | | Interpretable machine learning in solid state chemistry, with applications to perovskites, spinels, and rare-earth intermetallics: Finding descriptors using decision treesT12-P01 Nanode Battery Technologies, Manhattan College, University of Alberta | Publication | 2023-06-30 | | | Ahead by a Century: Discovery of Laves Phases Assisted by Machine LearningT12-P01 Nanode Battery Technologies, University of Alberta | Publication | 2024-03-19 | Ritobroto Sikdar, "Nilanjan Roy ", Selvaratnam, B., Vidyanshu Mishra, Dundappa Mumbaraddi, "Amit Mondal ", "Krishnendu Buxi ", Partha Pratim Jana, Mar, A. | | Materials discovery through machine learning: Experimental validation and interpretable modelsT12-P01 Nanode Battery Technologies, Manhattan College, University of Alberta | Activity | 2023-06-07 | | | Revisiting the classification of spinels through machine learningT12-P01 Nanode Battery Technologies, University of Alberta | Activity | 2023-06-06 | | | Machine-learning classification of Laves phases and prediction of new compoundsT12-P01 Nanode Battery Technologies, University of Alberta | Activity | 2023-06-08 | | | Can we use machine learning to find synthesizable compounds?T12-P01 Nanode Battery Technologies, University of Alberta | Activity | 2023-08-04 | | | Discovery of Li-containing compounds with channel structures guided by machine learningT12-P01 Nanode Battery Technologies, University of Alberta | Activity | 2023-08-01 | | | Materials discovery of intermetallics through machine learning: Experimental validation and interpretable modelsT12-P01 Nanode Battery Technologies, Hunter College, University of Alberta | Activity | 2023-09-25 | |
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