RESEARCH INTERESTS

molecular simulation, multiscale modelling, machine learning-aided molecular simulation, macromolecules, polymer-based materials, ionic liquids

ABOUT/BIOGRAPHY

Dr. Niki Vergadou holds a BSc in Physics from the University of Ioannina, Greece, an MSc Degree in Polymer Science and its Applications and a PhD (2006), both from the Chemistry Department of the University of Athens, Greece. Her work involves the development and implementation of computational methods and algorithms for the molecular simulation of materials, the prediction of their properties and the investigation of the molecular mechanisms that govern the macroscopic behavior of materials. Her research interests include the study of complex chemical systems such as non-ideal fluids, ionic liquids, macromolecular, graphitic and composite materials using a multitude of methodologies at various length and time-scales such as transition state theory of infrequent events (TST), molecular dynamics (MD) and Monte Carlo (MC) simulations, coarse-grained (CG) models and Kinetic Monte Carlo techniques (KMC). She is also working on the development of integrated schemes of artificial intelligence (AI) and machine learning (ML) methods in molecular simulation and materials modelling.

PUBLICATIONS

Schmidt, Patrick S., Kankanamge, Chathura J., Klose, Jörn, Jander, Julius H., Vergadou, Niki, Economou, Ioannis G., Klein, Tobias and Fröba, Andreas P., Fick Diffusion Coefficients of Polystyrene Oligomers with Dissolved Blowing Agents by Dynamic Light Scattering and Molecular Dynamics Simulations Macromolecules, Volume 58, Pages: 10238 – 10252, 2025 [doi]

Gerakinis, Dimitrios-Paraskevas, Ricci, Eleonora, Giannakopoulos, George, Karkaletsis, Vangelis, Theodorou, Doros N. and Vergadou, Niki, Molecular Simulation of Coarse-grained Systems using Machine Learning ACM International Conference Proceeding Series, Volume 43, Pages: 1 - 6, 2024 [doi]

Dellis, Spilios, Ricci, Eleonora, Gerakinis, Dimitrios-Paraskevas, Vergadou, Niki and Giannakopoulos, George, Self-Adaptive Optimization of Coefficients in Multi-Objective Loss Functions ACM International Conference Proceeding Series, Volume 46, Pages: 1 - 9, 2024 [doi]

Ricci, Eleonora and Vergadou, Niki, Integrating Machine Learning in the Coarse-Grained Molecular Simulation of Polymers Journal of Physical Chemistry B, Volume 127, Pages: 2302 – 2322, 2023 [doi]

Romanos, G., Vergadou, N. and Economou, I.G., Ionic Liquids in Carbon Capture CRC Press, Pages: 73-141, 2022 [doi]

Ricci, Eleonora, Giannakopoulos, George, Karkaletsis, Vangelis, Theodorou, Doros N. and Vergadou, Niki, Developing Machine-Learned Potentials for Coarse-Grained Molecular Simulations: Challenges and Pitfalls Article Number: 51, 2022 [doi]

Nasikas, Dimitris, Ricci, Eleonora, Giannakopoulos, George, Karkaletsis, Vangelis, Theodorou, Doros N. and Vergadou, Niki, Investigation of Machine Learning-Based Coarse-Grained Mapping Schemes for Organic Molecules Article Number: 51, 2022 [doi]

Ricci, E., Vergadou, N., Vogiatzis, G.G., De Angelis, M.G. and Theodorou, D.N., Molecular Simulations and Mechanistic Analysis of the Effect of CO2Sorption on Thermodynamics, Structure, and Local Dynamics of Molten Atactic Polystyrene Macromolecules, Volume 53, Pages: 3669-3689, 2020 [doi]

Vergadou, N. and Theodorou, D.N., Molecular modeling investigations of sorption and diffusion of small molecules in Glassy polymers Membranes, Volume 9, Article Number: 98, 2019 [doi]

Economou, I.G., Krokidas, P., Michalis, V.K., Moultos, O.A., Tsimpanogiannis, I.N. and Vergadou, N., The role of molecular thermodynamics in developing industrial processes and novel products that meet the needs for a sustainable future Pages: 635-660, 2017 [doi]

Vergadou, N., Androulaki, E. and Economou, I.G., Molecular Simulation Methods for CO2 Capture and Gas Separation With Emphasis to Ionic Liquids Taylor and Francis, Pages: 79-111, 2017 [doi]

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