Henry Thake

Henry Thake

PhD Student

Research Interests

Defective graphene structures
Metal catalysts on graphene
Magnetic nanomaterials
DFT calculations
Machine learning interatomic potentials
NEXAFS spectroscopy

Biography

Henry Thake is a PhD student investigating how local defects can be created in graphene networks and exploring their design principles for supporting novel catalysts and magnetic materials.

PhD Research

Started: September 2024

Office: G209, Department of Chemistry

Henry’s research focuses on identifying how certain local defects can be created in graphene networks and exploring their design principles for scaled growth. His work investigates:

  • How defective graphene structures support novel metal catalysts
  • Magnetic nanomaterials on defective graphene
  • How material properties depend on the underlying graphene architecture

Research Methodology

Henry employs a multi-scale computational approach:

  1. DFT Calculations: Generate high-accuracy training data
  2. Machine Learning Potentials: Enable predictions of precursor adsorption and interactions
  3. Chemical Vapor Deposition Modeling: Understand synthesis of defective graphene

Additionally, his research includes improving computational predictions of near-edge X-ray adsorption fine structure (NEXAFS) spectroscopy data through enhanced DFT simulations and machine learning acceleration techniques.

Educational Background

Henry completed dual undergraduate degrees (BA and MSci) in Natural Sciences from the University of Cambridge. His master’s thesis, supervised by Prof. Steve Jenkins, employed molecular dynamics simulations to investigate radical-mediated fluorination mechanisms on group 14 crystal surfaces.

Research Impact

Defective graphene has unique properties that make it attractive for:

  • Single-atom catalysis
  • Magnetic storage devices
  • Novel electronic materials
  • Sensors and energy storage

By understanding how to controllably create and utilize these defects, Henry’s work contributes to the development of next-generation graphene-based technologies.

Education

MSci in Natural Sciences
University of Cambridge
2024
BA in Natural Sciences
University of Cambridge
2023