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The production and the properties of lightweight composite panels, with expanded vermiculite as lightweight aggregate and geopolymer as binder, were investigated. Different compositions of the geopolymer binders (metakaolin or alumina-based) and two sizes of expanded vermiculite were tested. The produced composites were subjected tomicrostructural analyses, aswell as to thermal andmechanical tests. Densities ranged between 700 and 900 kg/m³, while the average strength and thermal conductivity were about 2 MPa and 0.2 W/mK, respectively. Results showthat lightweight composites can be produced with satisfactory density andmechanical and thermal properties compared with other materials used in building sector, such as plasterboard or cellular concrete. [ABSTRACT FROM AUTHOR]

Abstract: Mixtures of coal ashes from pulverized coal combustion (PCC) or fluidized bed combustion (FBC) and metakaolin were used to synthetize geopolymers. Upon full characterization of the raw powders (chemical and mineralogical composition), geopolymerization tests were conducted using an alkali aqueous solution of NaOH/Na2SiO3 at different dilutions. The produced geopolymers were subjected to SEM analysis, as well as to leaching, thermal and mechanical tests. The final microstructure and the properties of the geopolymers indicate that FBC ash can be conveniently used as a partially reactive filler in combination with the metakaolin powder. The composite material has good thermal performance and compressive strength (∼30 MPa) suitable for the building sector. [Copyright &y& Elsevier]

The development of QSAR models useful for the prediction of fish bioconcentration factor (BCF) for a wide range of different chemical classes is crucial for the assessment and prioritisation of potentially persistent bioaccumulative and toxic substances. In this study we present QSAR models for BCF developed on a wide range of chemical structural classes of environmental and toxicological interest (such as dyes and various chlorinated and brominated compounds). The aim is to provide valid QSAR models, statistically validated for predictivity, for the prediction of BCF in general, but also for problematical chemical classes such as highly hydrophobic chemicals. Several descriptors, calculated by different commercially available software packages, have been employed in order to take into account relevant information provided by physicochemical properties (octanol/water partition coefficient and water solubility) and molecular features (structural and quantum-chemical molecular descriptors). The best descriptor subsets for the models were selected using the Genetic Algorithm-Variable Subset Selection strategy (GA-VSS) and calculations were performed by ordinary least squares regression. Starting from a data set of 640 compounds (log K ow range from −2.34 to 12.66), we developed linear QSARs, firstly for a data set of 620 compounds (log K ow range from −2.34 to 10.35) and secondly specifically for 87 highly hydrophobic chemicals (log K ow range from 6.00 to 10.35). All these models have been statistically validated (both internally by cross-validation and bootstrap and externally, by “a priori” splitting of available data by Kohonen Map-ANN in training and prediction sets) and their structural chemical domain has been verified by the leverage approach. [Copyright &y& Elsevier]

Supporting or shaping a porous powder is important for industrial applications as optimized structure with high mass transfer, low pressure drop and high mechanical and chemical stability can be obtained. A new class of geopolymer-hydrotalcite composites with suitable mechanical and thermal properties were conceived as shaped materials for CO 2 adsorption applications at intermediate temperature (200–400 °C). Composite monoliths were produced mixing different commercial hydrotalcite-type (HyT) powders with a metakaolin-based geopolymer matrix with a molar ratio SiO 2 :Al 2 O 3 = 4.0. The compressive strength at room temperature and 500 °C ranged between 10 and 35 MPa, mainly depending on HyT powder morphology and composite total porosity. The composites were characterized and tested in term of CO 2 uptake. After calcination to convert HyT into an amorphous Mg:Al mixed solid oxide able to absorb CO 2 , the composites were tested in the CO 2 adsorption at 200 °C, with cycles of adsorption/desorption performed with intermediate regeneration at 500 °C. CO 2 adsorption capacity was in the range 0.375–0.461 mmol g−1 for HyT and between 0.109 and 0.145 mmol g−1 for composites, being 0.052 mmol g−1 the value for the geopolymer matrix. A partial deactivation of the HyT phases was also detected. • Geopolymer-hydrotalcite composites were developed for CO 2 uptake at 200 °C. • A partial deactivation of the hydrotalcite-type phases occurred in composites. • The contribution of physical reversible adsorption was ∼50% in composites. • The composites showed compressive strength at r.t. and 500 °C in the rage of 10–35 MPa. [ABSTRACT FROM AUTHOR]

