The use of Raman spectroscopy as a versatile characterization tool for calcium sulphoaluminate cements: a compositional and hydration study

Calcium sulphoaluminate (CSA) cement is considered the third series cement besides ordinary Portland cement (OPC) and calcium aluminate (CA) cement. It is produced from gypsum, bauxite and limestone at 1,300 °C and consists of yeelimite, belite and anhydrite as main mineral phases. In the last years, many attempts have been made in applying Raman spectroscopy for the characterization of cement, clinker minerals and supplementary cementing materials (SCMs), revealing that this technique is a valuable tool for the identification of different phases in cements. In this work micro-Raman spectroscopy has been used, together with X-ray diffraction, for the characterization of CSA cement and its main minerals. In order to identify which mineral phase is responsible for the different bands, Raman spectra have been acquired from synthesized yeelimite and belite phases (whose purity degree was checked by X-ray diffraction) and from calcium sulphate di-hydrate and anhydrous (gypsum and anhydrite, respectively). On these bases, Raman spectra collected on CSA clinker and cement have been successfully assigned. Moreover, Raman spectroscopy, together with X-ray diffraction, proved useful to follow the hydration process of CSA cement up to 28 days. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

---

Carbon materials for chemical capacitive energy storage

Carbon materials have attracted intense interests as electrode materials for electrochemical capacitors, because of their high surface area, electrical conductivity, chemical stability and low cost. Activated carbons produced by different activation processes from various precursors are the most widely used electrodes. Recently, with the rapid growth of nanotechnology, nanostructured electrode materials, such as carbon nanotubes and template-synthesized porous carbons have been developed. Their unique electrical properties and well controlled pore sizes and structures facilitate fast ion and electron transportation. In order to further improve the power and energy densities of the capacitors, carbon-based composites combining electrical double layer capacitors (EDLC)-capacitance and pseudo-capacitance have been explored. They show not only enhanced capacitance, but as well good cyclability. In this review, recent progresses on carbon-based electrode materials are summarized, including activated carbons, carbon nanotubes, and template-synthesized porous carbons, in particular mesoporous carbons. Their advantages and disadvantages as electrochemical capacitors are discussed. At the end of this review, the future trends of electrochemical capacitors with high energy and power are proposed.     

“Brick‐and‐Mortar” Self‐Assembly Approach to Graphitic Mesoporous Carbon Nanocomposites

Mesoporous carbon materials do not have sufficient ordering at the atomic scale to exhibit good electronic conductivity. To date, mesoporous carbons having uniform mesopores and high surface areas have been prepared from partially‐graphitizable precursors in the presence of templates. High temperature thermal treatments above 2000 °C, which are usually required to increase conductivity, result in a partial or total collapse of the mesoporous structures and reduced surface areas induced by growth of graphitic domains, limiting their applications in electric double layer capacitors and lithium‐ion batteries. In this work, we successfully implemented a “brick‐and‐mortar” approach to obtain ordered graphitic mesoporous carbon nanocomposites with tunable mesopore sizes below 850 °C without using graphitization catalysts or high temperature thermal treatments. Phenolic resin‐based mesoporous carbons act as mortar to highly conductive carbon blacks and carbon onions (bricks). The capacitance and resistivity of final materials can be tailored by changing the mortar to brick ratios.     

A simple method to disentangle nanoparticle optical properties by darkfield microspectroscopy

We present a darkfield optical microspectroscopy technique devoted to the disentangled measurement of the absorption and scattering cross sections of nanoparticle (NP) samples with variable concentration. The robustness of the method, including the needed instrumental calibrations, is examined in detail by analyzing and quantifying the major sources of statistic and systematic errors. As an exemplary case, results are presented on a gold NP colloid. The technique takes advantage of a simple inverted microscope, coupled with a spectrograph and equipped with a darkfield condenser and a variable numerical aperture objective to obtain spectra either in darkfield or brightfield optical configurations. By adopting the Lambert–Beer (LB) equation modeling, we were able to disentangle and measure with a single setup the absorption, scattering, and extinction coefficients of the same sample by combining three spectra, obtained by opportunely varying the objective numerical aperture. Typical plasmonic resonances were recognized at approximately 520 and 750 nm. Optical coefficients were measured as a function of particle number density (0.04–3.94 µm^?3, corresponding to 40 µM–4 mM nominal Au concentration) and good linearity was verified up to ～1.5 µm^?3 (～1 mM Au). Moreover, extinction and scattering cross sections were quantified and the validity of the LB approximation was reviewed. Besides its applications to plasmonic NPs, this method may be appropriate for any colloid, provided there exists a characteristic spectral feature in the ultraviolet‐visible‐near infrared range. This technique may be exploited to localize NPs in biological samples. Microsc. Res. Tech. 77:886–895, 2014. © 2014 Wiley Periodicals, Inc.     

Multiobjective optimization under uncertainty in tunneling: application to the design of tunnel support/reinforcement with case histories

In this paper, two questions common in tunnel design are addressed: (i) how to choose an optimum solution when more than one conflicting objective must be achieved; (ii) how to deal with data affected both by imprecision and randomness. Fuzzy Set Theory and Random Set Theory are used to develop a general interactive multiobjective procedure, which is then applied to the design of tunnel support/reinforcement. A case history illustrates how the procedure was successfully used in the preliminary design of a total of 40 km of tunnels in Central Italy. It is shown that the procedure allows the designer to become a knowledgeable decision maker because his interaction is required at the key points of the process, and because the trade-offs among the objective functions can be easily assessed. The designer's personal input is valued and clearly defined in its impact on the solution. The case history demonstrates that, without an optimization procedure, it is extremely likely (probability of 99%) that a solution is chosen, which either increases the costs without increasing safety, or decreases the safety without decreasing the costs. Finally, it is shown that both imprecision and randomness can be easily taken into account in tunnel design.     

Alternative Resilience Indices for City Ecosystems Subjected to Natural Hazards

Prompt and efficient responses against natural hazards are needed to build cities capable of withstanding disasters, namely resilient cities. This study aims at presenting and testing synthetic resilience indices over a real urban center threatened by multiple hazards, for which a global overview of city performance is requested. An integrated framework is proposed for quantitative resilience assessment by way of time‐independent synthetic indices. The approach proposed is in accordance to the complex network theory and uses a global indicator of the system connectivity to assess the city functioning also in case of network disruption. Resilience is evaluated as a proxy for systemic urban damage by modeling a city ecosystem as a hybrid social–physical network. Seismic and landslide scenario analyses are performed for the city of Sarno, Italy. A probability‐based approach is used to compute urban vulnerability. Subsequently, to highlight changes in results according to the type of disaster, a recovery strategy is simulated to assess efficiency and damage states in each recovery stage, and urban resilience.