By leveraging homomorphic encryption, catalysis researchers can perform secure data analytics on encrypted data. This means that they can run computations on datasets without needing to decrypt them first, thus maintaining the security of the data throughout the process. This capability is essential for machine learning applications in catalysis, where large datasets are analyzed to predict reaction outcomes or optimize processes.
