title: Finding Furfural Hydrogenation Catalysts via Predictive Modelling.
abstract: We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.
authors.affiliation: Van 't Hoff Institute of Molecular Sciences, University of Amsterdam Science Park 904, 1098XH Amsterdam, The Netherlands.
authors.forename: Zea
authors.initials: Z
authors.lastname: Strassberger
authors.forename: Maurice
authors.initials: M
authors.lastname: Mooijman
authors.forename: Eelco
authors.initials: E
authors.lastname: Ruijter
authors.forename: Albert H
authors.initials: AH
authors.lastname: Alberts
authors.forename: Ana G
authors.initials: AG
authors.lastname: Maldonado
authors.forename: Romano V A
authors.initials: RV
authors.lastname: Orru
authors.forename: Gadi
authors.initials: G
authors.lastname: Rothenberg