Polyoxometalate clusters in minerals: review and complexity analysis

Abstract

Most research on polyoxometalates (POMs) has been devoted to synthetic compounds. However, recent mineralogical discoveries of POMs in mineral structures demonstrate their importance in geochemical systems. In total, 15 different types of POM nanoscale-size clusters in minerals are described herein, which occur in 42 different mineral species. The topological diversity of POM clusters in minerals is rather restricted compared to the multitude of moieties reported for synthetic compounds, but the lists of synthetic and natural POMs do not overlap completely. The metal–oxo clusters in the crystal structures of the vanarsite-group minerals ([As3+V4+ 2V5+ 10As5+ 6O51]7−), bouazzerite and whitecapsite ([M 3+ 3Fe7(AsO4)9O8–;n (OH) n ]), putnisite ([Cr3+ 8(OH)16(CO3)8]8−), and ewingite ([(UO2)24(CO3)30O4(OH)12(H2O)8]32−) contain metal–oxo clusters that have no close chemical or topological analogues in synthetic chemistry. The interesting feature of the POM cluster topologies in minerals is the presence of unusual coordination of metal atoms enforced by the topological restraints imposed upon the cluster geometry (the cubic coordination of Fe3+ and Ti4+ ions in arsmirandite and lehmannite, respectively, and the trigonal prismatic coordination of Fe3+ in bouazzerite and whitecapsite). Complexity analysis indicates that ewingite and morrisonite are the first and the second most structurally complex minerals known so far. The formation of nanoscale clusters can be viewed as one of the leading mechanisms of generating structural complexity in both minerals and synthetic inorganic crystalline compounds. The discovery of POM minerals is one of the specific landmarks of descriptive mineralogy and mineralogical crystallography of our time.

Producing highly complicated materials. Nature does it better

“…The filling of the framework cavities by cations and H 2 O molecules more than doubles the complexity tõ 6112 bits per cell. The five most complex mineral structures reflect the basic mechanisms of the generation of crystal-structure complexity of minerals: the formation of nanoscale large polyatomic clusters (usually polyoxometalates (Krivovichev 2020)) and the modular architecture, when the structure is based upon a combination of one or several large modules (Krivovichev 2013a). The high hydration states also favor the high Shannon information content, due to the high number of H atoms.…”

“…is of statistical nature that allows exceptions, but works on a global scale. Recently, it was demonstrated that the Fedorov-Groth law is valid and statistically meaningful, when chemical complexity is expressed according to the equation (5) as the amount of Shannon chemical information per atom and the degree of symmetry as the order of the point group of a mineral (Krivovichev, Krivovichev 2020).…”

Natrophosphate, Arctic Mineral and Nuclear Waste Phase: Structure Refinements and Chemical Variability

“…From the structural point of view, natrophosphate belongs to the family of minerals containing polyoxometalate clusters as recently reviewed in [33]. The presence of the (FNa6) 5+ units at the core of the clusters allows to suggest that the mineral may serve as a precursor for the formation of antiperovskite structure motifs based upon anion-centered octahedra [34].…”

Information Entropy in Chemistry: An Overview

“…It is called information density and expressed in bits/Å 3 . Krivovichev with collaborators and followers applied these quantities to study various minerals [91][92][93][94][95][96][97][98][99][100][101] and found the relations between the crystallographic symmetries, size, and information entropy estimates (Table 4) and proposed the classification of the minerals, which is based on their complexity estimated with I values (Table 5). The latter means that the information entropy is associated with the complexity of the minerals (though the authors make a reservation that other approaches to assessing the complexity of the minerals can be used, such as exploiting the approximation of the crystal structures as the nets or invoking algorithmic complexity paradigm [96]).…”

“…Their original symmetries are reduced upon forming molecular crystals due to the influence of the neighbors of a crystal lattice (Table 6). Note that additional factors in addition to the structural complexity (e.g., layer stacking or complexity of hydrogen network) can be taken into account within the approach described above [97]. Table 6.…”