Samuel J. Hall

Samuel J. Hall

Postdoctoral Asisstant

Helmholtz-Zentrum Berlin

Biography

I am Dr. Sam Hall, a postdoctoral researcher at Helmholtz-Zentrum Berlin. My current work is focused on developing machine learning models for x-ray spectroscopy.

My background and interests are in computational spectroscopic simulations, mainly x-ray photoelectron spectroscopy, (XPS) and x-ray absorption spectroscopy (XAS). I specialise in using density functional theory (DFT) in order to calculate core-level spectroscopy of metal-organic interfaces. These types of spectra can often consist of overlapping features and significant broadening, making interpretation difficult. Through the use of first-principle simulations, I have been able to decompose spectra in terms of both atomic contributions and molecular orbital contributions. I have also looked into characterising how the interaction between the molecule and the metal surface changes spectra and highlighting how the different levels of interaction change spectra.

Interests
  • X-ray Spectroscopy (XPS, XAS)
  • Density Functional Theory
  • Molecule-Metal Interfaces
  • Graph Neural Networks
Education
  • PhD in Molecular Analytical Science, 2022

    University of Warwick

  • MSc in Molecular Analytical Science, 2018

    University of Warwick

  • MChem in Chemistry, 2016

    University of Leicester

Skills

Experience

 
 
 
 
 
Helmholtz-Zentrum Berlin
Postdoctoral Researcher
March 2023 – Present Berlin, Germany

Responsibilities include:

  • Analysing
  • Modelling
  • Deploying
 
 
 
 
 
University of Warwick
Postdoctoral Researcher
March 2022 – January 2023 Coventry, United Kingdom
Taught electronic engineering and researched semiconductor physics.

Accomplish­ments

Coursera
Neural Networks and Deep Learning
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Formulated informed blockchain models, hypotheses, and use cases.
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DataCamp
Object-Oriented Programming in R
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Projects

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Recent Publications

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(2022). Future Directions: General Discussion. Faraday Discuss..

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(2022). Topological Stone–Wales Defects Enhance Bonding and Electronic Coupling at the Graphene/Metal Interface. ACS Nano.

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(2022). Coexistence of Carbonyl and Ether Groups on Oxygen-Terminated (110)-Oriented Diamond Surfaces. Commun. Mater..

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Recent & Upcoming Talks

X-ray Absorption Spectra Prediction of Extended Graphene Oxide Nanoflakes using Graph Neural Networks
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X-ray Absorption Spectra Prediction of Extended Graphene Oxide Nanoflakes using Graph Neural Networks

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