Namita Krishnan
MSc Student

I am a Master’s student researching on the influence of doping on the lattice dynamics and sodium ion conductivity of Na₃SbS₄. Additionally, I am exploring the potential of machine learning force fields to model and predict these effects, aiming for computational efficiency compared to traditional ab initio molecular dynamics. My interest in this research stems from its critical relevance in advancing battery and energy technologies, aligning with my passion for contributing to the fight against climate change.
Educational background: B.Sc Physics (TUM 2022)
Hobbies: Reading, cooking, singing, hiking

Yufeng Xu
MSc Student

Hello! I’m Yufeng, a master student at TU Munich majoring in Chemistry.  I joined the group in February 2025 as a research intern, where my research focuses on modeling of high-entropy materials, aiming to uncover structure-property relationships that enhance ionic conductivity, with the goal of advancing materials for energy applications. I am passionate about bridging theoretical insights with experimental innovation to address key challenges in materials science. Education background: B. Sc Chemistry (University of Vienna, 2024)

Levon Satzger
MSc Student

I am a Master’s student currently investigating the performance of machine learning interatomic potentials (MLIPs) compared to density functional theory (DFT) for studying the properties of solid-state ionic conductors. My research aims to leverage the strengths of machine learning methods to characterize high-entropy alloys, providing deeper insight into their local structural and transport properties. Additionally, I am exploring the transferability of MLIPs across different materials to enable time-efficient and accurate materials analysis.
Educational background: B.Sc. Physics (LMU Munich, 2024)
Hobbies: Weightlifting, motorsports, cooking

Maximilian Whitfield
MSc Student

I’m a Master’s student conducting my thesis research jointly at the Max Planck Institute for Solid State Research and at TUM. My project combines computational and experimental approaches to study solid-state electrolytes, with a particular focus on light-induced structural dynamics that enable optoionic effects. Using machine learning–accelerated molecular dynamics simulations, I investigate the underlying mechanisms to support and guide experimental studies.
Educational Background: BSc. in Chemistry and Biochemistry from LMU

Ellen Williams
Visiting Researcher

I’m a master’s student from the University of Bath, UK. My research is focused on comparing the accuracy of using different exchange-correlation functionals for predicting the dynamic properties of solid-state ionic conductors. I am also comparing ab initio molecular dynamics with machine-learning molecular dynamics.

Educational Background: final year integrated master’s student, MPhys Physics (University of Bath)

Hobbies: reading, hiking, swimming

Luis Blank
HiWi student assistant