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Waterproofing systems of tunnels is of crucial importance for the long-term effectiveness of the underground works and for the possible impact on the surrounding environment. In conventional tunnelling, polymeric geomembranes are nowadays used with fluid barrier function, while nonwoven geotextiles and geonets are commonly employed with mechanical protection and drainage functions. After some descriptions of the main requirements of the geosynthetics used in tunnels and underground structures, the durability aspects of the materials forming the waterproofing systems are briefly outlined.

The electrification of the transport sector together with large renewable energy deployment requires powerful tools to efficiently use energy assets and infrastructure. In this framework, the forecast of electric vehicle demand and solar photovoltaic (PV) generation plays a fundamental role. This paper studies the impact of forecast accuracy on total electric cost of a simulated electric vehicles (EVs) charging station coupled with true solar PV and stationary battery energy storage. The optimal energy management system is based on the rolling horizon approach implemented in with a mixed integer linear program which takes as input the EV load forecast using long short-term memory (LSTM) neural network and persistence approaches and PV production forecast using a physical hybrid artificial neural network. The energy management system is firstly deployed and validated on an existing multi-good microgrid by achieving a discrepancy of state variables below 10% with respect to offline simulations. Then, eight weeks of simulations from each of the four seasons show that the accuracy of the forecast can increase operational costs by 10% equally distributed between the PV and EV forecasts. Finally, the accuracy of the combined PV and EV forecast matters more than single accuracies: LSTM outperforms persistence to predict the EV load (−30% root mean squared error), though when combined with PV forecast it has higher error (+15%) with corresponding higher operational costs (up to 5%). [ABSTRACT FROM AUTHOR]

Supported metal hydrides are key reactive intermediates in various catalytic processes, such as hydrogenation and dehydrogenation, but are often challenging to characterize spectroscopically. Here, deuterium solid state nuclear magnetic resonance spectroscopy is used to understand the structure of the corresponding silica‐supported zirconium hydrides after H/D exchange as an illustrative example of supported metal hydrides, which have been shown to display notable reactivity towards small molecules (e. g., CO2 and N2O) and to activate both C−H and C−C bonds, hence their use in to the conversion of hydrocarbons (alkanes, polyolefins etc.) [ABSTRACT FROM AUTHOR]

γ-Al 2 O 3 is used as both a catalyst and a support for catalytic active phases. The properties of γ-Al 2 O 3 have been ascribed to specific surface sites, with varying Al coordination number, acidity, and basicity, depending on the morphology of the material. Here, we combine surface-specific 27 Al{ 1 H} 2D high-field NMR (28.2T, 1.2 GHz for 1 H frequency) at fast MAS (50 kHz) to observe four main distinct families of surface Al-OH sites. Comparing the measured NMR signatures ( 27 Al δ iso , C Q , and 1 H δ iso ) to computed values from a large range of structural DFT models enables to identify specific edge and facet Al-OH surface sites in γ-Al 2 O 3 , including a distinct [4] Al-OH site with an unprecedented C Q approaching 18 MHz. This molecular-level description of alumina surfaces opens new opportunities to understand its unique properties, such as the stabilization of small particles down to single atoms, central to catalytic processes.

Advances in solid-state nuclear magnetic resonance (NMR) methods and hardware offer expanding opportunities for analysis of materials, interfaces, and surfaces. Here, we demonstrate the application of a very high magnetic field strength of 28.2 T and fast magic-angle-spinning rates (MAS, >40 kHz) to surface species relevant to catalysis. Specifically, we present as case studies the 1D and 2D solid-state NMR spectra of important catalyst and support materials, ranging from a well-defined silica-supported organometallic catalyst to dehydroxylated γ-alumina and zeolite solid acids. The high field and fast-MAS measurement conditions substantially improve spectral resolution and narrow NMR signals, which is particularly beneficial for solid-state 1D and 2D NMR analysis of 1 H and quadrupolar nuclei such as 27 Al at surfaces., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)