A novel method of determining interatomic potential for Al and Al-Li alloys and studying strength of Al-Al3Li interphase using evolutionary algorithms

S Roy and A Dutta and N Chakraborti, COMPUTATIONAL MATERIALS SCIENCE, 190, 110258 (2021).

DOI: 10.1016/j.commatsci.2020.110258

Aluminum, alloyed with Lithium, is used extensively in aerospace and cryogenic applications due to its high forming ability and desirable mechanical properties. However, a number of short-comings of these alloys led to intense research on the intrinsic phases and their effects. One such metastable phase, delta' (Al3Li) has immense impact on the properties, requiring extensive probing. Taylor-made interatomic potentials for this system is however unavailable. Therefore, in this study, the interatomic potentials for Al and binary Al-Li have been calculated based on second nearest neighbor modified embedded atom method (2NN MEAM) formulization. The potentials are created based on optimizing parameters for MEAM potential using reference vector guided Genetic Algorithm to predict certain physical properties like cohesive energy, elastic constants, lattice constant, stacking fault energy etc. in reasonable agreement with Density Functional Theory (DFT) calculations. An Evolutionary Deep Neural Net (EvoDN2) algorithm created the objective functions for optimization. The potential predicted for Aluminum can simultaneously produce six to seven various properties with minimum amount of error, thus validating the method. This new MEAM potential is used to study the interphase strength of Al3Li-Al. Metamodels are constructed for this purpose using this new potentials through EvoDN2 algorithm. Applying multi-objective evolutionary algorithms, the metamodels are then utilized to study the optimized working conditions for maximum interphase energy and minimum strain at failure, as this will signify maximum interphase strength.

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