Yes, data science techniques can predict catalyst deactivation by analyzing historical performance data and identifying degradation patterns. Predictive models can be developed to forecast when a catalyst will lose its activity, allowing for timely maintenance and replacement. This predictive capability is particularly valuable in industrial settings where catalyst performance directly impacts process efficiency and cost.
