Tracing the origin of VOCs in post-consumer plastic film bales

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

Integrating density functional theory and chemical ionization mass spectrometry techniques to assess benzophenone derivatives in food packaging: implications for enhancing food quality and safety

Benzophenone and related derivatives are widely used as photoinitiators for food packaging to cure inks or lacquers with ultraviolet (UV) light on cardboard and paper. However, there are concerns about the potential health risks of their migration into food. Knowing the physical and chemical properties of benzophenone and its derivatives could play a significant role in their quantification and analysis using chemical ionization mass spectrometry (CI-MS) methods. These parameters are evaluated using B3LYP/6-311++** density functional theory (DFT) implemented on Gaussian code. Ion-molecule chemistry through the selection of reagent ions, reaction energetics and kinetics, thermodynamic stability, and reactivity of molecules deemed to foster VOC identification and quantification via CI-MS techniques. The VOCs under study are expected to undergo exothermic reactions from H3 O+ , NH4 + , NO+ , and O2 + ions, except endothermic proton transfer from NH4 + to 2-hydroxy-4-methoxybenzophenone and 2,3,4-trihydroxy benzophenone. These compounds possess less proton affinities than NH3 and are least stable in their protonated forms. The DFT computed properties provide the basis for developing reliable and accurate methods to detect and measure the presence of benzophenone and its derivatives in packaging materials and food products.

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.