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2D-LC Bounding Gradient
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2026-02-19
Polymers are not single, well-defined molecules. They are complex distributions of chain lengths, chemical compositions, architectures, microstructures, particle sizes, and surface properties. These distributions determine how polymer materials behave, but they are often difficult to resolve with conventional analytical workflows.
Computational Polymer Analytics develops methods that combine advanced separations, mass spectrometry, chemometrics, and algorithmic data analysis to extract chemically meaningful information from complex polymer datasets. Led by Dr. Tijmen S. Bos within the CAST environment, this research line focuses on translating information-rich chromatographic and mass-spectrometric data into interpretable molecular distributions.
The work connects academic research with applied analytical practice through Innovative Data Evaluation And Separations (IDEAS)
Through IDEAS, Dr. Bos develops independent activities in chromatographic method development, polymer characterization, data analysis, software-supported workflows, and training for academic and industrial laboratories.
Focus areas: polymer characterization · LC-MS · multidimensional chromatography · chemometrics · algorithm development · automated data analysis · applied analytical workflows
Bio-based and cellulose-derived polymers are analytically challenging because chemical substitution patterns can vary across complex molecular distributions. We develop LC-MS and data-deconvolution workflows to characterize monomer composition and substitution patterns after controlled degradation, supporting deeper analysis of materials used in pharmaceuticals, food, coatings, and related applications.
Polymer conformation influences solution behavior, processing, and application performance. Instead of relying only on average descriptors, we develop algorithms that extract molecular-shape information across the molecular-weight distribution, enabling more detailed interpretation of intra- and intermolecular interactions.
Copolymer properties depend not only on molecular weight and overall composition, but also on how monomer units are arranged along the chain. We develop computational methods for reconstructing block-length distributions from fragmentation data, enabling detailed insight into copolymer microstructure and supporting more rational materials design.
Polymer nanoparticles can vary in particle size, surface charge, and related physicochemical properties. We develop separation-based and computational workflows to assess these distributions with greater detail, supporting applications where nanoparticle stability and performance depend on surface characteristics.
Living with Breakthrough: Two-Dimensional Liquid-Chromatography Separations of a Water-Soluble Synthetically Grafted Bio-Polymer
H.C. van de Ven, J. Purmova, G. Groeneveld, T.S. Bos, A.F.G. Gargano, Sj. van der Wal, Y. Mengerink, P.J. Schoenmakers,
Separations, 2020, 7 (3), 41. DOI: 10.3390/separations7030041.
Composition mapping of highly substituted cellulose-ether monomers by liquid chromatography–mass spectrometry and probability-based data deconvolution
T.S. Bos, J.S. Desport, A. Buijtenhuijs, J. Purmova, L. Karlson, B.W.J. Pirok, P.J. Schoenmakers, G.W. Somsen, J Chromatogr A 1689, 2023, 463758. DOI: 10.1016/j.chroma.2022.463758.
Quantitative assessment of polymer molecular shape based on changes in the slope of the Mark-Houwink plot derived from size-exclusion chromatography with triple detection
T.S. Bos, H.J.A. Philipsen, B.B.P. Staal, J. Purmova, R.J.L. Beerends, A. Buijtenhuijs, L. Karlson, P.J. Schoenmakers, G.W. Somsen,
J Appl Polym Sci 141, 2024, e55013. DOI: 10.1002/app.55013.
Fingerprinting of hydroxy propyl methyl cellulose by comprehensive two-dimensional liquid chromatography-mass spectrometry of monomers resulting from acid hydrolysis
Tijmen S Bos, Bob WJ Pirok, Leif Karlson, Staffan Schantz, Tina A Dahlseid, Dwight R Stoll, Govert W Somsen
Journal of Chromatography A, 2024, 464874. DOI: 10.1016/j.chroma.2024.464874
Development of a comprehensive normal-phase liquid chromatography × size-exclusion chromatography platform with ultraviolet spectroscopy and high-resolution mass spectrometry detection for the chemical characterization of complex polyesters
Gino Groeneveld, Andrea FG Gargano, Robert LC Voeten, Tijmen S Bos, Paul Buijsen, Ron AH Peters, Peter J Schoenmakers
Analytica Chimica Acta, 2024, 342086. DOI: 10.1016/j.aca.2024.343086
The Role of Artificial Intelligence and Machine Learning in Polymer Characterization: Emerging Trends and Perspectives
Rick S van den Hurk, Bob WJ Pirok, Tijmen S Bos
Introducing an algorithm to accurately determine copolymer block-length distributions
Rick S van den Hurk, Ynze Mengerink, Ron AH Peters, Arian C van Asten, Bob WJ Pirok, Tijmen S Bos
Analytica Chimica Acta, 2025, 343990. DOI: 10.1016/j.aca.2025.343990
Determination of Copolymer Block-Length Distributions Using Fragmentation Data Obtained from Tandem Mass Spectrometry
Tijmen S Bos, Rick S van den Hurk, Ynze Mengerink, Ton Brooijmans, Ron AH Peters, Arian C van Asten, Bob WJ Pirok
Negotiating system’s band broadening in hydrodynamic chromatography for the determination of particle-size distributions of polymeric nanoparticles
Joshka Verduin, Jordy D Kruijswijk, Stef RA Molenaar, Nino BL Milani, Tijmen S Bos, Ron AH Peters, Bob WJ Pirok, Govert W Somsen
Analytica Chimica Acta, 2025, 344342. DOI: 10.1016/j.aca.2025.344342
Assessment of Particle Size-Resolved Surface-Charge Density Distributions of Polymer Nanoparticles by Capillary Zone Electrophoresis
Jordy D Kruijswijk, Tijmen S Bos, Billy Van Zanten, Ton Brooijmans, Ron AH Peters, Kevin Jooß, Govert W Somsen
Analytical chemistry, 2025. DOI: 10.1021/acs.analchem.5c05189
Quantifying Poly(lactide-co-glycolide) Residual Dimer-Alternating Structure and Block-Length Distribution Using Controlled Chemical Degradation and Reverse-Phase Liquid Chromatography–Mass Spectrometry Analysis
Masashi Serizawa, Dion Snijders, Stefan van Berkel, Pieter van Delft, Tijmen S Bos, Bob WJ Pirok, Ron AH Peters, Peter J Schoenmakers, Andrea FG Gargano
Macromolecules, 2026. DOI: 10.1021/acs.macromol.5c03061
This tool is currently under active development, and the website is undergoing testing.
The study addresses size-resolved surface charge density (SCD) analysis of polymer nanoparticles (PNPs), revealing the significant variability of SCD that traditional methods overlook. By employing advanced capillary zone electrophoresis techniques, researchers can gain detailed insights into nanoparticle performance, benefiting applications in coatings, biomedical, and industrial contexts through collaborative innovations.
As multidimensional chromatography continues to expand its reach across complex analytical challenges, the precision of data interpretation increasingly depends on what happens after separation. In