The Ohlin group

Quick links:


While we understand reactions involving discrete molecules in solution well — the handle that organic chemists have on reaction mechanisms is admirable — our understanding of reactions on surfaces such as minerals and heterogeneous catalysts is quite poor. This is a significant issue, given the central importance of heterogeneous materials such as metal oxides in fields such catalysis, materials science, environmental science and geochemistry.
In fact, even a field such as evolutionary biology relies in part on the understanding of mineral at the interface with water. After all, cluster-containing enzymes may have their origin in small mineral fragments that have been taken up by cells, and that have subsequently been stabilised by the evolution of an organic scaffold.
Activation of a metal-oxide mineral proceeds at the surface. It can be very difficult to study this type of reactions, since extended surfaces can contain different surface features which differ enormously in reactivity. Bulk analysis will thus be misleading and will only provide overall reactivities, which will not give any meaningful mechanistic information.
The Ohlin group explores this type of reactions by working with discrete metal-oxide clusters instead of heterogeneous materials. By working with well-defined discrete metal oxide clusters in solution we can not only use solution-phase analytical techniques, but we also have complete confidence in the exact structure of the material. We know exactly what types of sites we have, how many they are, what they look like, and we can often follow the reactivity of each site individually. This way we can get reliable mechanistic information. The discreteness and limited size of our target molecules also mean that we have a wide range of computational methods at our disposal.

A particularly interesting class of discrete metal oxide clusters are the polyoxometalates. A few different areas that we focus on are described below.


The polyoxoniobates are different from the polyoxovanadates, -molybdates and -tungstates in that they typically are unstable at low pH, while showing good stability under more alkaline conditions. In addition, they are often more tolerant towards reducing conditions, suggesting their use as electron sinks, since they will seek to stay in or return to their higher oxidation states. Few homoleptic polyoxoniobates were until recently known, and their use as ligands is almost completely unexplored.

Figure: the ‘super’-Lindqvist ion [Ti12Nb6O44]10-.


NMR is an enormously powerful tool for the investigation of dynamic processes in solution. A classical treatment of exchange phenomena allows for the design and interpretation of one- or two-pulse experiments for the determination of ligand exchange on both diamagnetic and paramagnetic metals by line-broadening and saturation-transfer techniques

Figure: Saturation transfer between two species separated by only a few ppm – the pulse sequence consists of pi/2, precession, pi/2, mixing, pi/2, observation

Mass spectrometry

NMR typically requires suitable nuclei to be present in the analyte in order to do kinetic experiments. Mass spectrometry makes other requirements, but often constitutes a powerful technique for the characterisation of novel compounds and the investigation of their chemistries.

Figure: Stacked spectra obtained as a function of cone voltage.

Simulation and data decomposition

Modeling and data decomposition can be useful in testing hypotheses and making predictions before any wet chemistry has been done, and thus aid in the design of experiments. We use simulation to model pulses in NMR spectrometry, reduce spectroscopic data obtained from UV/VIS titrations and stopped-flow experiments using factor analysis, and to test boundary hypotheses.

In addition to this, we also use computational chemistry — chiefly density functional theory-based methods — to improve our understanding of the chemistry of metal oxides in solution.

Figure: Concentration profiles derived from OPA treatment of stopped flow data of an oxidation reaction