Enabling Accurate and High-Throughput Kinetics Predictions via Message Passing Neural Networks
Quantitative estimates for kinetic properties, namely reaction barrier heights and reaction energies, are essential for developing kinetic mechanisms, predicting reaction outcomes, and optimizing chemical processes. While ab initio methods, such as quantum chemistry, can be incredibly useful for pro...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/153044 |