From the beginning, the project has focused on analyzing MOFs for separating xylene isomers—a critical task for the chemical industry.
In the first phase (WP1), an existing MOF database was screened using a newly developed Python-based software package. This automated workflow, designed for HPC systems, enabled large-scale simulations to evaluate MOFs’ interactions with xylene mixtures by measuring adsorption, diffusion, and selectivity.
The simulations combined classical molecular dynamics, grand-canonical Monte Carlo, and Density Functional Theory to explore MOF flexibility during separation. This helped identify key structural features, such as pore size, diffusion paths, and adsorption energies, that influence performance. These insights were used to build a training dataset for the next phase (WP2).
In WP2, statistical methods including Principal Component Analysis (PCA), Cluster Analysis (CA), and Multiple Regression (MR) were applied to reveal complex structure-performance relationships. These techniques enabled the design of better MOFs using faster, simpler models, reducing reliance on expensive simulations.
Results have been shared through numerous invited talks and presentations, including:
- Invited Lecture: Suyetin M. (2025), Prediction of Adsorption and Separation Properties of Metal-Organic Frameworks: A Decade of Advancements from Molecular Simulations to Machine Learning Approaches. / Friedrich Schiller University Jena (Friedrich-Schiller-Universität Jena), Germany.
- Invited Lecture: Suyetin M. (2025), Multi-scale simulations of material properties. / Martin Luther University Halle-Wittenberg. (Martin-Luther-Universität Halle-Wittenberg), Germany.
- Suyetin M. (2024), Exploring the Limits of Zr-MOFs in Adsorption Pumps: A computational Study on their Potential for Cooling and Heating Applications / MOF2024, Singapore.
- Invited Lecture: Suyetin M. (2024), Current atomistic approaches for simulating material properties. / Helmholtz Association - Jülich Research Center, Germany.
- Invited Lecture: Suyetin M. (2024), Atomistic methods for modelling material properties. / Swansea University, UK.
- Suyetin M. (2023), Small Molecules Separation via Molecular Dynamics Simulations in Metal - Organic Frameworks / 9th bwHPC Symposium: Computational Chemistry and Materials Science, The University of Mannheim, Germany.
- Invited Lecture: Suyetin M. (2023) Investigating the separation of small molecules by utilizing Molecular Dynamics Simulations on Model of Flexible Metal-Organic Frameworks. / CECAM Flagship workshop: Fluids in porous materials: from fundamental physics to engineering applications, EPFL, Switzerland.
- Invited Lecture: Suyetin M. (2023) Simulation approaches in simulations of molecules separation / CECAM Flagship Workshop: Computational methods for modelling bionano interactions and nanomaterials functionality/The effective implicit surface model (EISM) for predicting and understanding peptide-surface interactions. University College Dublin, Ireland.
- Invited Lecture: Suyetin M. (2023) Application of simulation approaches for MOFs’ research. / School of Chemistry, the University of Manchester, UK.
