Application of chemometric tools in the QSAR development of VOC removal in plastic waste recycling

Deodorization and, in a broader sense, the removal of volatile organic compounds (VOCs) from plastic waste have become increasingly important in the field of plastic recycling, and various new decontamination techniques have been developed. Both in research and industrial practice, the selection of VOCs has been random or unsubstantiated, making it difficult to compare studies and assess decontamination processes objectively. Thus, this study proposes the use of Statistical Molecular Design (SMD) and Quantitative Structure - Activity Relationship (QSAR) as chemometric tools for the selection of representative VOCs, based on physicochemical properties. Various algorithms are used for SMD; hence, several frequently used D-Optimal Onion Design (DOOD) and Space-Filling (SF) algorithms were assessed. Hereby, it was validated that DOOD, by dividing the layers based on the equal-distance approach without so-called 'Adjacent Layer Bias', results in the most representative selection of VOCs. QSAR models that describe VOC removal by water-based washing of plastic waste as a function of molecular weight, polarizability, dipole moment and Hansen Solubility Parameters Distance were successfully established. An adjusted-R2 value of 0.77 ± 0.09 and a mean absolute error of 24.5 ± 4 % was obtained. Consequently, by measuring a representative selection of VOCs compiled using SMD, the removal of other unanalyzed VOCs was predicted on the basis of the QSAR. Another advantage of the proposed chemometric selection procedure is its flexibility. SMD allows to extend or modify the considered dataset according to the available analytical techniques, and to adjust the considered physicochemical properties according to the intended process.

Toward More Universal Prediction of Polymer Solution Viscosity for Solvent-Based Recycling

The viscosity of polymer solutions is important for both polymer synthesis and recycling. Polymerization reactions can become hampered by diffusional limitations once a viscosity threshold is reached, and viscous solutions complicate the cleaning steps during the dissolution–precipitation technique. Available experimental data is limited, which is more severe for green solvents, justifying dedicated viscosity data recording and interpretation. In this work, a systematic study is therefore performed on the viscosity of polystyrene solutions, considering different concentrations, temperatures, and conventional and green solvents. The results show that for the shear rate range of 1–1000 s^–1, the solutions with concentrations between 5 and 39 wt % display mainly Newtonian behavior, which is further confirmed by the applicability of the segment-based Eyring-NRTL and Eyring-mNRF models. Moreover, multivariate data analysis successfully predicts the viscosity of polystyrene solutions under different conditions. This approach will facilitate future data recording for other polymer–solvent combinations while minimizing experimental effort.

Environmental Performance Assessment of a Novel Process Concept for Propanol Production from Widely Available and Wasted Methane Sources

Currently, propanol production highly depends on conventional fossil resources. Therefore, an alternative production process, denoted as “C123”, is proposed and evaluated in which underutilized and methane-rich feedstocks such as biogas (scenario BG), marginal gas (scenario MG), and associated gas (scenario AG) are converted into propanol. A first modular-scale process concept was constructed in Aspen Plus, based on experimental data and know-how of the C123 consortium partners. The environmental performance of the considered scenarios was compared at the life cycle level by calculating key performance indicators (KPIs), such as the global warming burden. The results showed that scenario BG is the least dependent on fossil fuels for energy use. Scenario AG seems the most promising one based on almost all selected KPIs when taking into account the avoided gas flaring emissions. The performance of the C123 process concept could be improved by applying heat integration in the process concept.

The temporoinsular projection system: an anatomical study

OBJECTIVE

Connections between the insular cortex and the amygdaloid complex have been demonstrated using various techniques. Although functionally well connected, the precise anatomical substrate through which the amygdaloid complex and the insula are wired remains unknown. In 1960, Klingler briefly described the “fasciculus amygdaloinsularis,” a white matter tract connecting the posterior insula with the amygdala. The existence of such a fasciculus seems likely but has not been firmly established, and the reported literature does not include a thorough description and documentation of its anatomy. In this fiber dissection study the authors sought to elucidate the pathway connecting the insular cortex and the mesial temporal lobe.

METHODS

Fourteen brain specimens obtained at routine autopsy were dissected according to Klingler’s fiber dissection technique. After fixation and freezing, anatomical dissections were performed in a stepwise progressive fashion.

RESULTS

The insula is connected with the opercula of the frontal, parietal, and temporal lobes through the extreme capsule, which represents a network of short association fibers. At the limen insulae, white matter fibers from the extreme capsule converge and loop around the uncinate fasciculus toward the temporal pole and the mesial temporal lobe, including the amygdaloid complex.

CONCLUSIONS

The insula and the mesial temporal lobe are directly connected through white matter fibers in the extreme capsule, resulting in the appearance of a single amygdaloinsular fasciculus. This apparent fasciculus is part of the broader network of short association fibers of the extreme capsule, which connects the entire insular cortex with the temporal pole and the amygdaloid complex. The authors propose the term “temporoinsular projection system” (TIPS) for this complex.