Integration of data-intensive, machine learning and robotic experimental approaches for accelerated discovery of catalysts in renewable energy-related reactions
Technological advancements in recent decades have greatly transformed the field of material chemistry. Juxtaposing the accentuating energy demand with the pollution associated, urgent measures are required to ensure energy maximization, while reducing the extended experimental time cycle involved in...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2021-08-01
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| Series: | Materials Reports: Energy |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666935821000847 |