Systems Inorganics: Finding a Needle in a Haystack

In computational mass spectrometry, one often tackles the problem of correlating a mass spectrometry signal to a viable and chemically sound structure. Although such problems are commonly solved in organic chemistry, sometimes even with simple heuristics, they remain a challenge for all inorganic and nanomolecular systems. An apparent reason is that coordinate compounds exhibit many bonding connectivity modes.

In a recent work published in Chemical Science, Kondinski et al. tackled the correlation of a mass spectrometry signal to new, complex, and multinuclear inorganics made of vanadium, arsenic and oxygen atoms. Based on the composition, the molecular inorganic belongs to the family of spherical heteropolyoxovanadates (heteroPOVs), which are a well-known set of catalytically active and magnetically responsive materials.  However, finding what structure is being detected by the mass spectrometer initially appeared as a practically insurmountable problem. As the authors carefully enumerated in the paper, there are over 40,000 configurations in which one can formally construct a spherical heteroPOV.

The authors decided to take a different route and apply systems thinking. They integrated empirical evidence on formed structures, with the emergence of intramolecular strains as a factor of substitution configuration. These insights enabled them to navigate relatively quickly across the overall chemical space and allocate a handful of promising structures. Using ADF, they could optimize and rank structures, and allocate a viable molecular model that explains and correlates to experimental observations. The overall study revealed an unprecedented structural change: that is, when spherical heteroPOVs become gradually over-substituted by arsenic, the overall structural models leap into a cyclic (i.e. ring-like) assembly.

Kondinski, M. Rasmussen, S. Mangelsen, N. Pienack,   V. Simjanoski,   C. Nather,   D. L. Stares,   C. A. Schalley, W. Bensch, Composition-driven archetype dynamics in polyoxovanadates, Chem. Sci. 13, 6397-6412 (2022).

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