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Related Experiment Video

Updated: Apr 15, 2026

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

Martini 3 Coarse-Grain Model For Linear Perfluoroalkyl Substances.

Alessandro Calza^1,2, Matteo Calvaresi^1,2, Francesco Zerbetto¹

¹Dipartimento di Chimica "Giacomo Ciamician," Alma Mater Studiorum - Università di Bologna, 40129 Bologna, Italy.

Journal of Chemical Theory and Computation

|April 14, 2026

Summary

This summary is machine-generated.

Researchers developed a new computational model for per- and polyfluoroalkyl substances (PFAS), also known as "forever chemicals." This accurate model aids in predicting PFAS behavior and environmental interactions.

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MALDI-ToF MS Method for the Characterization of Synthetic Polymers with Varying Dispersity and End Groups

Published on: October 3, 2025

Area of Science:

Environmental Chemistry
Computational Chemistry
Materials Science

Background:

Per- and polyfluoroalkyl substances (PFAS) are widespread industrial chemicals with significant environmental and health concerns.
Understanding PFAS behavior requires advanced computational tools due to their persistence and diverse applications.

Purpose of the Study:

To develop an accurate and transferable coarse-grain model for simulating PFAS behavior.
To enable high-throughput computational studies on PFAS interactions with various substrates.

Main Methods:

Parametrization of a coarse-grain model for 18 linear perfluorocarboxylic and perfluorosulfonic acids using the Martini 3 force field.
Validation of the model through standard Martini procedures, self-aggregation studies, and interaction analysis with graphene.
Comparison of simulation results with all-atom simulations and experimental data.

Main Results:

The developed coarse-grain PFAS model accurately reproduces key structural and physical properties.
The model successfully predicts PFAS self-aggregation and interaction with graphene surfaces.
Simulation results show high consistency with experimental data and all-atom simulations.

Conclusions:

The new coarse-grain PFAS model provides a reliable tool for large-scale simulations.
This model facilitates the exploration of PFAS interactions with nanoparticles and biomolecules.
The study advances computational approaches for assessing environmental risks of PFAS.