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Entropy driven chain effects on ligation chemistry
We report the investigation of fundamental entropic chain effects that enable the tuning of modular ligation chemistry – for example dynamic Diels–Alder (DA) reactions in materials applications – not only classically via the chemistry of the applied reaction sites, but also via the physical and steric properties of the molecules that are being joined. Having a substantial impact on the reaction equilibrium of the reversible ligation chemistry, these effects are important when transferring reactions from small molecule studies to larger or other entropically very dissimilar systems. The effects on the DA equilibrium and thus the temperature dependent degree of debonding (%debond) of different cyclopentadienyl (di-)functional poly(meth-)acrylate backbones (poly(methyl methacrylate), poly(iso-butyl methacrylate), poly(tert-butyl methacrylate), poly(iso-butyl acrylate), poly(n-butyl acrylate), poly(tert-butyl acrylate), poly(methyl acrylate) and poly(isobornyl acrylate)), linked via a difunctional cyanodithioester (CDTE) were examined via high temperature (HT) NMR spectroscopy as well as temperature dependent (TD) SEC measurements. A significant impact of not only chain mass and length with a difference in the degree of debonding of up to 30% for different lengths of macromonomers of the same polymer type but – remarkably – as well the chain stiffness with a difference in bonding degrees of nearly 20% for isomeric poly(butyl acrylates) is found. The results were predicted, reproduced and interpreted via quantum chemical calculations, leading to a better understanding of the underlying entropic principles.
Assessment of Subsampling Strategies in Microspectroscopy of Environmental Microplastic Samples
The analysis of environmental occurrence of microplastic (MP) particles has gained notable attention within the past decade. An effective risk assessment of MP litter requires elucidating sources of MP particles, their pathways of distribution and, ultimately, sinks. Therefore, sampling has to be done in high frequency, both spatially and temporally, resulting in a high number of samples to analyze. Microspectroscopy techniques, such as FTIR imaging or Raman particle measurements allow an accurate analysis of MP particles regarding their chemical classification and size. However, these methods are time-consuming, which gives motivation to establish subsampling protocols that require measuring less particles, while still obtaining reliable results. The challenge regarding the subsampling of environmental MP samples lies in the heterogeneity of MP types and the relatively low numbers of target particles. Herein, we present a comprehensive assessment of different proposed subsampling methods on a selection of real-world samples from different environmental compartments. The methods are analyzed and compared with respect to resulting MP count errors, which eventually allows giving recommendations for staying within acceptable error margins. Our results are based on measurements with Raman microspectroscopy, but are applicable to any other analysis technique. We show that the subsampling-errors are mainly due to statistical counting errors (i.e., extrapolation from low numbers) and only in edge cases additionally impacted by inhomogeneous distribution of particles on the filters. Keeping the subsampling-errors low can mainly be realized by increasing the fraction of MP particles in the samples.