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Figure 6.3: Proposed lighthouse project highlighting the potential of homogenous catalysis in Power-to-X scenarios: Decen- tralized production of formic acid in an agricultural environment. The process scheme is adapted from [16]. 6.3.2 Accelerating catalyst discovery via information-guided approaches Traditionally, homogeneous catalyst development follows a largely linear workflow, in which the starting point is a lead structure derived from chemical intuition, extrapolation of previous knowl- edge, or even serendipity. Improvements and optimization are achieved primarily by evolutionary modifications of the ligand structure and screening under standard reaction conditions, and theo- retical rationalization is deduced a posteriori from the obtained data and mechanistic studies. A radically new approach that goes beyond these current linear catalyst development schemes will be crucial in discovering appropriate homogenous catalysts for Power-to-X transformations in the necessary timeframe. By coupling systematic experimental variation with the rapidly growing po- tential of digitalization via computational chemistry and artificial intelligence (see Section 8), we expect a robust framework for accelerating catalyst discovery can be established. To support such a goal, there is a need for: • Novel methods to rapidly generate pertinent, consistent, and accessible data on the molecular and process scale under operating conditions • A priori integration of computational chemistry and experiment to identify desired and un- desired reactivity channels • Dynamic descriptions of catalytic processes and time-resolved analyses of reaction progress, e.g. by monitoring low-concentration side products and short-lived intermediates • Novel methods for monitoring electrochemical or photochemical catalytic performance, in- cluding resolution of elementary steps 64PDF Image | sustainable production of fuels and chemicals
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