The selective hydrolysis of proteins by non‐enzymatic catalysis is difficult to achieve, yet it is crucial for applications in biotechnology and proteomics. Herein, we report that discrete hafnium metal‐oxo cluster [Hf18O10(OH)26(SO4)13⋅(H2O)33] (Hf18), which is centred by the same hexamer motif found in many MOFs, acts as a heterogeneous catalyst for the efficient hydrolysis of horse heart myoglobin (HHM) in low buffer concentrations. Among 154 amino acids present in the sequence of HHM, strictly selective cleavage at only 6 solvent accessible aspartate residues was observed. Mechanistic experiments suggest that the hydrolytic activity is likely derived from the actuation of HfIV Lewis acidic sites and the Brønsted acidic surface of Hf18. X‐ray scattering and ESI‐MS revealed that Hf18 is completely insoluble in these conditions, confirming the HHM hydrolysis is caused by a heterogeneous reaction of the solid Hf18 cluster, and not from smaller, soluble Hf species that could leach into solution.

This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.neucom.2016.04.015Missing values exist in many generated datasets in science. Therefore, utilizing missing data imputation methods is a common and important practice. These methods are a kind of treatment for uncertainty and vagueness existing in datasets. On the other hand, methods based on fuzzy-rough sets provide excellent tools for dealing with uncertainty, possessing highly desirable properties such as robustness and noise tolerance. Furthermore, they can find minimal representations of data and do not need potentially erroneous user inputs. As a result, utilizing fuzzy-rough sets for imputation should be an effective approach. In this paper, we propose three missing value imputation methods based on fuzzy-rough sets and its recent extensions; namely, implicator/t-norm based fuzzy-rough sets, vaguely quantified rough sets and also ordered weighted average based rough sets. These methods are compared against 11 state-of-the-art imputation methods implemented in the KEEL data mining software on 27 benchmark datasets. The results show, via non-parametric statistical analysis, that the proposed methods exhibit excellent performance in general.authorsversionPeer reviewe

The oxygen evolution reaction (OER) is a key bottleneck step of artificial photosynthesis and an essential topic in renewable energy research. Therefore, stable, efficient, and economical water oxidation catalysts (WOCs) are in high demand and cobalt-based nanomaterials are promising targets. Herein, we tackle two key open questions after decades of research into cobaltassisted visible-light-driven water oxidation: What makes simple cobalt-based precipitates so highly activeand to what extent do we need Co-WOC design? Hence, we started from Co(NO 3 ) 2 to generate a precursor precipitate, which transforms into a highly active WOC during the photocatalytic process with a [Ru(bpy) 3 ] 2+ /S 2 O 8 2− /borate buffer standard assay that outperforms state of the art cobalt catalysts. The structural transformations of these nanosized Co catalysts were monitored with a wide range of characterization techniques. The results reveal that the precipitated catalyst does not fully change into an amorphous CoO x material but develops some crystalline features. The transition from the precipitate into a disordered Co 3 O 4 material proceeds within ca. 1 min, followed by further transformation into highly active disordered CoOOH within the first 10 min. Furthermore, under noncatalytic conditions, the precursor directly transforms into CoOOH. Moreover, fast precipitation and isolation afford a highly active precatalyst with an exceptional O 2 yield of 91% for water oxidation with the visible-light-driven [Ru(bpy) 3 ] 2+ /S 2 O 8 2− assay, which outperforms a wide range of carefully designed Co-containing WOCs. We thus demonstrate that high-performance cobalt-based OER catalysts indeed emerge effortlessly from a self-optimization process favoring the formation of Co(III) centers in all-octahedral environments. This paves the way to new low-maintenance flow chemistry OER processes.

Polyoxometalates (POMs, metals=VV, NbV, TaV, MoVI, WVI) are molecular metal oxides that can be isolated without capping ligands. The high negative charge of polyoxoniobates (PONb) provides strong interactions with heterocations, advantageous for electrostatic assembly of modular materials. In four single‐crystal X‐ray structures, we demonstrate that carbonate combined with the very reactive decaniobate [Nb10O28]6− reassembles into a new decaniobate, [Nb10O25(CO3)6]12−, featuring three carbonate‐ligated Nb‐polyhedra. These Nb‐sites can be replaced by heterometals (lanthanides), and the tridentate carbonate can serve as an anchor point to build niobate‐frameworks. Small‐angle X‐ray scattering and two additional X‐ray structures reveal that the reaction pathway proceeds through a Nb24‐PONb intermediate, and the obtained PONb (with or without carbonate) is counterion, temperature, and solvent‐dependent (water or mixed water‐methanol). This provides an uncommon level of control for PONb chemistry.