A new mechanism for reactivity of multiply twinned gold nanoparticles resulting from their inherently strained structure provides a further explanation of the surprising catalytic activity of small gold nanoparticles. Atomic defect structural studies of surface strains and quantitative analysis of atomic column displacements in the decahedral structure observed by aberration corrected transmission electron microscopy reveal an average expansion of surface nearest neighbor distances of 5.6%, with many strained by more than 10%. Density functional theory calculations of the resulting modified gold d-band states predict significantly enhanced activity for carbon monoxide oxidation. The new insights have important implications for the applications of nanoparticles in chemical process technology, including for heterogeneous catalysis.

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An efficient protocol for the hydrogenation of platform molecules (e.g. succinic acid) in aqueous environments using supported metal nanoparticles on polysaccharide derived mesoporous carbonaceous materials is reported for the first time.

We report the first finding of diamond and moissanite in metasedimentary crustal rocks of Pohorje Mountains (Slovenia) in the Austroalpine ultrahigh‐pressure (UHP) metamorphic terrane of the Eastern Alps. Microscopic observations and Raman spectroscopy show that diamond occurs in situ as inclusions in garnet, being heterogeneously distributed. Under the optical microscope, diamond‐bearing inclusions are of cuboidal to rounded shape and of pinkish, yellow to brownish colour. The Raman spectra of the investigated diamond show a sharp, first order peak of sp3‐bonded carbon, in most cases centred between 1332 and 1330 cm−1, with a full width at half maximum between 3 and 5 cm−1. Several spectra show Raman bands typical for disordered graphitic (sp2‐bonded) carbon. Detailed observations show that diamond occurs either as a monomineralic, single‐crystal inclusion or it is associated with SiC (moissanite), CO2 and CH4 in polyphase inclusions. This rare record of diamond occurring with moissanite as fluid‐inclusion daughter minerals implies the crystallization of diamond and moissanite from a supercritical fluid at reducing conditions. Thermodynamic modelling suggests that diamond‐bearing gneisses attained P–T conditions of ≥3.5 GPa and 800–850 °C, similar to eclogites and garnet peridotites. We argue that diamond formed when carbonaceous sediment underwent UHP metamorphism at mantle depth exceeding 100 km during continental subduction in the Late Cretaceous (c. 95–92 Ma). The finding of diamond confirms UHP metamorphism in the Pohorje Mountains, the most deeply subducted part of Austroalpine units.

The concept of micelles was first proposed in 1913 by McBain and has rationalized numerous experimental results of the self-aggregation of surfactants. It is generally agreed that the aggregation number (Nagg) for spherical micelles has no exact value and a certain distribution. However, our studies of calix[4]arene surfactants showed that they were monodisperse with a defined Nagg whose values are chosen from 6, 8, 12, 20, and 32. Interestingly, some of these numbers coincide with the face numbers of Platonic solids, thus we named them “Platonic micelles”. The preferred Nagg values were explained in relation to the mathematical Tammes problem: how to obtain the best coverage of a sphere surface with multiple identical circles. The coverage ratio D(N) can be calculated and produces maxima at N = 6, 12, 20, and 32, coinciding with the observed Nagg values. We presume that this “Platonic nature” may hold for any spherical micelles when Nagg is sufficiently small.

Pumice rafts that arrived at the Nansei Islands, Japan, provided a unique opportunity to investigate the Fukutoku‐Oka‐no‐Ba (FOB) eruption of August 2021. Despite drifting for 2 months for ~1300 km, the drift pumice raft had a large volume and contained a variety of pumice clasts, some of which were deposited during a high tide in a typhoon, while others were washed up on a sandy beach. Most of the drift pumice clasts are gray in color, vesicular, and have a groundmass containing black enclaves. Rare black pumice and the main gray pumice components have similar trachytic compositions, with SiO2 = 61–62 mass% and total alkalis = 8.6–10 mass% (on an anhydrous basis). Both pumice types contain clinopyroxene, plagioclase, and rare olivine phenocrysts. Thin‐section observations show that the gray pumice has more elongated vesicles as compared with the black pumice that has spherical vesicles, even where the two types of pumice are in the same clast. The glass in the black pumice is transparent and brown in color, while that in the gray pumice is colorless. No micro or nano‐crystals were observed during electron and optical microscopy. Raman spectra of the brown‐colored glass exhibit a clear magnetite peak, suggesting magnetite nanolites cause the brown color. High‐Mg olivine in the black pumice has an equilibrium temperature of c. 1200 °C and a rim diffusion profile indicative of re‐equilibration with the surrounding melt over a period of hours to days. The textural relationships between the gray and black pumice suggest that the black pumice had become black and viscous before the two types of pumice mixed. Therefore, crystallization of magnetite nanolites and a corresponding increase in melt viscosity were important in the eruption preparation process, which then resulted in a large‐scale Plinian eruption.

Identifying the data structure including trends and groups/clusters in geochemical problems is essential to discuss the origin of sources and processes from the observed variability of data. An increasing number and high dimensionality of recent geochemical data require efficient and accurate multivariate statistical analysis methods. In this paper, we show the relationship and complementary roles of k-means cluster analysis (KCA), principal component analysis (PCA), and independent component analysis (ICA) to capture the true data structure. When the data are preprocessed by primary standardization (i.e., with the zero mean and normalized by the standard deviation), KCA and PCA provide essentially the same results, although the former returns the solution in a discretized space. When the data are preprocessed by whitening (i.e., normalized by eigenvalues along the principal components), KCA and ICA may identify a set of independent trends and groups, irrespective of the amplitude (power) of variance. As an example, basalt isotopic compositions have been analyzed with KCA on the whitened data, demonstrating clear rock type/ tectonic occurrence/mantle end-member discrimination. Therefore, the combination of these methods, particularly KCA on whitened data, is useful to capture and discuss the data structure of various geochemical systems, for which an Excel program is provided.Plain Language Summary This paper presents a new statistical method that effectively captures the structures of various types of multivariate data (not only geochemical data but also any type of data). The method is based on combinations of k-means cluster analysis, principal component analysis, and independent component analysis for preprocessed data. The corresponding Excel program file is provided.

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