How is High Dimensionality Handled in Catalysis Research?
Handling high dimensionality in catalysis research often involves the use of advanced computational methods and statistical techniques. Machine learning algorithms, such as neural networks and support vector machines, are increasingly used to analyze large datasets and identify correlations between variables. Additionally, high-throughput experimentation allows researchers to systematically vary multiple parameters and rapidly screen a large number of catalyst candidates.
