Accelerated Science

Machine learning can help accelerate materials science for climate change applications such as the design of solar fuels, battery conducting fluids, alternatives to cement, or better CO₂ sorbents. Some potentially relevant datasets are listed below.

Data

• The Materials Project: "[C]omputed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials."
• Inorganic Crystal Structure Database: "[T]he world's largest database for completely identified inorganic crystal structures."
• SciFinder: Chemical and materials science database (paid).
• "Concrete Compressive Strength" from the UCI Machine Learning Repository: Dataset of concrete compressive strength.