Dr Gareth Conduit of the University of Cambridge and Intellegens is speaking at the TMS Conference.

Presentation title: The modern-day blacksmith

Talk timing: 22 March, 2-2.30pm

Talk location: Hilton Bayfront Hotel – Sapphire Level, Ballroom L

We present a machine learning tool, Alchemite, that merges all possible sources of information about a material: simulations, physical laws, and experimental data. Starting from a database of CALPHAD predictions we train a machine learning model that can understand phase behavior, and use this model as an input to predict other material properties. We illustrate the approach with a case study that starts from a training set comprising just ten core results for alloy direct laser deposition, and use Alchemite to augment these with phase behavior & complementary material properties. We ask the model to design the composition and processing parameters of a nickel-base alloy for direct laser deposition, whose properties are then experimentally verified.[1]

[1] “Probabilistic neural network identification of an alloy for direct laser deposition” B.D. Conduit, T. Illston, S. Baker, D. Vadegadde Duggappa, S. Harding, H.J. Stone & G.J. Conduit, Materials & Design 168, 107644 (2019)