Оценка экологической опасности рассеивания газопылевого облака при массовых взрывах в карьерах

Heteroanion (HA) moieties have a key role in templating of heteropolyoxometalate (HPA) architectures, but clusters templated by two different templates are rarely reported. Herein, we show how a cross-shaped HPA-based architecture can self-sort the HA templates by pairing two different guests into a divacant {XYW₁₅O₅₄} building block, with four of these building block units being linked together to complete the cross-shaped architecture. We exploited this observation to incorporate HA templates into well-defined positions within the clusters, leading to the isolation of a collection of mixed-HA templated cross-shaped polyanions [(XYW₁₅O₅₄)₄(WO₂)₄]^32–/36– (X = H–P, Y = Se, Te, As). The template positions have been unambiguously determined by single crystal X-ray diffraction, NMR spectroscopy, and high-resolution electrospray ionization mass spectrometry; these studies demonstrated that the mixed template containing HPA clusters are the preferred products which crystallize from the solution. Theoretical studies using DFT calculations suggest that the selective self-sorting originates from the coordination of the template in solution. The cross-shaped polyoxometalate clusters are redox-active, and the ability of molecules to accept electrons is slightly modulated by the HA incorporated as shown by differential pulse voltammetry experiments. These results indicate that the cross-shaped HPAs can be used to select templates from solution, and themselves have interesting geometries, which will be useful in developing functional molecular architectures based upon HPAs with well-defined structures and electronic properties

From chemical gardens to chemobrionics

Chemical gardens are perhaps the best example in chemistry of a self-organizing nonequilibrium process that creates complex structures. Many different chemical systems and materials can form these self-assembling structures, which span at least 8 orders of magnitude in size, from nanometers to meters. Key to this marvel is the self-propagation under fluid advection of reaction zones forming semipermeable precipitation membranes that maintain steep concentration gradients, with osmosis and buoyancy as the driving forces for fluid flow. Chemical gardens have been studied from the alchemists onward, but now in the 21st century we are beginning to understand how they can lead us to a new domain of self-organized structures of semipermeable membranes and amorphous as well as polycrystalline solids produced at the interface of chemistry, fluid dynamics, and materials science. We propose to call this emerging field chemobrionics

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtubes

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtube

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtubes

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtube

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtubes

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtube

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtubes

Real-Time Direction Control of Self Fabricating Polyoxometalate-Based Microtube

An Accelerated Method for Investigating Spectral Properties of Dynamically Evolving Nanostructures

The discrete-dipole approximation (DDA) is widely applied to study the spectral properties of plasmonic nanostructures. However, the high computational cost limits the application of DDA in static geometries, making it impractical for investigating spectral properties during structural transformations. Here we developed an efficient method to simulate spectra of dynamically evolving structures by formulating an iterative calculation process based on the rank-one decomposition of matrices and DDA. By representing structural transformation as the change of dipoles and their properties, the updated polarizations can be computed efficiently. The improvement in computational efficiency was benchmarked, demonstrating up to several hundred times acceleration for a system comprising ca. 4000 dipoles. The rank-one decomposition accelerated DDA method (RD-DDA) can be used directly to investigate the optical properties of nanostructural transformations defined by atomic- or continuum-scale processes, which is essential for understanding the growth mechanisms of nanoparticles and algorithm-driven structural optimization toward enhanced optical properties

A Bio-Inspired, Small Molecule Electron-Coupled-Proton Buffer for Decoupling the Half-Reactions of Electrolytic Water Splitting

Electron-coupled-proton buffers (ECPBs) allow H2 and O2 evolution to be separated from each other in time during the electrolysis of water. Natural photosynthetic systems achieve an analogous feat during water splitting and employ a range of intermediate redox mediators such as quinone derivatives to aid this process. Drawing on this natural example, we show that a low molecular weight quinone derivative is capable of decoupling H2 evolution from O2 evolution at scale during electrochemical water splitting. This work could significantly lower the cost of ECPBs, paving the way for their more widespread adoption in water splitting

An Accelerated Method for Investigating Spectral Properties of Dynamically Evolving Nanostructures

The discrete-dipole approximation (DDA) is widely applied to study the spectral properties of plasmonic nanostructures. However, the high computational cost limits the application of DDA in static geometries, making it impractical for investigating spectral properties during structural transformations. Here we developed an efficient method to simulate spectra of dynamically evolving structures by formulating an iterative calculation process based on the rank-one decomposition of matrices and DDA. By representing structural transformation as the change of dipoles and their properties, the updated polarizations can be computed efficiently. The improvement in computational efficiency was benchmarked, demonstrating up to several hundred times acceleration for a system comprising ca. 4000 dipoles. The rank-one decomposition accelerated DDA method (RD-DDA) can be used directly to investigate the optical properties of nanostructural transformations defined by atomic- or continuum-scale processes, which is essential for understanding the growth mechanisms of nanoparticles and algorithm-driven structural optimization toward enhanced optical properties

An Accelerated Method for Investigating Spectral Properties of Dynamically Evolving Nanostructures

The discrete-dipole approximation (DDA) is widely applied to study the spectral properties of plasmonic nanostructures. However, the high computational cost limits the application of DDA in static geometries, making it impractical for investigating spectral properties during structural transformations. Here we developed an efficient method to simulate spectra of dynamically evolving structures by formulating an iterative calculation process based on the rank-one decomposition of matrices and DDA. By representing structural transformation as the change of dipoles and their properties, the updated polarizations can be computed efficiently. The improvement in computational efficiency was benchmarked, demonstrating up to several hundred times acceleration for a system comprising ca. 4000 dipoles. The rank-one decomposition accelerated DDA method (RD-DDA) can be used directly to investigate the optical properties of nanostructural transformations defined by atomic- or continuum-scale processes, which is essential for understanding the growth mechanisms of nanoparticles and algorithm-driven structural optimization toward enhanced optical properties