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==Data==
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''See the subpages listed [[Industry#Machine%20Learning%20Application%20Areas|above]] for application-specific datasets.''
 
''See the subpages listed [[Industry#Machine%20Learning%20Application%20Areas|above]] (e.g., the subpage on [[Accelerated Science|accelerated science]]) for application-specific datasets.''
Most industrial information is proprietary, so it may be useful for researchers to connect directly with factories, to negotiate confidential access to relevant data.
 
Most industrial information is proprietary, so it may be useful for researchers to connect directly with factories, to negotiate confidential access to relevant data.
* '''The Materials Project''': "[C]omputed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials." Available [https://materialsproject.org/ here].
*'''Inorganic Crystal Structure Database''': "[T]he world's largest database for completely identified inorganic crystal structures." Available [https://icsd.products.fiz-karlsruhe.de/en/ here].
*'''SciFinder''': Chemical and materials science database (paid), available [https://www.cas.org/products/scifinder here].
*'''"Concrete Compressive Strength"''': Dataset of concrete compressive strength available [https://archive.ics.uci.edu/ml/datasets/ here] via the UCI Machine Learning Repository.
*'''Open Catalyst Project:''' Dataset of 1.2 million molecular relaxations with results from over 250 million DFT calculations, aimed towards the discovery of new catalysts for use in renewable energy storage. Available [https://opencatalystproject.org/index.html here].
 
==Relevant Groups and Organizations==
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