A systematic and novel, multi-scale model based catalyst design methodology will be developed. The fundamental nature of the models used is unprecedented and will represent a breakthrough compared to the more commonly applied statistical, correlative relationships. The methodology will focus on the intrinsic kinetics of (potentially) large-scale processes for the conversion of renewable feeds into fuels and chemicals. Non-ideal behaviour, caused by mass and heat transfer limitations or particular reactor hydrodynamics, will be explicitly accounted for when simulating or optimizing industrial-scale applications. The selected model reactions are situated in the area of biomass upgrading to fuels and chemicals: fast pyrolysis oil stabilization, glycerol hydrogenolysis and selective oxidation of (bio)ethanol to acetaldehyde.

For the first time, a systematic microkinetic modelling methodology will be developed for oxygenates conversion. In particular, stereochemistry in catalysis will be assessed. Two types of descriptors will be quantified: kinetic descriptors that are catalyst independent and catalyst descriptors that specifically account for the effect of the catalyst properties on the reaction kinetics. The latter will be optimized in terms of reactant conversion, product yield or selectivity. Fundamental relationships will be established between the catalyst descriptors as determined by microkinetic modelling and independently measured catalyst properties or synthesis parameters. These innovative relationships allow providing the desired, rational feedback in from optimal descriptor values towards synthesis parameters for a new catalyst generation.

Their fundamental character will guarantee adequate extrapolative properties that can be exploited for the identification of a groundbreaking next catalyst generation.