Ion exchange represents a promising process for ammonium removal from municipal wastewater (MWW), in order to recover it for fertilizer production. Previous studies on ammonium ion exchange neglected the assessment of process robustness and the optimization the desorption/recovery step. This study aimed at developing a continuous-flow process of ammonium removal/recovery based on a metakaolin K-based geopolymer, named G13. Process robustness was assessed by operating 7 adsorption/desorption cycles with two types of MWW. These tests resulted in satisfactory and constant performances: operating capacity at 40 mg N L−1 in the inlet = 12 mg N g dry sorbent −1, bed volumes of treated MWW at the selected breakpoint = 199–226, ammonium adsorption yield = 88–91%. Empty bed contact time (EBCT) was decreased from 10 to 5 min without any reduction in performances. The NH 4 + adsorption process was effectively simulated by the Thomas model, allowing a model-based assessment of the effect of EBCT reductions on process performances. An innovative desorption procedure led to high ammonium recovery yields (86–100%) and to a desorbed product composed primarily of KNO 3 (54% w) and NH 4 NO 3 (39% w), two salts largely used in commercial fertilizers. The energy consumption of ammonium removal/recovery with G13 resulted 0.027 kWh m−3 treated WW , with a relevant reduction in comparison to traditional nitrification/denitrification, whereas the operational cost resulted equal to 60–110% of the cost of the benchmark process. These results show that G13 is a promising material to recover ammonium in a circular economy approach. [Display omitted] • Geopolymer G13 effectively removed & recovered NH 4 + from wastewater by ion exchange. • G13 resulted in high selectivity for NH 4 + and high operational capacity. • Performances resulted stable during 7 consecutive adsorption/desorption cycles. • Empty bed contact time was decreased from 10 to 5 min with no performance reduction. • Desorption led to product with high fertilizing power (KNO 3 54% w , NH 4 NO 3 39% w). [ABSTRACT FROM AUTHOR]

The tropospheric lifetime of most organic chemicals deriving from terrestrial emissions is mainly controlled by their degradation reaction with OH radicals and ozone during the daytime, and NO3 radicals at night. The studied data set, composed of 399 structurally heterogeneous volatile organic compounds (VOCs), consists of data for the three studied oxidation reactions, available either experimentally or from our herein reported quantitative structure–activity relationships (QSAR) models. A principal component analysis (PCA) model based on these principal oxidative degradations has been proposed to evaluate the overall tropospheric degradability of chemicals. The score of the first principal component can be proposed as an ATmospheric Degradability INdex (ATDIN) and is modelled by theoretical molecular descriptors to obtain a multiple linear regression (MLR) QSAR model with high predictive power, both internally and externally validated. This modelling approach allows a fast and preliminary VOC ranking according to their tendency to be degraded by atmospheric oxidants, starting only from the knowledge of their molecular structure. [Copyright &y& Elsevier]

The rate constant for the nighttime degradation of 114 heterogeneous organic compounds, through reaction with nitrate radicals in the troposphere, is predicted here by quantitative structure–activity relationships modelling. The multiple linear regression approach is based on a variety of theoretical molecular descriptors, selected by the genetic algorithms-variable subset selection procedure. The proposed model, calculated on a limited subset of compounds selected by a D-optimal experimental design and checked for reliability and robustness, has good predictivity, verified by internal (QLMO2=89.6%) and “external” validation (QEXT2=95.7%). The model applicability domain was always verified by the leverage approach in order to propose reliable predicted data. The average root-mean square error for the prediction of log kNO3 was 0.57, similar to (and even smaller than) the typical experimental error range. [Copyright &y& Elsevier]