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Circular economy emphasizes the idea of transforming products involving economic growth and improving the ecological system to reduce the negative consequences caused by the excessive use of raw materials. This can be achieved with the use of second-generation biomass that converts industrial and agricultural wastes into bulk chemicals. The use of catalytic processes is essential to achieve a viable upgrade of biofuels from the lignocellulosic biomass. We carried out density functional theory calculations to explore the relationship between 13 transition metals (TMs) properties, as catalysts, and their affinity for hydrogen and oxygen, as key species in the valourization of biomass. The relation of these parameters will define the trends of the hydrodeoxygenation (HDO) process on biomass-derived compounds. We found the hydrogen and oxygen adsorption energies in the most stable site have a linear relation with electronic properties of these metals that will rationalize the surface's ability to bind the biomass-derived compounds and break the C–O bonds. This will accelerate the catalyst innovation for low temperature and efficient HDO processes on biomass derivates, e.g. guaiacol and anisole, among others. Among the monometallic catalysts explored, the scaling relationship pointed out that Ni has a promising balance between hydrogen and oxygen affinities according to thed -band centre andd -band width models. The comparison of the calculated descriptors to the adsorption strength of guaiacol on the investigated surfaces indicates that thed -band properties alone are not best suited to describe the trend. Instead, we found that a linear combination of work function andd -band properties gives significantly better correlation.This article is part of a discussion meeting issue ‘Science to enable the circular economy’.

philosophical transactions - royal society. mathematical, physical and engineering sciences/philosophical transactions - royal society. mathematical, physical and engineering sciences

Biomass hydrodeoxygenation catalysts innovation from atomistic activity predictors