Atomic scale modelling of proton transport in grain boundaries of BCZY by ab-initio and machine learning molecular dynamics simulations

• Applicant: Sabrina Sicolo, Ph.D.
• Subject Area: Computer-Aided Design of Materials and Simulation of Materials Behaviour from Atomic to Microscopic Scale ; Materials in Sintering Processes and Generative Manufacturing Processes ; Theoretical Chemistry: Electronic Structure, Dynamics, Simulation ; Theoretical Chemistry: Molecules, Materials, Surfaces
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 556363981

This project investigates the atomic-scale mechanisms governing proton transport in Y-doped perovskite ceramic electrolytes, with a focus on the role of grain boundaries (GBs). Although the bulk regions of these materials offer high proton conductivity, grain boundaries often introduce significant resistance, limiting their performance in applications such as fuel cells and hydrogen-based energy devices. Understanding the chemical, structural, and electronic factors behind this resistance is essential for improving material design. The project aims to explore charge compensation mechanisms, defect segregation, and transport processes in both the bulk and at grain boundaries. Y-doping leads to acceptor defects compensated by oxygen vacancies and mobile protons, but the interplay of these defects, especially under different thermal and hydration conditions, remains incompletely understood. Grain boundaries act as sinks for defects and polarons, modifying local electrostatic environments and potentially trapping mobile species, which hampers conductivity. To address these challenges, we combine density functional theory (DFT) with machine learning-based molecular dynamics (ML-MD). DFT will be used to calculate defect formation energies, polaron behavior, and dopant interactions. This data informs ML-MD simulations, enabling large-scale modeling of proton diffusion in realistic polycrystalline microstructures. These simulations will capture the effects of GB structure, misorientation, dopant distribution, and strain on proton mobility. Key questions include how dopants and local chemistry influence defect stability and transport; how grain boundary characteristics affect proton trapping and polaron dynamics; and how microstructural features like curvature, GB energy, or local strain predict conductivity. The goal is to identify structure-property relationships that link atomic-scale processes to macroscopic performance. By integrating quantum and data-driven approaches, this project seeks to reveal the origins of grain boundary resistance and to define design principles for tailoring GB properties. The outcomes will support the development of advanced proton-conducting ceramics with enhanced efficiency and durability for energy applications.

• DFG Programme: Research Units
• Subproject of: FOR 5966: Synergistic Design of Proton Conducting Ceramics for Energy Technology (SynDiPET)
• Co-Investigator: Professor Dr. Karsten Albe