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Analytical chemistry researchers at the University of Amsterdam's Van 't Hoff Institute for Molecular Sciences (HIMS) have developed a novel algorithm that significantly improves the analysis of copolymers. It allows the determination of their block structure, which has until now been impossible using common analytical approaches. The researchers present their achievement in two recent papers in and .

The research was conducted within the public-private PARADISE consortium. It aims to better understand the hidden complexities of polymer materials and open the door to a new generation of smart, sustainable polymers by bringing advanced data analysis into the heart of materials science. The consortium consists of academic researchers at Vrije Universiteit Amsterdam (VU) and the University of Amsterdam (UvA) with experts from industrial partners Covestro, DSM, Shell, and Genentech.

The novel algorithm now published was developed in a cooperation between Ph.D. candidate Rick van den Hurk, postdoc researcher Tijmen Bos and associate professor Bob Pirok, together with scientists Ynze Mengerink at Brightlands Chemelot Campus and Prof. Ron Peters at Covestro.

Computationally unraveling the structure of a block copolymer

In copolymers, the block-length distribution reflects how frequently different block arrangements occur. This distribution plays a key role in determining a material's performance characteristics, including its flexibility, strength, and biodegradability.

Until now, accurately measuring these distributions at the molecular level has been a major challenge since traditional techniques such as nuclear magnetic resonance (NMR) can only offer averaged information.

The newly developed algorithm changes this by combining tandem mass spectrometry (MS/MS) data with a smart computational approach that takes fragmentation behavior into account. The algorithm allows researchers to reconstruct how abundant different block-lengths are present within a copolymer sample, giving a much more detailed picture of the material's internal structure. The algorithm driving this was recently published in Analytica Chimica Acta.

With their latest paper in Macromolecules, the group of Pirok has applied the algorithm to study polyamides and polyurethanes, which are industrial polymers that are found in everything from textiles to insulation foams. Notably, the findings showed that even polymers with the same chemical makeup can have very different block distributions, depending on how they were synthesized. These subtle differences can explain variations in material performance that would otherwise remain hidden.

The ability to determine block-length distributions with such precision not only improves our understanding of polymer chemistry but also opens the door to the rational design of next-generation materials. By fine-tuning the block arrangement, scientists and engineers can tailor materials more precisely to specific applications. It could also support the development of more sustainable materials, as better control over structure may lead to improved recyclability or allow for the use of bio-based feedstocks.