Presence of Siloxanes in the Biogas of a Wastewater Treatment Plant Separation in Condensates and Influence of the Dose of Iron Chloride on its Elimination

The siloxanes present in the biogas produced during anaerobic digestion damage the mechanism of cogeneration equipment and, consequently, negatively affect the energy valorization process. For this reason, the detection and elimination of these silicon-derived chemical compounds are a priority in the management of cogeneration facilities. In this regard, the objectives of this paper are, firstly, to characterize the siloxanes in the biogas and, secondly, to qualitatively evaluate the influence of the dose of iron chloride on its elimination. The research was performed at the Rincón de León Wastewater Treatment Plant (Alicante, Spain). The outflow biogas of the digesters and of the pressurized gasometers was sampled and analyzed. The results obtained made it possible to demonstrate, firstly, the absence of linear siloxanes and that, of the cyclic siloxanes, the predominant type was decamethylcyclopentasiloxane, and, secondly, that the addition of iron chloride in the digesters significantly reduces the siloxane content in the biogas. Additionally, it was demonstrated that the process of compression of the biogas, with the elimination of condensates, also produces significant reductions in the concentration of siloxanes in the biogas.

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.

Raman spectroscopy study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the thermal annealing pathway

We report a multi-wavelength Raman spectroscopy study of the structural changes along the thermal annealing pathway of a poly(furfuryl alcohol) (PFA) derived nanoporous carbon (NPC). The Raman spectra were deconvoluted utilizing G, D, D′, A and TPA bands. The appropriateness of these deconvolutions was confirmed via recovery of the correct dispersive behaviours of these bands. It is proposed that the ID/IG ratio is composed of two parts: one associated with the extent of graphitic crystallites (the Tuinstra–Koenig relationship), and a second related to the inter-defect distance. This model was used to successfully determine the variation of the in-plane size and intra-plane defect density along the annealing pathway. It is proposed that the NPC skeleton evolves along the annealing pathway in two stages: below 1600 °C it was dominated by a reduction of in-plane defects with a minor crystallite growth, and above this temperature growth of the crystallites accelerates as the in-plane defect density approaches zero. A significant amount of transpolyacetylene (TPA)-like structures was found to be remaining even at 2400 °C. These may be responsible for resistance to further graphitization of the PFA-based carbon at higher temperatures.