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The valorization of methane into oxygenated products has long intrigued the catalysis community, however, progress in the field is disparate and practical implementation remains elusive. This Review discusses recent advances in the area using performance indicators that reveal the gaps between academic investigations and industrial methane utilization and highlight possibilities for further developments.
Computational chemistry has the potential to aid in the design of heterogeneous catalysts; however, there is currently a large gap between the complexity of real systems and what can be readily computed at scale. This Review discusses the ways in which machine learning can assist in closing this gap to facilitate rapid advances in catalyst discovery.
Retrobiosynthesis aims to create novel biosynthetic pathways for the beneficial production of molecules of interest. This Review outlines how machine learning can help to advance retrobiosynthesis by improving retrosynthesis planning, enzyme identification and selection, and the engineering of enzymes and pathways.
