Finding Furfural Hydrogenation Catalysts via Predictive Modelling

Homogeneous Catalyzed Valorization of Furanics: A Sustainable Bridge to Fuels and Chemicals

The development of efficient biomass valorization is imperative for the future sustainable production of chemicals and fuels. Particularly, the last decade has witnessed the development of a plethora of effective and selective transformations of bio-based furanics using homogeneous organometallic catalysis under mild conditions. In this review, we describe some of the advances regarding the conversion of target furanics into value chemicals, monomers for high-performance polymers and materials, and pharmaceutical key intermediates using homogeneous catalysis. Finally, the incorporation of furanic skeletons into complex chemical architectures by multifunctionalization routes is also described.

Efficient and chemoselective hydrogenation of aldehydes catalyzed by well-defined PN3-pincer manganese(II) catalyst precursors: an application in furfural conversion

Well-defined and air-stable PN³-pincer manganese(II) complexes were synthesized and used for the hydrogenation of aldehydes into alcohols under mild conditions using MeOH as a solvent. This protocol is applicable for a wide range of aldehydes containing various functional groups. Importantly, α,β-unsaturated aldehydes, including ynals, are hydrogenated with the CC double bond/CC triple bond intact. Our methodology was demonstrated for the conversion of biomass derived feedstocks such as furfural and 5-formylfurfural to furfuryl alcohol and 5-(hydroxymethyl)furfuryl alcohol respectively.

Selective Hydrogenation of the Carbonyls in Furfural and 5-Hydroxymethylfurfural Catalyzed by PtNi Alloy Supported on SBA-15 in Aqueous Solution Under Mild Conditions

Valuable furfuryl alcohol (FFA) and 2,5-dihydroxymethylfuran (DHMF) could be produced by selective hydrogenation of biomass-derived furfural (FF) and 5-hydroxymethylfurfural (HMF) with high atom economy. In this study, SBA-15 (a kind of mesoporous silica molecular sieve)-supported low metal loading (3 wt% total metal content) PtNi alloy catalyst (PtNi/SBA-15) was synthesized via two steps, including the generation of PtNi alloy by hydrothermal method, and the immobilization of PtNi alloy on SBA-15. PtNi/SBA-15 has ordered mesoporous structure with high surface area, and high dispersion of the PtNi alloy with the formation of Pt^δ--Ni^δ+ surface pairs on SBA-15, which benefit hydrogen activation and selective carbonyl hydrogenation. The selective hydrogenation of FF and HMF over PtNi/SBA-15 in water solvent at 303 K with 1.5 MPa H₂ within 2 h, could respectively yield 64.6% FFA with 77.0% selectivity, and 68.2% DHMF with 81.9% selectivity. Besides, PtNi/SBA-15 exhibited a satisfactory water resistance and stability after recycling at least five runs.

Trends in computational molecular catalyst design

Computational methods have emerged as a powerful tool to augment traditional experimental molecular catalyst design by providing useful predictions of catalyst performance and decreasing the time needed for catalyst screening. In this perspective, we discuss three approaches for computational molecular catalyst design: (i) the reaction mechanism-based approach that calculates all relevant elementary steps, finds the rate and selectivity determining steps, and ultimately makes predictions on catalyst performance based on kinetic analysis, (ii) the descriptor-based approach where physical/chemical considerations are used to find molecular properties as predictors of catalyst performance, and (iii) the data-driven approach where statistical analysis as well as machine learning (ML) methods are used to obtain relationships between available data/features and catalyst performance. Following an introduction to these approaches, we cover their strengths and weaknesses and highlight some recent key applications. Furthermore, we present an outlook on how the currently applied approaches may evolve in the near future by addressing how recent developments in building automated computational workflows and implementing advanced ML models hold promise for reducing human workload, eliminating human bias, and speeding up computational catalyst design at the same time. Finally, we provide our viewpoint on how some of the challenges associated with the up-and-coming approaches driven by automation and ML may be resolved.

Designing bifunctional alkene isomerization catalysts using predictive modelling

Optimised isomerisation catalysts are found using an iterative approach combining experimental studies and descriptor modelling.

Ruthenium-catalyzed solvent-free conversion of furfural to furfuryl alcohol

Bidentate phosphine-modified Ru-based homogeneous catalyst systems were developed for any solvent-free conversion of furfural to furfuryl alcohol as a versatile biomass-based C₅-platform molecule.

1,2,3-Triazolylidene ruthenium(ii)-cyclometalated complexes and olefin selective hydrogenation catalysis

Silver(i) 1,2,3-triazol-5-ylidenes [(RCH₂C₂N₂(NMe)Ph)₂Ag][AgCl₂] (R = Ph 3a, C₆H₂iPr₃3b, C₆H₂Me₃3c) and [(PhCH₂C₂N₂(NMe)R)₂Ag][AgCl₂] (R = C₆H₄Me 3d, C₆H₄CF₃3e) were synthesized and subsequently treated with RuHCl(PPh₃)₃ and RuHCl(H₂)(PCy₃)₂ to give cyclometallated and Ru-hydride species as the major and minor products, respectively.

Screening substituent and backbone effects on the properties of bidentate P,P-donor ligands (LKB-PP(screen))

We present a computational exploration of the effect of systematic variation of backbones and substituents on the properties of bidentate, cis-chelating P,P donor ligands as captured by calculated parameters. The parameters used are the same as reported for our ligand knowledge base for bidentate P,P donor ligands, LKB-PP (Organometallics 2008, 27, 1372-1383; Organometallics 2012 31, 5302-5306), but calculation protocols have been streamlined, suitable for an extensive evaluation of ligand structures. Analysis of the resulting LKB-PP(screen) database with principal component analysis (PCA) captures the effects of changing backbones and substituents on ligand properties and illustrates how these are complementary variables for these ligands. While backbone variation is routinely employed in ligand synthesis to modify catalyst properties, only a limited subset of substituents is commonly accessed and here we highlight substituents which are likely to generate new ligand properties, of interest for the design and improved sampling of bidentate ligands in homogeneous organometallic catalysis.