Theory and modeling for Organic Electronics - Prof. Igor Zozoulenko's group
Our vision
Materials Science witnesses evolution from traditional “trial-and-error” approaches into cutting-edge computational materials discovery, device design, and machine learning. This paradigm shift, highlighted by two recent Nobel Prizes awarded in 2024 for advancements in materials simulation and discovery, is foundational to our vision: to establish computational modeling and simulation as standard tools in materials engineering, discovery and device design.
What we do:
We provide fundamental understanding of structure-property relationship, i.e. answering questions Why? How? E.g.:
We perform simulations and modelling of devices and materials to guide and interpret experiments
What we do: Materials
What we do: Scale, phenomena and methods
What we do: Recent and current projects
I. Electronic properties
Electronic and optical properties of p-doped and n-doped conducting polymers. Polymerization, Oxidation reduction reactions and hydrogen evolution. Intrinsic volumetric capacitance and the Density of States (DOS) of conducting polymers.
Representative publications:
I Sahalianov, et al., The intrinsic volumetric capacitance of conducting polymers: pseudo-capacitors or double-layer supercapacitors? RSC Advances, 2019, 9, 42498; https://doi.org/10.1039/C9RA10250G
Igor Zozoulenko, et al., Polarons, bipolarons, and absorption spectroscopy of PEDOT. ACS Applied Polymer Materials, 2018, 1, 83; https://doi.org/10.1021/acsapm.8b00061
.
II.Morphology
Morphology of conducting polymers; mechanical properties and water intake; swelling.
Representative publications:
M Modarresi, et al., Microscopic Understanding of the Granular Structure and the Swelling of PEDOT: PSS, Macromolecules, 2020, 53, 6267; https://doi.org/10.1021/acs.macromol.0c00877
S Ghosh, I Zozoulenko, Effect of Substrate on Structural Phase Transition in a Conducting Polymer during Ion Injection and Water Intake: A View from a Computational Microscope, ACS Applied Electronic Materials, 2020, 2, 4034; https://doi.org/10.1021/acsaelm.0c00833
ACS Appl. Electron. Mat., 2020, 2, 4034
Macromolecules 2021, 54, 6552
III. Transport
Electronic mobility and ion diffusion in conducting polymers. Temporal electron dynamics.
Representative publications:
N. Zahabi and I. Zozoulenko, Band Versus Hopping Transport in Conducting Polymers by Ab Initio Molecular Dynamics: Exploring the Effect of Electric Field, Trapping and Temperature Adv. Electron. Mater. 2024, 2400239; https://doi.org/10.1002/aelm.202400239
T. Sedghamiz, et al., What Can We Learn about PEDOT:PSS Morphology from Molecular Dynamics Simulations of Ionic Diffusion? 2023, Chemistry of Materials, 35, 5512; https://doi.org/10.1021/acs.chemmater.3c00873
N Rolland, et al., Large scale mobility calculations in PEDOT (Poly (3, 4-ethylenedioxythiophene)): Backmapping the coarse-grained MARTINI morphology, Computational Materials Science, 2020, 179, 109678; https://doi.org/10.1016/j.commatsci.2020.109678
Phys. Rev. Materials, 2018, 2, 045605
Chem. Mater., 2023, 35, 5512
Adv. Electron. Mater. 2024, 2400239
IV. Wood-based materials
Cellulose nanocrystals: assembly and re-generation; Water intake and drying. Colloidal stability; Lignin: structure and interaction with cellulose, water, solvents. Developing coarse-grained and supra coarse-grained molecular dynamics models. Representative publications:
J Pang, et al., A computational study of cellulose regeneration: Coarse-grained molecular dynamics simulations, Carbohydrate Polymers, 2023, 311, 120853; https://doi.org/10.1016/j.carbpol.2023.120853
AY Mehandzhiyski, et al., Microscopic Insight into the Structure–Processing–Property Relationships of Core–Shell Structured Dialcohol Cellulose Nanoparticles, ACS Appl. Bio Mat. 2022, 5, 4793; https://doi.org/10.1021/acsabm.2c00505
Mohit Garg, et al., Moisture Uptake in Nanocellulose: The Effect of Relative Humidity, Temperature and Degree of Crystallinity, Cellulose, 2021, 28, 9007; https://doi.org/10.1007/s10570-021-04099-9
ACS Applied Energy Materials, 2019, 2, 3568Cellulose nanocrystals covered by absorbed water molecules. Image: Aleksandar Mehandzhiyski.
V. Device modelling
Device modelling using Nernst-Planck-Poisson equations: battery half-cell, organic electrochemical transistors (OECT), organic electrolyte-gated field-effect transistor (EGOFET), redox-flow batteries, thermoelectric generators, electrochemical cells, thermal battery management and more.
Representative publications:
S. Lander et al., Controlling the rate of posolyte degradation in all-quinone aqueous organic redox flow batteries by sulfonated nanocellulose based membranes: The role of crossover and Michael addition, Journal of Energy Storage, 2024, 83, 110338. https://doi.org/10.1016/j.est.2023.110338
