The atomistic rationalization of the activity of transition metal oxides toward oxygen electrocatalysis is one of the most complex challenges in the field of electrochemical energy conversion. Transition metal oxides exhibit a wide range of structural and electronic properties, which are acutely dependent on composition and crystal structure. So far, identifying one or several properties of transition metal oxides as descriptors for oxygen electrocatalysis remains elusive. In this work, we performed a detailed experimental and computational study of LaMn x Ni 1– x O 3 perovskite nanostructures, establishing an unprecedented correlation between electrocatalytic activity and orbital composition. The composition and structure of the single-phase rhombohedral oxide nanostructures are characterized by a variety of techniques, including X-ray diffraction, X-ray absorption spectroscopy, X-ray photoelectron spectroscopy, and electron microscopy. Systematic electrochemical analysis of pseudocapacitive responses in the potential region relevant to oxygen electrocatalysis shows the evolution of Mn and Ni d-orbitals as a function of the perovskite composition. We rationalize these observations on the basis of electronic structure calculations employing DFT with HSE06 hybrid functional. Our analysis clearly shows a linear correlation between the OER kinetics and the integrated density of states (DOS) associated with Ni and Mn 3d states in the energy range relevant to operational conditions. In contrast, the ORR kinetics exhibits a second-order reaction with respect to the electron density in Mn and Ni 3d states. For the first time, our study identifies the relevant DOS dominating both reactions and the importance of understanding orbital occupancy under operational conditions.

Titanium is a strong, corrosion-resistant light—weight metal which is poised to replace steel in automobiles, aircraft, and watercraft. However, the titanium oxide (titania) layer that forms on the surface of titanium in air is notoriously difficult to lubricate with conventional lubricants, which restricts its use in moving parts such as bearings. Ionic liquids (ILs) are potentially excellent lubricants for titania but the relationship between IL molecular structure and lubricity for titania remains poorly understood. Here, three-ball-on-disk macrotribology and atomic force microscopy (AFM) nanotribology measurements reveal the lubricity of four IL lubricants: trioctyl(2-ethylhexyl)phosphonium bis(2-ethylhexyl)phosphate (P 8,8,8,6(2) BEHP), trihexyl(tetradecyl)phosphonium bis(2-ethylhexyl)phosphate (P 6,6,6,14 BEHP), trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate (P 6,6,6,14 ( i C 8 ) 2 PO 2 ), and trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide (P 6,6,6,14 TFSI). The macrotribology measurements demonstrated that friction decreased in P 6,6,6,14 TFSI by four times (μ = 0.13) compared to in hexadecane, even at 60°C and loads up to 10 N. On the other hand, P 8,8,8,6(2) BEHP reduced friction most effectively in the AFM nanotribology measurements. The results were interpreted in terms of the lubrication regime. The lower viscosity of P 6,6,6,14 TFSI coupled with its good boundary lubrication made it the most effective IL for the macrotribology measurements, which were in the mixed lubrication regime. Conversely, the cation structure of P 8,8,8,6(2) BEHP allowed it to adsorb strongly to the surface and minimized energy dissipation in the nanotribology measurements, although its high bulk viscosity inhibited its performance in the mixed regime. These results reinforce the importance of carefully selecting IL lubricants based on the lubrication regime of the sliding surfaces.

As the chemicals industry transitions towards a net zero future, rapid assessment of the sustainability metrics of different process results will be essential to support investment decisions in innovation and deployment. Life Cycle Analysis (LCA) offers the gold standard for process assessment, but LCA can take weeks or months to complete, with incomplete databases and inflexibility in comparing different chemical pathways.In this study, we demonstrate an alternative and complementary methodology. By simplifying the metrics used to describe chemical processes, each process may be linked to another by its feedstocks and products. This generates a network of the chemical industry, which may be investigated using graph theory principles. A case study of the plastics industry is provided, using publicly available information to quantitively compare with a more formalised and detailed LCA approach.This methodology proves useful for quickly estimating the carbon intensity and water footprint of thousands of routes. Further development, such as including Scope 3 emissions and additional industrial data, may further improve the methodology.