8 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
Optimal design of experiments in the context of machine-learning inter-atomic potentials: improving the efficiency and transferability of kernel based methods
Bartosz Barzdajn, Christopher P. Race
Data-driven, machine learning (ML) models of atomistic interactions are often based on flexible and non-physical functions that can relate nuanced aspects of atomic arrangements in…
Molecular dynamics simulations of neutron induced collision cascades in Zr - statistical modelling of irradiation damage and potential applications
Bartosz Barzdajn, Christopher P Race
Understanding the nature of irradiation damage often requires a multi-scale and multi-physics approach, i.e. it requires a significant amount of information from experiments, simul…
Development of data-driven spd tight-binding models of Fe -- parameterisation based on QSGW and DFT calculations including information about higher-order elastic constants
Bartosz Barzdajn, Alexander M Garrett, Thomas M Whiting +1
Quantum-mechanical (QM) simulations, thanks to their predictive power, can provide significant insights into the nature and dynamics of defects such as vacancies, dislocations and…
The roles of adhesion, internal heat generation and elevated temperatures in normally loaded, sliding rough surfaces
Benjamin Poole, Bartosz Barzdajn, Daniele Dini +2
The thermal effects of plastic and frictional heat generation and elevated temperature were examined along with the role of adhesion in the context of galling wear, using a represe…