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Connor Allen

PhD Title: Step into the unknown: modelling titanium alloys at extreme conditions

PhD Supervisor: Albert Bartok-Partay

About me:

My undergraduate degree was in Physics (MPhys) at Loughborough University and included a Diploma in Industrial studies while working for a defence contractor. My first experience in research was during my undergraduate studies, where I undertook a summer research project involving x-ray measurements for thin films, with Dr Kelly Morrison at Loughborough University. Following this, I then secured a placement year at a defence contractor prior to my final year. Here I was responsible for the characterisation of continuum strength models for metals against density functional theory (DFT) and experimental data. Once returning back to University, for my undergraduate research project I performed experiments on thin films to characterise alternative alloys for spin Seebeck measurements with Dr Kelly Morrison. I achieved a first class honours and was also awarded two prizes: one for the best overall degree mark and one for best final year project mark.

My research is now concerned with the high temperature and pressure behaviour of titanium alloys, In particular the system of interest is Ti-6Al-4V. This material is widely used in industry from aerospace to biomedicine due to it's material properties. However, despite the materials prevalence in industry, it is incredibly hard to characterise from a theoretical standpoint. Even more so accurately. My project is to better understand the material through the use of ab initio methods (DFT) and machine learning. This research will contribute to our understanding of the alloy so we can better predict how the material will behave in extreme conditions outside the realm of current experimental methods.

Background:

MPhys Physics, Loughborough University

Conferences:

Warwick (UK), HetSys Summer Conference, July 2021. Virtual Poster - "Gaussian Approximation Potentials for Ti based alloys."

Cergy (France), Artificial intelligence, mathematics and physics, September 2021. Virtual Talk - "A Gaussian Approximation Potential for the Ti-Al system".

Psi-k (Virtual), ML-IP 2021, November 2021. Virtual Poster - "A Gaussian Approximation Potential for the Ti-Al system".

University of Oxford (UK), AWE Materials and Analytical Student Conference 2022, April 2022, Talk - "Gaussian Approximation Potentials for Ti based alloys - Improving phonon representation in machine learned potentials"

SISSA, Trieste (Italy), Young Researcher’s Workshop on Machine Learning for Materials 2022, May 2022, Poster - "A Computationally Efficient Approach for Improving Phonon Representation in Machine Learned Potential"

EPFL, Lausanne (Switzerland), Psi-k Electronic Structure Theory Conference, August 2022, Poster - "A Computationally Efficient Approach for Improving Phonon Representation in Machine Learned Potential"

Papers:

Optimal data generation for machine learned interatomic potentialsLink opens in a new window

Connor Allen

Contact: Connor.Allen.1@warwick.ac.uk