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2025 - present

Post doc, University of Basel, Switzerland

2020 - 2024

PhD in Chemistry, University College London, UK

2017 - 2020

Master in Materials Science, Shandong University, China

2013 - 2017

Bachelor in Materials Science and Engineering, Shandong University, China

Xingfan Zhang is a computational scientist who employs advanced theoretical and simulation approaches, including interatomic potentials, DFT calculations, hybrid QM/MM models, molecular dynamics and Monte Carlo simulations, and minima hopping algorithms, to address scientific questions across materials science, chemistry, physics, and heterogeneous catalysis. His research centres on metal oxide materials, including their electronic structures, defect chemistry, and surface reactivity, which have direct implications for practical applications, particularly in heterogeneous catalysis and ionic conduction.

Xingfan completed his Master's degree in 2020 at Shandong University, China, working in Prof. Hui Li's group on atomic-scale surface oxidation mechanisms of materials. He obtained his PhD degree in 2024 from University College London (UCL), UK, supervised by Prof. Sir Richard Catlow, where he focused on elucidating the electronic and defect properties of cerium oxides (CeO­_2-x). Currently, Xingfan is a postdoctoral researcher at the University of Basel within the Computational Physics Group led by Prof. Stefan Goedecker. His ongoing projects involve structural prediction and mechanistic studies of metal-supported catalytic systems aimed at converting CO₂ into high-value chemical products.

A complete list of publications can be found on Google Scholar.

Selected publications are:

• Environment-Driven Variability in Absolute Band Edge Positions and Work Functions of Reduced Ceria
  J. Am. Chem. Soc., 2024, 146, 24, 16814–16829

• Bulk and Surface Contributions to Ionisation Potentials of Metal Oxides
  Angew. Chem. Int. Ed., 2023, 135(40): e202308411

• Toward a Consistent Prediction of Defect Chemistry in CeO₂
  Chem. Mater., 2023, 35(1): 207-227

• Atomic-scale understanding of oxidation mechanisms of materials by computational approaches: A review
  Mater. Des., 2022, 217: 110605

• Atomistic Origin of the Complex Morphological Evolution of Aluminum Nanoparticles during Oxidation: A Chain-like Oxide Nucleation and Growth Mechanism
  ACS Nano, 2019, 13(3): 3005-3014