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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Nanoplastics Remediation Sign in to save

Sample transformation in online separations: how chemical conversion advances analytical technology

Chemical Communications 2023 10 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Annika A. M. van der Zon, Joshka Verduin, Bob W.J. Pirok Rick S. van den Hurk, Andrea Gargano, Bob W.J. Pirok

Summary

This paper is not about microplastics — it reviews how chemical transformation techniques (molecular weight reduction, controlled degradation, derivatization) can be incorporated into analytical workflows to improve characterization of complex biological and synthetic polymer samples, including protein therapeutics and nanoparticles.

While the advent of modern analytical technology has allowed scientists to determine the complexity of mixtures, it also spurred the demand to understand these sophisticated mixtures better. Chemical transformation can be used to provide insights into properties of complex samples such as degradation pathways or molecular heterogeneity that are otherwise unaccessible. In this article, we explore how sample transformation is exploited across different application fields to empower analytical methods. Transformation mechanisms include molecular-weight reduction, controlled degradation, and derivatization. Both offline and online transformation methods have been explored. The covered studies show that sample transformation facilitates faster reactions (<i>e.g.</i> several hours to minutes), reduces sample complexity, unlocks new sample dimensions (<i>e.g.</i> functional groups), provides correlations between multiple sample dimensions, and improves detectability. The article highlights the state-of-the-art and future prospects, focusing in particular on the characterization of protein and nucleic-acid therapeutics, nanoparticles, synthetic polymers, and small molecules.

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