De novo optimization of heterogenous catalysts for industrial processes is an extremely difficult task, but one with serious benefits in terms of cost savings and time to market. Through this work we will move closer to our goal of using computational chemistry to build predictive catalysis models and to the elucidation of a series of catalyst design rules. Since raw material production from fossil fuels is unsustainable, there is a clear need to quickly develop cost effective industrial-scale syntheses of raw materials from sustainable bio-sourced materials. Since fluctuations in oil prices are unpredictable and can be quite large, having these alternative bio-based processes ready to go should help reduce raw material outages in the future. Additionally, the aim of our catalyst work is via co-development with supplier partners. As a consequence, success in modeling could foster further industrial interest in HPC.
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