Significance: Closed-shell metal–metal bonds are experimentally and theoretically substantiated as bona fide polar-covalent/ligand-unassisted/ground-state Cu(I)–Au(I) d ¹⁰ –d ¹⁰ bonds. Counterintuitively, replacing some of the gold content with copper leads to stronger metal–metal bonding (despite the lesser relativistic effects in Cu vs. Au) and higher phosphorescence quantum efficiency [despite much lower spin-orbit coupling constants ( ξ _SOC ) for 3d vs. 5d orbitals]. The former results are attributed to greater orbital mixing between (n+1)s/p orbitals of one metal with filled nd ¹⁰ orbitals of the other metal in the heterometallic vs. homometallic system, whereas the near-unity photoluminescence quantum yields and higher extinction coefficients in mixed-metal (Au/Cu) heterometallic vs. homometallic systems are attributed to symmetry reduction. The latter results are promising for enabling societally useful technologies (e.g., Ir-/rare-earth-free LEDs).

Following an increasing interest in the gold drug therapy field, nine new neutral azolate gold(I) phosphane compounds have been synthesized and tested as anticancer agents. The azolate ligands used in this study are pyrazolates and imidazolates substituted with deactivating groups such as trifluoromethyl, nitro or chloride moieties, whereas the phosphane co-ligand is the triphenylphosphane or the more hydrophilic TPA (TPA = 1,3,5-triazaphosphaadamantane). The studied gold(I) complexes are: (3,5-bis-trifluoromethyl-1H-pyrazolate-1-yl)-triphenylphosphane–gold(I) (1), (3,5-dinitro-1H-pyrazolate-1-yl)-triphenylphosphane–gold(I) (2), (4-nitro-1H-pyrazolate-1-yl)-triphenylphosphane–gold(I) (5), (4,5-dichloro-1H-imidazolate-1-yl)-triphenylphosphane–gold(I) (7), with the related TPA complexes (3), (4), (6) and (8) and (1-benzyl-4,5-di-chloro-2H-imidazolate-2-yl)-triphenylphosphane–gold(I) (9). The presence of deactivating groups on the azole rings improves the solubility of these complexes in polar media. Compounds 1–8 contain the N–Au–P environment, whilst compound 9 is the only one to contain a C–Au–P environment. Crystal structures for compounds 1 and 2 have been obtained and discussed. Interestingly, the newly synthesized gold(I) compounds were found to possess a pronounced cytotoxic activity on several human cancer cells, some of which were endowed with cis-platin or multidrug resistance. In particular, among azolate gold(I) complexes, 1 and 2 proved to be the most promising derivatives eliciting an antiproliferative effect up to 70 times higher than cis-platin. Mechanistic experiments indicated that the inhibition of thioredoxin reductase (TrxR) might be involved in the pharmacodynamic behavior of these gold species.

Trinuclear coinage metal metallacycles are obtained when two-coordinate metals are bonded to C, N or N, N anionic ligands of the proper symmetry to form cycles where metals alternate with bridging ligands. Cyclotrimers often exhibit semiplanar structures and mostly columnar or finite stacking in the solid state by means of metallophilic interactions. They show some peculiar properties with an impact on many different fields such as supramolecular architectures, luminescence, molecular recognition, host-guest chemistry, and acid-base chemistry. The comprehensive evaluation of the data shows that, depending on the nature of the central metal and bridging ligand, there is a fine balance of the energy involved in the inter-trimer bond cleavages and the energy gained from the formation of new intermolecular electrostatic interactions, proceeding occasionally to the chemical extreme of redox processes. In this review, a number of important developments are highlighted and systematically analyzed along with structural and computational data and chemical properties to rationalize and build a unifying leitmotif for this chemistry; the focus is made on the authors’ contributions in these areas.

The Human Activity Recognition is a focal point for Ambient Assisted Living, and may be implemented in several ways usually involving the use of different technologies, as wearable, video, environmental or radio frequency sensors, which can be used alone or in combination among them. Recently, the approaches based on machine learning have attracted a lot of interest, especially in order to create recognition systems that do not require a high detection capacity by the single sensor, as they base their decision on the processing of the information acquired from multiple sensors simultaneously. The aim of the present work is to derive information about the activities that are carried out inside the house on the basis of the data acquired by a set of sensors analyzing the air components. The Human Activity Recognition is then the result of a machine learning classification of the output of an array of low cost “commercial off-the-shelf” air quality sensors. The considered recognition system exploits electrochemical sensing, Wi-Fi technology, cloud computing, machine learning and application services. The obtained results evidence that a good accuracy in the recognition of “activities of daily living” is reached, even if a not calibrated sensing was performed.